Theoretical and Applied Mechanics Letters

Online First
Current Issue
Special Issue
Archive
Most Downloaded

Display Method：

Low-Computational Time and Accurate Classification of Flow Regimes in Bubble Columns for Aquaculture Aeration Using Probability Density Functions of Bubble Velocity Standard Deviation

Natee Thong-Un, Wongsakorn Wongsaroj, Jirayut Hansot, Weerachon Treenuson, Hiroshige Kikura

Accepted Manuscript , doi: 10.1016/j.taml.2025.100598

[Abstract] (0) [PDF 2160KB] (0)

Abstract:
This study explores the combination of ultrasound technology with a detection algorithm to categorize flow regimes in bubble columns used for aeration in aquaculture. An ultrasonic velocity profiler is used to obtain the standard deviation of the bubble velocity distributed throughout the column. The bubble velocity data for three known flow regimes were used to develop a probability density function (PDF) classification model. The experimental apparatus consisted of a circular tank equipped with a bubble generator and gas hold-up monitoring systems. The flow regimes of the experimental fluid were determined, and the classification was conducted via the PDF method. The results demonstrate that the classification accuracy is not lower than that of traditional machine learning methods.

Investigation of unsteady ventilated partial cavitating flow around an axisymmetric body with particular emphasis on the vortex structure

Deshuai Cui, Xinran Liu, Tairan Chen, Guoyu Wang

Accepted Manuscript , doi: 10.1016/j.taml.2025.100596

[Abstract] (78) [PDF 1661KB] (2)

Abstract:
This paper investigates the ventilated cavity phenomena of a symmetric body under specific conditions, focusing on the factors affecting the vortex structure. The ventilated cavitating flow development process is simulated with a homogeneous free surface model combined with a filter-based turbulence model. The results show the characteristics of the pressure pulse and the bubble shedding around the axisymmetric body. A quasiperiodic pressure pulse occurs at the middle of the body. In addition, three main types of vortexes occur in ventilated partial cavitation: large-scale cloud vortices, U-type vortices, and small-scale vortices. Further analysis revealed that the cavities and vortex structures have similar influencing factors. The vorticity transportation equation (VTE) is applied to analyze the main factors influencing the vortex. The results indicate that fluid density primarily affects large-scale cloud vortices, the velocity gradient plays a dominant role in U-type vortices, and fluid angular velocity is the main influencing factor for small-scale vortices.

Fine-tuning a large language model for automating computational fluid dynamics simulations

Zhehao Dong, Zhen Lu, Yue Yang

Accepted Manuscript , doi: 10.1016/j.taml.2025.100594

[Abstract] (64) [PDF 2732KB] (5)

Abstract:
Configuring computational fluid dynamics (CFD) simulations typically demands extensive domain expertise, limiting broader access. Although large language models (LLMs) have advanced scientific computing, their use in automating CFD workflows is underdeveloped. We introduce a novel approach centered on domain-specific LLM adaptation. By fine-tuning Qwen2.5-7B-Instruct on NL2FOAM, our custom dataset of 28716 natural language-to-OpenFOAM configuration pairs with chain-of-thought (CoT) annotations enables direct translation from natural language descriptions to executable CFD setups. A multi-agent system orchestrates the process, autonomously verifying inputs, generating configurations, running simulations, and correcting errors. Evaluation on a benchmark of 21 diverse flow cases demonstrates state-of-the-art performance, achieving 88.7% solution accuracy and 82.6% first-attempt success rate. This significantly outperforms larger generalpurpose models such as Qwen2.5-72B-Instruct, DeepSeek-R1, and Llama3.3-70B-Instruct, while also requiring fewer correction iterations and maintaining high computational efficiency. The results highlight the critical role of domain-specific adaptation in deploying LLM assistants for complex engineering workflows. Our code and fine-tuned model have been deposited at https://github.com/YYgroup/AutoCFD.

Aerodynamic optimization of supersonic airfoils using bijective cycle generative adversarial networks

Chenfei Zhao, Yuting Dai, Xue Wang, Chao Yang, Guangjing Huang

Accepted Manuscript , doi: 10.1016/j.taml.2025.100591

[Abstract] (104) [PDF 2208KB] (1)

Abstract:
An efficient, diversified, and low-dimensional airfoil parameterization method is critical to airfoil aerodynamic optimization design. This paper proposes a supersonic airfoil parameterization method based on a bijective cycle generative adversarial network (Bicycle-GAN), whose performance is compared with that of the cVAE-based parameterization method in terms of parsimony, flawlessness, intuitiveness, and physicality. In all four aspects, the Bicycle-GAN-based parameterization method is superior to the cVAE-based parameterization method. Combined with multifidelity Gaussian process regression (MFGPR) surrogate model and a Bayesian optimization algorithm, a Bicycle-GAN-based optimization framework is established for the aerodynamic performance optimization of airfoils immersed in supersonic flow, which is compared with the cVAE-based optimization method in terms of optimized efficiency and effectiveness. The MFGPR surrogate model is established using low-fidelity aerodynamic data obtained from supersonic thinairfoil theory and high-fidelity aerodynamic data obtained from steady CFD simulation. For both supersonic conditions, the CFD simulation costs are reduced by more than 20% compared with those of the cVAE-based optimization, and better optimization results are obtained through the Bicycle-GAN model. The optimization results for this supersonic flow point to a sharper leading edge, a smaller camber and thickness with a flatter lower surface, and a maximum thickness at 50% chord length. The advantages of the Bicycle-GAN and MFGPR models are comprehensively demonstrated in terms of airfoil generation characteristics, surrogate model prediction accuracy and optimization efficiency.

Probabilistic Interface Failure Model of Composite Electrodes in All-Solid-State Batteries Under Mechanical-Diffusion Coupling

Zehui Zhang, Jici Wen

Accepted Manuscript , doi: 10.1016/j.taml.2025.100593

[Abstract] (71) [PDF 1956KB] (0)

Abstract:
All-solid-state lithium metal batteries (ASSLMBs) are widely recognized as promising next-generation energy storage technologies that offer significant advantages in terms of safety and energy density. However, the long-term cycling stability of these batteries is often compromised by interfacial failures driven by coupled mechanical and diffusion effects. This study presents a probabilistic failure prediction model that quantifies interfacial damage and capacity loss in composite electrodes under the coupled influence of mechanical-diffusioninduced processes. We first develop a pseudo3D (P3D) interface failure model for a binary particle system to evaluate interfacial failure during the critical delithiation process. The P3D model is validated through mechanical-diffusion coupled simulations. Additionally, for multiparticle composite electrode films with heterogeneous particle sizes, we identify a key structural factor that governs the failure of the particle-solid electrolyte interface, which follows a three-parameter Burr distribution. Building on this, we develop a probabilistic model to predict the capacity fade in multiporject composite films. This work provides a comprehensive understanding of the critical geometric factors that influence interfacial stability, offering valuable theoretical insights and practical guidance for the rapid assessment, optimization, and enhancement of cycling stability in ASSLMBs.

Thermomechanical cubic closed-cell model of liquid-saturated soft composites with surface effects

Jun Yin, Fei Ti, Xuechao Sun, Lijun Su, Xiuwei Wan, Shaobao Liu

Accepted Manuscript , doi: 10.1016/j.taml.2025.100590

[Abstract] (62) [PDF 1502KB] (1)

Abstract:
Many animal and plant tissues, such as adipose tissue and fruits, can be taken as liquid-saturated soft composites, which have densely packed pores that are filled with liquid. Typically, when the pore dimensions are sufficiently small (at the micro- or nanoscale), surface effects significantly influence the mechanical properties of the material. To characterize the thermomechanical properties critical for animals and plants, we propose an idealized cubic closed-cell model in which liquid compressibility and surface stress (i.e., surface moduli and residual surface stress) are considered. Analytical solutions of the model are then employed to quantify how the surface stress, porosity and liquid bulk modulus affect the effective Young’s modulus, effective Poisson ratio and effective coefficient of thermal expansion (CTE) of the liquid-saturated soft composite. An increase in residual surface stress reduces both the effective modulus and effective CTE, whereas increasing the surface moduli result in a greater effective modulus and reduced effective CTE. The results provide critical insights into how surface effects govern the macroscopic thermomechanical behavior of liquid-saturated soft composites with small pores.

