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Characterizing the layer-specific viscoelasticity of soft materials from indentation tests by a unified transformer framework
Yuan Gao, Jun-Yuan Sheng, Jiankun Zhang, Libin Zhao
Accepted Manuscript , doi: 10.1016/j.taml.2026.100758
[Abstract] (0) [PDF 2243KB] (0)
Abstract:
Characterizing the mechanical properties of soft materials is essential for understanding tissue micromechanics, elucidating disease mechanisms, and informing the rational design of biomimetic materials. Biological materials often possess complex, multilayered structures, posing significant challenges in characterizing the mechanical properties of individual layers. Here, we develop UnifiedTrans, a dual-branch heterogeneous transformer framework for indentation-based inverse characterization of layered soft materials. As a representative demonstration, a bilayer system composed of a viscoelastic film bonded to a semi-infinite elastic substrate is considered. Dimensional analysis is first used to identify the normalized loading and relaxation responses. Accordingly, large-scale finite element simulations are constructed to generate indentation relaxation responses over the coupled geometric and material parameter space. The simulation database is then used to train UnifiedTrans, which embeds indentation curve samples and structural parameters as heterogeneous tokens. Finite element simulations reveal that the apparent relaxation behavior of the layered system deviates from the intrinsic response of the target layer, confirming the need for structure-aware inverse characterization. The results on the held-out test set and ablation studies further demonstrate that UnifiedTrans accurately recovers layer-specific viscoelastic parameters and outperforms late-fusion alternatives by enabling early interaction between curve tokens and structural condition tokens. The proposed framework establishes a general and extensible route for data-driven, indentation-based characterization of layer-specific viscoelasticity in soft materials.
Architecting resilience: Mechanical and multi-physics metamaterials for next-generation structural engineering
Liangyu Huang, Jiayi Hu, Fengrui Yang, Yuanlong Li, Yahao Pan, Wen Zhou, Jing Yu, Nan Hu
Accepted Manuscript , doi: 10.1016/j.taml.2026.100757
[Abstract] (0) [PDF 3590KB] (0)
Abstract:
Mechanical and multi-physics metamaterials offer a fundamentally different paradigm for structural engineering: rather than relying on composition or geometric size alone, their properties are encoded in multi-scale architecture. This review critically examines how metamaterial concepts may reshape the future of structural engineering through balancing sustainability and high performance, enabling multi-physics function, and upgrading of existing structures. First, we summarize load-bearing metamaterials that provide programmed collapse, energy absorption, quasi-zero-stiffness isolation, and elastic-wave control using various geometric options and composite manner. Second, we expect multi-physics metamaterials that may enable acoustic and elastic wave manipulation, passive thermal regulation, electromagnetic response, self-sensing, energy harvesting, and hydrodynamic wave control without sacrificing load-bearing capacity. Third, we analyze metamaterial-enabled retrofitting strategies for aging buildings and infrastructure, including attached resonant systems, architected confinement layers, prestressing-assisted strengthening, and reconfigurable interventions for local vibration suppression, stress redistribution, and adaptive service-life extension. Despite impressive advances at the unit-cell and component scales, this review also identifies five critical barriers to engineering implementation, including cross-scale design and modeling, large-scale manufacturing, long-term durability/reliability under coupled environmental factors, defect-tolerant quality control, and code acceptance. The review concludes that civil metamaterials should be regarded not as direct substitutes for conventional construction materials, but rather as programmable composite systems whose engineering value depends on validated mechanics, manufacturable design, life-cycle performance, and code-recognized performance criteria. A staged research roadmap is also proposed.
Bio-inspired wake interaction and load redistribution from rotating cylinder pairs to compact arrays using an immersed boundary method
Der Chang Lo
Accepted Manuscript , doi: 10.1016/j.taml.2026.100756
[Abstract] (30) [PDF 3167KB] (0)
Abstract:
Flow around rotating cylinder pairs and compact cylinder arrays is numerically investigated using a boundary-condition-enforced immersed boundary method on a Cartesian grid. The formulation combines direct forcing with a Lagrange-multiplier treatment of the boundary force, enabling velocity boundary conditions to be imposed exactly. After validation against rotating cylinder benchmarks, the method is applied to side-by-side cylinder pairs at Re = 200 and to compact arrays treated as two-dimensional, reduced-order models for coordinated active vortical systems. For cylinder pairs, inward counter-rotation yields the strongest suppression of vortex shedding and, at small gaps, produces a virtual composite-body-like wake; outward counter-rotation suppresses unsteadiness mainly through wake separation; and co-rotation deflects the combined wake and enhances mean lift. In 2 × 2 arrays, co-rotation produces strong load segregation, whereas checkerboard counter-rotation creates complementary local force pairs and markedly reduces the net drag. A 3 × 3 phase-lagged array at Re = 200, 600, and 1000 reveals a trade-off between array-level load reduction and local load specialization: G = 1 gives the lowest mean drag but the strongest mean-drag non-uniformity, G = 3 gives the highest mean lift and the largest total root-mean-square (RMS) loads, and G = 2 is a transitional regime with the greatest RMS-lift heterogeneity. Spectral analysis further shows that increasing Re fragments the far wake while the imposed phase organization remains detectable in the near field. These results establish a mechanism-based framework for wake-mediated coupling, load redistribution, and collective flow control in idealized active multi-body systems.
An Enskog-type model with velocity-dependent collision frequency for non-equilibrium evaporation
Zemin Huang, Lei Wu
Accepted Manuscript , doi: 10.1016/j.taml.2026.100750
[Abstract] (51) [PDF 2753KB] (0)
Abstract:
Near-vacuum evaporation is velocity selective, whereas reduced Enskog-Vlasov models typically use speed-independent relaxation. We develop a ν-Enskog model with a normalized speed-dependent collision frequency and a conservation-constrained target distribution. The model recovers the prescribed dense-gas viscosity and thermal conductivity while retaining the Vlasov mean field and Enskog corrections. Although both reduced models recover the same prescribed transport coefficients, the ν-Enskog model gives a lower kinetic heat flux through most liquid and diffuse-interface regions than the Shakhov-Enskog model, with the ordering reversed in the far vapor. It also predicts a denser and cooler interface, weaker vapor outflow, and a larger evaporation coefficient. Comparison with available full Enskog-Vlasov data is observable dependent. The ν-Enskog model gives smaller discrepancies for the evaporation coefficient and, marginally, the density profile. The effective-temperature-jump comparison and the temperature-component profiles at Tl = 0.45 do not establish an accuracy advantage for either model. The model is economical but, being local, cannot recover nonlinear and spatially nonlocal Enskog collision transfer.
Decoding Intrinsic Strength of Hexagonal Boron Nitride under Biaxial Loading from Two Coupled Deformation Modes
Jun Xia, Chaolei Sun, Kang Zhang, Wei Wang, Liya Wang, Ruijie Wang, Chun Tang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100749
[Abstract] (92) [PDF 1661KB] (0)
Abstract:
Fracture initiation in two-dimensional materials is ultimately governed by the deformation and failure of covalent bonds under complex loading, yet the underlying bond-level mechanisms remain insufficiently resolved. Here, we investigate the fracture behavior of hexagonal boron nitride (h-BN) under biaxial tensile loading by establishing a direct link between intrinsic strength and covalent bond deformation modes. Molecular dynamics simulations combined with a continuum mechanics description reveal that fracture initiation in pristine h-BN is controlled by a competition between two coupled bond-level deformation mechanisms: axial bond stretching and in-plane bond rotation. Under biaxial loading, multiple bond orientations are simultaneously activated, leading to a pronounced non-monotonic dependence of intrinsic strength on the load ratio, with a maximum variation of 18.9% observed across different loading states. This complex behavior arises from a transition between bond families governed by distinct deformation modes. By decoupling lattice deformation into stretching- and rotation-dominated contributions, we demonstrate that bond rotation becomes increasingly important as the loading state deviates from equal biaxial tension, despite its relatively small absolute energetic contribution. This framework is further extended to defective h-BN containing vacancy and crack defects, where defects amplify bond-level competition through localized stress concentration and enhanced bond rotation without altering the fundamental fracture mechanism. These results provide a unified atomistic picture of fracture initiation in both pristine and defective h-BN and highlight bond rotation as a critical mechanism governing fracture resistance in two-dimensional materials.
From Explosion Mechanics to Resilient Infrastructure: Bridging Mechanics, Materials and Structural Protection
Wensu Chen, Hong Hao
Accepted Manuscript , doi: 10.1016/j.taml.2026.100748
[Abstract] (134) [PDF 1162KB] (1)
Abstract:
The recently published Explosion Mechanics Roadmap provides a comprehensive review of recent advances in explosion and impact mechanics, spanning shock physics, dynamic material behaviour, computational modelling, structural response and protection, advanced protective materials and technologies, artificial intelligence, and engineering applications. Its breadth also highlights a critical challenge for the next stage of the field: translating advances in the understanding of extreme dynamic phenomena into safer and more resilient infrastructure. From a structural engineering perspective, addressing this challenge requires a shift from single-hazard and component-level resistance towards multi-hazard, integrated, intelligent, structure-level resilience. This Invited Perspective highlights five transitions that could help shape this development: from single-hazard resistance to multi-hazard resilience; from material and component level to integrated material–component–structure level; from high-fidelity simulation to trustworthy predictive approach; from pure data-driven Artificial Intelligence (AI) to integrated physics-informed, uncertainty-aware AI for prediction; and from structural resistance and survival to functionality and recovery. Ultimately, the next frontier of structural protection lies in connecting extreme loading hazards, mechanics, materials, structures, functionality and recovery within an integrated intelligent framework for resilient infrastructure.
A Geometry-Aware Triplane Field Network for Vehicle Aerodynamic Prediction
Kangkang Qi, Huiyu Yang, Keqi Ding, Yunpeng Wang, Yuntian Chen, Yuanwei Bin, Rikui Zhang, Jianchun Wang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100745
[Abstract] (135) [PDF 7781KB] (0)
Abstract:
High-fidelity computational fluid dynamics (CFD) is crucial to vehicle aerodynamic analysis, but its cost still constrains early-stage design exploration. Machine-learning-based surface-field prediction offers a faster alternative if the model can efficiently capture both global flow context and local geometric detail. This work proposes a machine-learning-based method, named the geometry-aware triplane field network (GTF-Net), for vehicle aerodynamic pressure and wall shear stress prediction. GTF-Net constructs triplane features directly from sampled surface points through a shared multilayer perceptron (MLP) and smooth bilinear rasterization. The planes are then processed by a dual-stream backbone that combines adaptive Fourier neural operator (AFNO) spectral mixing with convolutional neural network (CNN) refinement, so long-range aerodynamic coupling and local geometry-induced variations are modeled in the same representation. At the query stage, sampled triplane features are combined with vehicle-aligned directional coordinates, normal-projection features, and a voxel-based curvature proxy. GTF-Net is compared with Transolver, a geometry-informed neural operator (GINO), and TripNet, a triplane-based surrogate model. GTF-Net improves the relative L2 error from the strongest baseline value of 0.157 to 0.145 for pressure prediction and from 0.237 to 0.225 for wall shear stress prediction. The ablation results show that AFNO mixing, local CNN refinement, and query-side geometric encoding each contribute to accuracy, supporting the proposed mechanism of combining structured triplane representation with explicit aerodynamic geometry cues. Code and data are available at: https://github.com/qkk106329/GTF_Net.
Defect-Driven Brittleness in Hexagonal Boron Nitride (h-BN) Atomic Layers
Lei Luo, Tanglong Bai, Dong Zhang, Changhua Li, Kecheng Cao, Yanpeng Qi, Shizhe Feng, Hongti Zhang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100744
[Abstract] (138) [PDF 1604KB] (0)
Abstract:
Monolayer hexagonal boron nitride (h-BN), a two-dimensional wide-bandgap material for electronic devices, can exhibit reduced structural reliability due to defect-induced mechanical degradation. The mechanical properties and failure behavior of defect-driven monolayer single-crystal h-BN are systematically investigated. In specimens without defects large or sharp enough to trigger immediate instability, fracture proceeds through stable crack growth associated with a rising R-curve, allowing stepwise crack extension and about 30% higher energy dissipation than predicted by classical brittle fracture. By contrast, nanopore-containing specimens fail by abrupt catastrophic brittle fracture without experimentally resolvable stable crack propagation, and their fracture strength decreases to 11.2–32.4 GPa. The transition between the two modes is interpreted using stability analysis that compares the crack driving force with the rising resistance curve. A modified Griffith criterion indicates that the characteristic defect size associated with crack-initiation-controlled catastrophic fracture is several nanometers, with a predicted range of 2.6–29.8 nm, consistent with nanopores observed by electron microscopy. Statistical analysis further shows a “narrower is stronger” width dependence of fracture strength. These results establish quantitative correlations among defect scale, fracture mode, and mechanical performance, and provide guidance for defect engineering in h-BN-based devices.
Tensegrity-Inspired Auxetic Metamaterials with Coordinated Radial Contraction, Stiffness Tunability, and Impact Mitigation
Yipeng Luan, Meiling Zhang, Dongxu Qiao, Zhihui Zhang, Jianwei Sun, Luquan Ren
Accepted Manuscript , doi: 10.1016/j.taml.2026.100746
[Abstract] (139) [PDF 2055KB] (1)
Abstract:
Negative Poisson’s ratio (NPR) metamaterials have attracted considerable attention because of their auxetic behavior, while designs integrating multiple mechanical functions within a single structure remain relatively limited. In this study, a hexagonal tensegrity-inspired auxetic metamaterial is proposed, in which coordinated radial contraction and self-recovery are achieved through the coupling of spring interactions and geometric constraints. By selecting different combinations of tension and compression springs, the compressive mechanical response of the unit cell can be changed without changing its base geometry. Cyclic compression tests showed a stable mechanical response, with the peak force changing by only 2.64% after 1000 cycles. The structure was further extended into a seven-cell assembly, which reduced the peak impact force by approximately 86% under impact loading compared with direct impact on rigid ground. The seven-cell assembly was also integrated into a wheel structure, and indentation tests demonstrated cooperative deformation under localized loading. These results demonstrate a tensegrity-inspired NPR metamaterial architecture that integrates coordinated radial contraction, self-recovery, stiffness tunability, and impact mitigation.
Eigenfeature-enhanced machine learning method for distributed information prediction
Ruiqi Huang, Xu Wang, Yilang Liu, Weiwei Zhang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100747
[Abstract] (129) [PDF 2328KB] (0)
Abstract:
Force/thermal/acoustic/light/magnetic distributed information is a critical input for aeroelastic analysis, thermal protection system design, and stealth performance evaluation in aircraft. Efficiently constructing high-precision spatial or surface distribution models has long been a key challenge in engineering. Distributed information typically exhibits a low-dimensional feature structure that varies with input parameters, with proper orthogonal decomposition (POD) being the most representative data-driven dimensionality reduction method. This paper proposes an eigenfeature-enhanced machine learning method for distributed information prediction. The method first uses the POD technique to extract eigenfeature modes, which are then combined with flow conditions and coordinates as inputs to a fully connected neural network, enhancing both the network’s expressiveness and prediction accuracy. A case study on the transonic angle-of-attack and Mach number variations for the RAE2822 airfoil was conducted, comparing the performance differences between the proposed method and two classical machine learning modeling methods, namely, proper orthogonal decomposition combined with a deep neural network and a deep neural network. The results demonstrate that the proposed eigenfeature-enhanced method significantly enhances the prediction accuracy and robustness of the model while reducing training data requirements by more than 50% for the same accuracy level. The eigenfeature-enhanced machine learning method offers a novel solution for high-precision and robust modeling of distributed information.
