Pub Date : 2024-10-18DOI: 10.1016/j.advengsoft.2024.103792
Junxiang Li , Xiwei Guo , Longchao Cao , Xinxin Zhang
The performance of engineering structures often varies over time due to the randomness and time variability of material properties, environmental conditions and load effects. This paper proposes phase-type (PH) distribution-based methods for efficient time-variant reliability analysis. The core of the proposed methods is to approximate the extreme value of a stochastic process as a PH distributed random variable, and treat the time parameter as a uniformly distributed variable. Consequently, the time-variant reliability problem is transformed into a time-invariant one. Three representative time-invariant reliability methods, first-order reliability method (FORM), importance sampling (IS) and adaptive Kriging (AK) surrogate model-based IS method (AK-IS), are integrated with the PH distribution-based approximation strategy to form the proposed methods, namely PH-FORM, PH-IS and PH-AKIS. The efficiency and accuracy of these methods are demonstrated through three examples. All codes in the study are implemented in MATLAB and provided as supplementary materials.
{"title":"Time-variant reliability analysis using phase-type distribution-based methods","authors":"Junxiang Li , Xiwei Guo , Longchao Cao , Xinxin Zhang","doi":"10.1016/j.advengsoft.2024.103792","DOIUrl":"10.1016/j.advengsoft.2024.103792","url":null,"abstract":"<div><div>The performance of engineering structures often varies over time due to the randomness and time variability of material properties, environmental conditions and load effects. This paper proposes phase-type (PH) distribution-based methods for efficient time-variant reliability analysis. The core of the proposed methods is to approximate the extreme value of a stochastic process as a PH distributed random variable, and treat the time parameter as a uniformly distributed variable. Consequently, the time-variant reliability problem is transformed into a time-invariant one. Three representative time-invariant reliability methods, first-order reliability method (FORM), importance sampling (IS) and adaptive Kriging (AK) surrogate model-based IS method (AK-IS), are integrated with the PH distribution-based approximation strategy to form the proposed methods, namely PH-FORM, PH-IS and PH-AKIS. The efficiency and accuracy of these methods are demonstrated through three examples. All codes in the study are implemented in MATLAB and provided as supplementary materials.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"198 ","pages":"Article 103792"},"PeriodicalIF":4.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444664","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 : 2024-10-15DOI: 10.1016/j.advengsoft.2024.103794
Yanding Guo , Huafeng Wang , Wei Wang , Chahua Chen , Yi Wang
Since the existing topology designs of negative thermal expansion metamaterials are primarily based on the asymptotic homogenization theory, this paper conducts a topology optimization method of negative thermal expansion metamaterials based on the computationally efficient energy-based homogenization for the first time. In this research, (1) a new effective thermal stress coefficient equation is pioneeringly proposed using energy-based homogenization frame, where its theoretical derivation process is presented as well as its effectiveness and computational efficiency are verified by comparative cases. Additionally, the matlab code is open-sourced for public learning. (2) A topology optimization design of both 2D and 3D metamaterials with negative thermal expansion properties is established innovatively with Discrete Material Optimization (DMO). Its advantages are illustrated compared with the convectional method and its results are validated by Finite Element Method simulations. The new methods have promising applications in the evaluation and optimization of thermal expansion properties of composites.