Topology optimization for fluid–structure interaction problems considering heat transfer performance

Yuhui Jing, Li An, Sinan Yi, Jing Li, Pai Liu, Yaguang Wang, Xiaopeng Zhang

Accepted Manuscript , doi: 10.1016/j.taml.2025.100592

[Abstract] (57) [PDF 2131KB] (0)

Abstract:
Effectively controlling the deformation and temperature of heated structures is crucial for achieving high-performance active cooling through fluid flow. In this study, the topology optimization design of structures considering fluid–structure interactions and heat transfer performance was investigated, and then optimized designs of two-dimensional/three-dimensional cooling impingement systems obtained using the proposed method were obtained. In the optimization model, the objective function was constructed as a weighted combination of the mechanical deformations at specific locations and the average temperature within the designated solid channel structures. Additionally, explicit functional interpolation models were introduced to establish connections between the thermal, fluid, and solid properties, along with the element densities. In the analysis model, the strongly coupled structural mechanical deformation and fluid velocity field were analyzed via a dynamic-grid-based finite element model with a Winslow elliptic smoother to automatically track the fluid–structure interface during the process of optimization. To solve the optimization problems, the globally convergent moving asymptotic optimizer method was used to adjust the design variables on the basis of the sensitivity analysis. A demonstration of the efficacy of the proposed algorithm is provided through the presentation of several optimization examples. Furthermore, two- and three-dimensional cooling impingement systems were designed with the proposed method.

Aerodynamic uplift force improvement in single-strip high-speed pantograph via key parameter regulation with mechanism investigation

Yafeng Zoua, Xianghong Xu, Rui Zhou, Zichen Liu, Liming Lin

Accepted Manuscript , doi: 10.1016/j.taml.2025.100588

[Abstract] (74) [PDF 0KB] (0)

Abstract:
This study addresses the significant disparity in aerodynamic uplift forces experienced by single-strip high-speed pantographs under different operating directions. A systematic numerical investigation was conducted to evaluate the influence of key geometric parameters on aerodynamic characteristics, culminating in two targeted adjustment strategies. The reliability of the computational methodology was validated through comparative analysis, which revealed less than a 6% deviation in aerodynamic drag between the numerical simulations and wind tunnel tests. Aerodynamic decomposition revealed that the operating direction critically impacts the uplift force, which is governed by two factors: streamwise cross-strip positioning and the angular orientation of the arm hinge. These factors collectively determine the divergent aerodynamic responses of the panhead and frame during directional changes. By establishing a parametric database encompassing four strip-to-crossbar spacing configurations and six arm diameter variations, nonlinear response patterns of the uplift forces under different operating directions to geometric modifications were quantified. Both adjustment approaches, simultaneously reducing both streamwise and vertical strip-to-crossbar spacings to half of the original dimensions or increasing the upper arm spanwise diameter to 1.45 times and decreasing the lower arm spanwise diameter to 0.55 times the baseline values, successfully constrained aerodynamic uplift force deviations between operating directions within 3%.

Molecular understanding of phase behavior of hydrocarbon mixtures in nanopores and their influence on recovery dynamics

JingShan Wang, Yan Wang, BinHui Li, QingZhen Wang, SiWei Meng, RuoShi Chen, HengAn Wu, FengChao Wang

Accepted Manuscript , doi: 10.1016/j.taml.2025.100589

[Abstract] (71) [PDF 0KB] (0)

Abstract:
Understanding the phase behavior of hydrocarbons and their mixtures, especially under confinement, is crucial for the extraction of shale oil and gas. In this study, we employed molecular dynamics simulations to investigate the phase behaviors of three typical hydrocarbons (methane, pentane, and octane) in the bulk phase and in nanopores. We find that the confinement effect can alter the phase behavior of a single-component hydrocarbon. For the mixture of methane and octane in nanopores, a rather high proportion of methane could inhibit the capillary condensation of octane. We also studied the influence of phase behavior on the recovery dynamics of hydrocarbon mixtures from blind nanopores of different sizes at different gas‒oil ratios. The capillary condensation of the heavy hydrocarbon components in the nanopore throat could hinder the transport of light. These findings increase the understanding of the occurrence states of shale oil and gas and their migration through nanopore throats, providing practical guidance for shale oil and gas development.

Mechanics of origami/kirigami structures and metamaterials

Hongbin Fang, Haiping Wu

Accepted Manuscript , doi: 10.1016/j.taml.2025.100587

[Abstract] (64) [PDF 0KB] (1)

Abstract:
The ancient arts of paper folding and cutting— origami and kirigami— have long captivated both artists and engineers. Today, these techniques are inspiring the creation of adaptive structures and innovative metamaterials that challenge conventional mechanical paradigms. Whereas early research in origami/kirigami primarily addressed design principles and folding kinematics to achieve vast shape transformations, breakthroughs since the 2010s have unlocked new avenues in folding- and cutting-induced mechanics. By harnessing folding-induced deformations and leveraging strong geometric nonlinearities, researchers now realize exceptional mechanical properties such as auxetic behavior, high reconfigurability, programmable stiffness, impact absorption, and bi-stability or multi-stability.

Gradient-free optimization of non-differentiable hybrid neural solvers for spatially heterogeneous composites

Hanfeng Zhang, Tengfei Luo, Jian-Xun Wang

Accepted Manuscript , doi: 10.1016/j.taml.2025.100585

[Abstract] (84) [PDF 8151KB] (2)

Abstract:
The data-driven machine learning paradigm typically requires high-quality, large-scale datasets for training neural networks, which are often unavailable in many scientific and engineering applications. Integrating physics equations into machine learning models, either fully or partially, can mitigate these data requirements and improve generalizability; however, such approaches frequently rely on differentiable programming frameworks. This ability poses significant challenges when legacy or commercial numerical solvers, which are often non-differentiable and difficult to modify without introducing code changes, are integrated. This work addresses these challenges by leveraging the mini-batching iterative ensemble Kalman inversion (EKI) algorithm as a gradient-free training framework for hybrid neural models. The use of stochastic mini-batching significantly enhances the computational efficiency and convergence of EKI, making it well-suited for high-dimensional learning problems. The proposed method is demonstrated for modeling a fiber-reinforced composite plate, where heterogeneous local constitutive laws are parameterized by a trainable neural network embedded within the FEniCS finite element solver. Using the displacement field as indirect data, the hybrid neural FEM solver successfully predicts deformations by learning the local constitutive laws, even for unseen fiber volume fraction distributions and varying test loading conditions. These results demonstrate the effectiveness of iterative EKI in training hybrid neural models with non-differentiable components, paving the way for broader adoption of hybrid neural models in scientific and engineering applications.

DeepSeek vs. ChatGPT vs. Claude: A Comparative Study for Scientific Computing and Scientific Machine Learning Tasks

Qile Jiang, Zhiwei Gao, George Em Karniadakis

Accepted Manuscript , doi: 10.1016/j.taml.2025.100583

[Abstract] (71) [PDF 5840KB] (1)

Abstract:
Large language models (LLMs) have emerged as powerful tools for addressing a wide range of problems, including those in scientific computing, particularly in solving partial differential equations (PDEs). However, different models exhibit distinct strengths and preferences, resulting in varying levels of performance. In this paper, we compare the capabilities of the most advanced LLMsDeepSeek, ChatGPT, and Claudealong with their reasoning-optimized versions in addressing computational challenges. Specifically, we evaluate their proficiency in solving traditional numerical problems in scientific computing as well as leveraging scientific machine learning techniques for PDE-based problems. We designed all our experiments so that a nontrivial decision is required, e.g, defining the proper space of input functions for neural operator learning. Our findings show that reasoning and hybrid-reasoning models consistently and significantly outperform non-reasoning ones in solving challenging problems, with ChatGPT o3-mini-high generally offering the fastest reasoning speed.