A measurement-operator framework for generative reconstruction of flow fields from sparse and indirect sensing
Ding Wang, Weiyi Li, Zirun Jiang, Yuze Cai, Yuntian Chen, Shijun Liao, Shiyi Chen
Accepted Manuscript , doi: 10.1016/j.taml.2026.100741
[Abstract] (145) [PDF 5271KB] (0)
Abstract:
Inferring high-fidelity continuous flow fields from scattered and indirect sensor data, such as scanning LiDAR projections, poses a highly ill-posed inverse problem. While deep generative models provide expressive priors, existing architectures rely on uniform grids and direct masking, severely restricting their utility for off-grid and projected observations. We introduce measurement-operator flow matching (MOFM), a grid-free generative framework that natively assimilates diverse sensing modalities via a point-cloud conditioner. During inference, composable and retraining-free sampling guidance imposes measurement consistency, alongside strict divergence-free constraints for genuinely incompressible conditions. To ensure stable optimization across diverse flow regimes, a unified per-component normalization prevents massive ambient advection from washing out small-scale turbulent signatures. Evaluated on a canonical Kolmogorov flow and a complex wind-turbine wake, MOFM substantially reduces reconstruction error compared to parameter-matched baselines, faithfully preserving both the spatial velocity fields and the high-frequency turbulent energy spectrum.
Insensitivity of the scaling law for static-pressure variations in the gap flow of an air-bearing stage with suction ports to the horizontal motion of a levitated object
Hiroaki Oka, Hiroki Suzuki, Toshinori Kouchi
Accepted Manuscript , doi: 10.1016/j.taml.2026.100743
[Abstract] (153) [PDF 1833KB] (0)
Abstract:
This study aims to clarify how the horizontal motion of a levitated object affects the gap flow and the spatial distribution of static pressure in an air-bearing stage equipped with suction ports. High-resolution numerical simulations of the incompressible unsteady Stokes equations were performed. A fundamental element domain in which supply and suction ports are arranged alternately was considered, and the translational velocity, gap height, and element width were systematically varied. The mean flow, flow kinetic energy, and spatial variation of static pressure were evaluated. The results show that the asymmetry of the streamwise velocity field and the flow kinetic energy increase with translational velocity, whereas both the spatial distribution and the spatial RMS variation of static pressure depend only weakly on translational velocity. Furthermore, the levitation-height dependence of the normalized spatial variation of static pressure follows an inverse-cubic scaling law irrespective of the presence or absence of motion.
Spectral leakage-induced ill-posedness in frequency-domain dynamic load identification: modeling, compensation strategy, and validation
Te Yang, Zhichun Yang, Fuxing Zhao, Shuya Liang, Le Wang, Chengguang Su
Accepted Manuscript , doi: 10.1016/j.taml.2026.100742
[Abstract] (169) [PDF 0KB] (0)
Abstract:
Dynamic load identification in the frequency domain is a typical ill-posed inverse problem. Existing studies usually attribute its instability to the ill-conditioning of the frequency response function matrix and the amplification of measurement noise. This study shows that spectral leakage caused by the finite-length discrete Fourier transform is another important source of identification error, especially in lightly damped structures with narrowband resonant responses. A theoretical model is first developed to describe how leakage-induced distortion in the measured response spectrum propagates into the identified load spectrum. On the basis of this analysis, a linear spectral compensation function is proposed to correct the distorted response spectrum. The method is further extended to multidegree-of-freedom systems through a modal response compensation strategy, which can be combined with both direct inversion and Tikhonov regularization. Numerical simulations on single-degree-of-freedom and eight-degree-of-freedom systems, together with experimental validation on an eight-story shear frame, demonstrate that the proposed method effectively reduces leakage-induced identification errors. The results indicate that spectral compensation and regularization play complementary roles: the former corrects systematic signal-domain distortion, whereas the latter suppresses noise amplification during inversion. This work provides a physically interpretable and easily implementable enhancement to classical frequency-domain dynamic load identification methods.
CFDAgent with a general kinematics module: driving biological flapping flight simulation
Zhaoyue Xu, Hua-Dong Yao, Shizhao Wang, Guowei He
Accepted Manuscript , doi: 10.1016/j.taml.2026.100734
[Abstract] (157) [PDF 0KB] (0)
Abstract:
Automating moving-boundary computational fluid dynamics (CFD), particularly for simulations of biological flapping flight, requires complex coordination across geometry, meshing, kinematics, and postprocessing. We present an enhanced CFDAgent, a large language model (LLM)-orchestrated platform that executes the entire workflow end-to-end through natural-language dialogue, spanning geometry intake, solver execution, and iterative figure generation. The agent features a general kinematics module that directly converts natural-language motion specifications or measured trajectories into the periodic body motion incorporated into the solver. We validate the platform’s accuracy and versatility against three distinct benchmarks: a rotating sphere, a flapping plate, and a slow-flying Pallas’s long-tongued bat (Glossophaga soricina) with deforming wings. Furthermore, we apply the workflow to investigate the aerodynamic effects of hindwing damage in migrating painted lady butterflies (Vanessa cardui). The simulations show that increasing hindwing trailing-edge erosion alters the wake vortex structures, resulting in progressively greater aerodynamic lift loss.
Thermodynamic-constrained neural modeling for path-dependent geomaterials via dynamic skeleton states
Yi Zhu, Su Chen, Xiaojun Li
Accepted Manuscript , doi: 10.1016/j.taml.2026.100740
[Abstract] (166) [PDF 1704KB] (0)
Abstract:
To address the dual challenges of high-fidelity data dependency and unphysical generalization in data-driven constitutive modeling, this study introduces a reverse thermodynamics-informed neural network (Re-TINN). The framework innovatively establishes mappings between internal variables and both translational and dissipative stress to predict stress-strain responses while incorporating dynamic origin position information as memory variables to characterize the evolution of soil fabrics. By retroactively deriving the Helmholtz free energy and dissipation rate, the constraints imposed by the first and second laws of thermodynamics are enforced, thereby significantly improving the predictive performance in scenarios lacking experimental free energy or dissipation rate data. The model is extended to drained and undrained conditions, with validation against synthetic and experimental datasets demonstrating (1) superior accuracy compared with conventional data-driven models for noisy-data scenarios and (2) an enhanced ability to capture complex physics for path-dependent loading through the integration of dynamic reference states, as evidenced from the perspectives of variable independence, variable importance analysis, and ablation experiments.
Structural limitations of gas–surface scattering kernels for rarefied hypersonic aerothermodynamic prediction
Yichong Chen, Tianbai Xiao, Baoqing Meng, Guan Zhang, Yong Wang, Xu Wang, Yonghao Zhang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100738
[Abstract] (169) [PDF 2258KB] (0)
Abstract:
Hypersonic flight is often through the continuum–slip, transition, and free-molecular flow regimes, and the gas–surface interactions cause significant uncertainty in predicted aerodynamic force and heat, alongside gas-phase thermochemical non-equilibrium. The standard scattering kernel closure for the gas-flow boundary condition is limited at three levels. Its constant coefficients do not capture the variation in computed scattering data. Its separable functional form leaves a residual even when the coefficients are resolved in incident energy and angle. The framework itself omits the mass, species, and chemical energy exchange of reacting surfaces, where the choice between fully catalytic and non-catalytic walls alone shifts stagnation heating about twofold. The first two levels are quantified for the inert Ar–Pt pair on a chain from molecular dynamics through direct simulation Monte Carlo: resolved coefficients shift heat flux, drag, and pitching moment by more than the 5%–10% margins, and a non-separable residual persists at 16%–20% of the diffuse-wall heat flux. Both rest on the same extrapolation of the computed scattering data towards normal incidence. Tackling these limitations properly is a prerequisite for accurate prediction of aerodynamic force and heat above 60 km, and for the manoeuvre control that depends on it.
Mechanisms of mechanical reinforcement and thermal buffering in metallic and ceramic gyroid interpenetrating phase composites
Dong Li, Jinlong Yan, Hongnan Zhang, Chengzu Li, Peng Wang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100739
[Abstract] (174) [PDF 1986KB] (0)
Abstract:
Gyroid lattices are promising for lightweight load bearing and thermal buffering, but the role of resin infiltration strongly depends on the skeleton material. Herein, we compare metallic and ceramic gyroid interpenetrating phase composites with identical topologies and geometries. Four structures, namely, a stainless-steel gyroid lattice (SS-gyroid), a stainless-steel gyroid interpenetrating phase composite (SS-GIPC), an Al2O3 gyroid lattice (Al2O3-gyroid), and an Al2O3 gyroid interpenetrating phase composite (Al2O3-GIPC), were fabricated and evaluated in terms of compressive response, energy absorption, and transient thermal behavior. The SS-gyroid exhibited elastic deformation, plastic buckling, and progressive collapse, whereas the Al2O3-gyroid was dominated by progressive brittle fracture. After resin infiltration, the responses of the SS-GIPC and Al2O3-GIPC were distinctly material dependent. In the SS-GIPC, the resin phase constrained localized buckling of the metallic skeleton, increasing the yield stress and mean plateau stress to 146.81 and 152.36 MPa, respectively. In the Al2O3-GIPC, the resin phase constrained the fractured ceramic regions and bridged cracks, transforming brittle fracture into progressive damage and increasing the energy absorption density from 0.11 to 25.75 MJ/m3. Thermal-response experiments and finite element simulations revealed that the thermal diffusivities of SS-GIPC and Al2O3-GIPC decreased to 55.4% and 51.2% of those of their corresponding gyroid lattices, respectively, because of increased effective thermal resistance from the resin phase, multiphase interfaces, and tortuous heat-transfer pathways. This work clarifies the different roles of resin infiltration in metallic and ceramic gyroid systems and provides guidance for designing lightweight multifunctional composites that integrate load bearing, energy absorption, and thermal buffering.
Comparison of the blast resistance of acoustic metamaterial panels and micro-perforated sandwich panels
Wenjie Lu, Lin Chen, Chuanqing Chen, Xin Li, Minghui Lu, Yanfeng Chen
Accepted Manuscript , doi: 10.1016/j.taml.2026.100737
[Abstract] (205) [PDF 3599KB] (0)
Abstract:
How to conduct the coupled design for the sound absorption and anti-explosion properties of honeycomb structures is currently a challenge in the design of multi-functional structures. In the present study, the acoustic and blast response of two typical acoustic structures - acoustic metamaterial panels (AMP) and micro-perforated sandwich panels (MSP) - were experimentally investigated. Acoustic test results indicated that the designed AMP achieved a sound absorption coefficient of 0.78 at 800 Hz, while the MSP exhibited a coefficient exceeding 0.8 across a broad frequency band from 630 to 1600 Hz, demonstrating comparable effective absorption ranges. Subsequently, a series of blast tests were conducted to investigate their dynamic mechanical responses, including failure modes, deformation processes, and scaled-distance effects. Blast results revealed that the distance between the two structures from damaged to undamaged occurred between 250mm and 350mm. Analysis based on scaled distance showed that at a standoff distance of 300 mm, the AMP offered superior protective performance due to the integrity of its back face sheet. Conversely, at standoff distances of 350 mm and above, the MSP demonstrated better blast resistance owing to its smaller honeycomb core. Finally, a multifunctional evaluation model was established to quantitatively compare the overall performance of the two structures. These findings provide an experimental foundation for designing multifunctional metamaterials that integrate acoustic and mechanical performance.
Tension/compression-torsion mechanical metamaterials: A review on cell design paradigms and multimodal applications
Bofan Hu, Yajun Wang, Jianjie Lin, Lehua Qi, Xujiang Chao
Accepted Manuscript , doi: 10.1016/j.taml.2026.100736
[Abstract] (191) [PDF 6470KB] (0)
Abstract:
Traditional advanced structural materials are strictly bounded by their intrinsic physical properties, creating persistent design trade-offs between load-bearing capacity, weight, and directional deformation control. Tension/compression-torsion mechanical metamaterial (T/C-T MMs) break through these classic limitations by utilizing artificially engineered micro-architectures to smoothly convert standard one-dimensional axial stress waves into continuous, programmatic in-plane torsional rotations. This critical review provides a comprehensive synthesis of the recent milestones driving the rapid advancement of T/C-T MMs. We systematically map the core framework of microstructural synthesis into three dominant methodologies: parametric optimization based on predefined inclined-strut or ligament typologies, continuous and discrete topology optimization, and advanced data-driven machine learning schemes for rapid inverse structural discovery. Beyond basic geometric design, we comprehensively evaluate the translation of this cross-axis coupling mechanism into exceptional engineering application frontiers, specifically analyzing its role in low-frequency vibration damping, high-efficiency mass-specific energy absorption, compliance-guided soft robotics, and reconfigurable mechanical logic concealment arrays. Finally, we critique the underlying bottlenecks regarding scale-dependent boundary constraints, structural fatigue, and fabrication sensitivity, outlining future development trajectories that integrate multi-field stimuli-responsive materials and advanced additive manufacturing to pioneer next-generation intelligent structures.
An improved physics-informed neural network framework with dynamic balancing adaptive weighting for solving PDEs
Hejie Jiang, Jie Zhang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100727
[Abstract] (217) [PDF 2771KB] (1)
Abstract:
Physics-informed neural networks (PINNs) achieve the integration of physical information by embedding partial differential equations, boundary conditions, and initial conditions into the loss function, wherein the weighting of each loss component is critical to training accuracy. The adaptive weighting methods can adaptively adjust the importance of different loss components according to specific rules, while they are prone to inducing imbalances between different terms, thereby compromising network performance and training accuracy. Dynamic balancing adaptive weighting (DBAW) is proposed to address the weight imbalance issue. The DBAW method is developed on the basis of the theory of maximum likelihood estimation, which allocates greater weights to tasks with lower certainty, and weight imbalance is avoided by introducing an adjustable weight growth factor. The introduced adjustable weight growth factor accelerates the reduction in uncertainty for high-uncertainty tasks by imposing adjustable and strong penalties on them. This proportionally increases the weight of such high-uncertainty tasks and achieves dynamic weight balance among all loss tasks during the training process. An improved PINN framework based on the DBAW method—the dynamic balancing adaptive weighting synergy framework—is developed to solve complex problems. Four benchmark examples, namely, the diffusion-reaction equation, the Poisson equation, and the Navier-Stokes equations, are employed and solved to compare the proposed methods with other methods, and their outperformance in enhancing the prediction accuracy of PINNs is validated.
Deformation and energy absorption of meta-structure-reinforced granular composites under triaxial loading
Ying Tang, Yifei Sun
Accepted Manuscript , doi: 10.1016/j.taml.2026.100729
[Abstract] (225) [PDF 3293KB] (0)
Abstract:
Metastructure has been proven to possess distinct energy-absorbing capabilities under uniaxial loading conditions. However, its performance under complex loading conditions has rarely been reached. In this study, the deformation and energy absorption characteristics of a granular composite reinforced with a three-dimensionally printed re-entrant auxetic metastructure were investigated. The metastructure was fabricated from thermoplastic polyurethane and embedded in the granular material in single- and triple-layer configurations. Its re-entrant geometry generates a negative Poisson’s ratio response, thereby providing deformation-dependent lateral confinement to the surrounding granular material. A series of laboratory tests using monotonic, constant shear stress (CSS), and cyclic triaxial stress paths were carried out to investigate the mechanical response of the composites. The results demonstrate that the inclusion of the metastructure significantly enhances the composite strength and instability resistance. Triple-layer reinforcement increased the peak strength and residual strength of the composite by approximately 40% while delaying peak stress mobilization. During cyclic loading, energy absorption exhibited a nonlinear increase, increasing by approximately 90% and 200% for the single- and triple-layer configurations, respectively. To elucidate this nonlinearity, a layer-normalized net energy index was introduced to compare the relative energy absorption efficiency of the single- and triple-layer configurations. Moreover, the damping ratio slightly decreased with metastructure inclusion. These findings highlight the exceptional value of metastructure in optimizing energy absorption under complex stress conditions.