{"title":"Topology optimization for metamaterials with negative thermal expansion coefficients using energy-based homogenization","authors":"Yanding Guo , Huafeng Wang , Wei Wang , Chahua Chen , Yi Wang","doi":"10.1016/j.advengsoft.2024.103794","DOIUrl":"10.1016/j.advengsoft.2024.103794","url":null,"abstract":"<div><div>Since the existing topology designs of negative thermal expansion metamaterials are primarily based on the asymptotic homogenization theory, this paper conducts a topology optimization method of negative thermal expansion metamaterials based on the computationally efficient energy-based homogenization for the first time. In this research, (1) a new effective thermal stress coefficient equation is pioneeringly proposed using energy-based homogenization frame, where its theoretical derivation process is presented as well as its effectiveness and computational efficiency are verified by comparative cases. Additionally, the matlab code is open-sourced for public learning. (2) A topology optimization design of both 2D and 3D metamaterials with negative thermal expansion properties is established innovatively with Discrete Material Optimization (DMO). Its advantages are illustrated compared with the convectional method and its results are validated by Finite Element Method simulations. The new methods have promising applications in the evaluation and optimization of thermal expansion properties of composites.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"198 ","pages":"Article 103794"},"PeriodicalIF":4.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142432824","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 : 2024-10-12DOI: 10.1016/j.advengsoft.2024.103784
Sanjib Debnath , Swapan Debbarma , Sukanta Nama , Apu Kumar Saha , Runu Dhar , Ali Riza Yildiz , Amir H. Gandomi
Evolutionary algorithms (EAs) have a lot of potential to handle nonlinear and non-convex objective functions. Particularly, the backtracking search algorithm (BSA) is a popular nature-based evolutionary optimization method that has attracted many researchers due to its simple structure and efficiency in problem-solving across diverse fields. However, like other optimization algorithms, BSA is also prone to reduced diversity, local optima, and inadequate intensification capabilities. To overcome the flaws and increase the performance of BSA, this research proposes a centroid opposition-based backtracking search algorithm (CoBSA) for global optimization and engineering design problems. In CoBSA, specific individuals simultaneously acquire current and historical population knowledge to preserve population variety and improve exploration capability. On the other hand, other individuals execute the position from the current population's centroid opposition to progress convergence speed and exploitation potential. In addition, an elite process based on logistic chaotic local search was developed to improve the superiority of the current individuals. The suggested CoBSA was validated on a set of benchmark functions and then employed in a set of application examples. According to extensive numerical results and assessments, CoBSA outperformed the other state-of-the-art methods in terms of accurateness, reliability, and execution capability.
{"title":"Centroid opposition-based backtracking search algorithm for global optimization and engineering problems","authors":"Sanjib Debnath , Swapan Debbarma , Sukanta Nama , Apu Kumar Saha , Runu Dhar , Ali Riza Yildiz , Amir H. Gandomi","doi":"10.1016/j.advengsoft.2024.103784","DOIUrl":"10.1016/j.advengsoft.2024.103784","url":null,"abstract":"<div><div>Evolutionary algorithms (EAs) have a lot of potential to handle nonlinear and non-convex objective functions. Particularly, the backtracking search algorithm (BSA) is a popular nature-based evolutionary optimization method that has attracted many researchers due to its simple structure and efficiency in problem-solving across diverse fields. However, like other optimization algorithms, BSA is also prone to reduced diversity, local optima, and inadequate intensification capabilities. To overcome the flaws and increase the performance of BSA, this research proposes a centroid opposition-based backtracking search algorithm (CoBSA) for global optimization and engineering design problems. In CoBSA, specific individuals simultaneously acquire current and historical population knowledge to preserve population variety and improve exploration capability. On the other hand, other individuals execute the position from the current population's centroid opposition to progress convergence speed and exploitation potential. In addition, an elite process based on logistic chaotic local search was developed to improve the superiority of the current individuals. The suggested CoBSA was validated on a set of benchmark functions and then employed in a set of application examples. According to extensive numerical results and assessments, CoBSA outperformed the other state-of-the-art methods in terms of accurateness, reliability, and execution capability.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"198 ","pages":"Article 103784"},"PeriodicalIF":4.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142426494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-10DOI: 10.1016/j.advengsoft.2024.103787
Rongbo Zhou , Shuli Sun , Shiyu Fu
Mesh smoothing is a critical technique for enhancing mesh quality. Recently, polyhedral meshes have gained prominence in Computational Fluid Dynamics (CFD), with orthogonality being a common metric for evaluating these meshes. This paper introduces an innovative geometric method for smoothing and untangling polyhedral meshes, leveraging element shape transformation to improve orthogonality. The proposed method involves two primary operations. The first operation enhances individual element quality through geometric shape transformation achieved by node movement. This movement direction is determined by a combination of the node's normal vector and a correction vector. Following this transformation, temporary nodes of each element are established, and the node positions are updated using a weighted average of their corresponding temporary node set, a process referred to as element stitching. These operations can be iteratively applied to progressively enhance overall polyhedral mesh quality. The effectiveness and stability of this method are demonstrated through various examples, showing not only an improvement in mesh quality but also the elimination of inverted elements. CFD simulation results further indicate that the enhanced mesh quality positively impacts simulation accuracy.
