国际机械系统动力学学报(英文)最新文献

Cover Image, Volume 5, Number 2, June 2025 封面图片，第五卷，第2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/msd2.70036

引用次数: 0

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

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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

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

Fluid Dynamics and Infrared Stealth of Marine IRS Devices: A Review 船用IRS装置的流体动力学与红外隐身研究进展

IF 3.4

国际机械系统动力学学报(英文) Pub Date : 2025-05-15 DOI: 10.1002/msd2.70019

Yitao Zou, Zhenrong Liu, Xin Qiao, Yingying Jiang, Hong Shi, Yanlong Jiang

{"title":"Fluid Dynamics and Infrared Stealth of Marine IRS Devices: A Review","authors":"Yitao Zou, Zhenrong Liu, Xin Qiao, Yingying Jiang, Hong Shi, Yanlong Jiang","doi":"10.1002/msd2.70019","DOIUrl":"https://doi.org/10.1002/msd2.70019","url":null,"abstract":"Infrared suppression (IRS) devices for naval ships play a crucial role in reducing the infrared radiation signature of high-temperature exhaust, thereby enhancing the survivability of ships against infrared-guided weapons. This paper provides a comprehensive review of recent advancements in the design and optimization of IRS devices. The primary research problem of the devices is the need to effectively suppress infrared radiation from ship exhaust gases, which are the main targets of infrared-guided missiles. To achieve this, the paper analyzes the infrared characteristics of exhaust systems from the perspectives of fluid dynamics, radiation sources, and radiation transmission, with a detailed explanation of the associated physical mechanisms and computational methods. The working principles and structural features of commonly used IRS devices, such as eductor/diffuser (E/D) devices and DRES-Ball devices, are introduced, with a focus on the design and optimization of key components, including nozzles, mixing diffusers, and optical blocking obstacles. Advanced suppression technologies, such as water injection and aerosol particle dispersion, are also discussed as auxiliary methods to enhance the infrared stealth capabilities. The review highlights that the advanced cooling mechanisms and optical property modifications can significantly reduce the infrared radiation of exhaust plumes. Furthermore, the paper identifies several challenges and future research directions, including the performance impacts of multi-device coordinated operation, the development of intelligent adaptive control systems, and the pursuit of lightweight and modular designs to meet the high mobility requirements of modern naval ships. This review aims to provide theoretical support and technical guidance for the practical design of IRS devices, offering valuable insights for the development of next-generation infrared stealth technologies for naval vessels.","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 2","pages":"179-200"},"PeriodicalIF":3.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144472895","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

Application of Surrogate Modeling in Stochastic Analysis of an Ogee Spillway Structure 代理模型在Ogee溢洪道结构随机分析中的应用

IF 3.4

国际机械系统动力学学报(英文) Pub Date : 2025-05-14 DOI: 10.1002/msd2.70026

Kaywan Othman Ahmed, Nazim Abdul Nariman, Rawand Sardar Abdulrahman

{"title":"Application of Surrogate Modeling in Stochastic Analysis of an Ogee Spillway Structure","authors":"Kaywan Othman Ahmed, Nazim Abdul Nariman, Rawand Sardar Abdulrahman","doi":"10.1002/msd2.70026","DOIUrl":"https://doi.org/10.1002/msd2.70026","url":null,"abstract":"This study investigates the hydraulic performance of an Ogee spillway under varying flow rate conditions, gate opening heights, and spillway widths. Numerical simulations using Flow-3D, incorporating the (k-ε) turbulence model and Large Eddy Simulation (LES), were employed alongside surrogate models using MATLAB codes and LP-TAU to predict flow behavior. The analysis focused on pressure distribution, water velocity, and shear stress variations across seven sensor locations along the spillway. Results indicate that pressure distribution generally decreases with increasing flow rate but rises with greater gate opening height or spillway width. A reduction in gate opening height lowers the pressure in the initial region but increases it downstream. Two negative pressure zones were identified, one at the Ogee curve and another at the downstream sloping section, highlighting potential cavitation risks. Comparisons with experimental data confirmed a strong correlation, with minor discrepancies in specific sensors under varying conditions. The study demonstrates that numerical modeling, particularly using the (k-ε) turbulence model in Flow-3D, effectively assesses the hydraulic performance of controlled Ogee-type spillways.","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 2","pages":"290-311"},"PeriodicalIF":3.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473077","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