Non-intrusive spectral submanifold model reduction for geometrically nonlinear rotating structures with Coriolis and centrifugal forces
Hejun Gao, Yiliang Wang, Yan Qing Wang, Jie Yuan, Mingwu Li
Accepted Manuscript , doi: 10.1016/j.taml.2026.100726
[Abstract] (208) [PDF 3648KB] (0)
Abstract:
Rotating structures are widely observed in engineering applications such as turbomachinary and wind turbines. These rotating structures, particularly for blades made by lightweight materials, can undergo large deformation during operations and display complex nonlinear dynamics under the coupled interaction of geometric nonlinearity, Coriolis effect and centrifugal force. Finite element (FE) methods provide powerful and accurate modeling approaches for capturing the complex nonlinear dynamics for realistic rotating structures; however, their high dimensionality present significant challenges for efficient prediction of the nonlinear vibration. Here, we present a non-intrusive spectral submanifold (SSM) model reduction for these FE models of rotating structures. We use COMSOL to construct FE models and simulate these FE models to verify the accuracy of SSM-based reduction. We first compute the nontrivial static equilibrium induced by the centrifugal force and then construct a non-intrusively SSM-based reduced-order model (ROM) anchored at the equilibrium. These SSM-based ROMs enable efficient and accurate extraction of backbone and forced response curves. We use a suite of examples with increasing complexity to demonstrate the effectiveness of the SSM reduction, including a rotating beam, a twisted plate, a rotor with two disks, and an internally resonant fan with three blades. The obtained results also highlight the significant effects of the Coriolis force on the nonlinear vibration of rotating structures.
Advanced B-spline interpolation with the use of quaternions for spatial rotations: formulas for derivatives and non-uniform parametric distribution
V. Houdek, O. Verlinden, N. Capette, M. Hajžman
Accepted Manuscript , doi: 10.1016/j.taml.2026.100724
[Abstract] (221) [PDF 2008KB] (1)
Abstract:
Mechanics abounds in machines involving one- or two-degree-of-freedom subsystems with various purposes, such as vehicle suspension. Such systems are usually addressed according to the multibody approach, with the kinematics possibly involving a large number of constraint equations repeatedly solved around near configurations. As an alternative, this paper proposes solving the kinematics for a few key configurations (knots) and interpolating them in terms of parameters whose number is equal to the number of degrees of freedom. This work explores the application of cumulative B-splines for a consistent interpolation of either translations or rotations. Owing to the C2 continuity requirements, 4th-order B-splines are retained. The interpolation extends the computation of control points (de Boor points) to the case of non-uniformly distributed parameter values. On the other hand, expressions are provided to express the first and second derivatives necessary for velocities and accelerations. The method is illustrated on the example of a double wishbone suspension, and the influence of the knot density is analyzed according to kinematic and dynamic simulations. Moreover, a method is proposed to minimize the number of knots while controlling the interpolation error. An example of a spatial slider crank mechanism illustrates the ability of the method to manage large motions.
Wall effects on the self-propulsion of a 3D zebrafish
Tian-Yu Gao, Wei-Pei Huang, Pu-Zhen Liu, Kai-Jun Huang, Peng-Nan Sun
Accepted Manuscript , doi: 10.1016/j.taml.2026.100725
[Abstract] (223) [PDF 1897KB] (0)
Abstract:
Based on the finite volume method, this paper systematically investigates the hydrodynamic performance and wake evolution characteristics of a biomimetic zebrafish at different near-wall distances D* and tail-beat amplitudes A*. The results indicate that while swimming near a wall can achieve higher speed, it comes at the cost of efficiency: as D* decreases, the cruising speed and the input power increase, and the efficiency is reduced. The wall effect is particularly significant when D*≤0.7 and is amplified with increasing tail-beat amplitude. When swimming close to the wall, the fish body experiences an attractive force directed toward the wall. To maintain a constant near-wall distance, a yaw angle adjustment is needed, and this angle increases with increasing tail-beat amplitude. Wake analysis reveals that near the wall, both the circulation strength and the radius of the tail vortex ring increase. Although vortex-ring expansion tends to weaken the induced backward jet, the increase in circulation strength is more pronounced, resulting in an increased Γ/R ratio, which is consistent with the observed increase in swimming speed. This study elucidates the coupling mechanism of the effects of the near-wall distance and tail-beat amplitude on the wall, providing insights for understanding the dynamic characteristics of biomimetic fish swimming in proximity to a wall.
Unsteady flow reduced-order prediction model based on nontensor-product wavelet
Xinzhe Guo, Shufang Song, Weiwei Zhang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100722
[Abstract] (224) [PDF 2665KB] (0)
Abstract:
Unsteady flows are characterized by high dimensionality and strong nonlinearity. These factors make the computational cost of traditional numerical simulations extremely high, rendering them unable to meet the demands of real-time prediction and engineering optimization design. Among the classical reduced-order methods (ROMs), the adaptability of proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) is limited, while the tensor-product wavelet transform has a relatively weak ability to analyze high-dimensional spatial features. Therefore, this study proposes a multi-scale information measurement algorithm, MSII, to quantify the wavelet decomposition level, screen customized non-tensor-product wavelets that match the phase characteristics of the data, and then construct a reduced-order model for unsteady flow fields (NTPWT-ROM). This model couples the MSII algorithm to extract spatial features. After the temporal features are captured through a long short-term memory network, the flow field is reconstructed by the inverse wavelet transform. In this paper, research is carried out using the Burgers equation, AC equation, Darcy equation, flow around a cylinder, and the Navier-Stokes equations. Compared with POD-ROM, DMD-ROM, and TPWT-ROM, NTPWT-ROM yields significant improvements in prediction accuracy, computational efficiency, and extrapolation ability. The results indicate that the proposed method can provide a high-precision and high-efficiency reduced-order framework for the real-time prediction of complex flows and has remarkable application potential and promotional value in the fields of aerodynamic optimization design and active flow control.
Multiscale inverse design of mechanical cloaks via deep generative modeling
Jiakun Wang, Menghuan Wang, Qing Shang, Sheng Sun
Accepted Manuscript , doi: 10.1016/j.taml.2026.100723
[Abstract] (256) [PDF 2800KB] (2)
Abstract:
Mechanical cloaks offer a promising route for mitigating stress concentrations induced by defects; however, their design is hindered by the prohibitive cost of navigating high-dimensional topology spaces. Here, we propose a data-driven multiscale inverse design framework that integrates generative modeling with evolutionary optimization to realize heterogeneous truss-based cloaks. We first construct a comprehensive structure-property library of truss unit cells and train a conditional variational autoencoder (CVAE) to map target effective stiffness tensors to specific microstructural topologies. A high-throughput computational pipeline is subsequently established that couples finite element analysis with an SE-ResNet18 surrogate model to predict the cloaking performance from stiffness distributions. By embedding this surrogate within a genetic algorithm, we efficiently explore the design space to identify optimal stiffness fields, which are then reconstructed into physical structures via the CVAE. The optimized designs achieve a mean relative displacement-field error of 2.74 ±0.18% (standard deviation) across ten independent optimization runs, with finite element validation confirming that the reconstructed cloaks retain cloaking performance, achieving errors as low as 1.91% for the best-performing design. This work establishes a systematic AI-accelerated framework for the data-driven design of heterogeneous mechanical metamaterials.
Effects of angle of attack on near-free-surface bio-inspired propulsion: A numerical study using the smoothed-particle hydrodynamics method
Tian-Yu Gao, Peng-Nan Sun, Kai-Jun Huang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100718
[Abstract] (234) [PDF 1987KB] (0)
Abstract:
To address the high sensitivity of propulsion efficiency and stability to attitude variations in near-free-surface bionic propulsion systems, a numerical investigation of the hydrodynamic characteristics of an undulating NACA0012 hydrofoil using the δ+-SPH method is conducted in this study. By introducing angle-of-attack variations from α = -5° to 5° at a fixed submergence depth of H/L = 0.4, the effects of the angle of attack on cruising performance, free-surface response, and wake structure evolution are systematically analyzed. The results indicate that as the angle of attack increases, the cycle-averaged cruising velocity first increases but then decreases, whereas the input power coefficient increases monotonically and the overall propulsion efficiency decreases. The maximum cruising velocity and propulsion efficiency are achieved at α = -3° and α = -5°, respectively. Further analysis of the hydrodynamic loads reveals that at α = -3°, the force distribution is relatively balanced, thereby promoting stable cruising. Wake analysis demonstrated that the angle of attack controls the dominance and arrangement of positive and negative vortices by altering the relative strength of shear layers on the upper and lower surfaces. As the angle of attack increases, the wake tends to deflect toward the free surface and forms a typical “V” -shaped vortex street at α = 5°. Within the scope of this study, the case of α = -3° achieves an optimal balance among propulsion efficiency, cruising velocity, and attitude stability, providing a reference for attitude design and parameter optimization of near-free-surface bionic propulsion systems.
Geometry-guided adaptive optimization of Delaunay meshes via deep reinforcement learning
Xixi Shi, Junchen Zhu, Jin Sun, Hongjing Li, Haojie Zhang, Yao Chen, Yan Lu, Bojian Wang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100719
[Abstract] (250) [PDF 3353KB] (1)
Abstract:
Finite element analysis (FEA) faces significant challenges in maintaining mesh quality for unstructured Delaunay meshes with complex geometric features, whereas conventional optimization methods often encounter low-quality local optima. This paper proposes a novel deep deterministic policy gradient (DDPG)-driven framework to autonomously optimize node positions. First, nodes are initialized at the centroids of local polygon regions (composed of connected triangles around the target nodes) to establish topologically valid configurations; then, DDPG optimizes positions within these constrained regions. The DDPG reward mechanism integrates a distance penalty with element quality measurements, resulting in a balanced approach that outperforms methods that rely solely on quality-based rewards. This strategy enhances the overall mesh quality, improves the worst-element quality, and effectively eliminates low-quality elements while achieving strong results with small training datasets. Extensive experiments on 2D domains with curved boundaries and irregular internal voids (e.g., hollow mechanical components) demonstrate superiority over conventional methods such as Laplacian smoothing, centroidal Voronoi tessellation, and optimal Delaunay triangulation. Crucially, compared with a reference calculation solution in a load-bearing case study, optimized meshes substantially reduce FEA numerical errors—exemplified by stress calculation errors decreasing from 11.77% to 8.49%. Furthermore, DDPG-optimized meshes yield higher accuracy at lower densities and accelerate solution convergence with respect to the mesh density. This work introduces a deep reinforcement learning-based adaptive optimization framework for complex Delaunay triangulations, providing a robust tool for high-fidelity simulations.
Gas-kinetic scheme for conjugate heat transfer in low speed flows
Qibing Li
Accepted Manuscript , doi: 10.1016/j.taml.2026.100717
[Abstract] (248) [PDF 3534KB] (0)
Abstract:
The application of compressible flow solvers in low-speed fluid-solid conjugate heat transfer (CHT) problems benefits from algorithm simplicity but suffers from system stiffness under very low Mach number and the coupling method of fluid-solid interface. The mesoscopic gas-kinetic scheme (GKS) is improved to approximate incompressible flows with a finite Mach number, in which excessive viscous dissipation-induced temperature rise is mitigated by a specific heat ratio close to unity. A post pressure weighting is proposed to reduce the velocity deviation due to density variation resulting from pressure changes. Combined with a GKS for solid heat transfer, a new GKS suitable for low-speed fluid-solid CHT is developed under finite volume framework. The temperature for solid-solid and fluid-solid interface is reconstructed through temperature and heat flux continuity to account for differences in thermal conductivity. A CHT Couette flow and its analytic solution are constructed, with which the second-order spatial accuracy is validated. Numerical simulation of oil-immersed transformer winding cooling have demonstrated good development prospects.
Can instrumented spherical indentation truly sense its own induced damage?
Yuxuan Wang, Guangjian Peng, Zhongyu Piao, Yihui Feng, Jiangjiang Hu, Taihua Zhang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100720
[Abstract] (230) [PDF 1521KB] (0)
Abstract:
Instrumented indentation is a promising non-destructive method for assessing the fracture toughness of engineering structures. A foundational assumption in existing methods is that the elastic modulus obtained from spherical indentation decreases with depth, attributed to ductile damage induced by the indentation itself (called indentation-induced damage). However, this assumption lacks systematic experimental validation, and conflicting observations—reporting stable or even increasing modulus values—remain unexplained. Here, spherical indentation tests on four ductile metals (P92 steel, AA7075, AA2014, and TC4) show that the modulus does not exhibit a depth-dependent decrease. This study further investigates the mechanisms of elastic modulus degradation in P92 steel during plastic deformation and evaluates the sensitivity of instrumented indentation to different degradation mechanisms. The results reveal that during uniaxial tension, elastic modulus degradation prior to necking is primarily driven by reversible dislocation motion rather than void damage, whereas the indentation-derived elastic modulus is insensitive to dislocation effects but responds selectively to void-induced damage. Grid nanoindentation mapping on cross-sections of residual spherical indentations demonstrates that indentation-induced damage is spatially confined to a narrow region near the contact edge, where localized void nucleation is confirmed by electron microscopy. Crucially, the compressive stress state beneath the indenter fundamentally suppresses void growth and damage evolution. Finite element simulations incorporating experimentally-calibrated damage distributions confirm that the localized damage produces negligible variation in the measured elastic modulus. These findings challenge the core assumption underlying current indentation-based fracture toughness methods and provide mechanistic insights essential for developing reliable non-destructive evaluation techniques for ductile materials.
TransportBench: A Comprehensive Benchmark for Non-Equilibrium Flow Transport
Xu Wang, Minghao Li, Qizhen Hong, Yang Liu, Chen-an Zhang, Shuai Zhang, Wenhao Li, Yonghao Zhang, Tianbai Xiao
Accepted Manuscript , doi: 10.1016/j.taml.2026.100715
[Abstract] (250) [PDF 12957KB] (3)
Abstract:
Scientific machine learning models, as versatile tools for numerical simulation and analysis, are increasingly transforming the landscape of fluid mechanics research. However, existing datasets and benchmarks are primarily limited to continuum fluids and provide limited support for non-equilibrium transport phenomena. To address this gap, we present TransportBench, a high-fidelity dataset and standardized benchmark for non-equilibrium flow transport, designed to reveal the strengths and limitations of neural network models across diverse flow regimes.
Specifically, the dataset encompasses a broad physical spectrum, covering continuum and rarefied regimes, low-speed and hypersonic flows, inert and chemically reactive gases, and both translational and internal-energy non-equilibrium effects. Built upon this dataset, we systematically benchmark representative neural architectures using unified evaluation protocols to probe key challenges in learning non-equilibrium flows, including robustness to shock-dominated discontinuities and multi-scale effects, as well as generalization across geometry and physical parameters.
Numerical results demonstrate that model performance exhibits a pronounced dependence upon the specific flow characteristics. No single architecture consistently performs best for all the tasks. Instead, different models exhibit distinct performance patterns, which may be related to their architectural priors when capturing smooth flow fields, shock-induced discontinuities, and high-order non-equilibrium statistics. By jointly providing the non-equilibrium flow dataset and model benchmark, TransportBench offers a new testbed for the development, evaluation, and diagnosis of scientific machine learning methods for fluid transport beyond the Navier-Stokes hydrodynamics. The benchmark datasets1 and implementation codes2 are available under the MIT license.
