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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] (0) [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] (0) [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] (6) [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] (29) [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] (32) [PDF 2134KB] (0)
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] (50) [PDF 4206KB] (0)
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] (89) [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] (81) [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] (80) [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] (92) [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] (80) [PDF 0KB] (0)
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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] (85) [PDF 2013KB] (1)
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] (115) [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] (92) [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] (85) [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] (93) [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] (94) [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] (111) [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] (194) [PDF 2625KB] (2)
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] (117) [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] (268) [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] (176) [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] (246) [PDF 16291KB] (5)
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] (177) [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] (407) [PDF 2359KB] (18)
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] (187) [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] (182) [PDF 1240KB] (0)
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] (171) [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] (177) [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] (174) [PDF 10287KB] (2)
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] (211) [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] (211) [PDF 2445KB] (1)
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] (185) [PDF 2553KB] (0)
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] (383) [PDF 3535KB] (13)
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] (212) [PDF 2997KB] (5)
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] (347) [PDF 2507KB] (12)
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] (287) [PDF 3373KB] (6)
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] (293) [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] (303) [PDF 2849KB] (6)
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] (260) [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] (263) [PDF 3484KB] (2)
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] (269) [PDF 3671KB] (0)
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] (229) [PDF 3433KB] (0)
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] (235) [PDF 3142KB] (2)
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] (270) [PDF 1904KB] (5)
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] (181) [PDF 3354KB] (2)
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] (187) [PDF 2145KB] (0)
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] (205) [PDF 4876KB] (0)
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] (208) [PDF 2908KB] (1)
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.
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