Pub Date : 2026-02-01Epub Date: 2025-12-05DOI: 10.1016/j.advengsoft.2025.104081
Chang Liu, Detao Wan, Zhe Wang, Dean Hu
Robotic manipulators used in confined operational environments, such as next-generation nuclear facilities, must satisfy demanding requirements. These include remote operability, spatial adaptability, and resilience to environmental constraints. This paper presents a curvature-constrained path planning framework based on the Multi-branch Rapidly-Exploring Random Tree (Mb-RRT) algorithm, specifically designed for a cable-driven snake-arm manipulator tasked with inspection operations in restricted workspaces. The Mb-RRT algorithm integrates direction-aware nearest-node selection, curvature-compliant path extension, and a multi-path reuse mechanism enabled by a Path Pass Diagram (PP-Diagram) and Connection Relationship Matrix (CR-Matrix). These enhancements significantly improve search efficiency and path feasibility in cluttered environments with limited curvature freedom. Simulation studies indicate that under a 26° joint deflection constraint, feasible paths were successfully generated in 92.2 % of cases within 500 iterations. When the iteration limit was extended to 10,000, the success rate increased to 100 %. The proposed framework is further validated through experimental deployment, achieving terminal positioning errors below 2.02 mm. These results confirm the effectiveness and practical applicability of the Mb-RRT framework as a planning module for curvature-constrained motion in snake-arm manipulators operating under spatially restrictive conditions.
{"title":"Mb-RRT: A curvature-constrained path planning framework for cable-driven snake-arm manipulators in confined environments","authors":"Chang Liu, Detao Wan, Zhe Wang, Dean Hu","doi":"10.1016/j.advengsoft.2025.104081","DOIUrl":"10.1016/j.advengsoft.2025.104081","url":null,"abstract":"<div><div>Robotic manipulators used in confined operational environments, such as next-generation nuclear facilities, must satisfy demanding requirements. These include remote operability, spatial adaptability, and resilience to environmental constraints. This paper presents a curvature-constrained path planning framework based on the Multi-branch Rapidly-Exploring Random Tree (Mb-RRT) algorithm, specifically designed for a cable-driven snake-arm manipulator tasked with inspection operations in restricted workspaces. The Mb-RRT algorithm integrates direction-aware nearest-node selection, curvature-compliant path extension, and a multi-path reuse mechanism enabled by a Path Pass Diagram (PP-Diagram) and Connection Relationship Matrix (CR-Matrix). These enhancements significantly improve search efficiency and path feasibility in cluttered environments with limited curvature freedom. Simulation studies indicate that under a 26° joint deflection constraint, feasible paths were successfully generated in 92.2 % of cases within 500 iterations. When the iteration limit was extended to 10,000, the success rate increased to 100 %. The proposed framework is further validated through experimental deployment, achieving terminal positioning errors below 2.02 mm. These results confirm the effectiveness and practical applicability of the Mb-RRT framework as a planning module for curvature-constrained motion in snake-arm manipulators operating under spatially restrictive conditions.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104081"},"PeriodicalIF":5.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-05DOI: 10.1016/j.advengsoft.2025.104085
Kyung Bo Lee , Tae Hee Lee , Yena Lee , Jung-Wuk Hong
Blast pressure propagation and crater morphology from surface detonations are governed by explosive type, geometry, soil properties, and the position of the explosive relative to the soil. In this study, multi-material arbitrary Lagrange–Eulerian (MMALE) simulations are conducted to investigate the effects of contact angle variations on blast pressure and crater morphology for TNT and Aluminized Enhanced Blast Explosive (AEBE). The discretized MMALE model is verified by comparing the results with experimental results, and the blast pressure and crater morphology are accurately predicted. Numerical simulations reveal that contact angle variations lead to nonlinear changes in blast pressure and crater morphology. AEBE produces consistently higher peak overpressure than TNT, and crater aspect ratio and volume are strongly influenced by contact angle. Polynomial regression models effectively characterize the nonlinear and systematic variations associated with contact angle changes. An effective methodology is established to evaluate the effects of variations in contact angle with both TNT and AEBE.