Hydrodynamic performance of bionic streamlined remotely operated vehicle based on CFD and overlapping mesh technology

Bin Guan, Junjie Li

Accepted Manuscript , doi: 10.1016/j.taml.2025.100584

[Abstract] (71) [PDF 1574KB] (0)

Abstract:
To meet the intelligent detection needs of underwater defects in large hydropower stations, the hydrodynamic performance of a bionic streamlined remotely operated vehicle containing a thruster protective net structure is numerically simulated via computational fluid dynamics (CFD) and overlapping mesh technology. The results show that the entity model generates greater hydrodynamic force during steady motion, whereas the square net model experiences greater force and moment during unsteady motion. The lateral and vertical force coefficients of the entity model are 4.32 and 3.13 times greater than those of the square net model in the oblique towing test simulation. The square net model also offers better static and dynamic stability, with a 24.5% increase in dynamic stability, achieving the highest lift-to-drag ratio at attack angles of 6°~8°. This research provides valuable insights for designing and controlling underwater defect detection vehicles for large hydropower stations.

Study of an adaptive bump control mechanism for shock wave/boundary layer interactions in supersonic flows

Shan-shan Tian, Liang Jin, Wei Huang, Yang Shen, Kai An

Accepted Manuscript , doi: 10.1016/j.taml.2025.100586

[Abstract] (70) [PDF 2023KB] (0)

Abstract:
The stability of supersonic inlets faces challenges due to various changes in flight conditions, and flow control methods that address shock wave/boundary layer interactions under only one set of conditions cannot meet developmental requirements. This paper proposes an adaptive bump control scheme and employs dynamic mesh technology for numerical simulation to investigate the unsteady control effects of adaptive bumps. The obtained results indicate that the use of moving bumps to control shock wave/boundary layer interactions is feasible. The adaptive control effects of five different bump speeds are evaluated. Within the range of bump speeds studied, the analysis of the flow field structure reveals the patterns of change in the separation zone area during the control process, as well as the relationship between the bump motion speed and the control effect on the separation zone. It is concluded that the moving bump endows the boundary layer with additional energy.

Revisiting Taylor bubble motion in an oscillating vertical tube

Quan Yao, Guangzhao Zhou

Accepted Manuscript , doi: 10.1016/j.taml.2025.100581

[Abstract] (112) [PDF 2920KB] (1)

Abstract:
In this study, we numerically investigate the rise of a Taylor bubble in a vertically oscillating round tube. The results show that increasing the oscillation frequency and amplitude reduces the bubble rise velocity, which is consistent with previously reported experimental findings. Analysis of the flow in the annular film region indicates that the influence of tube wall oscillations is minimal. This suggests that the effect of tube oscillations is essentially equivalent to that of an oscillating piston above the bubble, leading to a similar mechanism for bubble deceleration. Using a theoretical formula from the literature, we demonstrate that at sufficiently high frequencies, the amplitude of the tube velocity oscillations becomes the sole control parameter affecting bubble deceleration. This study enhances our understanding of Taylor bubble behavior in mechanically oscillating environments and provides useful insights into the design of control strategies for Taylor bubble motion in vertical slug flows.

The impact attenuation behavior of three-dimensional soft elastomeric lattices

Bin Xia, Wenmiao Yang, Junwei Shi, Lichen Wang, Zeang Zhao

Accepted Manuscript , doi: 10.1016/j.taml.2025.100579

[Abstract] (137) [PDF 1385KB] (1)

Abstract:
Cellular structures, distinguished by their porous characteristics, are frequently adopted in designs aimed at impact isolation, owing to their lightweight attributes and exceptional ability to absorb energy during impact events. However, lattice structures often rely on plastic deformation to absorb energy. However, in applications such as sports protection and robotic grasping, there is a need for a reusable impact isolation structure, which can be effectively achieved by three-dimensional flexible lattice structures. In this study, a theoretical calculation method for soft lattice structures is proposed, and on the basis of this method, a three-dimensional soft lattice structure for impact isolation is designed. In this paper, the predictive theory for the quasistatic mechanical properties, including stiffness and buckling strength, of threedimensional soft lattice structures is described. On the basis of the quasizero stiffness characteristics inherent in body-centered cubic (BCC), octahedral (OCT), and octahedral (RD) structures, a soft impact isolation structure is designed. The soft structure, constructed utilizing TPU material, demonstrated a peak impact isolation efficiency of 83%, despite possessing a thickness of described. On the basis of. The work presented in this paper provides new design methodologies and support for reusable impact isolation structures in applications such as reconfigurable robots and space capture missions.

Explainable artificial intelligence model for the prediction of undrained shear strength

Ho-Hong-Duy Nguyen, Thanh-Nhan Nguyen, Thi-Anh-Thu Phan, Ngoc-Thi Huynh, Quoc-Dat Huynh, Tan-Tai Trieu

Accepted Manuscript , doi: 10.1016/j.taml.2025.100578

[Abstract] (128) [PDF 2235KB] (4)

Abstract:
Machine learning (ML) models are widely used for predicting undrained shear strength (USS), but interpretability has been a limitation in various studies. Therefore, this study introduced shapley additive explanations (SHAP) to clarify the contribution of each input feature in USS prediction. Three ML models, artificial neural network (ANN), extreme gradient boosting (XGBoost), and random forest (RF), were employed, with accuracy evaluated using mean squared error, mean absolute error, and coefficient of determination (R²). The RF achieved the highest performance with an R² of 0.82. SHAP analysis identified pre-consolidation stress as a key contributor to USS prediction. SHAP dependence plots reveal that the ANN captures smoother, linear feature-output relationships, while the RF handles complex, non-linear interactions more effectively. This suggests a non-linear relationship between USS and input features, with RF outperforming ANN. These findings highlight SHAP’s role in enhancing interpretability and promoting transparency and reliability in ML predictions for geotechnical applications.

Hydrodynamic characteristics around offshore pipelines and oscillatory pore pressures in sand beds under combined random wave and current loads

Yue Xu, Lin Cui, Dong-sheng Jeng, Mingqing Wang, Ku Sun, Bing Chen

Accepted Manuscript , doi: 10.1016/j.taml.2025.100575

[Abstract] (146) [PDF 6862KB] (1)

Abstract:
This paper experimentally investigates the wave pressure and pore pressure within a sandy seabed around two pipelines under the action of random waves (currents). The experiments revealed that when the random wave plus current cases are compared with the random wave-only case, the forward current promotes wave propagation, whereas the reversed backward current inhibits wave propagation. Furthermore, the wave pressure on the downstream pipeline decreases as the relative spacing ratio increases and increases as the diameter increases. However, alterations in the relative spacing ratio or dimensions of the downstream pipeline exert a negligible influence on the wave pressure of the upstream pipeline. Moreover, the relative spacing ratio between the pipelines and the dimensions of the pipelines considerably influence the pore pressure in the sand bed. When the relative spacing ratio remains constant, increasing the downstream pipeline diameter will increase the pore-water pressure of the soil below the downstream pipeline.

Kolmogorov-Arnold Networks modeling of wall pressure wavenumber-frequency spectra under turbulent boundary layers

Zhiteng Zhou, Yi Liu, Shizhao Wang, Guowei He

Accepted Manuscript , doi: 10.1016/j.taml.2025.100573

[Abstract] (128) [PDF 3813KB] (1)

Abstract:
The empirical models for wavenumber-frequency spectra of wall pressure are broadly used in the fast prediction of aerodynamic and hydrodynamic noise. However, it needs to fit the parameter using massive data and is only used for limited cases. In this letter, we propose KAN-base models for wavenumber-frequency spectra of pressure fluctuations under turbulent boundary layers. The results are compared with DNS results. In turbulent channel flows, it is found that the KAN-base model leads to a smooth wavenumber-frequency spectrum with sparse samples. In the turbulent flow over an axisymmetric body of revolution, the KAN-base model captures the wavenumber-frequency spectra near the convective peak.

