国际机械系统动力学学报(英文)最新文献_第6页

Back Cover Image, Volume 5, Number 2, June 2025 封底图片，第五卷，第二期，2025年6月

IF 3.4

国际机械系统动力学学报(英文) Pub Date : 2025-06-25 DOI: 10.1002/msd2.70037

引用次数: 0

Robust Control for Uncertain Vertical Electric Stabilization System With Flexible Nonlinearity Using Backstepping Idea 含柔性非线性的不确定垂直电镇定系统的鲁棒控制

IF 3.6

国际机械系统动力学学报(英文) Pub Date : 2025-06-20 DOI: 10.1002/msd2.70029

Peng Liu, Tan Lu, He Zhang

{"title":"Robust Control for Uncertain Vertical Electric Stabilization System With Flexible Nonlinearity Using Backstepping Idea","authors":"Peng Liu, Tan Lu, He Zhang","doi":"10.1002/msd2.70029","DOIUrl":"https://doi.org/10.1002/msd2.70029","url":null,"abstract":"A robust control method for the uncertain vertical electric stabilization system (VESS) with flexible nonlinearity is proposed, and the mismatched uncertainty is considered and compensated based on the backstepping idea. First, based on evaluating the coupling effects of the flexible nonlinearity, the analytical dynamics model of the VESS is established. Second, the tracking error is defined as the evaluation of the system's pitch-pointing tracking control, and then the mismatched state space model with two interconnected subsystems is established as the controlled system. Third, the original mismatched system is converted to the locally matched system using the backstepping design to transform the system state variables. The robust control is proposed to handle the flexible nonlinearity and mismatched uncertainty, which can make both the original system and the reconfigured system present practical stability. Finally, the effectiveness of the proposed control is verified by numerical simulation experiments. This study should be the first to consider flexible nonlinearity coupling and two different uncertainties (matched and mismatched uncertainty) in the design of pitch-pointing tracking control for the vertical electric stabilization system (VESS).","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 3","pages":"443-462"},"PeriodicalIF":3.6,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transfer Learning in Physics-Informed Neurals Networks: Full Fine-Tuning, Lightweight Fine-Tuning, and Low-Rank Adaptation 物理信息神经网络中的迁移学习：完全微调，轻量级微调和低秩适应

IF 3.4

国际机械系统动力学学报(英文) Pub Date : 2025-06-06 DOI: 10.1002/msd2.70030

Yizheng Wang, Jinshuai Bai, Mohammad Sadegh Eshaghi, Cosmin Anitescu, Xiaoying Zhuang, Timon Rabczuk, Yinghua Liu

{"title":"Transfer Learning in Physics-Informed Neurals Networks: Full Fine-Tuning, Lightweight Fine-Tuning, and Low-Rank Adaptation","authors":"Yizheng Wang, Jinshuai Bai, Mohammad Sadegh Eshaghi, Cosmin Anitescu, Xiaoying Zhuang, Timon Rabczuk, Yinghua Liu","doi":"10.1002/msd2.70030","DOIUrl":"https://doi.org/10.1002/msd2.70030","url":null,"abstract":"AI for PDEs has garnered significant attention, particularly physics-informed neural networks (PINNs). However, PINNs are typically limited to solving specific problems, and any changes in problem conditions necessitate retraining. Therefore, we explore the generalization capability of transfer learning in the strong and energy forms of PINNs across different boundary conditions, materials, and geometries. The transfer learning methods we employ include full finetuning, lightweight finetuning, and low-rank adaptation (LoRA). Numerical experiments include the Taylor-Green Vortex in fluid mechanics and functionally graded materials with elastic properties, as well as a square plate with a circular hole in solid mechanics. The results demonstrate that full finetuning and LoRA can significantly improve convergence speed while providing a slight enhancement in accuracy. However, the overall performance of lightweight finetuning is suboptimal, as its accuracy and convergence speed are inferior to those of full finetuning and LoRA.","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 2","pages":"212-235"},"PeriodicalIF":3.4,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Numerical Simulation of Transient Heat Conduction With Moving Heat Source Using Physics Informed Neural Networks 基于物理信息神经网络的移动热源瞬态热传导数值模拟