{"title":"Smoothing and untangling for polyhedral mesh based on element shape transformation","authors":"Rongbo Zhou , Shuli Sun , Shiyu Fu","doi":"10.1016/j.advengsoft.2024.103787","DOIUrl":"10.1016/j.advengsoft.2024.103787","url":null,"abstract":"<div><div>Mesh smoothing is a critical technique for enhancing mesh quality. Recently, polyhedral meshes have gained prominence in Computational Fluid Dynamics (CFD), with orthogonality being a common metric for evaluating these meshes. This paper introduces an innovative geometric method for smoothing and untangling polyhedral meshes, leveraging element shape transformation to improve orthogonality. The proposed method involves two primary operations. The first operation enhances individual element quality through geometric shape transformation achieved by node movement. This movement direction is determined by a combination of the node's normal vector and a correction vector. Following this transformation, temporary nodes of each element are established, and the node positions are updated using a weighted average of their corresponding temporary node set, a process referred to as element stitching. These operations can be iteratively applied to progressively enhance overall polyhedral mesh quality. The effectiveness and stability of this method are demonstrated through various examples, showing not only an improvement in mesh quality but also the elimination of inverted elements. CFD simulation results further indicate that the enhanced mesh quality positively impacts simulation accuracy.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"198 ","pages":"Article 103787"},"PeriodicalIF":4.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142426493","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 : 2024-10-10DOI: 10.1016/j.advengsoft.2024.103791
Bu-Seog Ju , Hoyoung Son , Shinyoung Kwag , Sangwoo Lee
With the introduction of probabilistic safety assessment in nuclear power plants, a fragility analysis is critical to evaluating the probability of a failure of structures. However, such fragility analysis requires a large amount of finite element analyses due to explicit consideration and quantification of all sources of uncertainty. This study aims to present a sequential machining learning-based framework that can sequentially and efficiently estimate the fragility of containment vessels in nuclear power plants while minimizing finite element analyses, and the proposed framework is applied for performing a fragility analysis of a prestressed concrete containment vessel subjected to internal pressure. Within the framework, machine learning models are used to predict the behavior of the containment vessel based on collected analytical data from finite element analyses. The predicted data are used to estimate fragility curves through maximum likelihood estimation within the proposed framework, and the number of analytical data for training machine learning models is sequentially increased until the required convergence index of the estimated fragility curve is reached. In addition, the final fragility curves obtained from the proposed framework are compared with the fragility curves (benchmark) obtained from 1000 analytical data. This proposed framework can significantly reduce computational costs by estimating the fragility curve with the minimum number of finite element analyses.
{"title":"Sequential machine learning based fragility analysis: Sequential ML-FA for reactor containment vessel subjected to internal pressure","authors":"Bu-Seog Ju , Hoyoung Son , Shinyoung Kwag , Sangwoo Lee","doi":"10.1016/j.advengsoft.2024.103791","DOIUrl":"10.1016/j.advengsoft.2024.103791","url":null,"abstract":"<div><div>With the introduction of probabilistic safety assessment in nuclear power plants, a fragility analysis is critical to evaluating the probability of a failure of structures. However, such fragility analysis requires a large amount of finite element analyses due to explicit consideration and quantification of all sources of uncertainty. This study aims to present a sequential machining learning-based framework that can sequentially and efficiently estimate the fragility of containment vessels in nuclear power plants while minimizing finite element analyses, and the proposed framework is applied for performing a fragility analysis of a prestressed concrete containment vessel subjected to internal pressure. Within the framework, machine learning models are used to predict the behavior of the containment vessel based on collected analytical data from finite element analyses. The predicted data are used to estimate fragility curves through maximum likelihood estimation within the proposed framework, and the number of analytical data for training machine learning models is sequentially increased until the required convergence index of the estimated fragility curve is reached. In addition, the final fragility curves obtained from the proposed framework are compared with the fragility curves (benchmark) obtained from 1000 analytical data. This proposed framework can significantly reduce computational costs by estimating the fragility curve with the minimum number of finite element analyses.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"198 ","pages":"Article 103791"},"PeriodicalIF":4.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142426492","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 : 2024-10-09DOI: 10.1016/j.advengsoft.2024.103790
Osezua Ibhadode , Yun-Fei Fu , Ahmed Qureshi
Topology optimization has revolutionized the design of structures for various applications, particularly with the advancement of additive manufacturing. However, existing open-source codes for topology optimization have limitations, such as restricted domain initialization and lack of a CAD output after optimization. A novel open-source Matlab code, FreeTO, is presented, and it addresses these limitations by enabling the initialization of 3D arbitrary geometries and providing an STL file post-optimization. FreeTO utilizes a structured mesh and a smooth-edge (boundary) algorithm to generate smooth topological boundaries. The code is demonstrated through six practical design cases, showcasing its effectiveness in compliance minimization, compliant mechanisms, and self-supporting problems. FreeTO offers a user-friendly, all-in-one topology optimization package, making it an invaluable tool for educators, researchers, and practitioners. Future developments will focus on eliminating a few geometrical deviations in the optimized topologies, incorporating speedups, and extending the code to apply to more applications.