Herglotz type Noether theorems of nonholonomic systems with generalized fractional derivatives

Yuan-Yuan Deng, Yi Zhang

Accepted Manuscript , doi: 10.1016/j.taml.2025.100574

[Abstract] (126) [PDF 1390KB] (1)

Abstract:
Fractional calculus is widely used to deal with nonconservative dynamics because of its memorability and non-local properties. In this paper, the Herglotz principle with generalized operators is discussed, and the Herglotz type equations for nonholonomic systems are established. Then, the Noether symmetries are studied, and the conserved quantities are obtained. The results are extended to nonholonomic canonical systems, and the Herglotz type canonical equations and the Noether theorems are obtained. Two examples are provided to demonstrate the validity of the methods and results.

Analytical Finite-Integral-Transform and Gradient-Enhanced Machine Learning Approach for Thermoelastic Analysis of FGM Spherical Structures with Arbitrary Properties

Palash Das, Dipayan Mondal, Md. Ashraful Islam, Md. Abdullah Al Mohotadi, Prokash Chandra Roy

Accepted Manuscript , doi: 10.1016/j.taml.2025.100576

[Abstract] (136) [PDF 1765KB] (2)

Abstract:
This study introduces a novel mathematical model that combines the finite integral transform (FIT) and gradient-enhanced physics-informed neural network (g-PINN) to address thermomechanical problems in functionally graded materials (FGMs) with varying properties. The model employs a multilayer heterostructure homogeneous (MHH) approach within the FIT to linearize and approximate various parameters, such as the thermal conductivity, specific heat, density, stiffness, thermal expansion coefficient, and Poisson's ratio. The provided FIT and gPINN techniques are highly proficient in solving the PDEs of energy equations and equations of motion in a spherical domain, particularly when dealing with space-time dependent boundary conditions (B.C.s). The FIT method simplifies the governing partial differential equations into ordinary differential equation for efficient solutions, whereas the g-PINN bypasses linearization, achieving high accuracy with fewer training data (error < 3.8%). The approach is applied to a spherical pressure vessel, solving energy and motion equations under complex boundary conditions. Furthermore, the extensive parametric studies are conducted herein to demonstrate the impact of different property profiles and radial locations on the transient evolution and dynamic propagation of thermomechanical stresses. However, the accuracy of the presented approach is evaluated by comparing the g-PINN results, which have an error of less than 3.8%. Moreover, this model offers significant potential for optimizing materials in high-temperature reactors and chemical plants, improving safety, extending lifespan, and reducing thermal fatigue under extreme processing conditions.

Deep Transfer Learning for Three-dimensional Aerodynamic Pressure Prediction under Data Scarcity

Hao Zhang, Yang Shen, Wei Huang, Zan Xie, Yao-bin Niu

Accepted Manuscript , doi: 10.1016/j.taml.2025.100571

[Abstract] (153) [PDF 1919KB] (0)

Abstract:
Aerodynamic evaluation under multi-condition is indispensable for the design of aircraft, and the requirement for mass data still means a high cost. To address this problem, we propose a novel Point-Cloud Multi-condition Aerodynamics Transfer Learning (PCMCA-TL) framework that enables aerodynamic prediction in data-scarce scenarios by transferring knowledge from well-learned scenarios. We modified the PointNeXt segmentation architecture to a PointNeXtReg+ regression model, including a working condition input module. The model is first pre-trained on a public dataset with 2000 shapes but only one working condition and then fine-tuned on a multi-condition small-scale spaceplane dataset. The effectiveness of the PCMCA-TL framework is verified by comparing the pressure coefficients predicted by direct training, pretraining, and TL models. Furthermore, by comparing the aerodynamic force coefficients calculated by predicted pressure coefficients in seconds with the corresponding CFD results obtained in hours, the accuracy highlights the development potential of deep transfer learning in aerodynamic evaluation.

Traction performance and efficiency of cone friction CVT

Vít Řípa, Karel Petr, Jan Flek, Gabriela Achtenová, František Lopot

Accepted Manuscript , doi: 10.1016/j.taml.2025.100570

[Abstract] (125) [PDF 1871KB] (1)

Abstract:
This study investigates the traction performance and efficiency of a conical friction continuously variable transmission. A new mathematical model was developed and validated through experimental measurements using a custom-built test rig to predict these parameters accurately. The results showed a close correlation between theoretical predictions and experimental data. Key findings include the impact of load on efficiency and the model’s ability to predict performance under various operating conditions. The study provides detailed insights into the dynamics of conical friction variator and demonstrates the model's effectiveness in predicting real-world behavior. The developed model can assist in selecting optimal parameters during the design phase and can be applied to other developing variator systems to achieve maximum efficiency.

Light-fueled self-rotation of a liquid crystal elastomer rod enabled by lateral constraint

Kai Li, Pengsen Xu, Lin Zhou

Accepted Manuscript , doi: 10.1016/j.taml.2025.100569

[Abstract] (157) [PDF 1829KB] (0)

Abstract:
Recent experiments have found that a liquid crystal elastomer (LCE) rod supported in the middle can rotate continuously under horizontal illumination due to the combined impacts of gravity and light-fueled lateral bending deformation. Similar to traditional gravity-driven systems, it is constrained by the direction of gravity and cannot be applied in microgravity environments. This study introduces a lateral constraint to a liquid crystal elastomer rod system, enabling self-rotation under lighting from any direction, including horizontal and vertical illumination. Through theoretical modeling, the results indicate that the system can steadily rotate under the combined impacts of lateral forces and vertical illumination. Factors like thermal energy flux, thermal conductivity coefficient, the LCE rod length, contraction coefficient, and friction coefficient affect the angular velocity of the self-rotation. The numerical computations align closely with the experimental data. Our proposed steadily self-rotating system features a simple structure with constant self-rotation. It operates independently of gravity direction, making it an excellent choice for special environments, such as the microgravity conditions on the Moon. The lateral constraint strategy presented in this study offers a general approach to expanding the applications of gravity-driven self-sustained motion, with promising potential, especially in microgravity settings, where its versatility under varying lighting conditions could yield valuable insights.

New exact traveling wave solutions of the coupled Boussinesq equations

Mingyue Wang, Youhe Zhou, Jizeng Wang

Accepted Manuscript , doi: 10.1016/j.taml.2024.100568

[Abstract] (149) [PDF 1216KB] (0)

Abstract:
The Boussinesq equations, pivotal in the analysis of water wave dynamics, effectively model weakly nonlinear and long wave approximations. This study utilizes the complete discriminant system within a polynomial approach to derive exact traveling wave solutions for the coupled Boussinesq equation. The solutions are articulated through soliton, trigonometric, rational, and Jacobi elliptic functions. Notably, the introduction of Jacobi elliptic function solutions for this model marks a pioneering advancement. Contour plots of the solutions obtained by assigning values to various parameters are generated and subsequently analyzed. The methodology proposed in this study offers a systematic means to tackle nonlinear partial differential equations in mathematical physics, thereby enhancing comprehension of the physical attributes and dynamics of water waves.

Investigation of dynamic behavior of human skin tissue under microparticle impact in the context of transdermal drug delivery: Numerical and analytical perspectives

Jianbo Shen, Jiacai Huang, Yaoke Wen, Sebastien Rothd

Accepted Manuscript , doi: 10.1016/j.taml.2024.100567

[Abstract] (181) [PDF 1476KB] (1)

Abstract:
The understanding of the impact of high-velocity microparticles on human skin tissue is important for the administration of drugs during transdermal drug delivery. This paper aims to numerically investigate the dynamic behavior of human skin tissue under micro-particle impact in transdermal drug delivery. The numerical model was developed based on a coupled Smoothed Particle Hydrodynamics (SPH) and FEM method via commercial FE software RADIOSS. Analytical analysis was conducted applying the Poncelet model and was used as validation data. A hyperelastic one-term Ogden model with one pair of material parameters (μ,α) was implemented for the skin tissue. Sensitivity studies reveal that the effect of parameter α on the penetration process is much more significant than μ. Numerical results correlate well with the analytical curves with various particle diameters and impact velocities, its capability of predicting the penetration process of micro-particle impacts into skin tissues. This work can be further investigated to guide the design of transdermal drug delivery equipment.