IF 3.4

国际机械系统动力学学报(英文) Pub Date : 2025-06-05 DOI: 10.1002/msd2.70031

Anirudh Kalyan, Sundararajan Natarajan

引用次数: 0

Three Benefits of Using Nonlinear Compliance in Robotic Systems Performing Cyclic Tasks: Energy Efficiency, Control Robustness, and Gait Optimality 在执行循环任务的机器人系统中使用非线性顺应性的三个好处：能源效率，控制鲁棒性和步态最优性

IF 3.6

国际机械系统动力学学报(英文) Pub Date : 2025-05-25 DOI: 10.1002/msd2.70012

Rezvan Nasiri, Mahdi Khoramshahi, Mohammad Javad Yazdanpanah, Majid Nili Ahmadabadi

{"title":"Three Benefits of Using Nonlinear Compliance in Robotic Systems Performing Cyclic Tasks: Energy Efficiency, Control Robustness, and Gait Optimality","authors":"Rezvan Nasiri, Mahdi Khoramshahi, Mohammad Javad Yazdanpanah, Majid Nili Ahmadabadi","doi":"10.1002/msd2.70012","DOIUrl":"https://doi.org/10.1002/msd2.70012","url":null,"abstract":"Nonlinearity in parallel compliance can be exploited to improve the performance of locomotion systems in terms of (1) energy efficiency, (2) control robustness, and (3) gait optimality; that is, attaining energy efficiency across a set of motions. Thus far, the literature has investigated and validated only the first two benefits. In this study, we present a new mathematical framework for designing nonlinear compliances in cyclic tasks encompassing all three benefits. We present an optimization-based formulation for each benefit to obtain the desired compliance profile. Furthermore, we analytically prove that, compared to linear compliance, using nonlinear compliance leads to (1) lower energy consumption, (2) better closed-loop performance, specifically in terms of tracking error, and (3) a higher diversity of natural frequencies. To compare the performance of linear and nonlinear compliance, we apply the proposed methods to a diverse set of robotic systems performing cyclic tasks, including a 2-DOF manipulator, a 3-DOF bipedal walker, and a hopper model. Compared to linear compliance, the nonlinear compliance leads to better performance in all aspects; for example, a 70% reduction in energy consumption and tracking error for the manipulator simulation. Regarding gait optimality, for all robotic simulation models, compared to linear compliance, the nonlinear compliance has lower energy consumption and tracking error over the considered set of motions. The proposed analytical studies and simulation results strongly support the idea that using nonlinear compliance significantly improves robotic system performance in terms of energy efficiency, control robustness, and gait optimality.","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 3","pages":"564-575"},"PeriodicalIF":3.6,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of Orthotropic Variable Foundations and Unconventional Support Conditions on Nonlinear Hygrothermoelectric Vibration of Porous Multidirectional Piezoelectric Functionally Graded Nonuniform Plate 正交各向异性变基础和非常规支护条件对多孔多向功能梯度非均匀板非线性湿热电振动的影响