{"title":"Numerical study of explosive–soil contact angle effects on blast pressure and crater morphology with TNT and aluminized explosives","authors":"Kyung Bo Lee , Tae Hee Lee , Yena Lee , Jung-Wuk Hong","doi":"10.1016/j.advengsoft.2025.104085","DOIUrl":"10.1016/j.advengsoft.2025.104085","url":null,"abstract":"<div><div>Blast pressure propagation and crater morphology from surface detonations are governed by explosive type, geometry, soil properties, and the position of the explosive relative to the soil. In this study, multi-material arbitrary Lagrange–Eulerian (MMALE) simulations are conducted to investigate the effects of contact angle variations on blast pressure and crater morphology for TNT and Aluminized Enhanced Blast Explosive (AEBE). The discretized MMALE model is verified by comparing the results with experimental results, and the blast pressure and crater morphology are accurately predicted. Numerical simulations reveal that contact angle variations lead to nonlinear changes in blast pressure and crater morphology. AEBE produces consistently higher peak overpressure than TNT, and crater aspect ratio and volume are strongly influenced by contact angle. Polynomial regression models effectively characterize the nonlinear and systematic variations associated with contact angle changes. An effective methodology is established to evaluate the effects of variations in contact angle with both TNT and AEBE.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104085"},"PeriodicalIF":5.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-08DOI: 10.1016/j.advengsoft.2025.104084
Anugrah Jo Joshy, John T. Hwang
Applications of numerical optimization span a wide range of fields, from finance and economics to the natural sciences and engineering. Optimization techniques employed in each field are specialized to exploit the structure of the underlying problems. As optimization problems grow in scale and complexity, they uncover bottlenecks in existing optimization algorithms and necessitate further specialization of the algorithms. Such specialization requires expert knowledge of the underlying mathematical theory and the software implementation of current algorithms. However, currently available optimization libraries lack the modularity, transparency, and accessibility needed for customization and experimentation, as they often provide only monolithic implementations of algorithms. To overcome the challenges posed by this limitation in algorithm development and education, we present modOpt, an open-source Python framework designed to facilitate the construction, customization, and study of optimization algorithms. Its modular architecture enables students and researchers to tailor existing algorithms to new applications by only altering the relevant modules, eliminating the need to understand or reimplement an algorithm in its entirety. The framework is written entirely in Python and supports both novice and advanced users through clear documentation, built-in visualization, and fully transparent implementations of pedagogical algorithms. To facilitate testing and benchmarking of new algorithms, the framework features interfaces to modeling frameworks such as OpenMDAO and CSDL, interfaces to general-purpose optimization algorithms such as SNOPT and SLSQP, and an interface to the CUTEst test problem set. This level of interoperability—spanning 12 external algorithms, 10 pedagogical algorithms, 4 modeling tools, and a benchmark test set—is unique to modOpt and is not available in other optimization libraries. In this paper, we present the software architecture of modOpt, review its various features, discuss several educational and performance-oriented algorithms within modOpt, and present numerical studies illustrating its unique capabilities. modOpt is available as an open-source project on GitHub at https://github.com/lsdolab/modopt, with comprehensive documentation hosted at https://modopt.readthedocs.io/.