Computational Method for Designing the Retaining Reinforcement Concrete Wall Under Hydrodynamic Load in Marine 船舶水动力荷载下钢筋混凝土挡土墙设计的计算方法

IF 3.4

国际机械系统动力学学报(英文) Pub Date : 2025-05-13 DOI: 10.1002/msd2.70021

Arshia Shishegaran, Aydin Shishegaran

{"title":"Computational Method for Designing the Retaining Reinforcement Concrete Wall Under Hydrodynamic Load in Marine","authors":"Arshia Shishegaran, Aydin Shishegaran","doi":"10.1002/msd2.70021","DOIUrl":"https://doi.org/10.1002/msd2.70021","url":null,"abstract":"Health monitoring and damage detection for important and special infrastructures, especially marine structures, are one of the important challenges in structural engineering because they are subjected to corrosion and hydrodynamic loads. Simulation of marine structures under corrosion and hydraulic loads is complex; thus, a combination of point cloud data sets, validation finite element model, parametric studies, and machine-learning methods was used in this study to estimate the damaged surface of retaining reinforced concrete walls (RRCWs) and the load-carrying capacity of RRCWs according to design parameters of RRCWs. After validation of the finite element method (FEM), 144 specimens were simulated using the FEM and the obtained displacement-control loading. Compressive strength, thickness of RRCWs, strength of reinforcement bars, and ratio of reinforcement bars were considered as the design parameters. The results show that the thickness of RRCWs has the most effect on decreasing the damaged surface and load-carrying capacity. Furthermore, the results demonstrate that Gene Expression Programming (GEP) performs better than all models and can predict the damaged surface and load-carrying capacity with 99% and 97% accuracy, respectively. Moreover, by decreasing the thickness of RRCWs, the damaged surface is reduced to 2.5%, and by increasing the thickness, the load-carrying capacity is increased to 51%–59%.","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 2","pages":"324-344"},"PeriodicalIF":3.4,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473206","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

SCT-BEM for Transient Heat Conduction and Wave Propagation in 2D Thin-Walled Structures 二维薄壁结构瞬态热传导和波传播的SCT-BEM

IF 3.4

国际机械系统动力学学报(英文) Pub Date : 2025-04-26 DOI: 10.1002/msd2.70015

Xiaotong Gao, Yan Gu

{"title":"SCT-BEM for Transient Heat Conduction and Wave Propagation in 2D Thin-Walled Structures","authors":"Xiaotong Gao, Yan Gu","doi":"10.1002/msd2.70015","DOIUrl":"https://doi.org/10.1002/msd2.70015","url":null,"abstract":"Traditional boundary element method (BEM) faces significant challenges in addressing dynamic problems in thin-walled structures. These challenges arise primarily from the complexities of handling time-dependent terms and nearly singular integrals in structures with thin-shapes. In this study, we reformulate time derivative terms as domain integrals and approximate the unknown functions using radial basis functions (RBFs). This reformulation simplifies the treatment of transient terms and enhances computational efficiency by reducing the complexity of time-dependent formulations. The resulting domain integrals are efficiently evaluated using the scaled coordinate transformation BEM (SCT-BEM), which converts domain integrals into equivalent boundary integrals, thereby improving numerical accuracy and stability. Furthermore, to tackle the challenges inherent in thin-body structures, a nonlinear coordinate transformation is introduced to effectively remove the near-singular behavior of the integrals. The proposed method offers several advantages, including greater flexibility in managing transient terms, lower computational costs, and improved stability for thin-body problems.","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 2","pages":"266-276"},"PeriodicalIF":3.4,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473073","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