Explosion Mechanics Roadmap
Qiang Wu, Jianbo Hu, Minqiang Jiang, Xiaohu Yao, Sen Chen, Jianguo Ning, Xiangzhao Xu, Guiji Wang, Yupei Qin, Xin Yu, Yan Liu, Xinjie Wang, Fenglei Huang, Shurui Li, Xiao Ma, Chuanyu Pan, Hua Fu, Pu Song, Weibing Li, Mingyang Wang, Yong He, Wei-Tao Wu, Hao Lu, Jimin He, Li Chen, Bin Feng, Longmiao Chen, Xin Li, Guangfa Gao, Qingming Zhang, Renrong Long, Fangyun Lu, Kehui Wang, Jie Li, Tianhan Xu, Gan Li, Haozhe Xing, Zhigang Zhai, Ting Si, Xisheng Luo, Xianqian Wu, Xianxu Zheng, Qiang Wan, Jun Zhang, Jicheng Li, Junhong Chen, Yi Ding, Tao Suo, Yulong Li, Yazhou Guo, Yang Cai, Minxue Tang, Anmin He, Meizhen Xiang, Jun Chen, Qilin Xiong, Zhenhuan Li, Xinming Qiu, Haoru Xie, Yong Liang, Xiong Zhang, Shuai Wang, Aohan Wang, Shujuan Hou, Qiming Liu, Xumeng Ren, Lin Dai, Kangwei Liu, Weiguo Guo, Kangbo Yuan, Zhihua Wang, Zhiwu Zhu, Long Ji, Lingyi Meng, Haijun Wu, Hao Pan, Tuanwei Zhang, Wanghui Li, Yonggang Wang, Fenghua Zhou, Mingtao
Accepted Manuscript , doi: 10.1016/j.taml.2026.100714
[Abstract] (587) [PDF 9189KB] (3)
Abstract:
Explosion mechanics originated from China’s “Two Bombs and One Satellite” project and was named by Hsue-Shen Tsien in 1963. It primarily studies the occurrence patterns of explosions, as well as the utilization, control, and protection of their mechanical effects. As an interdisciplinary subject, it involves fluid mechanics, solid mechanics, physics, and chemistry. The core of this discipline lies in understanding how high-power-density energy is transmitted through shock waves and other means within an extremely short time, leading to high-speed flow, large deformation, and even the failure of media. Since its inception, explosion mechanics has made a series of significant contributions to China’s national security and defense, aerospace, advanced manufacturing, and major engineering projects. Four distinguished scientists—Che-Min Cheng (2012), Kai-Jia Cheng (2013), Ze-Shan Wang (2017), and Qi-Hu Qian (2018)—have successively won the National Highest Science and Technology Award. In recent years, this field has continued to make breakthroughs following the “Four-Extreme” strategy, focusing on energetic materials, detonation technology, impact physics, and damage and protection. Moreover, the number of researchers engaged in explosion mechanics has grown rapidly. Nevertheless, the development of explosive mechanics still faces challenges, including the need for full-chain innovation from fundamental research to engineering applications, and the paradigm shift from Galileo’s “experiments-mathematics” approach to artificial-intelligence-empowered scientific research. In this Roadmap, we aim to provide a broad overview of recent and potential future activities in explosive mechanics and to present a development roadmap by gathering contributions from scientists with diverse backgrounds. We believe that these contributions will significantly stimulate the generation of original achievements and the advancement of state-of-the-art experimental, theoretical, and numerical tools. We also hope, this Roadmap will further establish the strategic importance of explosion mechanics as both a “shield” and a “spear” for safeguarding national security, and as a “masterful hand” in solving major engineering problems.
Multi-objective aerodynamic optimization of ride height and Rake angle in a Sedan car using CFD and machine learning
Mahdi Kheirkhah, Ehsan Roohi, Mahmoud Pasandidehfard
Accepted Manuscript , doi: 10.1016/j.taml.2026.100716
[Abstract] (278) [PDF 4523KB] (0)
Abstract:
This study investigates the aerodynamic performance of an Audi A4 sedan using computational fluid dynamics (CFD) and machine learning (ML) analysis. The CFD setup was first validated against published DrivAer Notchback wind-tunnel data, showing a Cd deviation of 3.25%, and was subsequently applied to the Audi A4-like sedan geometry. The ride height varied from 1.336 to 1.536 m, and the rake angle ranged from 0° to 5° across the four Reynolds numbers (Re=4.87 × 106, 9.75 × 106, 14.61 × 106, and 19.48 × 106). In our ML analysis, gradient boosting emerged as the most accurate predictive model (R2 ≈ 0.91 for Cd and 0.96 for the lift coefficient, Cl), outperforming random forest and LightGBM. Differential evolution optimization was performed under balanced, drag-focused, and downforce-focused conditions. The Reynolds number had a minimal effect on the optimum location; therefore, detailed results are reported for Re=9.75 × 106, with other Re values showing similar trends. The baseline geometry (ride height=1.436 m, rake angle=0°) had Cd=0.313 and Cl=+0.029. Balanced optimization resulted in Cd=0.287 (-8.31%) and Cl=-0.083 (corresponding to a net change in Cl of -0.112 relative to the baseline). The minimum drag condition reached Cd=0.285 (-8.95%) with a slight positive lift (Cl=+0.014), whereas the maximum downforce optimization reached Cl=-0.108 with a 6.71% drag penalty (Cd=0.334). Recognizing the resolution limits of the dataset, near-optimal solutions were found within approximate ride-height ranges of ≈ 1.34-1.36 m and rake angles of ≈ 0.1°-4.6°, indicating robust aerodynamic performance rather than singular precise geometrical points. The machine learning predictions were validated against CFD with < 3% error in Cd. However, owing to the limited training set of 100 CFD samples, Cl predictions exhibited higher validation errors, with the most notable discrepancies occurring in the balanced condition. Finally, under simplified energy estimation assumptions, the minimum-drag configuration indicates an idealized decrease in aerodynamic energy/fuel consumption of approximately 9.1%, whereas the maximum-downforce configuration substantially increases the downforce at the expense of higher drag.
Far-field asymptotic behavior of the meniscus and generalized Archimedean buoyancy of a superhydrophobic spherical surface
Jiaxing Cai, Bowen Zhu, Yongliang Yu
Accepted Manuscript , doi: 10.1016/j.taml.2026.100713
[Abstract] (292) [PDF 0KB] (0)
Abstract:
Most small water-walking arthropods rely on surface tension to maintain flotation, and for those supported by superhydrophobic leg tips piercing the water surface, each contact region can be mechanically approximated as a spherical surface. The resulting meniscus deformation encodes the forces, thereby enabling inference from the liquid surface shape. However, existing methods rely on full-field three-dimensional reconstruction or precise measurement of the contact angle and contact line. This study reveals that the far-field meniscus profile induced by a superhydrophobic spherical surface exhibits an asymptotic behavior: it is dominated by the generalized Archimedean buoyancy and the liquid properties but insensitive to local geometric details and the contact angle. Accordingly, on the basis of this structure and numerical fitting, a practical asymptotic relationship is established that links the far-field meniscus depth to the generalized Archimedean buoyancy. In light of these findings, a method is proposed to infer the buoyancy using the far-field meniscus profile. Furthermore, validation experiments on three superhydrophobic spheres confirm that the method achieves a relative error below 1% within the applicable parameter range.
Dynamic prediction of soft recoil brakes considering cavitation and flow contraction effects
Xinlei Duan, Longmiao Chen, Jiawei Fu, Chen Liang, Shiyu Chen, Junfei Shi
Accepted Manuscript , doi: 10.1016/j.taml.2026.100711
[Abstract] (291) [PDF 0KB] (0)
Abstract:
Soft recoil technology has emerged as a viable approach for balancing the firepower and mobility of modern large-caliber artillery systems. Accurate prediction of the hydraulic resistance provided by the soft recoil brake is imperative for ensuring the safety and stability of artillery firing. However, existing theoretical models are deficient in their inability to characterize the energy dissipation mechanisms within the recoil brake, resulting in poor physical interpretability. Fluid-structure interaction simulations of the recoil brake, which are based on computational fluid dynamics, incur extremely high computational costs. To address these limitations, this study proposes a dynamic prediction model for soft recoil brakes. Initially, pressure drop models through the throttle orifice are established for both cavitation and noncavitation conditions. A hydraulic resistance model derived from the soft recoil mechanism is subsequently developed. After the differential equations of artillery motion are integrated, a dynamic prediction model is obtained. The pressure drop model is validated using CFD methods, and the flow mechanism and cavitation evolution in the throttle orifice are analyzed. A high degree of accuracy is indicated for the pressure drop model under cavitation conditions. To validate the proposed dynamic prediction model, live-fire experiments are conducted on a specific soft recoil artillery. It is evident from the results that there is a favorable trend consistency between the theoretical predictions and the experimental data. The average coefficient of determination (R2) across the five live-fire test sets reaches 0.99782. This study provides theoretical support for the structural optimization design of soft recoil brakes.
Stress evolution of the temporomandibular joint during a real clenching cycle
Youyi He, Baotian Zhu, Haolin Li, Deqiang Yin, Yang Liu
Accepted Manuscript , doi: 10.1016/j.taml.2026.100712
[Abstract] (277) [PDF 0KB] (0)
Abstract:
Quantifying the stress distribution within the temporomandibular joint (TMJ) under real occlusal conditions is crucial for systematically comprehending its physiological functions. In the current study, we proposed an occlusal force driving pattern to integrate clinically measured occlusal data into a three-dimensional (3D) finite element model reconstructed from computed tomography (CT) and magnetic resonance imaging (MRI) of a volunteer. This proposition was verified jointly by the conventional muscular force strategy and theoretical model. The high-stress region of the right disc was significantly larger than that of the left disc. The occlusal force driving pattern not only more accurately characterizes the true state of an individual but also reduces stress by balancing structural parameters.
Correction of the interior ballistic model for the two-stage light gas gun based on machine learning
Quanyu Jiang, Yadong Li, Zhenghua Chang, Bing Liu, Minqiang Jiang, Zishang Liu, Yizhe Liu, Qiu Wang, Bingchen Wei, Kun Zhang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100710
[Abstract] (265) [PDF 1996KB] (1)
Abstract:
Two-stage light gas guns are vital for hypervelocity impact research, but their detonation-driven mechanism involving multiple interdependent parameters challenges velocity prediction and parameter optimization. In this study, a machine learning (ML) framework for predicting the projectile velocity of a DBR-30 detonation-driven two-stage light gas gun was proposed. Seven key features were selected, and five ML models (support vector regression, Gaussian processes, decision trees, K-nearest neighbors (KNN) and gradient boosting) were evaluated using five-fold cross-validation with Bayesian hyperparameter optimization. The results confirm the superiority of the KNN model, which not only records the highest accuracy but also features the fastest execution speed. By combining pressure sensor measurements with feature importance analysis, the inherent limitations of quasi-one-dimensional theoretical models suggest that an important source of discrepancy is their failure to account for the coupling effect between the rupture pressure of Diaphragm II and the gas compression rate inside the pump tube. This study confirms that fusing experimental data with ML enables high-precision velocity prediction, reduces experimental costs and time, and provides insights for refining theoretical models by addressing oversimplified assumptions. Such an ML high-precision and efficient framework offers a new paradigm for optimizing detonation-driven two-stage light gas guns.
Formal invariance of fractional-order operators under Fourier transform
Yajun Yin, Ruiheng Jiang, Zhizhen Jiang, Tianyi Zhou, Zhimo Jian
Accepted Manuscript , doi: 10.1016/j.taml.2026.100707
[Abstract] (284) [PDF 1502KB] (0)
Abstract:
This paper derives fractal/fractional-order operators in the spatial domain from mechanical structures. To ensure the computability of these operators, on the basis of the derivative and integral theorems of the Fourier transform, the form invariance of integer-order operators under the Fourier transform is extended to general operators, including fractional-order and non-rational operators. Accordingly, the postulate of “form invariance of operators under the Fourier transform” is proposed. On the basis of this postulate, the algebraic operational rules of spatial-domain operators are clarified, the consistency between fractional-order/non-rational operators and Fourier multiplier operators is demonstrated, and a concise methodology for applying spatial-domain operators in engineering is established.
Analysis of the power generation and wake effect of a wind farm in the Hexi Corridor
Zhizhao Zang, Ye Li, Deshun Li
Accepted Manuscript , doi: 10.1016/j.taml.2026.100709
[Abstract] (273) [PDF 1904KB] (0)
Abstract:
With the centralized construction of gigawatt-scale wind power bases in regions with complex terrain, the wake interference effect among large-scale wind turbine clusters has become a critical factor in constraining power generation efficiency. In this study, the Jiuquan Wind Power Base in the Hexi Corridor, China, is investigated, and the Weather Research and Forecasting model coupled with the Fitch wind farm parameterization scheme are used to systematically simulate the impact of the seasonal atmospheric boundary layer stability on the spatiotemporal evolution of the wake and power performance. Validation against meteorological maximum observations confirmed the applicability of the coupled model in complex terrain. The results reveal significant seasonal heterogeneity in wake effects, identifying atmospheric stability as the dominant mechanism governing wake recovery and diffusion. In the winter, which is dominated by stable atmospheric stratification and weak background turbulence, wake recovery is retarded, and the propagation distances are extended. This results in a peak mean velocity deficit ratio of 0.307 and a severe “deep array effect”, causing the wake-induced capacity factor loss rate to reach an annual maximum of 74%. Conversely, vigorous thermal turbulence in summer facilitates momentum exchange and wake dissipation, reducing the mean velocity deficit ratio to 0.20 and limiting the capacity factor loss rate to 45%. Although power output fluctuations are enhanced in summer, the overall capacity factor achieves its annual optimum (0.28). This study elucidates the interaction mechanism between atmospheric stability and large-scale wind farm wakes in complex terrain and quantifies the seasonal power losses caused by wakes, providing a theoretical basis for micrositing optimization and operational scheduling of large-scale wind power bases.
Microstructure reconstruction of inhomogeneous materials using elastic waves and deep learning
Sheng Sang, Ziping Wang, Jiadi Fan
Accepted Manuscript , doi: 10.1016/j.taml.2026.100708
[Abstract] (263) [PDF 1270KB] (0)
Abstract:
Accurate characterization of microstructures in inhomogeneous materials is crucial for understanding and predicting their macroscopic mechanical behavior. In this work, we propose a deep learning-based inverse framework for reconstructing complex and realistic microstructures of inhomogeneous materials directly from elastic wave responses. Unlike the conventional machine learning classifiers employed in previous studies, the proposed framework uses advanced deep neural networks capable of capturing highly nonlinear relationships between elastic wave propagation and heterogeneous microstructural features. The elastic wave response is used as the model input, while the corresponding spatial microstructure is predicted as the output. Numerical simulations based on finite element wave propagation are conducted to generate comprehensive training and testing datasets with increased material complexity and spatial heterogeneity. The results demonstrate that the proposed deep learning model can accurately and robustly reconstruct realistic microstructures from elastic wave data, significantly outperforming traditional machine learning approaches in terms of prediction accuracy and generalizability. This study highlights the potential of elastic-wave-driven deep learning as a powerful nondestructive inverse tool for microstructure characterization in complex engineered inhomogeneous materials.
State-dependent transmission and mobility shape traveling waves in epidemic reaction-diffusion systems
Yaoyu Guan, Zhihui Wang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100705
[Abstract] (289) [PDF 3279KB] (1)
Abstract:
A central question in non-equilibrium statistical physics is how microscopic internal states shape macroscopic spatiotemporal dynamics. We address this using an epidemic reaction-diffusion model in which both transmission and diffusivity depend on infection age. Asymptotic analysis of the characteristic equations quantifies how microscopic dynamics control the speed of traveling waves. A non-equilibrium-induced regime shift is identified: near the epidemic threshold (basic reproductive number R0≈1), the wave speed follows universal FisherKPP scaling, whereas at large R0 it becomes sensitive to early-stage viral growth. A weighted bridging formula is proposed to interpolate between these limits and accurately predict wave speeds across the full R0 range, in agreement with direct simulation Monte Carlo (DSMC) results. When diffusivity is also age-dependent, DSMC reveals pronounced micro-macro interaction: strong individual-level velocity heterogeneity coexists with only moderate reductions in wave speed and width, consistent with pulled-front dynamics. These results uncover a correction to classical scaling laws arising from the coupling between infection history and spatial transport.
Modulations of ultra-broadband acoustic chirped pulses
Qixuan Wei, Yu Wei, Kun Wang, Peipei Jia, Jun Yang, Gengkai Hu
Accepted Manuscript , doi: 10.1016/j.taml.2026.100706
[Abstract] (292) [PDF 2134KB] (2)
Abstract:
A chirped pulse is a signal whose frequency increases or decreases with time. Such pulses are widely used in radar imaging and wireless communications. Chirped pulse amplification is a technique that involves amplifying ultrashort pulses to high power levels by first temporal stretching the pulse, then amplifying it, and finally compressing it. Stretching and compression are typically achieved using devices that introduce a nonlinear dispersion relation—such as grating pairs in optics or active phased arrays in acoustics—ensuring that different frequency components travel different distances. However, passive temporal stretching and compression of underwater acoustic pulses remain challenging because of the difficulty in precisely engineering nonlinear dispersion relations in elastic media. In this paper, we propose a composite lattice that integrates a non-local lattice with a pantographic lattice to control nonlinear dispersion relations and achieve passive temporal stretching and compression of ultra-broadband underwater acoustic pulses. The transmittance of acoustic waves through a finite-thickness slab based on this composite lattice is analyzed. Additionally, an application for underwater acoustic encryption and decryption is proposed and validated with a discrete model. This work reveals new possibilities for controlling waterborne sound.