Erratum to “Penetration resistance of Al₂O₃ ceramic-ultra-high molecular weight polyethylene (UHMWPE) composite armor: Experimental and numerical investigations”

Wencheng Lu, Yiding Wu, Minghui Ma, Yilei Yu, Xuan Zhou, Guangfa Gao

Accepted Manuscript , doi: 10.1016/j.taml.2024.100565

[Abstract] (175) [PDF 671KB] (0)

Abstract:
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Globally optimized dynamic mode decomposition: A first study in particulate systems modelling

Abhishek Gupta, Barada Kanta Mishra

Accepted Manuscript , doi: 10.1016/j.taml.2024.100563

[Abstract] (144) [PDF 1290KB] (1)

Abstract:
This paper introduces dynamic mode decomposition (DMD) as a novel approach to model the breakage kinetics of particulate systems. DMD provides a data-driven framework to identify a best-fit linear dynamics model from a sequence of system measurement snapshots, bypassing the nontrivial task of determining appropriate mathematical forms for the breakage kernel functions. A key innovation of our method is the instilling of physics-informed constraints into the DMD eigenmodes and eigenvalues, ensuring they adhere to the physical structure of particle breakage processes even under sparse measurement data. The integration of eigen-constraints is computationally aided by a zeroth-order global optimizer for solving the nonlinear, nonconvex optimization problem that elicits system dynamics from data. Our method is evaluated against the state-of-the-art optimized DMD algorithm using both generated data and real-world data of a batch grinding mill, showcasing over an order of magnitude lower prediction errors in data reconstruction and forecasting.

Field Inversion and Machine Learning Based on the Rubber-Band Spalart-Allmaras Model

Wu Chenyu, Zhang Yufei

Accepted Manuscript , doi: 10.1016/j.taml.2024.100564

[Abstract] (132) [PDF 1615KB] (0)

Abstract:
Machine learning (ML) techniques have emerged as powerful tools for improving the predictive capabilities of Reynolds-averaged Navier-Stokes (RANS) turbulence models in separated flows. This improvement is achieved by leveraging complex ML models, such as those developed using field inversion and machine learning (FIML), to dynamically adjust the constants within the baseline RANS model. However, the ML models often overlook the fundamental calibrations of the RANS turbulence model. Consequently, the basic calibration of the baseline RANS model is disrupted, leading to a degradation in the accuracy, particularly in basic wall-attached flows outside of the training set. To address this issue, a modified version of the Spalart-Allmaras (SA) turbulence model, known as Rubber-band SA (RBSA), has been proposed recently. This modification involves identifying and embedding constraints related to basic wall-attached flows directly into the model. It is shown that no matter how the parameters of the RBSA model are adjusted as constants throughout the flow field, its accuracy in wall-attached flows remains unaffected. In this paper, we propose a new constraint for the RBSA model, which better safeguards the law of wall in extreme conditions where the model parameter is adjusted dramatically. The resultant model is called the RBSApoly model. We then show that when combined with FIML augmentation, the RBSA-poly model effectively preserves the accuracy of simple wall-attached flows, even when the adjusted parameters become functions of local flow variables rather than constants. A comparative analysis with the FIML-augmented original SA model reveals that the augmented RBSA-poly model reduces error in basic wall-attached flows by 50% while maintaining comparable accuracy in trained separated flows. These findings confirm the effectiveness of utilizing FIML in conjunction with the RBSA model, offering superior accuracy retention in cardinal flows.

Enriching harmonic balance with non-smooth Bernoulli bases for accelerated convergence of non-smooth periodic systems

Yu Zhou, Jianliang Huang, Li Wang

Accepted Manuscript , doi: 10.1016/j.taml.2024.100562

[Abstract] (179) [PDF 4404KB] (5)

Abstract:
The harmonic balance method (HBM) has been widely applied to get the periodic solution of nonlinear systems, however, its convergence rate as well as computation efficiency is dramatically degraded when the system is highly non-smooth, e.g., discontinuous. In order to accelerate the convergence, an enriched HBM is developed in this paper where the non-smooth Bernoulli bases are additionally introduced to enrich the conventional Fourier bases. The basic idea behind is that the convergence rate of the HB solution, as a truncated Fourier series, can be improved if the smoothness of the solution becomes finer. Along this line, using non-smooth Bernoulli bases can compensate the highly non-smooth part of the solution and then, the smoothness of the residual part for Fourier approximation is improved so as to achieve accelerated convergence. Numerical examples are conducted on systems with non-smooth restoring and/or external forces. The results confirm that the proposed enriched HBM indeed increases the convergence rate and the increase becomes more significant if more non-smooth bases are used.

Large-stroke snap-through instability in the axial direction of a bi-stable structure with high slenderness

Huan Zhou, Qian Sun, Haibin Xia, Yiwei Xiong, Youchao Yuan, Yin Huang, Jianghong Yuan

Accepted Manuscript , doi: 10.1016/j.taml.2024.100561

[Abstract] (235) [PDF 1201KB] (5)

Abstract:
Mechanical snap-through instability of bi-stable structures may find many practical applications such as state switching and energy transforming. Although there exist diverse bi-stable structures capable of snap-through instability, it is still difficult for a structure with high slenderness to undergo the axial snapthrough instability with a large stroke. Here, an elastic structure with high slenderness is simply constructed by a finite number of identical, conventional bistable units with relatively low slenderness in series connection. For realizing the axial snap-through instability with a large stroke, common scissors mechanisms are further introduced as rigid constraints to guarantee the synchronous snapthrough instability of these bi-stable units. The global feature of the large-stroke snap-through instability realized here is robust and even insusceptible to the local out-of-synchronization of individual units. The present design provides a simple and feasible way to achieve the large-stroke snap-through instability of slender structures, which is expected to be particularly useful for state switching and energy transforming in narrow spaces.

Determination of angle of attack and dynamic stall loop in the complex vortical flow of a vertical axis wind turbine

Wenzhong Shen, Tao Xie, Lingpeng Ge, Jiamin Yin, Zhenye Sun

Accepted Manuscript , doi: 10.1016/j.taml.2024.100560

[Abstract] (203) [PDF 1218KB] (1)

Abstract:
To improve the vertical axis wind turbine (VAWT) design, the angle of attack (AOA) and airfoil data must be treated correctly. The present paper develops a method for determining AOA on a VAWT based on computational fluid dynamics (CFD) analysis. First, a CFD analysis of a two-bladed VAWT equipped with a NACA 0012 airfoil is conducted. The thrust and power coefficients are validated through experiments. Second, the blade force and velocity data at monitoring points are collected. The AOA at different azimuth angles is determined by removing the blade self-induction at the monitoring point. Then, the lift and drag coefficients as a function of AOA are extracted. Results show that this method is independent of the monitoring points selection located at certain distance to the blades and the extracted dynamic stall hysteresis is more precise than the one with the “usual” method without considering the self-induction from bound vortices.

Numerical investigation on transonic flutter characteristics of an airfoil with split drag rudder

Yongchang Li, Yuting Dai, Chen Song, Chao Yang, Guangjing Huang

Accepted Manuscript , doi: 10.1016/j.taml.2024.100554

[Abstract] (198) [PDF 1347KB] (1)

Abstract:
In this paper, a series of flutter simulations are carried out to investigate the effects of split drag rudder (SDR) on the transonic flutter characteristic of rigid NACA 64A010. A structural dynamic model addressing two-degree-of-freedom pitch-plunge aeroelastic oscillations was coupled with the unsteady Reynolds-averaged Navier-Stokes equations to perform flutter simulation. Meanwhile, the influence mechanism of SDR on flutter boundary is explained through aerodynamic work and the correlated shock wave location. The results show that the SDR delays the shock wave shifting downstream, and the Mach number corresponding to reaching freeze region increases as the split angle increases. Therefore, the peak value of aerodynamic moment coefficient amplitude and the sharp ascent process of phase occurs at higher Mach number, which leads to the delay in the occurrence of the transonic dip. Besides, before the transonic dip of airfoil without SDR occurs, the aerodynamic moment phase of airfoil with the SDR decreases slowly due to the decrease in the speed of shock wave moving downstream. This results in an increased flutter speed when employing the SDR before the transonic dip of airfoil without SDR occurs. Meanwhile, the effects of asymmetric split angles on the transonic flutter characteristics are also investigated. Before the transonic dip of airfoil without SDR occurs, the flutter characteristic is dominated by the smaller split angle.