IF 3.6

国际机械系统动力学学报(英文) Pub Date : 2025-05-25 DOI: 10.1002/msd2.70027

Pawan Kumar, Sontipee Aimmanee, Suraj Prakash Harsha

{"title":"Effect of Orthotropic Variable Foundations and Unconventional Support Conditions on Nonlinear Hygrothermoelectric Vibration of Porous Multidirectional Piezoelectric Functionally Graded Nonuniform Plate","authors":"Pawan Kumar, Sontipee Aimmanee, Suraj Prakash Harsha","doi":"10.1002/msd2.70027","DOIUrl":"https://doi.org/10.1002/msd2.70027","url":null,"abstract":"This article investigates the nonlinear vibration behavior of porous multidirectional piezoelectric functionally graded nonuniform (PFGN) plates resting on orthotropic variable elastic foundations and subjected to hygrothermal loading. The sigmoidal law is employed to define the multidirectional gradation properties, incorporating porosity along both the axial and thickness directions. The governing equations for the porous multidirectional PFGN plate are derived using the modified first-order shear deformation theory (FSDT) with nonlinear von Kármán strain and Hamilton's principle. A higher-order finite element (FE) approach, combined with a modified Newton-Raphson method, is utilized to solve the resulting equations. The study reveals that orthotropic variable elastic foundations significantly influence the vibration behavior of multidirectional PFGN porous plates compared to conventional elastic foundations under hygrothermal loading. Additionally, the effects of various parameters such as thickness ratio, tapered ratio, material exponent, boundary conditions, porosity distribution, electrical loading, temperature variation, and moisture change on the vibration behavior are comprehensively analyzed. The results of this study have direct applications in energy harvesting and structural health monitoring, offering a novel approach to designing and optimizing smart materials for engineering systems operating under hygrothermal and thermoelectrical conditions.","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 3","pages":"535-563"},"PeriodicalIF":3.6,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145129379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influence of Velocity Feedback Time Delay on the Nonlinear Dynamic Characteristics of Maglev Trains Under Unsteady Aerodynamic Forces 非定常气动力作用下速度反馈时滞对磁悬浮列车非线性动力特性的影响

IF 3.6

国际机械系统动力学学报(英文) Pub Date : 2025-05-22 DOI: 10.1002/msd2.70022

Jia-Xuan Li, Zhi-Wei Liu, Xiang Liu

{"title":"Influence of Velocity Feedback Time Delay on the Nonlinear Dynamic Characteristics of Maglev Trains Under Unsteady Aerodynamic Forces","authors":"Jia-Xuan Li, Zhi-Wei Liu, Xiang Liu","doi":"10.1002/msd2.70022","DOIUrl":"https://doi.org/10.1002/msd2.70022","url":null,"abstract":"Time delays frequently arise in active control systems due to sensor sampling, signal transmission, and actuator response, making their effects on system dynamics non-negligible. This paper investigates how velocity feedback time delay influences the nonlinear dynamic characteristics of a maglev train subjected to unsteady aerodynamic forces. First, a time-delay dynamic model of the maglev system under unsteady aerodynamic forces is developed. Then, using the method of multiple scales (MMS), the frequency response equations for the maglev train are derived, and the steady-state solutions are evaluated for a stability assessment. Finally, the influence mechanism of time delay on the system's nonlinear vibration is explored under various parameters, such as unsteady aerodynamic force, train mass, displacement, and velocity feedback gain coefficients, with a particular focus on mitigating adverse effects stemming from the time delay. The results reveal that time delay plays a pivotal role in determining the vibration amplitude and overall system stability and that its influence exhibits periodic characteristics. In practical applications, judiciously tuning the time delay can help avoid its adverse impact. This study offers theoretical insights into the severe vibrations observed in real maglev operations and offers guidance for designing and optimizing control strategies to enhance ride comfort and system reliability.","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 4","pages":"707-720"},"PeriodicalIF":3.6,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145824775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explainable Artificial Intelligence (XAI) for Material Design and Engineering Applications: A Quantitative Computational Framework 材料设计与工程应用的可解释人工智能（XAI）：一个定量计算框架