Real-time actuator line simulations of wind farm flows enabled by the lattice Boltzmann method and GPUs
Seiya Watanabe, Changhong Hu
Accepted Manuscript , doi: 10.1016/j.taml.2026.100700
[Abstract] (328) [PDF 4206KB] (1)
Abstract:
This study investigates the feasibility of achieving real-time performance in high-fidelity wind farm simulations using the actuator line model (ALM). While such large eddy simulations have traditionally been considered too computationally demanding, we address this challenge by utilizing the lattice Boltzmann method (LBM) accelerated by multi-graphics processing unit (multi-GPU) computing. By employing a computation-communication overlap technique, the proposed approach achieves excellent strong scaling performance, maintaining a parallel efficiency of 97.4% from 2 to 8 GPUs for a system comprising 1.42 billion grid points while attaining a high execution throughput of 8,308 million lattice updates per second per GPU. Real-time performance evaluations for a wind farm consisting of twelve 15 MW turbines confirm that real-time capability is achieved at standard ALM resolutions of 32 and 48 points per rotor diameter, with execution-to-physical time ratios of 0.38 and 0.79, respectively. Even at a higher resolution of 64 points per diameter, the ratio remains 1.41, indicating that high-resolution ALM analyses are likely to be achievable in real time on next-generation GPUs. Furthermore, weak scaling evaluations demonstrate a parallel efficiency of 86% from 4 to 32 GPUs, confirming that real-time performance can be sustained for larger wind farms by increasing the number of GPUs in proportion to the number of turbines. These results indicate that LBM-based simulations constitute a powerful tool for real-time wind farm flow prediction.
Evolution of the invariants of the velocity gradient tensor in a spatially transitional channel flow
Ze Yang, Jian Li, Feng Li, Pengyong Xie, Yuemin Ma, Feng Liu, Jian Fang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100704
[Abstract] (355) [PDF 3427KB] (12)
Abstract:
A direct numerical simulation was employed to investigate the topological features of spatially developing turbulent channel flows. All fluctuating velocity gradients, together with their statistical properties, were quantified at three separate streamwise regions (transition, non-equilibrium and equilibrium regions) and three different wall-normal locations that represent three significantly different fluid layers (viscous, buffer and outer layers). Our findings reveal that the transition region exhibits a backward energy transfer mechanism, as indicated by the positive skewness of the longitudinal velocity derivative. This phenomenon is notably evident for the buffer layer. The backward energy transfer process is correlated with anomalous topological manifestations in the invariant plane corresponding to the velocity gradient tensor, such as the Q-R plane (Q and R are the 2nd and 3rd invariants, respectively) in the transition region, which exhibits a unique “non-teardrop” shape, a striking departure from the canonical teardrop shape seen in equilibrium turbulent flows. This anomalous topology is associated with a predominance of tube-like structures, which is further confirmed by a negatively skewed intermediate eigenvalue of the strain-rate tensor. In contrast, the turbulent flows revert to the classical forward energy cascade in the non-equilibrium and equilibrium regions. In addition, the Schur decomposition of the velocity gradient tensor is adopted to analyze the non-local characteristics of the spatially developing transitional channel flows. In comparison with the non-equilibrium and equilibrium regions, the flows dominated by nonlocal effects extend farther along the wall-normal direction in the transition region. In the near-wall locations within the transition region, both the non-local statistics of enstrophy (or dissipation) and enstrophy production (or strain self-amplification) play a dominant role in the flow evolution compared with their local counterparts. The numerical results reported in this work are expected to provide critical physical insights into the intrinsic dynamics of the backward energy transfer process in spatially evolving turbulent channel flows.
Flight test validation of high-fidelity overset mesh predictions for UAV longitudinal dynamics
Ahmad Indra Siswantara, Angga Septiyana, Fadilah Hasim, Novita Atmasari, Prasetyo Ardi Probo Suseno, Eries Bagita Jayanti, Kurnia Hidayat, M. Gilang Pratama Putra, Danartomo Kusumoaji
Accepted Manuscript , doi: 10.1016/j.taml.2026.100702
[Abstract] (320) [PDF 4019KB] (0)
Abstract:
This research establishes a high-fidelity dynamic modeling framework for the Skywalker 1800 unmanned aerial vehicle (UAV) by integrating computational fluid dynamics (CFD) with flight test validation. To capture unsteady aerodynamic phenomena, overset (Chimera) mesh simulations were performed for plunging, pitching, and flapping motions. Stability derivatives were extracted using Fourier decomposition and rigorously validated against instrumented flight test data. System identification via the output error method was applied to both CFD-generated responses and real-world flight logs. Results reveal that the comprehensive set of stability derivatives extracted from the unsteady overset simulations including CLα, Cmα, Cmq, and Cmα provides a highly accurate foundation for mathematical modeling. When implemented into a 6-DoF longitudinal simulation, the predicted dynamic responses closely matched the actual flight test telemetry under identical control inputs. Minor discrepancies are attributed to aeroelastic effects inherent in the foam airframe. Ultimately, this study demonstrates that unsteady overset simulations are highly effective for capturing the complete aerodynamic characteristics essential for reliable UAV flight dynamics modeling.
Theoretical velocity limit of reluctance coilgun
Zhipeng Zhou, Songlin Cai, Xin Fang, Shiyuan Yan, Lanhong Dai, Guiji Wang, Mingqiang Jiang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100699
[Abstract] (335) [PDF 0KB] (0)
Abstract:
The reluctance electromagnetic coil gun is attractive for engineering and scientific applications because of its high launch-velocity precision. The velocity limit is fundamental to the application of reluctance coilguns. However, the physical mechanism governing this limit remains unclear. In this work, a theoretical model for the launch process is developed and validated experimentally. Dimensional analysis identifies three governing dimensionless numbers, including one electromagnetic Euler number and two Deborah numbers. The electromagnetic Euler number, i.e., the ratio of electromagnetic force to inertial force, determines the theoretical velocity limit. The two Deborah numbers describe the relationship between the current response time and projectile transit time. Suitable Deborah numbers are required to approach the velocity limit. Finally, the velocity limit is found to scale with the one-third power of the charging voltage. This work clarifies the coupling effects among the governing parameters of a reluctance coilgun.
Free Vibration Analysis of Thick Sandwich Cylindrical Shells with GPLRC faces and TPMS core
S. M. S. Sajjadieh, Y. Kiani
Accepted Manuscript , doi: 10.1016/j.taml.2026.100701
[Abstract] (323) [PDF 0KB] (0)
Abstract:
In this study, the vibration behavior of three-layer sandwich cylindrical shells with triply periodic minimal surface (TPMS) cores and graphene platelet (GPL) reinforced composite (RC) face sheets was analytically investigated. To accurately model the shear stress distribution in the thickness direction, high-order shear deformation theory (HSDT) was used, and the governing equations were derived using Hamilton’s principle. Then, assuming simply supported boundary conditions, these equations were solved analytically based on the Navier solution method to evaluate the natural frequencies explicitly with high accuracy. To evaluate the accuracy of the model, the results obtained from the analysis of FG-TPMS cores and GPLRC layers were compared with reputable studies available in the literature, and very good agreement was observed. Next, the effect of key parameters, including the core topology type (IWP, gyroid, and primitive), density distribution pattern (A and B), graphene weight fraction, layer thickness ratio, and geometric ratios, on natural frequencies was investigated. The results show that the B3 density pattern provides the greatest increase in stiffness and the greatest enhancement of natural frequencies, and increasing the thickness of the GPLRC layers causes a uniform increase in the frequency of the primary modes. The findings of this research can be used in the optimal design of lightweight structures with high dynamic performance, especially in mechanical and aerospace engineering applications.
Two-dimensional bulge evolution under a vertical magnetic field
Shuojun Teng, Junhua Pan, Mingjiu Ni
Accepted Manuscript , doi: 10.1016/j.taml.2026.100698
[Abstract] (295) [PDF 0KB] (1)
Abstract:
This study investigates the bulge behavior on the surface of a liquid metal pool within a fusion configuration. Emphasis is placed on the two-dimensional dynamic collapse and subsequent evolution of the bulge under the influence of a vertical magnetic field. The evolution process is characterized by two distinct stages: the collapse phase and the wave propagation phase. The bulge collapses downward under the combined action of gravity and the Lorentz force, generating a leading wave due to the surrounding outflow, which subsequently evolves into propagations. Utilizing weakly nonlinear shallow water theory, in conjunction with classical perturbation techniques and physical modeling, we derive the evolution equations governing the spreading and propagation behavior of the bulge evolution under a vertical magnetic field. Furthermore, scaling laws describing wave amplitude attenuation are obtained, which are validated against direct numerical simulations, demonstrating both accuracy and applicability. Therefore, the present work provides a theoretical basis and engineering reference for understanding the dynamic behavior of bulge phenomena in fusion divertors.
Mechanistic Insights into Turbulence-Induced Instability of Gas Layers in Superhydrophobic Microgrooves
Qiurui Zhang, Ziyin Wang, Bo Zhang, Yin Yao, Zhilong Peng, Ankang Gao, Shaohua Chen
Accepted Manuscript , doi: 10.1016/j.taml.2026.100703
[Abstract] (331) [PDF 2013KB] (2)
Abstract:
Drag reduction is of great importance in engineering applications, including underwater vehicles and long-distance pipeline transport. By trapping gas inside the microgrooves, the superhydrophobic surface can effectively reduce drag by replacing the liquid–solid interface with a liquid–gas interface. However, the gas layer is prone to instability under external disturbances, and the underlying mechanism remains insufficiently understood. In this study, we numerically investigate the instability of the gas layer confined in rectangular microgrooves using a coupled Reynolds-averaged Navier–Stokes (RANS) and volume-of-fluid (VOF) method. The results show that gas depletion under turbulent flow evolves through three distinct stages: impact compression, fracture and dispersion, and equilibrium retention. Most of the gas loss occurs during the initial impact-compression stage. Parametric studies indicate that increasing the groove length and depth, enlarging the Young’s contact angle, and reducing the groove width can effectively suppress gas loss during this stage. Further quantitative analysis reveals that the horizontal pressure difference between the liquid and gas phases is the primary factor governing gas depletion, playing a much more significant role than interfacial shear stress. The optimized geometric and wettability parameters enhance gas retention mainly by reducing this pressure difference. These findings clarify the pressure-driven mechanism responsible for gas-layer instability and provide quantitative guidance for the design of durable superhydrophobic drag-reduction surfaces operating under turbulent flow conditions.
Dynamic approach for investigation of integrated tensegrity-shell system using multi-particle position method
Angelo Vumiliya, Ani Luo, Heping Liu, Sanaullah, Andrés González-Fallas
Accepted Manuscript , doi: 10.1016/j.taml.2026.100690
[Abstract] (332) [PDF 3190KB] (0)
Abstract:
This work introduces a dynamic model for a tensegrity-shell structure using the multi-particle position method. The approach begins by removing rigid body motions to determine the deformation field of the structure and derives stresses in the axial elements through the endpoints positions (particles). The shell element strains are derived through the deformation gradient obtained by minimizing the relative displacement errors of particles. The projection of this value onto the direction of the particle of interest and its adjacent defines the particle strain, leading to stress derivation using the linear elastic model. This simplifies the elastic strain potential energy and, with kinetic energy, forms the Lagrangian equation. Unlike conventional finite element methods for shell elements, which rely on displacement variables, shape functions, and intricate strain computations, this approach establishes a straightforward relationship between the strains and particle positions, thus simplifying the expression for elastic potential energy for the formulation of the dynamic equation. Validation with commercial software and case studies confirms its accuracy and efficiency, showing its potential as a robust alternative for coupled discrete-continuum model dynamic analysis.
Stress-release-induced evolution of pore-fracturefracture morphology and connectivity in deep coal seams: a case study of the Daning–Jixian block
Wenjie Yao, Haifeng Zhao, Peiyuan Li, Jielun Luo, Yawei Li
Accepted Manuscript , doi: 10.1016/j.taml.2026.100697
[Abstract] (335) [PDF 5212KB] (0)
Abstract:
Despite its potential for deep coal seam stimulation, the large scale application of stress release technology remains limited by the lack of quantitative evaluation methods and physically interpretable models for parameter optimization. In this study, a controlled stress release experimental framework was established to investigate the effects of three key parameters, including the initial stress level, stress release magnitude, and stress release rate, on pore-fracture evolution in coal. High resolution micro CT scanning and three dimensional reconstruction were used to quantitatively characterize pore structure, throat geometry, and connectivity before and after stress release. The results show that stress release significantly increases reservoir porosity, connected pore volume, and coordination number, indicating enhanced pore connectivity and seepage capacity. A higher stress release rate of 1 MPa/min promotes microfracture activation and throat enlargement, whereas a larger stress release magnitude of 15 MPa further strengthens fracture connectivity and pore–throat coupling. Under higher initial stress conditions, stress release induces a more evident multi scale pore–throat response characterized by the simultaneous development of small pores, large pores, and intermediate to large throats. Based on these observations, a quantitative evaluation model for stress release effectiveness was established by relating stress release parameters to pore-fracture structural evolution. The model was validated using field data from the Daning–Jixian Block and shows good agreement with the observed production response. The proposed model provides a quantitative framework for evaluating stress release modification and optimizing stress release parameters in deep coalbed methane reservoirs.
Response characteristics analysis and theoretical prediction model of ultrahigh overload in penetration
Zhongchen Cao, Tao Li, Ran Jing, Jianli Shao, Qiming Liu, Baojun Shi
Accepted Manuscript , doi: 10.1016/j.taml.2026.100696
[Abstract] (306) [PDF 2439KB] (0)
Abstract:
Ultrahigh overload during projectile penetration governs the survivability of fuzes and onboard electronics, yet the transient peak overload remains difficult to predict. This work combines penetration experiments, validated numerical simulations, and dimensional analysis to establish a physically interpretable prediction model for the peak overload during normal penetration of ductile steel plates. Two projectile-target penetration experiments with different impact velocities and plate thicknesses are conducted to characterize the penetration morphology and velocity attenuation. The numerical model reproduces the residual velocity and perforation diameter with maximum errors below 2%. Based on the dominant inertial, geometric, strength, and wave-propagation parameters, a dimensionless nonlinear relation for peak overload is then derived and calibrated. An additional instrumented penetration experiment with an embedded high-g accelerometer measured a peak overload of 139,600 g, while the theoretical model showed an error of ∼6%. The proposed model provides a transparent and efficient tool for overload assessment, directly supporting the safety and reliability design of munitions.
Parametric modeling and optimization of rim-driven propulsor blades: insights into computational fluid dynamics and metamodeling
Afshar Kasaei, Wenjiang Yang, Javad Isavand
Accepted Manuscript , doi: 10.1016/j.taml.2026.100688
[Abstract] (357) [PDF 6880KB] (1)
Abstract:
Rim-driven propulsors (RDPs) are promising candidates for next-generation electrified propulsion systems because of their high efficiency, compact architecture, and reduced mechanical complexity. This study presents an integrated framework for the aerodynamic analysis and multiobjective optimization of RDP blade geometries by coupling high-fidelity computational fluid dynamics (CFD) with surrogate modeling and neural network-based optimization. A parametric design space is explored, including the chord distribution, number of blades, hub ratio, taper ratio, pitch angle, and key airfoil parameters such as thickness and camber characteristics. Kriging-based metamodels were first developed to accelerate design space exploration, achieving coefficients of prognosis (CoP) exceeding 96% for thrust, torque, and propulsive efficiency. Multiobjective optimization is conducted using the strength Pareto evolutionary algorithm 2 (SPEA2), with Pareto-optimal solutions ranked via the technique for order preference by similarity to the ideal solution method under equal objective weighting. To improve the predictive accuracy and robustness—particularly near design space boundaries—a complementary neural network surrogate is introduced. The neural network demonstrates low prediction error and strong agreement with the CFD results, outperforming the metamodel in terms of the regression evaluation metrics and Pareto-front similarity metrics. The optimized RDP designs achieve significant improvements in thrust and propulsive efficiency relative to the baseline configuration, with only moderate increases in torque demand. Flow-field analyses confirm that these gains stem from enhanced pressure differentials and more uniform blade loading. The proposed CFD-surrogate-neural network framework provides a robust and efficient methodology for RDP optimization and is readily applicable to electrified aviation, marine propulsion, and automotive applications.