Reduction in wave shoaling over a linear transition bottom using a porous medium

I. Magdalena, Ivan Jonathan Kristianto, Hany Q. Rif'atin, Amila Sandaruwan Ratnayake, Cherdvong Saengsupavanich, I. Solekhudinn, M. Helmi

Accepted Manuscript , doi: 10.1016/j.taml.2024.100556

[Abstract] (204) [PDF 1790KB] (0)

Abstract:
Wave shoaling, which involves an increase in wave amplitude due to changes in water depth, can damage shorelines. To mitigate this damage, we propose using porous structures such as mangrove forests. In this study, we use a mathematical model to examine how mangroves, acting as a porous breakwater, can reduce wave shoaling amplitude. Shallow water equations are used as the governing equations and are modified to account for the presence of porous media. To measure the wave reduction generated by the porous media, the wave transmission coefficient is estimated using analytical and numerical approaches. The separation of variables method and the staggered finite volume method are utilized for each approach, respectively. The numerical results are then validated against the previously obtained analytical solutions. We then vary the friction and porosity parameters, influenced by the presence and extent of porous media, to evaluate their effectiveness in reducing wave shoaling.

Modeling and characterization of contact behavior of asperities with irregular shapes

Jiaxin Huanga, Chen Suna, Jubing Chena

Accepted Manuscript , doi: 10.1016/j.taml.2024.100535

[Abstract] (418) [PDF 23416KB] (2)

Abstract:
This paper introduces a model for characterizing the contact behavior of irregular asperities, transforming it into a superposition of sinusoidal asperity contact behaviors. A new sinusoidal asperity model is developed for bilinear hardening under plane strain conditions. Empirical equations are proposed, considering geometric shapes, tangent modulus, and Young's modulus. The frequency of asperity height is extracted through Fourier transform for irregular asperities. Contact area and pressure are predicted using the sinusoidal asperity model, and the behavior of irregular asperities is obtained by superimposing those with the first three frequencies. Experimental validation is conducted with milling and knurling-formed asperities, showing good alignment between the model and experimental results. In rough surface models, the proposed irregular asperity model exhibits greater accuracy in predicting contact behavior than a single sinusoidal asperity when interference exceeds 10% of the amplitude.

The Significant Contribution of Stochastic Forcing to Nonlinear Energy Transfer in Resolvent Analysis

Youhua Wang, Ting Wu, Guowei He

Accepted Manuscript , doi: 10.1016/j.taml.2024.100521

[Abstract] (582) [PDF 1959KB] (27)

Abstract:
Nonlinear energy transfer is represented through eddy viscosity and stochastic forcing within the framework of resolvent analysis. Previous investigations estimate the contribution of eddyviscosity-enhanced resolvent operator to nonlinear energy transfer. The present article estimates the contribution of stochastic forcing to nonlinear energy transfer and demonstrates that the contribution of stochastic forcing cannot be ignored. These results are achieved by numerically comparing the eddy-viscosity-enhanced resolvent operator and stochastic forcing with nonlinear energy transfer in turbulent channel flows. Furthermore, the numerical results indicate that composite resolvent operators can improve the prediction of nonlinear energy transfer.

Quantification and reduction of uncertainty in aerodynamic performance of GAN-generated airfoil shapes using MC dropouts

Kazuo Yonekura, Ryuto Aoki, Katsuyuki Suzuki

Accepted Manuscript , doi: 10.1016/j.taml.2024.100504

[Abstract] (473) [PDF 2212KB] (2)

Abstract:
Generative adversarial network (GAN) models are widely used in mechanical designs. The aim in the airfoil shape design is to obtain shapes that exhibits the required aerodynamic performance, and conditional GAN is used for that aim. However, the output of GAN contains uncertainties. Additionally, the uncertainties of labels have not been quantified. This paper proposes an uncertainty quantification method to estimate the uncertainty of labels using Monte Carlo dropout. In addition, an uncertainty reduction method is proposed based on imbalanced training. The proposed method was evaluated for the airfoil generation task. The results indicated that the uncertainty was appropriately quantified and successfully reduced.

Magnetically-actuated Intracorporeal Biopsy Robot Based on Kresling Origami

Long Huang, Tingcong Xie, Lairong Yin

Accepted Manuscript , doi: 10.1016/j.taml.2024.100500

[Abstract] (480) [PDF 2324KB] (0)

Abstract:
The introduction of wireless capsule endoscopy has brought a revolutionary change in the diagnostic procedures for gastrointestinal disorders. Biopsy, an essential procedure for disease diagnosis, has been integrated into robotic capsule endoscopy to augment diagnostic capabilities. In this study, we propose a magnetically driven biopsy robot based on a Kresling origami. Considering the bistable properties of Krelsing origami and the elasticity of the creases, a foldable structure of the robot with constant force characteristics is designed. The folding motion of the structure is used to deploy the needle into the target tissue. The robot is capable of performing rolling motion under the control of an external magnetic drive system, and a fine needle biopsy technique is used to collect deep tissue samples. We also conduct in vitro rolling experiments and sampling experiments on apple tissues and pork tissues, which verify the performance of the robot.

Select All

Display Method: |

A Real Space Moiré Inversion Technique and Its Practical Applications in Real Space for Lattice Reconstruction

Bo Cui, Hongye Zhang, Miao Li, Dong Zhao, Huimin Xie, Zhanwei Liu

Theoretical and Applied Mechanics Letters 14 (2024) 100518. doi: 10.1016/j.taml.2024.100518

[Abstract] (560) [PDF 2337KB] (27)

Abstract:
Distinct physical properties emerge at the nanoscale in Moiré materials, such as bilayer graphene and layered material superposition. This study explores similar structural features within a second-generation nickel-based superalloy, unveiling potential formation mechanisms. Introducing the real space Moiré inversion method (RSMIM) for nanoscale imaging, combined with the transmission electron microscopy (TEM) nano-Moiré inversion method, we reveal spatial angles between specimen and reference lattices in 3D. Simultaneously, we reconstruct the Moiré pattern region to deepen us understand the phenomenon of Moiré formation. Focused on face-centered cubic structures, the research identifies six spatial angles, shedding light on Moiré patterns in the superalloy. The RSMIM not only enhances understanding but also expands 3D structure measurement capabilities. The RSMIM served to validate TEM nano-Moiré inversion results, ascertaining the spatial relative angle between lattices, and establishing a theoretical simulation model for Moiré patterns. This study marks a substantial step toward designing high-performance nanomaterials by uncovering dynamic Moiré variations.

Tunable Supra-Transmission of a Stacked Miura-Origami Based Meta-Structure

Qiwei Zhang, Hongbin Fang

Theoretical and Applied Mechanics Letters 14 (2024) 100523. doi: 10.1016/j.taml.2024.100523

[Abstract] (479) [PDF 3469KB] (18)

Abstract:
The origami-based meta-structure has wide application in areas such as energy and wave transmission. Existing research has demonstrated the occurrence of supra-transmission in origami meta-structures and revealed its underlying mechanism. However, studies on how to regulate the phenomenon of supra-transmission are still very limited. In this work, we choose the meta-structure composed of stacked-Miura ori (SMO) as the subject. The SMO unit possesses two topologically distinct stable configurations, enabling the meta-structure to possess a rich variety of periodic layouts. Based on the established equivalent dynamic model of the SMO-based meta-structure, we employ numerical simulation methods and find that the supra-transmission threshold could be adjusted by tuning the periodic layout of the meta-structure. Furthermore, the probability of supra-transmission is also highly dependent on the periodic layout. Increasing the number of SMO units under the bulged-out configuration in each periodic layout decreases the likelihood of supratransmission occurring. The findings of this study yield an extensive array of foundational insights into the wave dynamics of origami structures. Furthermore, these insights translate into practical guidelines for designing origami-based meta-structure with tunable and programmable dynamic characteristics.

