Pub Date : 2025-12-19DOI: 10.1016/j.advengsoft.2025.104090
Jie You , Yonghong Zhao , Liangyue Jia , Nan Wang , Zhibin Sun , Wenkai Zou , Yu Hu , Liang Liu , Chuanyang Zhang
Finite-element analysis (FEA) is the benchmark for crashworthiness evaluation, yet its prohibitive computational cost and labour-intensive re-meshing make it unsuitable for iterative structural optimization. Although surrogate models offer partial relief, they still demand large simulation datasets and frequent mesh updates. Focusing on the vehicle front crash condition, proposing a Sectional Force-Based Multi-Stage Physics Informed Surrogate Model (SFB-MSPISM) that integrates sectional force features with semi-empirical physical priors (i.e., the Gérard buckling formula) in a two-stage architecture, thereby reducing the training data requirement and virtually eliminating manual re-meshing. In Stage-1, a Physics-Informed XGBoost-CNN-Transformer ensemble (PI-XCT) is proposed to predict the peak sectional force and energy absorption of five key beams; In Stage-2, a multi-output XGBoost regressor is proposed to estimate the maximum crash acceleration and the Toe-board intrusion. Trained on fewer than 130 high-fidelity simulations (100 data for Stage-1 and 26 data for Stage-2), SFB-MSPISM attains a coefficient of determination of 0.97 for peak deceleration and a mean intrusion error of 2.525 mm (≤5 %), while reducing per-design evaluation time from 6.5 h to 0.038 s. These results show a speed-up exceeding five orders of magnitude and virtually eliminate human intervention, thereby enabling millisecond-scale, physically consistent crashworthiness assessment for rapid design exploration.
{"title":"A fast crashworthiness assessment framework: Sectional force-based multi-stage physics informed surrogate model","authors":"Jie You , Yonghong Zhao , Liangyue Jia , Nan Wang , Zhibin Sun , Wenkai Zou , Yu Hu , Liang Liu , Chuanyang Zhang","doi":"10.1016/j.advengsoft.2025.104090","DOIUrl":"10.1016/j.advengsoft.2025.104090","url":null,"abstract":"<div><div>Finite-element analysis (FEA) is the benchmark for crashworthiness evaluation, yet its prohibitive computational cost and labour-intensive re-meshing make it unsuitable for iterative structural optimization. Although surrogate models offer partial relief, they still demand large simulation datasets and frequent mesh updates. Focusing on the vehicle front crash condition, proposing a Sectional Force-Based Multi-Stage Physics Informed Surrogate Model (SFB-MSPISM) that integrates sectional force features with semi-empirical physical priors (i.e., the Gérard buckling formula) in a two-stage architecture, thereby reducing the training data requirement and virtually eliminating manual re-meshing. In Stage-1, a Physics-Informed XGBoost-CNN-Transformer ensemble (PI-XCT) is proposed to predict the peak sectional force and energy absorption of five key beams; In Stage-2, a multi-output XGBoost regressor is proposed to estimate the maximum crash acceleration and the Toe-board intrusion. Trained on fewer than 130 high-fidelity simulations (100 data for Stage-1 and 26 data for Stage-2), SFB-MSPISM attains a coefficient of determination of 0.97 for peak deceleration and a mean intrusion error of 2.525 mm (≤5 %), while reducing per-design evaluation time from 6.5 h to 0.038 s. These results show a speed-up exceeding five orders of magnitude and virtually eliminate human intervention, thereby enabling millisecond-scale, physically consistent crashworthiness assessment for rapid design exploration.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104090"},"PeriodicalIF":5.7,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790899","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 : 2025-12-19DOI: 10.1016/j.advengsoft.2025.104087
Teoman Toprak , Michael Loibl , Guilherme H. Teixeira , Irina Shishkina , Chen Miao , Josef Kiendl , Benjamin Marussig , Florian Kummer
In the field of scientific computing, one often finds several alternative software packages (with open or closed source code) for solving a specific problem. These packages sometimes even use alternative methodological approaches, e.g., different numerical discretizations. If one decides to use one of these packages, it is often not clear which one is the best choice. To make an informed decision, it is necessary to measure the performance of the alternative software packages for a suitable set of test problems, i.e., to set up a benchmark. However, setting up benchmarks ad-hoc can become overwhelming as the parameter space expands rapidly. Very often, the design of the benchmark is also not fully set at the start of some project. For instance, adding new libraries, adapting metrics, or introducing new benchmark cases during the project can significantly increase complexity and necessitate laborious re-evaluation of previous results. This paper presents a proven approach that utilizes established Continuous Integration tools and practices to achieve high automation of benchmark execution and reporting. Our use case is the numerical integration (quadrature) on arbitrary domains, which are bounded by implicitly or parametrically defined curves or surfaces in 2D or 3D.