{"title":"modOpt: A modular development environment and library for optimization algorithms","authors":"Anugrah Jo Joshy, John T. Hwang","doi":"10.1016/j.advengsoft.2025.104084","DOIUrl":"10.1016/j.advengsoft.2025.104084","url":null,"abstract":"<div><div>Applications of numerical optimization span a wide range of fields, from finance and economics to the natural sciences and engineering. Optimization techniques employed in each field are specialized to exploit the structure of the underlying problems. As optimization problems grow in scale and complexity, they uncover bottlenecks in existing optimization algorithms and necessitate further specialization of the algorithms. Such specialization requires expert knowledge of the underlying mathematical theory and the software implementation of current algorithms. However, currently available optimization libraries lack the modularity, transparency, and accessibility needed for customization and experimentation, as they often provide only monolithic implementations of algorithms. To overcome the challenges posed by this limitation in algorithm development and education, we present modOpt, an open-source Python framework designed to facilitate the construction, customization, and study of optimization algorithms. Its modular architecture enables students and researchers to tailor existing algorithms to new applications by only altering the relevant modules, eliminating the need to understand or reimplement an algorithm in its entirety. The framework is written entirely in Python and supports both novice and advanced users through clear documentation, built-in visualization, and fully transparent implementations of pedagogical algorithms. To facilitate testing and benchmarking of new algorithms, the framework features interfaces to modeling frameworks such as OpenMDAO and CSDL, interfaces to general-purpose optimization algorithms such as SNOPT and SLSQP, and an interface to the CUTEst test problem set. This level of interoperability—spanning 12 external algorithms, 10 pedagogical algorithms, 4 modeling tools, and a benchmark test set—is unique to modOpt and is not available in other optimization libraries. In this paper, we present the software architecture of modOpt, review its various features, discuss several educational and performance-oriented algorithms within modOpt, and present numerical studies illustrating its unique capabilities. modOpt is available as an open-source project on GitHub at <span><span>https://github.com/lsdolab/modopt</span><svg><path></path></svg></span>, with comprehensive documentation hosted at <span><span>https://modopt.readthedocs.io/</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104084"},"PeriodicalIF":5.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-06DOI: 10.1016/j.advengsoft.2025.104074
Hyoungwoo Kim , Robert Chiodi , Marc Day , Yong Jea Kim , Dong-hyuk Shin
A new algorithm is presented to simulate multiphase flows with surface tension in a pathway for spray combustion simulation. The algorithm combines capabilities from two open-source packages, including the interface reconstruction library (IRL), a library of computational geometry routines to enable the volume of fluid (VOF) method, and PeleLM, a solver for the reacting Navier-Stokes equations. Additionally, surface tension is implemented using the continuum surface force (CSF) model with an improved height function technique in the volume fraction field. Spurious errors in volume fraction arising from our combined strategy are corrected through a topology-based method that improves both numerical stability and accuracy. Multiple validation simulations are conducted, including (i) translations and rotations of Zalesak’s disk, (ii) a stationary circular droplet with surface tension, (iii) an oscillating elliptical droplet, and (iv) three-dimensional deformation of a spherical droplet. Results indicate that the combined scheme retains the favorable properties of each of the component algorithms.
{"title":"A geometric volume of fluid-based multiphase flow solver extension to the reacting flow solver, PeleLM","authors":"Hyoungwoo Kim , Robert Chiodi , Marc Day , Yong Jea Kim , Dong-hyuk Shin","doi":"10.1016/j.advengsoft.2025.104074","DOIUrl":"10.1016/j.advengsoft.2025.104074","url":null,"abstract":"<div><div>A new algorithm is presented to simulate multiphase flows with surface tension in a pathway for spray combustion simulation. The algorithm combines capabilities from two open-source packages, including the interface reconstruction library (IRL), a library of computational geometry routines to enable the volume of fluid (VOF) method, and PeleLM, a solver for the reacting Navier-Stokes equations. Additionally, surface tension is implemented using the continuum surface force (CSF) model with an improved height function technique in the volume fraction field. Spurious errors in volume fraction arising from our combined strategy are corrected through a topology-based method that improves both numerical stability and accuracy. Multiple validation simulations are conducted, including (<em>i</em>) translations and rotations of Zalesak’s disk, (<em>ii</em>) a stationary circular droplet with surface tension, (<em>iii</em>) an oscillating elliptical droplet, and (<em>iv</em>) three-dimensional deformation of a spherical droplet. Results indicate that the combined scheme retains the favorable properties of each of the component algorithms.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104074"},"PeriodicalIF":5.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-05DOI: 10.1016/j.advengsoft.2025.104094
Nan Xu, Yanhui Liu, Hongjin Chen, Ming Gao
Concrete filled steel tube (CFST) columns are vulnerable to lateral impact from automobiles, ships and derailed trains as global transportation rapidly expands. The theoretical research about impact response is challenging as it involves a series of physical phenomena. This research aims to establish simplified mathematic model to evaluate CFST deflection and damage reliability through machine learning techniques, where input features contain 11 variables. 410 impact specimens were gathered and they were divided at 8:2 ratio for model training and testing. Nine hybrid algorithms were created, IGWO (Improved Grey Wolf Optimizer)-Ann (artificial neural networks) performed the best deflection prediction with correlation coefficient of 0.90. The simplified model of deflection was established, and its computational efficiency is substantially superior to theoretical methods. The credibility of IGWO-Ann was verified by Shapley Additive exPlanations analysis. Furthermore, the explicit equations of damage probability and damage reliability were proposed. Sensitivity analysis indicated that section outer diameter and steel strength influence dramatically damage probability. Finally, an impact-resistant procedure was suggested, which provides an efficient, user-friendly and precise method for structural engineers.