Impact-Induced Jetting of Perforated and Liquid-Filled Sandwich Protective Structures: Design and Characterization
Huiyao Gao, Zhiyang Zhang, Qiyue Zhang, Dujiang Zhang, Tian Jian Lu, Zhenyu Zhao
Accepted Manuscript , doi: 10.1016/j.taml.2026.100689
[Abstract] (311) [PDF 2866KB] (0)
Abstract:
Internal blast loads typically exhibit complex waveforms and large cumulative impulses. Conventional antiblast structures are constrained in lightweight design, whereas blast suppression structures often suffer from insufficient reliability. Neither approach fully satisfies the growing demands for light weight, compactness, and high reliability in protective systems. To address this challenge, this study proposes an all-metallic liquid-filled sandwich structure with a perforated front panel. Impact tests using aluminum foam projectiles were conducted on purpose-designed and fabricated sandwich specimens. A numerical model combining smoothed particle hydrodynamics with the finite element method was developed to predict the dynamic response of the perforated liquid-filled sandwich. The results demonstrate that the proposed structure generates pronounced impact-induced liquid jetting along with a coupled transient structural response, providing a physical basis and design insights for subsequent blast protection studies.
Drag-thrust transition of a burst-and-coast flapping foil
Li-Ming Chao, Yunfeng Gao, Guozhen Ma, Xin Ma, Hexi Baoyin, Xiaomin Wang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100681
[Abstract] (362) [PDF 3118KB] (0)
Abstract:
Burst-and-coast locomotion is widely employed by flying and swimming animals, yet its influence on the drag-thrust transition of flapping foils placed in a uniform flow remains poorly understood. In this study, we numerically investigate a two-dimensional flapping foil undergoing burst-and-coast oscillation over a wide range of flapping kinematics and duty cycles. We show that burst-and-coast oscillation systematically shifts the drag-thrust boundary and derive a scaling relation that unifies burst-and-coast and continuous flapping within a single framework. The proposed formulation accurately predicts the drag-thrust transition across the parameter space examined. Wake visualisation further reveals that burst-and-coast oscillation generates a richer variety of vortex patterns than continuous flapping, although wake structures alone do not uniquely determine thrust generation. These results provide new insight into how temporal intermittency reshapes thrust generation and drag balance, with implications for the design of bio-inspired intermittent propulsion systems.
GPU-Parallelized Discrete Element Framework for Global Regolith Migration on Irregular Asteroid Surfaces
Zhi-Jun Song, Yang Yu, Jian-Yang Li
Accepted Manuscript , doi: 10.1016/j.taml.2026.100680
[Abstract] (439) [PDF 2625KB] (4)
Abstract:
Asteroid surfaces are commonly covered by regolith composed of unconsolidated granular material. Driven by microgravity and complex terrain, the regolith particles exhibits unpredictable flow characteristics, which presents major challenges for designing exploration missions and understanding asteroid evolutionary processes. To meet the specific needs of regolith modeling, this study advances an existing CPU–GPU hybrid discrete element method (DEM) by developing a highly specialized GPU-parallelized DEM for irregular asteroids. By substantially enhancing computational performance, this model overcomes traditional limitations that restrict DEM simulations to local scales, finally achieving true global-scale modeling of regolith dynamics. The validity and applicability of the code to real asteroid scenarios are confirmed through rigorous benchmark tests—namely, particle–particle collisions, particle–wall impacts, and the spin-up driven regolith evolution on asteroid 2008 EV5. Overall, our simulations demonstrate that the framework can securely handle actual particle sizes and realistic terrain, successfully reproducing key processes observed during space missions, such as grain-size segregation and mass shedding triggered by surface landslides.
Extended Morse potential modeling of bilayer transition metal dichalcogenides: Fermi-Dirac-like and built-in-Lennard-Jones truncations
Maryam Tajadod, Tang Shunjie, Zhu Xiaowan, Pan Douxing
Accepted Manuscript , doi: 10.1016/j.taml.2026.100682
[Abstract] (381) [PDF 2502KB] (1)
Abstract:
The interfacial potential plays a decisive role in governing the mechanical behavior and interlayer coupling physics of layered crystals, yet its development has been hindered by the scarcity of both mathematically reliable parameter sets and physically consistent truncation schemes. Here, we conduct a systematic parameterization of the classical Morse potential for nine representative 1T-phase transition metal dichalcogenides across five stacking configurations, including two antiparallel stackings and three parallel stackings, while proposing two distinct truncation schemes. First, we employ dispersion-corrected first-principles calculations to determine equilibrium interlayer distances, binding energies, and interfacial adhesion strengths. Subsequently, we derive static equilibrium equations, binding energy relations, and adhesion strength formulations from the Morse potential framework to analytically resolve three essential Morse parameters. For truncations, we introduce (1) a Fermi-Dirac-like form in the Morse-T1 model and (2) a built-in-Lennard-Jones form in the Morse-T2 model, collectively involving five parameters that are efficiently determined, achieving optimal convergence and stability. Comparative analysis reveals that Morse-T2 significantly outperforms Morse-T1 in predicting the energy-distance relationship of antiparallel stackings, attributable to the superior short-range correction capability of its built-in-Lennard-Jones truncation. When applied to parallel stackings, Morse-T2 further demonstrates excellent agreement with dispersion-corrected first-principles calculations in binding energy curves, suggesting its generalizability across broader 1T-phase dichalcogenides.
Solving compressible Navier‒Stokes equations using the feature-enhanced neural network
Jiahao Song, Wenbo Cao, Weiwei Zhang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100679
[Abstract] (598) [PDF 2188KB] (7)
Abstract:
Physics-informed neural networks (PINNs) have shown remarkable prospects in solving partial differential equations (PDEs) involving fluid mechanics. However, the method has thus far succeeded only in inviscid flows and incompressible viscous flows, while the solution of compressible viscous flows still faces significant challenges. In previous work, we proposed a feature-enhanced neural network (FENN), which enhances the ability of PINNs to approximate flows by introducing beneficial features into the network inputs, thereby improving the performance in solving PDEs. In this study, we extend the FENN to compressible viscous flows, which are governed by the compressible Navier–Stokes equations, including the continuity, momentum, and energy equations. By solving four forward problems under different flow conditions and geometries together with a parametric problem involving the angle of attack, we validate the effectiveness of the FENN. In contrast, existing advanced methods that are well established for inviscid flows and incompressible viscous flows fail in this scenario. To the best of our knowledge, this is the first time that a PINN-like method has successfully solved forward and parametric problems involving compressible viscous flows.
From structural heterogeneity to mechanical weakening: size effect in thick electrodes
Jinyang Huang, Huadong Gao, Yicheng Song, Bo Lu, Junqian Zhang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100676
[Abstract] (436) [PDF 1719KB] (1)
Abstract:
The pursuit of higher energy density through thick lithium-ion battery electrodes is fundamentally challenged by their increased susceptibility to cracking during fabrication. This work reveals that this failure stems from a pronounced size effect. As the active layer thickens, drying-induced binder migration creates a steeper gradient in porosity from top to bottom. This amplified mesostructural heterogeneity directly governs the macroscopic mechanical weakening. We developed a robust method using a soft substrate to fabricate damage-free, free-standing thick active layers for accurate tensile testing, which confirmed the systematic reduction in both modulus and strength with increasing thickness. Mesostructure-based finite element simulations establish a direct causal link, showing that the porosity gradient elevates local stress concentrations and reduces the effective load-bearing capacity. By establishing a mechanistic link between mesostructure and macroscopic performance, this study provides a critical foundation for designing high-energy-density thick electrodes.
Prediction of high-speed spatiotemporal turbulence based on Koopman neural operator
Kuijun Zuo, Sheng Zou, Siwei Dong, Tingting Li, Qianqian Shen
Accepted Manuscript , doi: 10.1016/j.taml.2026.100675
[Abstract] (640) [PDF 16291KB] (6)
Abstract:
Research on high-speed turbulent boundary layers is essential for drag reduction design in aerospace vehicles, and the emergence of artificial intelligence technologies has introduced an entirely new paradigm for such investigations. This paper develops a neural network architecture based on the Koopman operator for the temporal prediction of high-speed turbulent boundary layers. First, a direct numerical simulation of the lifting-body model was performed, yielding a windward region dataset for training and prediction with the neural operator model. Extensive qualitative and quantitative analyses demonstrate that the constructed Koopman operator model outperforms existing classical neural network and operator-based models in both memory consumption and training speed, while also achieving a substantial improvement in model interpretability. For turbulent boundary layers characterized by high-frequency features, the Koopman operator accurately captures small scale flow structures over short temporal intervals, while simultaneously achieving significant reductions in computational cost and memory requirements.
Electro-mechanical contact characterization model for bolted interfaces
Wanglong Zhang, Haiyang Zhang, Xueqi Zhang, Wurui Ta, Hui Cheng, Kaifu Zhang, Youhe Zhou
Accepted Manuscript , doi: 10.1016/j.taml.2026.100673
[Abstract] (413) [PDF 1355KB] (2)
Abstract:
The threaded contact interface is difficult to detect because of its complexity and internal contact characteristics, such as the squeezing contact between the thread of a shear bolt and the hole wall. How to non-destructively detect the contact force of the thread contact interface is the key issue to solve the problem of thread damage detection, which is highly important for the normal use of bolts. This paper aims to explore a new electrical measurement method that measures the contact force state between the thread of a shear bolt and the hole wall by measuring the squeezing contact electrical signal. However, owing to the influence of the helical structure, the contact force between the thread and the hole wall is very complex and includes both normal and shear forces. In this paper, contact forces are measured by measuring electrical signals under pressure. By combining the electrical contact model, a thread/hole wall electro-mechanical contact model is established, forming the principle of contact force measurement. Compared with traditional contact mechanics theory, this paper considers the influence of the helical configuration on the interface contact behavior, providing a theoretical reference for predicting bolt thread failure. The accuracy of the model was verified through experiments, with a maximum error of less than 10%. Further research and analysis were conducted on the parameters of the electro-mechanical contact model and actual engineering. This model can be used to measure the normal contact force between the shear thread and the hole wall, laying the foundation for detecting thread failure.
Simulation of pulse wave alterations induced by carotid artery stenosis: a foundation for noninvasive monitoring and diagnosis
Xuehang Sun, Zhiming Kong, Tianxiao Xu, Bensen Li, Yuning Pan, Fuxing Miao
Accepted Manuscript , doi: 10.1016/j.taml.2026.100674
[Abstract] (727) [PDF 2359KB] (19)
Abstract:
The carotid artery serves as the vital pathway connecting the heart to the brain. Over 60% of cerebral infarctions result from carotid artery stenosis, making this condition one of the leading threats to human health. Therefore, early diagnosis and effective management of carotid artery stenosis are of paramount importance. Currently, clinical diagnosis primarily relies on imaging examinations, including ultrasound, computed tomography angiography, magnetic resonance angiography, and digital subtraction angiography. However, these diagnostic methods inevitably carry varying degrees of side effects for the human body. Thus, this study proposes a novel method for the early prediction and diagnosis of carotid artery stenosis based on pulse waveform analysis using mechanical principles. Considering blood viscosity and vascular lumen stenosis rate parameters, a bidirectional fluid-solid coupling model of blood vessels was established for the stenotic carotid artery. By analyzing the effects of the stenosis rate on pressure drop responses at both ends of the plaque, axial velocity wave responses, and blood flow patterns at the bifurcation, a sensitive correlation was probed between the stenosis rate and pressure drops at both ends of the plaque along the blood flow direction. Furthermore, the intimal shear stress at the stenotic site significantly increases with increasing stenosis rate. These findings propose a novel approach for predicting and diagnosing carotid stenosis using pulse wave parameters, laying a theoretical foundation for the clinical assessment of disease progression.
Compressibility effects on secondary motions in turbulent square duct flows
Qingqing Zhou, Yonghao Zhao, Ming Yu, Xianxu Yuan
Accepted Manuscript , doi: 10.1016/j.taml.2026.100671
[Abstract] (437) [PDF 2358KB] (2)
Abstract:
This study employs implicit large-eddy simulation to investigate the compressibility effects of turbulent flows in square ducts across a range of bulk Mach numbers and bulk temperatures. We focus on the impact on secondary flows and the associated momentum and heat transport. The results show that secondary motions redistribute the wall shear stress and heat flux, generating a local peak near the duct corner at the highest Mach numbers. This is attributed to changes in the attenuation of the mean streamwise vorticity near the wall. While the generalized Reynolds analogy for the mean velocity and temperature fields remains valid, the resemblance between their fluctuations is weakened. This occurs because the large-scale secondary circulations become significant compared to turbulent fluctuations in the outer region, leading to a deviation of the turbulent Prandtl number from unity.
Flow of room-temperature ionic liquids through a charged conical nanopore under electric fields
Weiru Li, Xikai Jiang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100672
[Abstract] (412) [PDF 1240KB] (1)
Abstract:
Electric-field-driven flow and transport of room-temperature ionic liquids (RTILs) through nanopores underpin various applications, such as energy storage and nanopore sensing. In this work, we studied the flow of RTILs through a charged conical nanopore under electric fields using continuum simulations, in which a Landau-Ginzburg-type model was used to describe ion transport and the Navier-Stokes equation was used to predict the flow. We found a flow rectification phenomenon and fluid vortices in the system; fluid vortices were observed to occur near the nanopore base and the corner of the reservoir, which could be used to enhance the mixing of solutes in RTILs. In the initial constant-current charging process, nonmonotonic variations in flow rates through the system as a function of time were observed and traced to the formation of electrical double layers (EDLs) near the charged nanopore wall. This finding suggests a new method of using the flow rate as a macroscopic measure to detect EDL dynamics at the nanoscale, a process that is difficult to visualize directly in experiments.
Numerical study on the parachute inflation process under aircraft wake effect based on structured arbitrary Lagrange-Euler method
Yonghao Li, Rui Gao, Wei Jiang, Bowen Qiu, Li Yu
Accepted Manuscript , doi: 10.1016/j.taml.2026.100670
[Abstract] (462) [PDF 1622KB] (4)
Abstract:
In airborne and airdrop missions, the inflation performance of parachutes is significantly influenced by aircraft wakes. To improve the computational efficiency of numerical research, the structured arbitrary Lagrange-Euler (S-ALE) method is introduced in this paper to simulate the parachute inflation process in airborne and airdrop missions. On this basis, the comprehensive influence of aircraft wakes on the parachute inflation process is thoroughly investigated and analyzed in this paper. The results indicate that the S-ALE method is highly consistent with the arbitrary Lagrange-Euler (ALE) method in predicting the variations in key characteristics throughout the parachute inflation process. The relative error of the maximum opening load between the two methods is within 5%. The computational efficiency of the S-ALE method is approximately 22.5% higher than that of the ALE method. Furthermore, under the influence of the aircraft wake, the parachute inflation time is approximately 44% of that without the aircraft wake, and the maximum drag coefficient is approximately 128% of that without the aircraft wake. This study elucidates the influence of transport aircraft wakes on the parachute inflation process and provides a reference for modeling parachute fluid-structure interaction problems in large-scale scenarios.