On the impact of debris accumulation on power production of marine hydrokinetic turbines: Insights gained via LES

Mustafa Meriç Aksen, Kevin Flora, Hossein Seyedzadeh, Mehrshad Gholami Anjiraki, Ali Khosronejad

Theoretical and Applied Mechanics Letters 14 (2024) 100524. doi: 10.1016/j.taml.2024.100524

[Abstract] (501) [PDF 3157KB] (9)

Abstract:
We present a series of large-eddy simulations to systematically investigate the impact of debris accumulation on the hydrodynamics and power production of a utility-scale marine hydrokinetic (MHK) turbine under various debris loads lodged on the upstream face of the turbine tower. The turbine blades are modeled using turbine resolving, actuator line, and actuator surface methods. Moreover, the influence of debris on the flow field is captured by directly resolving individual logs and employing a novel debris model. Analyzing the hydrodynamics effects of various debris accumulations, we show that an increase in the density of debris accumulation leads to more flow bypassing beneath the turbine blade. This, in turn, reduces the flow momentum that reaches the MHK blades at the lower depths, inducing significant fluctuation in power production. Further, it is shown that debris-induced turbulent fluctuations contribute to significant variability in the MHK turbine's power production.

Effective Permittivity of Compacted Granular Materials: Effects of Interfacial Polarization and Pore-filling Fluids

Xu Wang, Chongpu Zhai, Yixiang Gan

Theoretical and Applied Mechanics Letters 14 (2024) 100525. doi: 10.1016/j.taml.2024.100525

[Abstract] (437) [PDF 2341KB] (11)

Abstract:
Interfacial polarization dominates the permittivity spectra of heterogeneous granular materials for the intermediate frequency range (i.e., from kHz to MHz). In this study, we examine the corresponding dielectric responses of compacted glass sphere packings saturated with pore-filling fluids under various compressive stresses. The effective permittivity spectra are observed to exhibit consistently a plateau-to-plateau drop, described by low-frequency permittivity, characteristic frequency, and high-frequency permittivity. The permittivity spectra under different compressive levels are found to be influenced by the packing structure, compressive stress, and electrical property contrasts between solid and fluid (specifically permittivity and conductivity). For considered measurement conditions, the variation of packing structure and its associated porosity is found to be more significant than the stress evolution in controlling the interfacial polarization, thus the permittivity spectra, as supported by analytical and numerical results for unit cells. Furthermore, to gain a general rule for dielectric responses for saturated granular materials, we train multi-layer artificial neural network (ANN) models based on a series of simulations for unit cells with various structures, stresses, and electrical and dielectric properties. The predictions with two-layer ANN agree well with experimental measurements, presenting errors smaller than 5% for both low-frequency and high-frequency permittivity. This study offers an effective predicting approach for the dielectric behaviour of heterogeneous and multiphase materials.

A two-scale method to include essential behavior of bolted connections in structures including elevated temperatures

Qingfeng Xu, Hèrm Hofmeyer, Johan Maljaars

Theoretical and Applied Mechanics Letters 14 (2024) 100526. doi: 10.1016/j.taml.2024.100526

[Abstract] (446) [PDF 5977KB] (7)

Abstract:
A two-scale method is proposed to simulate the essential behavior of bolted connections in structures including elevated temperatures. It is presented, verified, and validated for the structural behavior of two plates, connected by a bolt, under a variety of loads and elevated temperatures. The method consists of a global-scale model that simulates the structure (here the two plates) by volume finite elements, and in which the bolt is modelled by a spring. The spring properties are provided by a small-scale model, in which the bolt is modelled by volume elements, and for which the boundary conditions are retrieved from the global-scale model. To ensure the small-scale model to be as computationally efficient as possible, simplifications are discussed regarding the material model and the modelling of the threads. For the latter, this leads to the experimentally validated application of a non-threaded shank with its stress area. It is shown that a non-linear elastic spring is needed for the bolt in the global-scale model, so the post-peak behavior of the structure can be described efficiently. All types of bolted connection failure as given by design standards are simulated by the two-scale method, which is successfully validated (except for net section failure) by experiments, and verified by a detailed system model, which models the structure in full detail. The sensitivity to the size of the part of the plate used in the small-scale model is also studied. Finally, multi-directional load cases, also for elevated temperatures, are studied with the two-scale method and verified with the detailed system model. As a result, a computationally efficient finite element modelling approach is provided for all possible combined load actions (except for nut thread failure and net section failure) and temperatures. The two-scale method is shown to be insightful, for it contains a functional separation of scales, revealing their relationships, and consequently, local small-scale non-convergence can be handled. Not presented in this paper, but the two-scale method can be used in e.g. computationally expensive two-way coupled fire-structure simulations, where it is beneficial for distributed computing and densely packed bolt configurations with stiff plates, for which a single small-scale model may be representative of several connections.

An Implicit Factorized Transformer with Applications to Fast Prediction of Three-dimensional Turbulence

Huiyu Yang, Zhijie Li, Xia Wang, Jianchun Wang

Theoretical and Applied Mechanics Letters 14 (2024) 100527. doi: 10.1016/j.taml.2024.100527

[Abstract] (474) [PDF 2341KB] (8)

Abstract:
Transformer has achieved remarkable results in various fields, including its application in modeling dynamic systems governed by partial differential equations. However, transformer still face challenges in achieving long-term stable predictions for three-dimensional turbulence. In this paper, we propose an implicit factorized transformer (IFactFormer) model, which enables stable training at greater depths through implicit iteration over factorized attention. IFactFormer is applied to large eddy simulation of three-dimensional homogeneous isotropic turbulence (HIT), and is shown to be more accurate than the FactFormer, Fourier neural operator (FNO), and dynamic Smagorinsky model (DSM) in the prediction of the velocity spectra, probability density functions of velocity increments and vorticity, temporal evolutions of velocity and vorticity root-mean-square value and isosurface of the normalized vorticity. IFactFormer can achieve long-term stable predictions of a series of turbulence statistics in HIT. Furthermore, IFactFormer showcases superior computational efficiency compared to the conventional DSM in large eddy simulation.

Cut layout optimization for design of kirigami metamaterials under large stretching

Chen Du, Yiqiang Wang, Zhan Kang

Theoretical and Applied Mechanics Letters 14 (2024) 100528. doi: 10.1016/j.taml.2024.100528

[Abstract] (422) [PDF 2284KB] (7)

Abstract:
Kirigami metamaterials have gained increasing attention due to their unusual mechanical properties under large stretching. However, most metamaterial designs obtained with trial-and-error approaches tend to lose their desirable properties under large tensile strains due to occurrence of instability caused by out-of-plane buckling. To cope with this limitation, this paper presents a systematic approach of cut layout optimizing for designing kirigami metamaterials working at large tensile strains by fully exploiting their out-of-plane buckling behaviors. This method can also mitigate the local stress concentration issue at the hinges of conventional kirigami designs working at in-plane deformation modes. The effectiveness of the proposed method is demonstrated through several examples regarding metamaterial design with negative Poisson's ratio and specified flip angle pattern. It is shown that the proposed method is capable of addressing the highly nonlinear deformation impacts on the mechanical performance under large stretching, to meet the growing and diverse demands in the field of kirigami metamaterials.

Motion of a small bubble in forced vibrating sessile drop

Jia-Qi Cheng, Fei Zhang, Chun-Yu Zhang, Hang Ding

Theoretical and Applied Mechanics Letters 14 (2024) 100529. doi: 10.1016/j.taml.2024.100529

[Abstract] (474) [PDF 1473KB] (13)

Abstract:
In this letter, the motion of small gas bubbles within sessile water drops on a vibrating substrate is investigated numerically using a two-phase diffuse interface method. Depending on the amplitude of the plate vibration, the motion of the gas bubbles falls into three distinct regimes: oscillating within the drop, sticking to the substrate, or escaping from the drop. In particular, the motion of oscillating bubbles follows a harmonic function, and is found to be closely related to a combined effect of the deformation of the sessile drop and the vibration of the plate. To interpret the underlying mechanism, we analyze the dominant forces acting on the bubbles in the non-inertial framework fixed to the plate, and take account of the periodic deformation of the drop, which effectively induces flow acceleration inside the drop. As a result, we establish a theoretical model to predict the bubble motion, and correlate the amplitude and phase difference of the bubble with the Bond and Strouhal numbers. The theoretical prediction agrees with our numerical results. These findings and theoretical analysis provide new insights into controlling bubble motion in sessile drops.