{"title":"Employing Continuous Integration inspired workflows for benchmarking of scientific software — A use case on numerical cut element quadrature","authors":"Teoman Toprak , Michael Loibl , Guilherme H. Teixeira , Irina Shishkina , Chen Miao , Josef Kiendl , Benjamin Marussig , Florian Kummer","doi":"10.1016/j.advengsoft.2025.104087","DOIUrl":"10.1016/j.advengsoft.2025.104087","url":null,"abstract":"<div><div>In the field of scientific computing, one often finds several alternative software packages (with open or closed source code) for solving a specific problem. These packages sometimes even use alternative methodological approaches, e.g., different numerical discretizations. If one decides to use one of these packages, it is often not clear which one is the best choice. To make an informed decision, it is necessary to measure the performance of the alternative software packages for a suitable set of test problems, i.e., to set up a benchmark. However, setting up benchmarks ad-hoc can become overwhelming as the parameter space expands rapidly. Very often, the design of the benchmark is also not fully set at the start of some project. For instance, adding new libraries, adapting metrics, or introducing new benchmark cases during the project can significantly increase complexity and necessitate laborious re-evaluation of previous results. This paper presents a proven approach that utilizes established Continuous Integration tools and practices to achieve high automation of benchmark execution and reporting. Our use case is the numerical integration (quadrature) on arbitrary domains, which are bounded by implicitly or parametrically defined curves or surfaces in 2D or 3D.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104087"},"PeriodicalIF":5.7,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790985","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 : 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":"2025-12-18","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}
To overcome the limitations of single Graphics Processing Unit (GPU) configurations in terms of computational resources and acceleration performance, this study develops a multi-GPU parallel computing framework for the explicit finite element method (FEM) that incorporates a parallel contact algorithm. A hybrid parallelization approach is adopted, combining coarse-grained parallelism with subdomains mapped to GPUs and fine-grained parallelism with elements mapped to threads, along with a stream-per-element-type concurrency technique to achieve efficient multi-GPU computation of element internal forces. For the global contact search phase, a GPU-to-GPU contact node communication algorithm is designed, and a GPU-parallelized bucket sort algorithm is developed. To address inter-GPU contact node drift after sliding, a communication and reorganization strategy for remote nodes is proposed. A complete inter-GPU contact force communication scheme is constructed based on the penalty contact algorithm. The performance of the proposed multi-GPU explicit FEM framework is evaluated through a series of benchmark simulations, demonstrating a maximum speedup of 223.29 on four GPUs, significantly enhancing the computational efficiency for drop-test simulations.