Theory and Mechanisms of Mechanical Equilibrium Stability and Vibration Control in a Novel Tristable Meta-structure
Hongyu Li, Bin Ke, Zhu Liang, Ying Zhang, Narueporn Nartasilpa, Lu Zhang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100669
[Abstract] (420) [PDF 2003KB] (3)
Abstract:
Multistable mechanical meta-structures offer promising potential for energy dissipation and vibration control. However, existing analytical models still face some essential challenges and difficulties, including (i) providing explicit local-design guidance, (ii) characterizing tristability, (iii) constructing general phase diagrams, and (iv) quantifying vibration-control performance. To address these challenges, this paper proposes a novel axial tristable metamaterial structure by exploring the controlled buckling of a slender rod. The analytical model is established through equilibrium-stability analysis and validated using an energy-based formulation, enabling direct interpretation of parameter responses for engineering design. By introducing a dimensionless representation, a general phase diagram is constructed to illustrate the tristable response and rapidly optimize the design under prescribed variables. In addition, a frequency expression is derived through dynamic analysis to realize vibration tuning. Finite element simulations show close agreement with theoretical predictions, which validates the accuracy and applicability of the proposed framework. The results provide a general theoretical basis and practical design guidance for developing high-performance self-centering dampers with programmable tristable behavior.
Convergence-accelerated simplified unified wave-particle method via local time-stepping for 3D hypersonic non-equilibrium flow simulation
Sirui Yang, Chengwen Zhong, Hao Jin, Sha Liu, Congshan Zhuo
Accepted Manuscript , doi: 10.1016/j.taml.2026.100668
[Abstract] (436) [PDF 10287KB] (3)
Abstract:
Multiscale hypersonic flows involve high-temperature and rarefied gas effects, which pose significant challenges for accurate prediction using classical computational fluid dynamics. The simplified unified wave-particle (SUWP) method is an efficient multiscale method that classifies molecules into colliding and free-transport parts and evolves them using a Navier-Stokes (N-S) solver and a particle solver, respectively. For steady-state problems, the local time-stepping (LTS) technique accelerates the evolution of the flow field by enforcing flux conservation across cell interfaces, thereby substantially reducing computational cost. This technique has been widely adopted in multiscale deterministic methods, and analogous variable time-step strategies exist in the direct simulation Monte Carlo method. In this work, a convergence-accelerated simplified unified wave-particle method based on the LTS technique is developed to effectively reduce the computational cost. Compared to the original SUWP method, the proposed method demonstrates a speedup ratio of approximately four. The accuracy and efficiency of the proposed method are validated through three-dimensional test cases.
Performance evaluation and optimization analysis of series-augmented electromagnetic railguns using a multiphysics coupling model
Donghui Liu, Bo Sun, Zhiyang Shu, Baoqiang Zhang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100666
[Abstract] (431) [PDF 2156KB] (6)
Abstract:
Electromagnetic railguns convert electromagnetic energy into kinetic energy to propel projectiles to hypervelocity regimes, establishing them as cornerstone technologies for next generation weapon systems requiring high-precision, long-range strike capabilities. To further enhance the muzzle velocity of the projectile, series-augmented railgun configurations have been presented to optimize the energy density, addressing conventional constraints on acceleration efficiency. This study proposes a multiphysics coupling model, integrating H-formulation and an arbitrary Lagrangian‒Eulerian method, to evaluate the electromagnetic-thermal-mechanical performance of series-augmented electromagnetic railguns and guide their structural optimization design. The contact resistance and contact thermal conductance at the armature-rail interfaces are calculated using the energy variational method and the Cooper-Mikic-Yovanovich method, respectively. Moreover, the friction at the armature-rail interfaces is also considered in the simulation. The magnetic field and temperature estimated by the simulation are in agreement with those measured experimentally for conventional two-rail railguns. The computational results demonstrate that adopting an eight-rail architecture not only elevates the energy conversion efficiency but also boosts the muzzle velocity of the projectile to 30.94% above that of a two-rail railgun, thereby validating the performance advantages of multirail configurations in electromagnetic launch systems. The effect of the number of rails on the fatigue life of the armature is discussed. Thermal analysis also reveals that the accumulation of localized heat at the armature-rail interface is caused by the friction between the armature and rails. This work provides a theoretical framework for multiphysics optimization in the design of series-augmented electromagnetic railguns.
Finite element-based design and analysis of lattice-structured lumbar interbody fusion cages for additive manufacturing applications
S Meganathan, M Sunil Kumar, MS Alphin, Mehar Kulmani, K Kamakshi Priya, Smerat Aseel
Accepted Manuscript , doi: 10.1016/j.taml.2026.100665
[Abstract] (454) [PDF 2445KB] (2)
Abstract:
This study presents the development and biomechanical assessment of a finite element model for lumbar interbody fusion cages incorporating three distinct lattice architectures—body-centered cubes (BCCs), face-centered cubes, and face diagonal cubes (FDCs)—fabricated using additive manufacturing. Two commonly used biomaterials, polyether ether ketone (PEEK) and Ti-6Al-4 V titanium alloy, were considered for cage construction. The validated L4–L5 lumbar spine segment was subjected to physiological loading conditions comprising a pure moment of 7.5 Nm and an axial follower load of 280 N across six primary postures: flexion, extension, left and right lateral bending, and left and right axial rotation. The analysis focused on total deformation and von Mises stress (VMS) distribution in both the cages and vertebral endplates. The results revealed that the FDC lattice PEEK cage experienced the highest deformation of 0.623 mm during lateral bending, while the BCC lattice made of Ti-6Al-4 V exhibited the lowest VMS of 119 MPa, demonstrating superior load-bearing behavior. Endplate stress analysis indicated that the BCC lattice with PEEK effectively reduced localized stresses at the L4 and L5 interfaces, confirming favorable biomechanical compatibility. These outcomes emphasize the combined influence of lattice geometry, material selection, and spinal posture on implant performance, offering valuable guidance for optimizing interbody fusion device designs.
A stable least squares finite difference-based fractional step lattice Boltzmann method for incompressible flows
Yang Xiao, Kangle Chen, Liming Yang
Accepted Manuscript , doi: 10.1016/j.taml.2026.100664
[Abstract] (389) [PDF 2553KB] (2)
Abstract:
In this work, a fractional step lattice Boltzmann method (FS-LBM) enhanced by the least-squares finite difference (LSFD) approach is proposed to simulate incompressible flows. The conventional FS-LBM consists of prediction and correction steps, with the latter typically involving the solution of an anti-diffusion equation that requires discretizing the Laplacian operator. Previous studies have employed discretization schemes such as the central difference (CD) stencil and the finite difference stable stencil (SS). While the SS stencil improves numerical stability, it does so at the cost of considerably reduced accuracy compared with the CD stencil. To achieve a better balance between accuracy and stability, the LSFD method is introduced to discretize the Laplacian operator. The proposed method is validated through two- and three-dimensional isothermal and thermal flows. Numerical results demonstrate that the FS-LBM with LSFD maintains second-order convergence, offers superior stability compared to both CD and SS stencils, and achieves higher accuracy than the SS stencil. Furthermore, analysis of weighting functions within the LSFD framework shows that an appropriate choice of weighting function can significantly enhance accuracy, with the W2 weighting function performing best in 2D cases and W5 in 3D cases.
Large language model-assisted sensitivity analysis and parameter optimization in computational fluid dynamics
Chen Yuxuan, Zhang Long, Zhu Xu, Zhou Hua, Ren Zhuyin
Accepted Manuscript , doi: 10.1016/j.taml.2026.100660
[Abstract] (661) [PDF 3535KB] (14)
Abstract:
Integrating natural language interfaces with computational fluid dynamics (CFD) workflows presents transformative opportunities for both industry and research. In this study, we introduce OptMetaOpenFOAM, an innovative framework that employs a large language model (LLM)-driven multiagent architecture to automate sensitivity analyses and parameter optimization tasks in CFD via natural language instructions. By automating complex tasks via natural language inputs, the framework empowers nonexpert users to perform sensitivity analyses and parameter optimizations with markedly improved efficiency. The framework's efficacy is demonstrated through comprehensive testing across 11 distinct CFD tasks—including fluid flow, combustion, and heat transfer—originating from standard OpenFOAM tutorials and an external validation case involving hydrogen combustion chamber optimization. Remarkably, concise natural language commands (∼200 characters) successfully triggered elaborate computational sequences involving simulation setup, postprocessing, sensitivity analysis, and parameter optimization, translating into over 2,000 lines of automated code execution. These outcomes highlight the considerable potential of LLM-driven methodologies to advance CFD capabilities, offering enhanced accessibility, accuracy, and efficiency for both research-oriented and industrial CFD applications. The code is available at https://github.com/Terry-cyx/MetaOpenFOAM.
A structural fatigue life assessment method based on an unequal interval stress range distribution and an improved Manson‒Halford cumulative damage model
Chen Daoyun, Luo Caiying, Zhu Weiqiang, Deng Miao, Zhong Minshi, Liu Xinlong, Yang Wenbin, Xiao Qian, Zhu Haiyan
Accepted Manuscript , doi: 10.1016/j.taml.2026.100657
[Abstract] (470) [PDF 2997KB] (10)
Abstract:
Structural fatigue life assessment involves compiling stress cycle data and applying damage theory for analysis and prediction. However, traditional equal interval compilation methods can introduce errors owing to improper stress grading, and conventional linear cumulative damage models often yield low prediction accuracy. To address these issues, this paper introduces a fuzzy clustering approach for unequal interval classification and demonstrates its superiority through damage error comparisons. Furthermore, an enhanced Manson‒Halford model that incorporates strength degradation and load interaction effects is employed to evaluate the remaining life of various materials. The accuracy of this improved model is confirmed via comprehensive comparative analyses across various loading conditions and damage models. Ultimately, by integrating the unequal interval stress range distribution with the refined Manson‒Halford cumulative damage model, this study achieves reliable and accurate structural fatigue life predictions, thus providing a robust framework for fatigue assessments in engineering applications.
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Research Article
A hydraulic fracture and natural fracture interaction criterion considering the influence of intermediate principal stress and T-stress
Haifeng Zhao, Wang Zhang, Hongwei Shi, Hong Guo, Yawei Li
Theoretical and Applied Mechanics Letters  16 (2026) 100645.   doi: 10.1016/j.taml.2025.100645
[Abstract] (650) [PDF 2507KB] (21)
Abstract:
Unconventional reservoirs such as shale and tight sandstone exhibit low porosity and low permeability. By applying horizontal wellbore fracturing techniques, a fracture network with a certain degree of complexity can be created within the reservoir to enhance oil and gas recovery. The interaction between hydraulic fracture(HF) and natural fracture(NF) plays a crucial role in determining the complexity of the fracture network. This study examines the interaction process between HF and NF, using the unified strength theory as the fracture initiation criterion for the fracture on the opposite side of natural fractures, and considering the influence of T-stress on the radius of the nonlinear zone. An interaction criterion that accounts for both intermediate principal stress and T-stress effects is proposed, and the predictions are highly consistent with experimental results. The results of the sensitivity analysis indicate that T-stress influences the critical radius of the nonlinear zone, thereby causing disturbances in the magnitude of induced stress. With T-stress taken into account, the extent of the penetration zone increases, and the extent of the opening zone decreases. However, at high approach angles, the influence of T-stress diminishes. As the Poisson’s ratio, cohesion, and fracture toughness increase, the tensile strength decreases, making HF more likely to penetrate NF, resulting in a single fracture morphology. A lower stress differential and a lower tensile-to-compressive ratio promote the opening of natural fractures. Additionally, as the intermediate principal stress coefficient increases, the ranges of the opening and slip zones expand, while the penetration zone shrinks.
Experimental study on the effects of joint span and shape on crack initiation and propagation in PMMA plates by the caustics method
Houtian Zhang, Qishen Wang, Jianyin Lei, Peng Qiu, Zhifang Liu, Zhihua Wang
Theoretical and Applied Mechanics Letters  16 (2026) 100646.   doi: 10.1016/j.taml.2025.100646
[Abstract] (565) [PDF 3373KB] (16)
Abstract:
This study employed a dynamic caustics system integrated with a Hopkinson pressure bar, Schlieren optics, and a high-speed camera to investigate how joint span and shape affect crack initiation and propagation. First, crack penetration into joints with different spans (10 mm, 30 mm, 50 mm) and different shapes (“u” and “n”) was visualized. Then, crack-tip stress intensity factors and propagation velocity were measured by high-speed caustics patterns. Finally, fractal dimensions of crack trajectories were obtained to quantitatively evaluate the complexity of the crack layout. Based on loading time, the crack behavior is divided into 4 phases: first precrack initiation, propagation toward the joint, secondary initiation from the joint and final propagation toward the boundary. Since the phase 1 duration increases with span, crack initiation from precracks clearly depends on span length. In phases 2 and 3, reflected waves occur from the joint interface; furthermore, they are confirmed to be Rayleigh waves through wave velocity. Meanwhile, the reflected Rayleigh waves from the “n”-shaped joint have a significant effect on crack propagation in phase 2. In phase 4, crack trajectories initiating from joint ends are heavily influenced by joint span, which is associated with crack interaction. Furthermore, different opening orientations (“u” and “n”) of arc-shaped joints have different effects on crack behavior. The “u”-shaped joint exhibits crack behavior similar to that of same-span line-shaped joints. The “n”-shaped joint demonstrates a strong fracture resistance. This work advances the understanding of fracture resistance as influenced by joint span and shape variations.
A regularization technique for accurate reconstruction of numerical solution of wave propagation problems
Salvatore Lopez
Theoretical and Applied Mechanics Letters  16 (2026) 100648.   doi: 10.1016/j.taml.2025.100648
[Abstract] (541) [PDF 3671KB] (1)
Abstract:
In the numerical solution of wave propagation problems, spurious oscillations occur in the exact time integration of the related equation of motion. This is due to the high frequencies introduced by the spatial discretization, given the small size of the mesh elements and the integration step required to capture the wave phenomena. Currently, an answer to this problem is given by the use of the smoothing properties, intrinsic to the scheme or obtained through artificial viscosity, of dissipative time integration methods. More recently, in an alternative approach to the problem, the solution has been regularized via a post processing smoothing technique. In particular, on the basis of an initial nondissipative scheme, at a fixed observation time a series of steps of an appropriate dissipative time integration method achieves the desired smoothing. However, in both approaches, as the dissipative steps are performed, the noise progressively decreases, but the important values related to the peak regions of the solution degrade significantly. Here we describe a regularization process that automatically returns a solution where the noise has been eliminated but does not affect the significant regions of the solution. The presented technique recognizes the flat or peak shapes of the original solution among the oscillating components representing the noise. Operationally, the presented algorithm, starting from a nondissipative step-by-step scheme for time integration, iteratively smooths the related kinematic quantities and finally recovers the regularized solution as a suitable composition of smoothed and unsmoothed subdomains.
Shock wave propagation of nest-like structures under axial impact
Chang Liu, Qing Peng, Yueguang Wei, Xiaoming Liu
Theoretical and Applied Mechanics Letters  16 (2026) 100649.   doi: 10.1016/j.taml.2025.100649
[Abstract] (525) [PDF 2849KB] (9)
Abstract:
Inspired by natural bird nests, nest-like structures consist of randomly packed slender particles confined within a container. This study investigates the dynamic behavior of nest-like structures by finite element simulation and a shock model. Under dynamic impact conditions, the nest-like structures exhibit distinct mechanisms compared to quasistatic loading. A confined deformation zone with nearly uniform stress forms near the loading end. This zone propagates steadily into the undeformed region at a constant velocity. Notably, the expansion speed exceeds the loading rate but remains significantly slower than the stress wave speed in solid material. We proposed a rigid-perfectly plastic-locking shock model to quantitatively establish how initial conditions govern two critical dynamic responses: the stress in the confined zone and the expansion velocity of the confined zone. These dynamic characteristics of nest-like structures demonstrate their potential for impact resistance.