随着全球交通运输的迅速扩张，钢管混凝土（CFST）柱容易受到汽车、船舶和出轨列车的横向冲击。由于冲击响应涉及一系列物理现象，其理论研究具有一定的挑战性。本研究旨在通过机器学习技术建立CFST挠度和损伤可靠性评估的简化数学模型，其中输入特征包含11个变量。收集410个冲击试件，按8:2的比例进行模型训练和试验。建立了9种混合算法，其中IGWO (Improved Grey Wolf Optimizer)-Ann （artificial neural networks）的偏转预测效果最好，相关系数为0.90。建立了挠度的简化模型，其计算效率大大优于理论方法。通过Shapley加性解释分析验证了IGWO-Ann的可信度。在此基础上，建立了损伤概率和损伤可靠度的显式方程。敏感性分析表明，截面外径和钢强度对损伤概率影响较大。最后，提出了一种抗冲击程序，为结构工程师提供了一种高效、方便和精确的方法。
{"title":"Prediction models of deflection and damage reliability for laterally impacted CFST based on data-driven technology","authors":"Nan Xu, Yanhui Liu, Hongjin Chen, Ming Gao","doi":"10.1016/j.advengsoft.2025.104094","DOIUrl":"10.1016/j.advengsoft.2025.104094","url":null,"abstract":"<div><div>Concrete filled steel tube (CFST) columns are vulnerable to lateral impact from automobiles, ships and derailed trains as global transportation rapidly expands. The theoretical research about impact response is challenging as it involves a series of physical phenomena. This research aims to establish simplified mathematic model to evaluate CFST deflection and damage reliability through machine learning techniques, where input features contain 11 variables. 410 impact specimens were gathered and they were divided at 8:2 ratio for model training and testing. Nine hybrid algorithms were created, IGWO (Improved Grey Wolf Optimizer)-Ann (artificial neural networks) performed the best deflection prediction with correlation coefficient of 0.90. The simplified model of deflection was established, and its computational efficiency is substantially superior to theoretical methods. The credibility of IGWO-Ann was verified by Shapley Additive exPlanations analysis. Furthermore, the explicit equations of damage probability and damage reliability were proposed. Sensitivity analysis indicated that section outer diameter and steel strength influence dramatically damage probability. Finally, an impact-resistant procedure was suggested, which provides an efficient, user-friendly and precise method for structural engineers.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104094"},"PeriodicalIF":5.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper presents the results of the development of an original mathematical model and a numerical algorithm for pore network modeling of non-Newtonian flows of power law fluids in microchannel media. The pore network model is based on an original method of connecting one-dimensional and three-dimensional CFD solvers into a conjugated hydrodynamic model with a common pressure field. The non-Newtonian properties of a liquid are taken into account in a pore network model by setting a generalized resistance coefficient. An original microfluidic chips simulating fractured and porous rock were created to test the developed numerical method of pore network modeling of non-Newtonian flows. The flow of polymer solutions in a microfluidic chip has been studied experimentally. Testing has shown that the pore network algorithm for the case of a non-Newtonian (power law) flow in a single circular tube coincides with the analytical solution with an error below 0.01 %. The average uncertainty in determining the pressure drop in a microfluidic chip by the proposed algorithm over a wide range of fluid flow rates and their rheological characteristics does not exceed 10 %. At the same time, the computational efficiency of the pore network model is demonstrated to be 180 times of magnitude higher than that of the CFD model for a fractured microchip model and to be 720 times for a porous microchip model, all other things being equal and with close accuracy compared to the experiment.