{"title":"FreeTO - Freeform 3D topology optimization using a structured mesh with smooth boundaries in Matlab","authors":"Osezua Ibhadode , Yun-Fei Fu , Ahmed Qureshi","doi":"10.1016/j.advengsoft.2024.103790","DOIUrl":"10.1016/j.advengsoft.2024.103790","url":null,"abstract":"<div><div>Topology optimization has revolutionized the design of structures for various applications, particularly with the advancement of additive manufacturing. However, existing open-source codes for topology optimization have limitations, such as restricted domain initialization and lack of a CAD output after optimization. A novel open-source Matlab code, FreeTO, is presented, and it addresses these limitations by enabling the initialization of 3D arbitrary geometries and providing an STL file post-optimization. FreeTO utilizes a structured mesh and a smooth-edge (boundary) algorithm to generate smooth topological boundaries. The code is demonstrated through six practical design cases, showcasing its effectiveness in compliance minimization, compliant mechanisms, and self-supporting problems. FreeTO offers a user-friendly, all-in-one topology optimization package, making it an invaluable tool for educators, researchers, and practitioners. Future developments will focus on eliminating a few geometrical deviations in the optimized topologies, incorporating speedups, and extending the code to apply to more applications.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"198 ","pages":"Article 103790"},"PeriodicalIF":4.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142426491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-08DOI: 10.1016/j.advengsoft.2024.103789
Shiran Zhu , Ruiwen Guo , Xin Jin , Xiaofei Ma , Jinxiong Zhou , Ning An
Deployable rib-mesh reflector antennas, known for their ultralight nature and high deployment-to-stowage ratio, have been attracting attention from both the aerospace industry and academia. Form finding is a critical step in determining the equilibrium shape of the reflector under a specific internal stress distribution, which is a prerequisite in evaluating the surface accuracy of these antennas. This paper presents a comprehensive methodology for iteratively implementing the nonlinear finite element method for form finding of cable-membrane structures supported by flexible frames. The method is integrated into the commercial finite element code ABAQUS with Python scripts, and its accuracy and efficiency are validated through a few benchmark examples. Subsequently, the proposed method is applied to analyze the surface accuracy of umbrella-like rib-mesh reflector antennas. The effect of key design parameters such as the number and rigidity of ribs, the magnitude and anisotropy of membrane stress, and the amount of pretension force in boundary cables on the antenna’s surface accuracy has been highlighted. The effort not only establishes a robust and user-friendly strategy for form finding of cable-membrane structures supported by flexible frames but also provides valuable insights into the surface accuracy of umbrella-like rib-mesh reflector antennas. To facilitate the application of the FEM-based form-finding method, the source code for this paper is publicly available via a permanent link on GitHub https://github.com/SCU-An-Group/FEM-based-Form-Finding.