A New Cyclic Cohesive Zone Model for Fatigue Damage Analysis of Welded Vessel

Changyuan Shen, Xiaozhou Xia, Dake Yi, Zhongmin Xiao

Theoretical and Applied Mechanics Letters 14 (2024) 100531. doi: 10.1016/j.taml.2024.100531

[Abstract] (458) [PDF 3651KB] (5)

Abstract:
A new cyclic cohesive zone fatigue damage model is proposed to address the fatigue problem spanning high and low cycle stages. The new damage model is integrated with the damage extrapolation technique to improve calculation efficiency. The model's effectiveness in regulating the low-cycle fatigue evolution rate, overall fatigue damage evolution rate, and stress level at the fatigue turning point is assessed through the comparison of the S-N curves. The fatigue damage model's high precision is proved based on the minor deviation of stress at the turning point of the S-N curve from the actual scenario. Finally, the fatigue damage evolution is simulated considering the effects of pre-load pressure and welding residual stress. It is observed that laser welding induces a significant residual tensile stress, accelerating fatigue damage evolution, while compressive loading impedes fatigue damage progression.

Multi-objective optimization of a bistable curved shell with controllable thickness based on machine learning, Theoretical and Applied Mechanics Letters

Shiqing Huang, Chenjie Zhao, Xiaoqian Ning, Wenhua Zhang, Huifeng Xi, Zhiwei Wang, Changxian Wang

Theoretical and Applied Mechanics Letters 14 (2024) 100532. doi: 10.1016/j.taml.2024.100532

[Abstract] (422) [PDF 4033KB] (7)

Abstract:
Bistable curved shells have become a promising low-cost application in energy absorption fields owing to recent advances in material and technology. Significant research has been conducted to improve their energy absorption effect through forward prediction and singleobjective optimization. However, these approaches may not fully explore their functional potential. In this study, we propose a multi-objective optimization framework based on the principle of main objective optimization that combines neural networks and genetic algorithms. The energy absorption effect and backward snapping force of the bistable curved shell are improved synchronously. Meanwhile, a reverse design algorithm is developed to generate the preset load-displacement curve, which further expands the application of machine learning methods in the field of multi-objective optimization. The combination of machine learning and multi-objective optimization is highly effective for building meta-structures with specific performance requirements and has potential applications in solving complex optimization tasks in various fields.

Evaporation Mechanisms during Droplet Levitation and Coalescence Based on Molecular Dynamics

Fengming Chen, Tieqiang Gang, Lijie Chen

Theoretical and Applied Mechanics Letters 14 (2024) 100533. doi: 10.1016/j.taml.2024.100533

[Abstract] (463) [PDF 6041KB] (3)

Abstract:
Droplet levitation and coalescence mechanisms have consistently been a focal point in scientific research. From the perspective of molecular interactions, we investigated the influence of vapor pressure on the levitation and coalescence of droplets. The evaporation of nanodroplets and liquid pools under different initial environments was simulated by nonequilibrium molecular dynamics. The study analyzed the effects of evaporation during the processes of droplet levitation and coalescence and determined the existence of the Knudsen layer. Knudsen layers consisting of water molecules rather than clusters are generated during the evaporation. The definition, properties, and mechanisms of the layers were investigated.

PLA-based additively manufactured samples with different infill percentages under freeze-thaw cycles; mechanical, cracking, and microstructure characteristics

Reza Ale Ali, Hamid Reza Karimi, Razie Mohamadi

Theoretical and Applied Mechanics Letters 14 (2024) 100536. doi: 10.1016/j.taml.2024.100536

[Abstract] (415) [PDF 3882KB] (3)

Abstract:
The layered nature of the parts produced by 3D printing makes them susceptible to freezethaw damage. This research investigates the effect of the freeze-thaw cycles on the tensile, bending, and fracture resistance of samples made of Polylactic acid (PLA) material. For this purpose, the samples with 100, 75, 50, and 25 infill percentages were subjected to 4, 8, and 12 freeze-thaw cycles. The results show that the infill percentage and cycle affect freeze-thaw resistance. So, although for 100% infill samples, the 4, 8, and 12 cycles averagely reduce the tensile strength by 5, 15, and 25. The same trends can also be seen for flexural strength and, more severely, fracture resistance. Reviewing the microstructure with a Scanning electron microscopy (SEM) device shows freeze-thaw’s destructive effect (both the strand’s surface and their joints). In the end, simple statistical analyses were presented to evaluate a model for anticipating the effect of freeze-thaw on mechanical resistance.

Topology transition description of horseshoe vortex system in juncture flows with velocity characteristic lines

Bo Hu, Hua Zhang, Ran Li, Qingkuan Liu

Theoretical and Applied Mechanics Letters 14 (2024) 100557. doi: 10.1016/j.taml.2024.100557

[Abstract] (250) [PDF 2731KB] (5)

Abstract:
Particle image velocimetry and numerical simulation results of juncture flows were analyzed to parametrically investigate topology transition. The vortex system evolutions from non-vortex to multi-vortex with variations in obstacle bluntness, obstacle width, flow velocity and boundary layer thickness are discussed from the perspective of velocity characteristic lines. The velocity characteristic lines of u = 0, v = 0, and ▽²v = 0 are adopted to describe the vortex system evolution. The motions of the characteristic lines with juncture flow parameters are described in detail, and the corresponding reflections of the vortex system patterns are illustrated. A panoramic picture of the development of velocity characteristic lines corresponding to the HSV topology transition from a non-vortex to a multi-vortex system with variations in the juncture flow parameter is established. Two methods for determining the attachment/separation pattern of the most upstream singularity are proposed. One method is based on the number of intersections of the u = 0 and v = 0 velocity characteristic curve lines, and the other is based on the relative positions of the most upstream feet of the u = 0 and v = 0 loop curves with both feet attached to the wall.

Numerical study on micro-fracture mechanism of rock dynamic failure induced by abrupt unloading under high in-situ stresses

Yuezong Yang, Anye Li, Zhushan Shao, Kui Wu, Wei Wei, Wenhui Du, Yujie Wang

Theoretical and Applied Mechanics Letters 14 (2024) 100558. doi: 10.1016/j.taml.2024.100558

[Abstract] (216) [PDF 4655KB] (4)

Abstract:
Rock burst is a kind of severe engineering disaster resulted from dynamic fracture process of rocks. The macro failure behaviors of rocks are primarily formed after experiencing the initiation, propagation, and coalescence of micro-cracks. In this paper, the grain-based discretized virtual internal bond model is employed to investigate the fracturing process of unloaded rock under high in-situ stresses from the micro-fracture perspective. The simulated micro-fracturing process reveals that the longitudinal stress waves induced by unloading lead to the visible unloading effect. The influences of in-situ stresses, mineral grain sizes, and grain heterogeneity on rock macro and micro fracture are investigated. Micro-crack areas of tensile and shear cracks and micro-crack angles are statistically analyzed to reveal the rock micro-fracture characteristics. The simulated results indicate that the combined effect of the stress state transition and the unloading effect dominates the rock unloading failure. The vertical and horizontal in-situ stresses determine the stress state of surrounding rock after unloading and the unloading effect, respectively. As the vertical stress increases, the stress level after unloading is higher, and the shear failure characteristics become more obvious. As the horizontal stress increases, the unloading effect increases, leading to the intensification of tensile failure. The mineral grain size and grain heterogeneity also have nonnegligible influences on rock unloading failure. The micro-fracture perspective provides further insight into the unloading failure mechanism of deep rock excavation.