{"title":"Development and testing of a new pore network algorithm for modeling flows of power law fluids in porous media","authors":"S.A. Filimonov , A.I. Pryazhnikov , D.V. Guzei , A.V. Minakov","doi":"10.1016/j.advengsoft.2025.104091","DOIUrl":"10.1016/j.advengsoft.2025.104091","url":null,"abstract":"<div><div>The paper presents the results of the development of an original mathematical model and a numerical algorithm for pore network modeling of non-Newtonian flows of power law fluids in microchannel media. The pore network model is based on an original method of connecting one-dimensional and three-dimensional CFD solvers into a conjugated hydrodynamic model with a common pressure field. The non-Newtonian properties of a liquid are taken into account in a pore network model by setting a generalized resistance coefficient. An original microfluidic chips simulating fractured and porous rock were created to test the developed numerical method of pore network modeling of non-Newtonian flows. The flow of polymer solutions in a microfluidic chip has been studied experimentally. Testing has shown that the pore network algorithm for the case of a non-Newtonian (power law) flow in a single circular tube coincides with the analytical solution with an error below 0.01 %. The average uncertainty in determining the pressure drop in a microfluidic chip by the proposed algorithm over a wide range of fluid flow rates and their rheological characteristics does not exceed 10 %. At the same time, the computational efficiency of the pore network model is demonstrated to be 180 times of magnitude higher than that of the CFD model for a fractured microchip model and to be 720 times for a porous microchip model, all other things being equal and with close accuracy compared to the experiment.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104091"},"PeriodicalIF":5.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-18DOI: 10.1016/j.advengsoft.2025.104088
Wei Chen , Dingding Wang , Ping Xiang , Peng Shi , Junsong Hu
In this research, a concise and efficient numerical approach is presented to explore the size-dependent free vibration behavior of functionally graded (FG) microplates composed of graphene origami (GOri)-enabled auxetic metamaterial (GOEAM), supported by Winkler, Pasternak, or Kerr foundations. The FG microplate is modeled as a multilayered structure composed of isotropic and homogeneous GOEAM layers, with a stepwise GOri dispersion through the thickness. At the same time, AI-assisted micromechanical modeling using genetic programming (GP) techniques are employed to precisely describe the complex material behavior. In addition, a refined plate theory involving four independent variables is adopted to incorporate both bending responses and shear effects. To address size-dependent phenomena, the modified couple stress theory (MCST), which introduces an intrinsic material length scale parameter (MLSP), is embedded within the conventional continuum mechanics framework. Thereafter, applying Hamilton’s principle, the weak formulation governing the size-dependent free vibration of the FG-GOEAM microplate placed on Winkler, Pasternak, or Kerr-type foundations is established. The corresponding numerical results are then acquired using the isogeometric analysis (IGA) technique. After validating the convergence and efficacy of the methodology presented herein, an extensive investigation was conducted to examine how several factors such as GOri dispersion pattern, weight fraction, folding degree, MLSP, and foundation stiffness affect the free vibration performance of the FG metamaterial microplates. The study demonstrates that the inclusion of MLSP alters how the frequencies of FG-GOEAM microplates varies with changes in GOri weight fraction and folding degree. Specifically, in general, an increase in the MLSP accentuates the increasing trend of frequency as GOri weight fraction rises, and gradually transforms the decreasing trend of frequency with the reduction of GOri folding degree into an increasing one. Additionally, the Pasternak shear layer coefficient and the Kerr foundation's intermediate shear layer coefficient dominantly influence the microplates' frequency.