{"title":"Form finding of cable-membrane structures with flexible frames: Finite element implementation and application to surface accuracy analysis of umbrella-like rib-mesh reflectors","authors":"Shiran Zhu , Ruiwen Guo , Xin Jin , Xiaofei Ma , Jinxiong Zhou , Ning An","doi":"10.1016/j.advengsoft.2024.103789","DOIUrl":"10.1016/j.advengsoft.2024.103789","url":null,"abstract":"<div><div>Deployable rib-mesh reflector antennas, known for their ultralight nature and high deployment-to-stowage ratio, have been attracting attention from both the aerospace industry and academia. Form finding is a critical step in determining the equilibrium shape of the reflector under a specific internal stress distribution, which is a prerequisite in evaluating the surface accuracy of these antennas. This paper presents a comprehensive methodology for iteratively implementing the nonlinear finite element method for form finding of cable-membrane structures supported by flexible frames. The method is integrated into the commercial finite element code ABAQUS with Python scripts, and its accuracy and efficiency are validated through a few benchmark examples. Subsequently, the proposed method is applied to analyze the surface accuracy of umbrella-like rib-mesh reflector antennas. The effect of key design parameters such as the number and rigidity of ribs, the magnitude and anisotropy of membrane stress, and the amount of pretension force in boundary cables on the antenna’s surface accuracy has been highlighted. The effort not only establishes a robust and user-friendly strategy for form finding of cable-membrane structures supported by flexible frames but also provides valuable insights into the surface accuracy of umbrella-like rib-mesh reflector antennas. To facilitate the application of the FEM-based form-finding method, the source code for this paper is publicly available via a permanent link on GitHub <span><span>https://github.com/SCU-An-Group/FEM-based-Form-Finding</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"198 ","pages":"Article 103789"},"PeriodicalIF":4.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142426490","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 : 2024-10-05DOI: 10.1016/j.advengsoft.2024.103788
Yeqi Liu , Deping Yu , Wu Zhao , Kai Zhang
Detecting weld defects in battery trays is crucial for the safety of new energy vehicles. Existing methods for weld surface defect detection, relying on traditional computer vision algorithms and convolutional neural networks with substantial image-level labeled data, face challenges in accurately identifying small defects, especially with limited samples. To address these issues, we developed an innovative Segmentation-Assisted Classification with Convolutional Neural Networks (SACNN) model. SACNN integrates a common feature extraction subnet, a segmentation subnet enhanced by a multi-scale feature fusion module, and a classification subnet specifically designed for precise defect detection. A joint loss function co-trains the segmentation and classification subnets using both image-level and pixel-level labels, enhancing the model’s ability to accurately detect small defect regions. Our model demonstrates notable improvement, achieving accuracy gains ranging from 2% to 18% compared to existing state-of-the-art methods, with an overall accuracy of 94.09% on an industrial dataset of battery tray welds. To further evaluate the generalization capability of our model, we evaluated it on the publicly available Magnetic Tile dataset, achieving state-of-the-art results in this challenging context. Additionally, we conducted comprehensive ablation studies to validate the contribution of each component in our approach and utilized visualization techniques to enhance the interpretability of our model. These advancements represent a significant contribution to the state of the art in aluminum alloy weld defect detection.
{"title":"Segmentation-assisted classification model with convolutional neural network for weld defect detection","authors":"Yeqi Liu , Deping Yu , Wu Zhao , Kai Zhang","doi":"10.1016/j.advengsoft.2024.103788","DOIUrl":"10.1016/j.advengsoft.2024.103788","url":null,"abstract":"<div><div>Detecting weld defects in battery trays is crucial for the safety of new energy vehicles. Existing methods for weld surface defect detection, relying on traditional computer vision algorithms and convolutional neural networks with substantial image-level labeled data, face challenges in accurately identifying small defects, especially with limited samples. To address these issues, we developed an innovative Segmentation-Assisted Classification with Convolutional Neural Networks (SACNN) model. SACNN integrates a common feature extraction subnet, a segmentation subnet enhanced by a multi-scale feature fusion module, and a classification subnet specifically designed for precise defect detection. A joint loss function co-trains the segmentation and classification subnets using both image-level and pixel-level labels, enhancing the model’s ability to accurately detect small defect regions. Our model demonstrates notable improvement, achieving accuracy gains ranging from 2% to 18% compared to existing state-of-the-art methods, with an overall accuracy of 94.09% on an industrial dataset of battery tray welds. To further evaluate the generalization capability of our model, we evaluated it on the publicly available Magnetic Tile dataset, achieving state-of-the-art results in this challenging context. Additionally, we conducted comprehensive ablation studies to validate the contribution of each component in our approach and utilized visualization techniques to enhance the interpretability of our model. These advancements represent a significant contribution to the state of the art in aluminum alloy weld defect detection.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"198 ","pages":"Article 103788"},"PeriodicalIF":4.0,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142426489","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 : 2024-10-03DOI: 10.1016/j.advengsoft.2024.103785
Tiendung Vu , Son H. Nguyen
This paper investigates the performance of a recently proposed polygonal plate element with alpha (α)-assumed rotations and shear strains, referred to as αARS-Poly, in free vibration analysis. The αARS-Poly element utilizes a simple and efficient approach involving a scaling factor (α) to enhance the accuracy of assumed rotations and shear strains. To fully explore the advantages of this element, we undertake a comprehensive analysis of free vibration in plate structures using a range of models with complex geometries. Numerical results demonstrate that the αARS-Poly element offers stability and reliability within smooth mode shapes. Furthermore, it significantly outperforms the previous polygonal Reissner-Mindlin plate element with piecewise-linear shape functions (PRMn-PL), achieving frequencies that closely match reference solutions, thereby validating its accuracy and robustness for dynamic applications.