{"title":"A Multi-GPU explicit finite element framework with a parallel contact algorithm for drop testing of electronic products","authors":"Xinggang Cao, Xiang Zhao, Zhenhui Liu, Yongjie Pei, Yong Cai, Xiangyang Cui","doi":"10.1016/j.advengsoft.2025.104086","DOIUrl":"10.1016/j.advengsoft.2025.104086","url":null,"abstract":"<div><div>To overcome the limitations of single Graphics Processing Unit (GPU) configurations in terms of computational resources and acceleration performance, this study develops a multi-GPU parallel computing framework for the explicit finite element method (FEM) that incorporates a parallel contact algorithm. A hybrid parallelization approach is adopted, combining coarse-grained parallelism with subdomains mapped to GPUs and fine-grained parallelism with elements mapped to threads, along with a stream-per-element-type concurrency technique to achieve efficient multi-GPU computation of element internal forces. For the global contact search phase, a GPU-to-GPU contact node communication algorithm is designed, and a GPU-parallelized bucket sort algorithm is developed. To address inter-GPU contact node drift after sliding, a communication and reorganization strategy for remote nodes is proposed. A complete inter-GPU contact force communication scheme is constructed based on the penalty contact algorithm. The performance of the proposed multi-GPU explicit FEM framework is evaluated through a series of benchmark simulations, demonstrating a maximum speedup of 223.29 on four GPUs, significantly enhancing the computational efficiency for drop-test simulations.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104086"},"PeriodicalIF":5.7,"publicationDate":"2025-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738712","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 : 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":"2025-12-08","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 : 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":"2025-12-06","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 : 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":"2025-12-05","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 : 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":"2025-12-05","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 : 2025-12-03DOI: 10.1016/j.advengsoft.2025.104068
Xudong Jiang , Taigui Bai , Peichao Du , Zhenyu Huang
Due to their compact structure and complex hydrodynamic environment, bulb-type turbine-generator units are highly susceptible to multi-source load unbalance rising from hydraulic, electromagnetic, and mechanical interactions, leading to nonlinear vibration behaviors in the rotor-bearing system and posing challenges to stable operation and fault diagnosis. To investigate such dynamics, a nonlinear rotor-bearing dynamic model is first developed based on the Jeffcott rotor theory, incorporating three typical sources of load unbalance: mass eccentricity, angular misalignment, and inadequate oil supply pressure. Nonlinear oil-film forces are modeled to reflect realistic hydrodynamic effects. A dedicated experimental platform is constructed with integrated modules for motor actuation, fault loading, and sensor-based data acquisition. Vibration signals in and directions are collected under varying speeds and fault intensities. A comprehensive analysis using time-domain plots, frequency spectra, orbit diagrams and radar plots reveals distinct fault-specific features. Furthermore, 160 labeled samples across eight rotational speeds are collected, from which 16 time–frequency features are extracted to form a dataset. To enhance fault identification, a Hybrid CNN–Transformer diagnostic model is proposed for the first time in the context of hydropower units. The model integrates convolutional feature extraction with global temporal attention, achieving superior adaptability to varying operating states. Results demonstrate that the model achieves a high classification accuracy of 98.75% on the test set. Confusion matrices show clear decision boundaries, and the average AUC exceeds 0.995, indicating excellent discriminative power. Compared to conventional MLP and LSTM models, the proposed method outperforms in terms of accuracy, robustness, and convergence rate, highlighting its effectiveness and adaptability for fault diagnosis of nonlinear, multi-source load unbalance in bulb-type hydro-turbine units.