{"title":"Isogeometric free vibration analysis of size-dependent functionally graded graphene origami-enabled auxetic metamaterial microplates supported by Winkler/Pasternak/Kerr foundation","authors":"Wei Chen , Dingding Wang , Ping Xiang , Peng Shi , Junsong Hu","doi":"10.1016/j.advengsoft.2025.104088","DOIUrl":"10.1016/j.advengsoft.2025.104088","url":null,"abstract":"<div><div>In this research, a concise and efficient numerical approach is presented to explore the size-dependent free vibration behavior of functionally graded (FG) microplates composed of graphene origami (GOri)-enabled auxetic metamaterial (GOEAM), supported by Winkler, Pasternak, or Kerr foundations. The FG microplate is modeled as a multilayered structure composed of isotropic and homogeneous GOEAM layers, with a stepwise GOri dispersion through the thickness. At the same time, AI-assisted micromechanical modeling using genetic programming (GP) techniques are employed to precisely describe the complex material behavior. In addition, a refined plate theory involving four independent variables is adopted to incorporate both bending responses and shear effects. To address size-dependent phenomena, the modified couple stress theory (MCST), which introduces an intrinsic material length scale parameter (MLSP), is embedded within the conventional continuum mechanics framework. Thereafter, applying Hamilton’s principle, the weak formulation governing the size-dependent free vibration of the FG-GOEAM microplate placed on Winkler, Pasternak, or Kerr-type foundations is established. The corresponding numerical results are then acquired using the isogeometric analysis (IGA) technique. After validating the convergence and efficacy of the methodology presented herein, an extensive investigation was conducted to examine how several factors such as GOri dispersion pattern, weight fraction, folding degree, MLSP, and foundation stiffness affect the free vibration performance of the FG metamaterial microplates. The study demonstrates that the inclusion of MLSP alters how the frequencies of FG-GOEAM microplates varies with changes in GOri weight fraction and folding degree. Specifically, in general, an increase in the MLSP accentuates the increasing trend of frequency as GOri weight fraction rises, and gradually transforms the decreasing trend of frequency with the reduction of GOri folding degree into an increasing one. Additionally, the Pasternak shear layer coefficient and the Kerr foundation's intermediate shear layer coefficient dominantly influence the microplates' frequency.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104088"},"PeriodicalIF":5.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-27DOI: 10.1016/j.advengsoft.2025.104092
Jin Wang , Mingliang Zhu , Jiahao Cao , Jiamin Guo , Zhiwei Miao
The cable dome is widely recognized for its lightweight, structural efficiency, and ease of length adjustment for active displacement control. However, achieving effective active control critically depends on the optimal placement of actuators. This paper proposes a physics-informed neural network (PINN) and singular value decomposition (SVD) framework to optimize actuator placement. Specifically, we introduce a PINN-based loss function that simultaneously incorporates structural control accuracy and essential physical constraints, enhancing the optimization efficiency and accuracy. The use of SVD within the PINN framework systematically extracts dominant sensitivity directions from the structural response sensitivity matrix, significantly reducing computational complexity and improving predictive capability. The approach is validated through numerical studies involving four different cable dome configurations. Results demonstrate that the developed method achieves substantial reductions (over 85 %) in structural displacement, while requiring actuators on only 5–10 % of structural elements. The proposed method provides a practical, efficient, and reliable solution for actuator placement, addressing a critical engineering challenge in active control of cable domes.
{"title":"A physics-informed neural network and singular value decomposition framework for actuator placement optimization in cable dome","authors":"Jin Wang , Mingliang Zhu , Jiahao Cao , Jiamin Guo , Zhiwei Miao","doi":"10.1016/j.advengsoft.2025.104092","DOIUrl":"10.1016/j.advengsoft.2025.104092","url":null,"abstract":"<div><div>The cable dome is widely recognized for its lightweight, structural efficiency, and ease of length adjustment for active displacement control. However, achieving effective active control critically depends on the optimal placement of actuators. This paper proposes a physics-informed neural network (PINN) and singular value decomposition (SVD) framework to optimize actuator placement. Specifically, we introduce a PINN-based loss function that simultaneously incorporates structural control accuracy and essential physical constraints, enhancing the optimization efficiency and accuracy. The use of SVD within the PINN framework systematically extracts dominant sensitivity directions from the structural response sensitivity matrix, significantly reducing computational complexity and improving predictive capability. The approach is validated through numerical studies involving four different cable dome configurations. Results demonstrate that the developed method achieves substantial reductions (over 85 %) in structural displacement, while requiring actuators on only 5–10 % of structural elements. The proposed method provides a practical, efficient, and reliable solution for actuator placement, addressing a critical engineering challenge in active control of cable domes.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104092"},"PeriodicalIF":5.7,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-11-13DOI: 10.1016/j.advengsoft.2025.104063