IF 3.4

国际机械系统动力学学报(英文) Pub Date : 2025-05-20 DOI: 10.1002/msd2.70017

Bokai Liu, Pengju Liu, Weizhuo Lu, Thomas Olofsson

{"title":"Explainable Artificial Intelligence (XAI) for Material Design and Engineering Applications: A Quantitative Computational Framework","authors":"Bokai Liu, Pengju Liu, Weizhuo Lu, Thomas Olofsson","doi":"10.1002/msd2.70017","DOIUrl":"https://doi.org/10.1002/msd2.70017","url":null,"abstract":"The advancement of artificial intelligence (AI) in material design and engineering has led to significant improvements in predictive modeling of material properties. However, the lack of interpretability in machine learning (ML)-based material informatics presents a major barrier to its practical adoption. This study proposes a novel quantitative computational framework that integrates ML models with explainable artificial intelligence (XAI) techniques to enhance both predictive accuracy and interpretability in material property prediction. The framework systematically incorporates a structured pipeline, including data processing, feature selection, model training, performance evaluation, explainability analysis, and real-world deployment. It is validated through a representative case study on the prediction of high-performance concrete (HPC) compressive strength, utilizing a comparative analysis of ML models such as Random Forest, XGBoost, Support Vector Regression (SVR), and Deep Neural Networks (DNNs). The results demonstrate that XGBoost achieves the highest predictive performance (<math></math>), while SHAP (Shapley Additive Explanations) and LIME (Local Interpretable Model-Agnostic Explanations) provide detailed insights into feature importance and material interactions. Additionally, the deployment of the trained model as a cloud-based Flask-Gunicorn API enables real-time inference, ensuring its scalability and accessibility for industrial and research applications. The proposed framework addresses key limitations of existing ML approaches by integrating advanced explainability techniques, systematically handling nonlinear feature interactions, and providing a scalable deployment strategy. This study contributes to the development of interpretable and deployable AI-driven material informatics, bridging the gap between data-driven predictions and fundamental material science principles.","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 2","pages":"236-265"},"PeriodicalIF":3.4,"publicationDate":"2025-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MSTMM-Validated Machining Efficiency and Surface Roughness Improvement Using Evolutionary Optimization Algorithm 基于进化优化算法的mstmm验证加工效率和表面粗糙度改进

IF 3.4

国际机械系统动力学学报(英文) Pub Date : 2025-05-19 DOI: 10.1002/msd2.70013

Adeel Shehzad, Yuanyuan Ding, Yu Chang, Yiheng Chen, Xiaoting Rui, Hanjing Lu

{"title":"MSTMM-Validated Machining Efficiency and Surface Roughness Improvement Using Evolutionary Optimization Algorithm","authors":"Adeel Shehzad, Yuanyuan Ding, Yu Chang, Yiheng Chen, Xiaoting Rui, Hanjing Lu","doi":"10.1002/msd2.70013","DOIUrl":"https://doi.org/10.1002/msd2.70013","url":null,"abstract":"Ultra-precision machining (UPM) has been extensively employed for the production of high-end precision components. The process is highly precise, and the associated cost of production is also high. Optimization of machining parameters in UPM can significantly improve machining efficiency and surface roughness. This study proposes an innovative approach that couples transfer matrix methods for multibody systems (MSTMM) and particle swarm optimization (PSO) to optimize the machining parameters, aiming to simultaneously improve the machining efficiency and surface roughness of UPM machined components. Initially, the dynamic model of an ultra-precision fly-cutting (UPFC) machine tool was developed using MSTMM and validated by machining tests. Subsequently, the PSO algorithm was employed to optimize the machining parameters. Based on the optimized parameters, a 40% reduction in machining time and an 18.6% improvement in surface roughness peak-to-valley (PV) value have been achieved. The proposed method and the optimized parameters were verified through simulations using the MSTMM model, resulting in a minimal error of only 0.9%.","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 2","pages":"354-371"},"PeriodicalIF":3.4,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning-Assisted Sensitivity Analysis for Stochastic Fatigue Life Modeling of Metals 金属随机疲劳寿命建模的机器学习辅助灵敏度分析

IF 3.6

国际机械系统动力学学报(英文) Pub Date : 2025-05-19 DOI: 10.1002/msd2.70024

Tran C. H. Nguyen, N. Vu-Bac

引用次数: 0