{"title":"Polygonal plate element method for free vibration analysis using an efficient alpha (α)-assumed rotations and shear strains","authors":"Tiendung Vu , Son H. Nguyen","doi":"10.1016/j.advengsoft.2024.103785","DOIUrl":"10.1016/j.advengsoft.2024.103785","url":null,"abstract":"<div><div>This paper investigates the performance of a recently proposed polygonal plate element with alpha (<em>α</em>)-assumed rotations and shear strains, referred to as <em>α</em>ARS-Poly, in free vibration analysis. The <em>α</em>ARS-Poly element utilizes a simple and efficient approach involving a scaling factor (<em>α</em>) to enhance the accuracy of assumed rotations and shear strains. To fully explore the advantages of this element, we undertake a comprehensive analysis of free vibration in plate structures using a range of models with complex geometries. Numerical results demonstrate that the <em>α</em>ARS-Poly element offers stability and reliability within smooth mode shapes. Furthermore, it significantly outperforms the previous polygonal Reissner-Mindlin plate element with piecewise-linear shape functions (PRM<em>n</em>-PL), achieving frequencies that closely match reference solutions, thereby validating its accuracy and robustness for dynamic applications.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"198 ","pages":"Article 103785"},"PeriodicalIF":4.0,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142426488","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 : 2024-10-02DOI: 10.1016/j.advengsoft.2024.103786
Kairen Shen, Hao Wang
To develop digital twin (DT) of road infrastructure, one critical element is computation of pavement responses (strains, stresses, and deflections) under traffic and environmental loading. This study aims to develop high-efficient asphalt pavement modeling software based on semi-analytical finite element method (SAFEM) for DT application. The algorithms address important aspects in vehicle-tire-pavement interaction modeling, such as dynamic vehicular loading, three-dimensional (3-D) non-uniform tire contact stress, viscoelastic behavior of asphalt material, and interface bonding condition. The simulation accuracy is verified by comparison with full-scale test and field measurements, and the relative differences are around 5 % to 20 %. Techniques including optimized discrete Fourier transform, parallel computing, graphics processing unit (GPU) acceleration, and sparse matrices are implemented for computation efficiency. As compared to the traditional 3-D FEM, SAFEM shows significant savings in computation time and storage usage. The high efficiency and accuracy make the software full of potential to be applied for DT of roadway infrastructure.
{"title":"Development of high-efficient asphalt pavement modeling software for digital twin of road infrastructure","authors":"Kairen Shen, Hao Wang","doi":"10.1016/j.advengsoft.2024.103786","DOIUrl":"10.1016/j.advengsoft.2024.103786","url":null,"abstract":"<div><div>To develop digital twin (DT) of road infrastructure, one critical element is computation of pavement responses (strains, stresses, and deflections) under traffic and environmental loading. This study aims to develop high-efficient asphalt pavement modeling software based on semi-analytical finite element method (SAFEM) for DT application. The algorithms address important aspects in vehicle-tire-pavement interaction modeling, such as dynamic vehicular loading, three-dimensional (3-D) non-uniform tire contact stress, viscoelastic behavior of asphalt material, and interface bonding condition. The simulation accuracy is verified by comparison with full-scale test and field measurements, and the relative differences are around 5 % to 20 %. Techniques including optimized discrete Fourier transform, parallel computing, graphics processing unit (GPU) acceleration, and sparse matrices are implemented for computation efficiency. As compared to the traditional 3-D FEM, SAFEM shows significant savings in computation time and storage usage. The high efficiency and accuracy make the software full of potential to be applied for DT of roadway infrastructure.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"198 ","pages":"Article 103786"},"PeriodicalIF":4.0,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142426495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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