Acar Can Kocabıçak , Kyle Nelson , Saeed Althamer , Senai Yalçınkaya , Gregor Kosec , Lihua Wang , Magd Abdel Wahab
Flow forming is a high-precision metal forming process used to produce thin-walled, rotationally symmetric components with enhanced mechanical properties. This study investigates the two-roller vertical forward flow forming process for EN36B steel through Finite Element Analysis (FEA) using FORGE® NxT 4.0, complemented by experimental validation. Material properties of EN36B steel, including elasticity, thermal, physical, and plasticity characteristics, were modelled with JmatPro software to ensure accurate simulations. Experimental trials included microstructural characterisation, hardness testing, surface roughness evaluation, and twist measurements to validate the numerical model. The FEA simulations provided critical insights into key process parameters such as Von Mises stress, strain, Latham-Cockroft damage, and force dynamics. Defects such as bulging and material build-up were effectively predicted and modelled. Dimensional accuracy was assessed using 3D GOM scanning, revealing a maximum thickness error of 0.3 mm. Discrepancies in force measurements between simulations and experiments were minimal, with deviations of 6.5 % for radial forces and 2.5 % for axial forces. Surface roughness improved significantly, with values decreasing from 2.1 μm Ra to 0.7 μm Ra after vertical forward flow forming.
Furthermore, the hardness increased from 186 HV to 260 MPa (around 40 %) after the forming due to the work hardening process with plasticity. Tensile stress of the workpiece increased from 620 MPa to 880 MPa without an additional heat treatment process. Due to the roller's high force on the workpiece's outer surface, the hardness testing revealed a maximum value of 279 HV on the outer surface, reducing to a minimum of 236 HV closer to the inner surface. The hardness error between FEA and experimental results is around 2 %. Electron Backscatter Diffraction (EBSD) analysis indicated higher grain deformation at the outside surface compared to the middle and inner surface of the flow-formed tube. The vertical forward flow forming process reached a maximum temperature of approximately 200 °C, which was efficiently managed through water cooling. The study highlights the utility of Arbitrary Lagrangian-Eulerian (ALE) formulations and remeshing techniques in simulating complex deformation patterns. These methods provide critical insights for optimising the flow forming process and advancing the manufacture of EN36B steel components.
{"title":"Finite element modelling and experimental validation of two-roller vertical forward flow forming process of EN36B steel","authors":"Acar Can Kocabıçak , Kyle Nelson , Saeed Althamer , Senai Yalçınkaya , Gregor Kosec , Lihua Wang , Magd Abdel Wahab","doi":"10.1016/j.advengsoft.2025.104063","DOIUrl":"10.1016/j.advengsoft.2025.104063","url":null,"abstract":"<div><div>Flow forming is a high-precision metal forming process used to produce thin-walled, rotationally symmetric components with enhanced mechanical properties. This study investigates the two-roller vertical forward flow forming process for EN36B steel through Finite Element Analysis (FEA) using FORGE® NxT 4.0, complemented by experimental validation. Material properties of EN36B steel, including elasticity, thermal, physical, and plasticity characteristics, were modelled with JmatPro software to ensure accurate simulations. Experimental trials included microstructural characterisation, hardness testing, surface roughness evaluation, and twist measurements to validate the numerical model. The FEA simulations provided critical insights into key process parameters such as Von Mises stress, strain, Latham-Cockroft damage, and force dynamics. Defects such as bulging and material build-up were effectively predicted and modelled. Dimensional accuracy was assessed using 3D GOM scanning, revealing a maximum thickness error of 0.3 mm. Discrepancies in force measurements between simulations and experiments were minimal, with deviations of 6.5 % for radial forces and 2.5 % for axial forces. Surface roughness improved significantly, with values decreasing from 2.1 μm Ra to 0.7 μm Ra after vertical forward flow forming.