Casting computational fluid mechanics into a convex quadratic optimization framework
Hussam Sababha, Haithem Taha, Mohammed Daqaq
Theoretical and Applied Mechanics Letters  16 (2026) 100651.   doi: 10.1016/j.taml.2025.100651
[Abstract] (492) [PDF 999KB] (1)
Abstract:
We employ the principle of a minimum pressure gradient to transform problems in unsteady computational fluid dynamics (CFD) into a convex optimization framework subject to linear constraints. This formulation permits solving, for the first time, CFD problems efficiently via well-established quadratic programming tools. The proposed approach is demonstrated via three benchmark examples. In particular, through comparison with traditional CFD tools, the proposed framework is capable of predicting the flow field in a lid-driven cavity, in a uniform pipe (Poiseuille flow), and that past a backward facing step. The results highlight the potential of the method as a simple, robust, and potentially transformative alternative to traditional CFD approaches.
Continuous image representation based on deep learning for reducing interpolation bias in DIC
Lianpo Wang, Zhaoyang Lei
Theoretical and Applied Mechanics Letters  16 (2026) 100652.   doi: 10.1016/j.taml.2025.100652
[Abstract] (510) [PDF 3484KB] (4)
Abstract:
After more than forty years of development, the accuracy of digital image correlation (DIC) methods has reached an extremely high level. However, the interpolation bias of DIC has not been resolved. With the flourishing of deep learning in the field of image superresolution, it has become possible to use deep learning-based image superresolution methods to reduce DIC interpolation bias. To achieve this goal, this paper improves the local implicit image function (LIIF) method based on the characteristics of speckle images to obtain LIIF-S, achieving continuous image representation and arbitrary resolution interpolation. Subsequently, LIIF-S is used as the interpolation algorithm of the inverse compositional-Gaussian Newton (IC-GN) method to reduce the interpolation bias. The simulation experiment results show that LIIF-S not only improves the accuracy by more than one order of magnitude compared to traditional interpolation algorithms but also that the interpolation bias does not have sinusoidal characteristics. In addition, the effectiveness and generalization of the LIIF-S method in unseen real-world scenarios have also been demonstrated through physical experiments. The code and dataset are publicly available at https://github.com/LianpoWang/SLIIF.
Establishment of the damage tolerance criterion of projectile-borne electronics in the high-g extreme environment
Weilong Yang, Qiming Liu, Tao Li, Xu Han
Theoretical and Applied Mechanics Letters  16 (2026) 100653.   doi: 10.1016/j.taml.2026.100653
[Abstract] (516) [PDF 3671KB] (3)
Abstract:
Projectile-borne electronics are essential components for precision-guided munitions. However, they are subjected to a complex overload environment characterized by high-frequency vibrations, high temperatures, and high pressures during launch. Evaluating overload damage presents a significant challenge. Consequently, this study aims to establish a damage tolerance criterion for projectile-borne electronics in high-g extreme environments using impact overload tests and high-precision numerical simulations. Initially, an impact overload test device was designed and implemented, considering the guidance segment and chamber firing characteristics, to ascertain the overload damage characteristics of projectile-borne electronics. Subsequently, a simulation model incorporating projectile-borne electronics was established and validated to identify the most vulnerable regions and critical overload responses under various conditions. Based on the simulation data, the overload damage tolerance curve was established using a power function regression fitting method. Leveraging the concept of impulse equivalence, the damage tolerance criterion for the high-g extreme environment was formulated. The criterion’s accuracy and practicality were further verified through experimental damage results of electronic components. This study provides a practical design foundation for the anti-high-overload design of projectile-borne electronics.
Confinement effect on phase behavior and critical properties of pure/mixed n-alkanes in shale quartz nanopores: Insights from Gauge-Gibbs ensemble Monte Carlo simulation
Yifan Li, Jun Yao, Hai Sun, Yongfei Yang, Junjie Zhong
Theoretical and Applied Mechanics Letters  16 (2026) 100655.   doi: 10.1016/j.taml.2026.100655
[Abstract] (460) [PDF 3433KB] (5)
Abstract:
Shale formations contain many pores 2–50 nm in size. These pores can make up more than 20% of the total pore volume. In such small pores, interactions between the pore walls and fluids cannot be ignored. This leads to significant confinement effects on the fluids. Alkanes are the main components of shale oil and gas. Their thermodynamic properties are key to understanding the distribution, efficient extraction, and industrial application of shale reserves. In this study, we used molecular simulations to study the phase behavior of methane, n-dodecane and n-eicosane in shale nanopores. We compared how chain length affects their phase behavior. First, we optimized the critical exponent values to improve the calculation accuracy of the critical parameters. To quantitatively evaluate confinement effects, we investigated the vapor-liquid equilibrium and critical properties of n-alkanes in nanopores with different pore sizes and geometries. The results show that in water-wet hydroxylated silica pores, the shifts in confined critical properties of n-alkanes do not exhibit a clear carbon chain length dependence. Based on the simulation results, we established predictive models for the critical properties of pure fluid. Finally, using a multicomponent shale oil reservoir as an example, we explored the influence of confinement effects on phase diagrams and the evolution of fluid component distribution during the pressure depletion process.
Large eddy simulation of dust transport using the regularized lattice Boltzmann method
Tao Liu, Jinlong Lin, Xuhui Li, Yongliang Feng
Theoretical and Applied Mechanics Letters  16 (2026) 100656.   doi: 10.1016/j.taml.2026.100656
[Abstract] (484) [PDF 3142KB] (9)
Abstract:
HighlightA numerical framework is developed for dust transport by coupling the regularized lattice Boltzmann method (RLBM) with large eddy simulation (LES) in an Eulerian–Eulerian formulation. The model incorporates wall-modeled LES through a wall shear stress treatment and adopts a recursive regularization strategy to enhance numerical stability for high Reynolds turbulence. Dust transport is modeled using an additional distribution function governed by an eddy-diffusion-based paradigm. The model is validated using two benchmark cases: the inviscid Taylor-Green vortex with dust and a high-Reynolds-number turbulent channel flow. It is then applied to simulate dust transport in the atmospheric boundary layer, where large-scale coherent structures drive lateral dispersion and influence vertical transport and particle residence time. The effects of particle size are systematically examined, showing that larger particles exhibit stronger settling due to inertia, while smaller particles remain suspended through enhanced coupling with turbulence. A negative correlation between streamwise velocity and particle concentration is also identified, highlighting the interaction between turbulent flow structures and particulate transport.
Development of a large language model-driven intelligent agent for predicting relative permeability in oil and gas reservoirs
Jiulong Wang, Yuanchun Zhou, Xuhui Zhang, Junming Lao, Hongqing Song
Theoretical and Applied Mechanics Letters  16 (2026) 100658.   doi: 10.1016/j.taml.2026.100658
[Abstract] (516) [PDF 1904KB] (11)
Abstract:
To address the challenges and difficulties in predicting the relative permeability of reservoirs using traditional physics-driven and data-driven approaches, this paper proposes a collaborative analysis intelligent agent for the relative permeability of oil and gas reservoirs based on a large model. By constructing a multiagent collaborative workflow, integrated collaboration of data, models, and analysis results is achieved. The intelligent agent automatically completes data preprocessing, feature extraction, parameter calibration, small model calling, and output and evaluation of prediction results based on preset task dependencies. At the same time, by introducing deep learning-based embedding of physical information, the analysis efficiency and accuracy are significantly improved. The results show that compared with traditional physical analysis methods, this method improves the accuracy of reservoir relative permeability prediction by 10%, has a computational efficiency 10 times higher than traditional deep learning algorithms, and a computational speed 100–1,000 times higher than conventional physical models. This study further enhances the efficiency and intelligence of physical property analysis of oil and gas reservoirs, providing a new research direction for the intelligent development of oil and gas digitization.
On the mean-velocity scaling in the turbulent piston boundary layer of a motored internal-combustion engine
Max Hasenzahl, Suad Jakirlić, Christian Hasse
Theoretical and Applied Mechanics Letters  16 (2026) 100667.   doi: 10.1016/j.taml.2026.100667
[Abstract] (360) [PDF 3354KB] (3)
Abstract:
The turbulent flow in internal combustion engines is inherently complex due to moving geometries and time-varying topologies. This complexity is reflected in the wall-bounded regions, where experimental and numerical studies have reported velocity profiles that deviate substantially from classical turbulent boundary-layer behavior, often lacking a distinct logarithmic region. However, a systematic assessment of the applicability of established mean-velocity scaling methods under such conditions has not yet been performed. Here, we investigate the mean velocity within the boundary layer developing on the piston surface of a motored internal combustion research engine, for which experimental and numerical high-resolution near-wall boundary layer data have recently become available. Several scaling and transformation approaches are examined in terms of their ability to provide universal mean-velocity profiles relative to the classical logarithmic wall law. The results show that none of the tested transformations achieves a universal collapse of the velocity profiles across different piston locations and crank-angle positions. At the piston center, however, the semi-local scaling and the Trettel-Larsson (TL) transformation yield an effective collapse of the mean profiles. Nevertheless, none of the transformations fully aligns the profiles with the classical logarithmic law, with the TL transformation performing best in this regard. These findings confirm and quantify that the absence of a distinct logarithmic region is an inherent feature of the engine boundary layer.
Investigation of cavitation flow characteristics and vortex structures on a new lifting-body model
Yuan Lu, Tezhuan Du, Yongjiu Wang, Guoxin Yang, Yiwei Wang, Jingzhu Wang, Renfang Huang
Theoretical and Applied Mechanics Letters  16 (2026) 100678.   doi: 10.1016/j.taml.2026.100678
[Abstract] (383) [PDF 2145KB] (6)
Abstract:
This paper employs a new lifting-body model investigated through a cavitation tunnel, in which high-speed photography is combined with large eddy simulation to analyze flow characteristics under different cavitation numbers. The simulated cavity structures agree well with the experimental observations. Particular attention is given to the evolutionary characteristics of leading-edge vortex cavitation. The results demonstrate that the spiral vortex structure formed at the leading edge develops without periodic vortex shedding. Through analysis of vortex structures and surface pressure distribution, it is revealed that the secondary vortex induced by flow separation exhibits significant correlation with surface pressure, while increasing the cavitation number does not alter the established separation pattern.
article
Moment flux-based discrete velocity method based on the Boltzmann-BGK equations along the characteristic line
Wei Liu, Yong Liu, Haihu Liu
Theoretical and Applied Mechanics Letters  16 (2026) 100654.   doi: 10.1016/j.taml.2026.100654
[Abstract] (421) [PDF 4876KB] (11)
Abstract:
This paper introduces an improved scheme based on the discrete velocity method. Specifically, the reconstruction of the velocity distribution function and numerical flux at the interface is founded on the solution of the Bhatnagar-Gross-Krook equation along the characteristic line. The proposed method accurately considers molecular transport and collision effects at the interface, thereby enabling accurate modeling from rarefied to continuum flow regimes. Additionally, the implicit discretization of the microscopic equations and incorporation of macroscopic equations result in accelerated convergence properties for steady-state problems. The proposed numerical approach is validated through several cases, including Rayleigh flow, lid-driven cavity flow, flow past an NACA0012 airfoil, and supersonic flow around a sphere. Numerical results demonstrate that the proposed method can efficiently and accurately obtain multiscale flow properties.
Comparison and applications of solid weighting functions for fluid-particle modeling using the lattice Boltzmann-discrete element coupling method
Duo Wang, Yuman Han, Yi Zheng, Songyan Wang, Xiaofang Jiang, Shiyi Jiang, Mengdi Sun, Zhejun Pan
Theoretical and Applied Mechanics Letters  16 (2026) 100662.   doi: 10.1016/j.taml.2026.100662
[Abstract] (447) [PDF 2908KB] (8)
Abstract:
This paper presents a comparative study of the solid weighting functions within the text of the modified partially saturated method (MPSM), which is an effective fluid-solid boundary condition in the lattice Boltzmann-discrete element coupling method (LBM-DEM). In its original form, the solid weighting function is τ-dependent. Past studies have shown that the computational drag is viscosity-dependent when using the τ-dependent solid weighting function to solve fluid-particle interactions. To address this issue, two modified solid weighting functions, namely, the higher-order function and the solid-coverage function, are proposed. Nevertheless, the literature lacks a comparison of these functions, especially for viscosity dependence. In this study, the solid weighting functions are implemented and tested through two benchmark multiphase configurations, i.e., a sphere settling between two parallel plates and the ‘drafting, kissing and tumbling’ of two settling spheres. The computational accuracy, viscosity dependence and convergence of the two modified functions are validated and compared against the original τ-dependent function. The LBM-DEM-MPSM formulation is then applied to study the settling behavior of a particle pack with varying solid fractions in a narrow fracture, which highlights the potential of employing the LBM-DEM-MPSM approach to a broader range of fluid-particle systems.
Investigation on Savonius turbine technology as harvesting instrument of non-fossil energy: Technical development and potential implementation
Aditya Rio Prabowo, Dandun Mahesa Prabowoputra
2020, 10(4): 262-269   doi: 10.1016/j.taml.2020.01.034
[Abstract](4103) [FullText HTML](2095) [PDF 3192KB](160)
Crack propagation simulation in brittle elastic materials by a phase field method
Xingxue Lu, Cheng Li, Ying Tie, Yuliang Hou, Chuanzeng Zhang
2019, 9(6): 339-352   doi: 10.1016/j.taml.2019.06.001
[Abstract](4039) [FullText HTML](2237) [PDF 3845KB](149)
Mechanistic Machine Learning: Theory, Methods, and Applications
2020, 10(3): 141-142   doi: 10.1016/j.taml.2020.01.041
[Abstract](11428) [FullText HTML](2002) [PDF 4844KB](143)
Physics-informed deep learning for incompressible laminar flows
Chengping Rao, Hao Sun, Yang Liu
2020, 10(3): 207-212   doi: 10.1016/j.taml.2020.01.039
[Abstract](4260) [FullText HTML](2441) [PDF 4226KB](135)
On the Weissenberg effect of turbulence
Yu-Ning Huang, Wei-Dong Su, Cun-Biao Lee
2019, 9(4): 236-245   doi: 10.1016/j.taml.2019.03.004
[Abstract](3706) [FullText HTML](1838) [PDF 2579KB](134)
Dynamic mode decomposition and reconstruction of transient cavitating flows around a Clark-Y hydrofoil
Rundi Qiu, Renfang Huang, Yiwei Wang, Chenguang Huang
2020, 10(5): 327-332   doi: 10.1016/j.taml.2020.01.051
[Abstract](3891) [FullText HTML](1946) [PDF 2862KB](114)
On the interaction between bubbles and the free surface with high density ratio 3D lattice Boltzmann method
Guo-Qing Chen, A-Man Zhang, Xiao Huang
2018, 8(4): 252-256   doi: 10.1016/j.taml.2018.04.006
[Abstract](3767) [FullText HTML](2253) [PDF 2725KB](113)
Secondary flows in statistically unstable turbulent boundary layers with spanwise heterogeneous roughness
Ali Amarloo, Pourya Forooghi, Mahdi Abkar
12 (2022) 100317   doi: 10.1016/j.taml.2021.100317
[Abstract](1150) [PDF 18599KB](111)
Multiscale mechanics
G.W. He, G.D. Jin
11 (2021) 100238   doi: 10.1016/j.taml.2021.100238
[Abstract](2715) [FullText HTML](1966) [PDF 2196KB](106)
Physics-constrained bayesian neural network for fluid flow reconstruction with sparse and noisy data
Luning Sun, Jian-Xun Wang
2020, 10(3): 161-169   doi: 10.1016/j.taml.2020.01.031
[Abstract](2907) [FullText HTML](832) [PDF 2974KB](103)
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Computer simulation of Cu: ALOOH/Water in a microchannel heat sink using a porous media technique and solved by numerical analysis AGM and FEM TAML editorial board member Prof. Yihui Zhang and his collaborators developed a novel microlattice design for 3D shape programming TAML 2021 Awards TAML‘s Author and His Team Win the State Second-Class Natural Sciences Award of 2014 TAML‘s Author and His Team Win the State Second-Class Natural Sciences Award of 2015 Congratulations to Theoretical and Applied Mechanics Letters 2015 Best Paper Award Winners Congratulations to Theoretical and Applied Mechanics Letters 2014 Best Paper Award Winners Theoretical and Applied Mechanics Letters is indexed in CSCD and Scopus
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