{"title":"Nonlinear dynamic behavior and fault diagnosis of rotor-bearing systems subjected to multi-source load unbalance in bulb-type turbine-generator units","authors":"Xudong Jiang , Taigui Bai , Peichao Du , Zhenyu Huang","doi":"10.1016/j.advengsoft.2025.104068","DOIUrl":"10.1016/j.advengsoft.2025.104068","url":null,"abstract":"<div><div>Due to their compact structure and complex hydrodynamic environment, bulb-type turbine-generator units are highly susceptible to multi-source load unbalance rising from hydraulic, electromagnetic, and mechanical interactions, leading to nonlinear vibration behaviors in the rotor-bearing system and posing challenges to stable operation and fault diagnosis. To investigate such dynamics, a nonlinear rotor-bearing dynamic model is first developed based on the Jeffcott rotor theory, incorporating three typical sources of load unbalance: mass eccentricity, angular misalignment, and inadequate oil supply pressure. Nonlinear oil-film forces are modeled to reflect realistic hydrodynamic effects. A dedicated experimental platform is constructed with integrated modules for motor actuation, fault loading, and sensor-based data acquisition. Vibration signals in <span><math><mi>X</mi></math></span> and <span><math><mi>Y</mi></math></span> directions are collected under varying speeds and fault intensities. A comprehensive analysis using time-domain plots, frequency spectra, orbit diagrams and radar plots reveals distinct fault-specific features. Furthermore, 160 labeled samples across eight rotational speeds are collected, from which 16 time–frequency features are extracted to form a dataset. To enhance fault identification, a Hybrid CNN–Transformer diagnostic model is proposed for the first time in the context of hydropower units. The model integrates convolutional feature extraction with global temporal attention, achieving superior adaptability to varying operating states. Results demonstrate that the model achieves a high classification accuracy of 98.75% on the test set. Confusion matrices show clear decision boundaries, and the average AUC exceeds 0.995, indicating excellent discriminative power. Compared to conventional MLP and LSTM models, the proposed method outperforms in terms of accuracy, robustness, and convergence rate, highlighting its effectiveness and adaptability for fault diagnosis of nonlinear, multi-source load unbalance in bulb-type hydro-turbine units.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"213 ","pages":"Article 104068"},"PeriodicalIF":5.7,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145658450","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 : 2025-11-25DOI: 10.1016/j.advengsoft.2025.104071
Ondřej Ježek , Ján Kopačka , Martin Isoz , Dušan Gabriel , Pavel Maršálek , Martin Šotola , Radim Halama
This paper presents a novel post-processing methodology for extracting high-quality geometries from density-based topology optimization results. Current post-processing approaches often struggle to simultaneously achieve smooth boundaries, preserve volume fraction, and maintain topological features. We propose a robust method based on a signed distance function (SDF) that addresses these challenges through a two-stage process: first, an SDF representation of density isocontours is constructed, which is followed by geometry refinement using radial basis functions (RBFs). The method generates smooth boundary representations that appear to originate from much finer discretization, while maintaining the computational efficiency of coarse mesh optimization. Our approach can reduce maximum equivalent stress values compared to conventional methods. This reduction is achieved through continuous geometric transitions at boundaries. The resulting implicit boundary representation facilitates seamless export to standard manufacturing formats without intermediate reconstruction steps, providing a robust foundation for practical engineering applications where high-quality geometric representations are essential.
{"title":"Smooth geometry extraction from SIMP topology optimization: Signed distance function approach with volume preservation","authors":"Ondřej Ježek , Ján Kopačka , Martin Isoz , Dušan Gabriel , Pavel Maršálek , Martin Šotola , Radim Halama","doi":"10.1016/j.advengsoft.2025.104071","DOIUrl":"10.1016/j.advengsoft.2025.104071","url":null,"abstract":"<div><div>This paper presents a novel post-processing methodology for extracting high-quality geometries from density-based topology optimization results. Current post-processing approaches often struggle to simultaneously achieve smooth boundaries, preserve volume fraction, and maintain topological features. We propose a robust method based on a signed distance function (SDF) that addresses these challenges through a two-stage process: first, an SDF representation of density isocontours is constructed, which is followed by geometry refinement using radial basis functions (RBFs). The method generates smooth boundary representations that appear to originate from much finer discretization, while maintaining the computational efficiency of coarse mesh optimization. Our approach can reduce maximum equivalent stress values compared to conventional methods. This reduction is achieved through continuous geometric transitions at boundaries. The resulting implicit boundary representation facilitates seamless export to standard manufacturing formats without intermediate reconstruction steps, providing a robust foundation for practical engineering applications where high-quality geometric representations are essential.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"212 ","pages":"Article 104071"},"PeriodicalIF":5.7,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145618140","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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