</div><div>Furthermore, the hardness increased from 186 HV to 260 MPa (around 40 %) after the forming due to the work hardening process with plasticity. Tensile stress of the workpiece increased from 620 MPa to 880 MPa without an additional heat treatment process. Due to the roller's high force on the workpiece's outer surface, the hardness testing revealed a maximum value of 279 HV on the outer surface, reducing to a minimum of 236 HV closer to the inner surface. The hardness error between FEA and experimental results is around 2 %. Electron Backscatter Diffraction (EBSD) analysis indicated higher grain deformation at the outside surface compared to the middle and inner surface of the flow-formed tube. The vertical forward flow forming process reached a maximum temperature of approximately 200 °C, which was efficiently managed through water cooling. The study highlights the utility of Arbitrary Lagrangian-Eulerian (ALE) formulations and remeshing techniques in simulating complex deformation patterns. These methods provide critical insights for optimising the flow forming process and advancing the manufacture of EN36B steel components.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"212 ","pages":"Article 104063"},"PeriodicalIF":5.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145520411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-11-06DOI: 10.1016/j.advengsoft.2025.104048
Dong Liang , Manjun Cui , Shiyou Li , Boyan Chang , Zhen Wang , Junpeng Zhang
Due to complex nonlinear closed-loop constraints and structural flexibility, the dynamic modeling and control issue on flexible parallel robots is much more challenging compared to serial counterparts. Oriented to the demand of the high-end manufacturing field, this paper proposes a novel lightweight redundant parallel robot with cross layout of guide rail. Based on assumed mode discretization and Kane’s formulation, a general rigid-flexible coupling dynamic model of arbitrary branch incorporating n-order modes is derived. Leveraging modular ideology, the complete rigid-flexible coupling dynamic model of the system is established combining with nonlinear constraint equations, which is solved by the Runge-Kutta algorithm, modal truncation and forward dynamics methodology. The dynamic response comparison results between the redundant parallel robot and the non-redundant parallel robot reveal that the redundant actuation can suppress the elastic vibration. The rigid-flexible coupling dynamic model is then validated by a physical simulation model developed through the MATLAB/Simscape® platform using the finite segment approach. The electromechanical coupling dynamic model is further formulated by integrating the rigid-flexible coupling dynamic model with the permanent magnet synchronous motor and smart material. An adaptive intelligent composite control strategy is proposed to achieve trajectory tracking and vibration suppression. The comparison results with the other three control strategies demonstrate that the adaptive intelligent composite control strategy has superior control performance, exhibiting potential application prospects.
{"title":"Rigid-flexible coupling dynamic modeling and adaptive intelligent composite control for a novel redundantly actuated flexible parallel robot","authors":"Dong Liang , Manjun Cui , Shiyou Li , Boyan Chang , Zhen Wang , Junpeng Zhang","doi":"10.1016/j.advengsoft.2025.104048","DOIUrl":"10.1016/j.advengsoft.2025.104048","url":null,"abstract":"<div><div>Due to complex nonlinear closed-loop constraints and structural flexibility, the dynamic modeling and control issue on flexible parallel robots is much more challenging compared to serial counterparts. Oriented to the demand of the high-end manufacturing field, this paper proposes a novel lightweight redundant parallel robot with cross layout of guide rail. Based on assumed mode discretization and Kane’s formulation, a general rigid-flexible coupling dynamic model of arbitrary branch incorporating <em>n</em>-order modes is derived. Leveraging modular ideology, the complete rigid-flexible coupling dynamic model of the system is established combining with nonlinear constraint equations, which is solved by the Runge-Kutta algorithm, modal truncation and forward dynamics methodology. The dynamic response comparison results between the redundant parallel robot and the non-redundant parallel robot reveal that the redundant actuation can suppress the elastic vibration. The rigid-flexible coupling dynamic model is then validated by a physical simulation model developed through the MATLAB/Simscape® platform using the finite segment approach. The electromechanical coupling dynamic model is further formulated by integrating the rigid-flexible coupling dynamic model with the permanent magnet synchronous motor and smart material. An adaptive intelligent composite control strategy is proposed to achieve trajectory tracking and vibration suppression. The comparison results with the other three control strategies demonstrate that the adaptive intelligent composite control strategy has superior control performance, exhibiting potential application prospects.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"212 ","pages":"Article 104048"},"PeriodicalIF":5.7,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145467796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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