Computers & Structures最新文献

{"title":"Stabilization and improvement of the convergence of hybrid-Trefftz stress elements for plate bending analysis","authors":"","doi":"10.1016/j.compstruc.2024.107519","DOIUrl":"10.1016/j.compstruc.2024.107519","url":null,"abstract":"<div><div>The polynomial boundary basis usually applied in the implementation of hybrid-Trefftz stress elements for plate bending is extended to render its rate of convergence insensitive to the shear-to-bending stiffness ratio of the plate. The boundary basis is also extended to improve the accuracy of the element in the modelling of boundary layer effects and of singular stress fields caused by wedge effects. Numerical testing problems are selected to illustrate and validate the effect of the proposed extensions on the stabilization and improvement of finite element solutions. The solutions modelling boundary layer effects in Mindlin-Reissner plates are used to recover the equivalent shear and corner force concepts of the Kirchhoff plate bending model.</div></div>","PeriodicalId":50626,"journal":{"name":"Computers & Structures","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0045794924002487/pdfft?md5=1a34466f1902b9a08c3c30857fd81bc4&pid=1-s2.0-S0045794924002487-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311685","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}

{"title":"Uncertainty quantification of acoustic metamaterial bandgaps with stochastic material properties and geometric defects","authors":"","doi":"10.1016/j.compstruc.2024.107511","DOIUrl":"10.1016/j.compstruc.2024.107511","url":null,"abstract":"<div><div>Acoustic metamaterials are a subject of increasing study and utility. Through designed combinations of geometries with material properties, acoustic metamaterials can be built to arbitrarily manipulate acoustic waves for various applications. Despite the theoretical advances in this field, however, acoustic metamaterials have seen limited penetration into industry and commercial use. This is largely due to the difficulty of manufacturing the intricate geometries that are integral to their function and the sensitivity of metamaterial designs to material batch variability and manufacturing defects. Capturing the effects of stochastic material properties and geometric defects requires empirical testing of manufactured samples, but this can quickly become prohibitively expensive with higher precision requirements or with an increasing number of input variables. This paper demonstrates how uncertainty quantification techniques, and more specifically the use of polynomial chaos expansions and spectral projections, can be used to greatly reduce sampling needs for characterizing acoustic metamaterial dispersion curves. With a novel method of encoding geometric defects in a 1D, interpretable, resolution-independent way, our uncertainty quantification approach allows for both stochastic material properties and geometric defects to be considered simultaneously. Two to three orders of magnitude sampling reductions down to <span><math><mo>∼</mo><msup><mrow><mn>10</mn></mrow><mrow><mn>0</mn></mrow></msup></math></span> and <span><math><mo>∼</mo><msup><mrow><mn>10</mn></mrow><mrow><mn>1</mn></mrow></msup></math></span> were achieved in 1D and 7D input space scenarios, respectively. Remarkably, this reduction in sampling was possible while preserving accurate output probability distributions of the metamaterial performance characteristics (bandgap size and location).</div></div>","PeriodicalId":50626,"journal":{"name":"Computers & Structures","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311686","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}

{"title":"On thermomechanical problems in a topology optimisation method based on non-uniform rational basis spline entities","authors":"","doi":"10.1016/j.compstruc.2024.107530","DOIUrl":"10.1016/j.compstruc.2024.107530","url":null,"abstract":"<div><div>This paper presents a new method to deal with thermomechanical topology optimisation (TO) problems based on a pseudo-density algorithm reformulated in the context of Non Uniform Rational Basis Spline (NURBS) entities. Specifically, a NURBS entity is used to represent the topological descriptor, providing an implicit filtering effect thanks to the local support propriety. The problem is formulated in the most general case of inhomogeneous Neumann-Dirichlet boundary conditions and design-dependent thermal sources and thermomechanical loads. In this context, a study on the combined effect of design-dependent heat sources, thermomechanical loads and applied forces and displacements on the optimal topologies is carried out. Furthermore, the influence of the penalisation schemes involved in the definition of the stiffness matrix, conductivity matrix, thermal loads and thermal sources on the optimised topology is investigated through a wide campaign of sensitivity analyses. Finally, sensitivity analyses are also conducted to investigate the influence of the integer parameters of the NURBS entity on the optimised solution. The effectiveness of the approach is tested on 2D and 3D benchmark problems.</div></div>","PeriodicalId":50626,"journal":{"name":"Computers & Structures","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142311687","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}

{"title":"Three-dimensional meso-scale modeling of asphalt concrete","authors":"","doi":"10.1016/j.compstruc.2024.107535","DOIUrl":"10.1016/j.compstruc.2024.107535","url":null,"abstract":"<div><p>An efficient method to address the three-dimensional modeling of the visco-elasto-plastic material behavior, specifically of bituminous conglomerates used in asphalt concrete production, is proposed. The method resorts to one of the most recent formulations for asphalt creep modeling, represented by the modified Huet-Sayegh fractional rheological model. The Grünwald-Letnikov representation of the fractional operator is adopted to treat the operator numerically in an efficient manner. Further, a coupling scheme between the creep model and elasto-plasticity is proposed by adopting the additive decomposition of the total strain tensor. This enables the numerical assessment of the mechanical behavior for bituminous materials under short- to long-term loading. In this context, both constant strain rate tests, and creep recovery tests are numerically simulated.</p><p>Numerical analyses are conducted at the meso-scale with the aim to evaluate the development of inelastic strains in the binder during creep, due to the local interaction between the different material components.</p></div>","PeriodicalId":50626,"journal":{"name":"Computers & Structures","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0045794924002645/pdfft?md5=8e71369e88ebf5de1ea95712443db967&pid=1-s2.0-S0045794924002645-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142270536","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}

{"title":"AI-enabled indirect bridge strain sensing using field acceleration data","authors":"","doi":"10.1016/j.compstruc.2024.107531","DOIUrl":"10.1016/j.compstruc.2024.107531","url":null,"abstract":"<div><p>Life-cycle performance assessment of bridges is crucial for decisions pertaining to functionality, maintenance, and rehabilitation while accounting for inherent epistemic and aleatoric uncertainties stemming from noise or structural degradation. Since fatigue from repeated cyclic loads is a prominent source of performance degradation in bridges, a continuous and efficient method for structural monitoring is necessary. In fatigue assessment, engineers rely on strain response, which can be challenging to collect due to the labor-intensive and costly deployment of strain gauges that are not conveniently reusable. This paper proposes an indirect sensing approach that converts acceleration signals to strain signals, enabling a convenient and robust paradigm for a continuous, and accurate bridge fatigue assessment. A combination of convolutional neural networks and transformers are used in this work for estimating strain signals from acceleration measurements. The efficacy of the proposed framework is demonstrated through data collected from the Gene Hartzell Memorial Bridge in Pennsylvania, USA. Furthermore, physical insights have been drawn from the results that reinforce the rationale behind the proposed artificial neural network architecture. This novel framework for indirect sensing can be readily employed for strain estimation from acceleration measurements of the bridges, upon adequate training, which will contribute to bridge condition and life-cycle assessment.</p></div>","PeriodicalId":50626,"journal":{"name":"Computers & Structures","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142270537","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}

{"title":"Enhancing topology optimization with adaptive deep learning","authors":"","doi":"10.1016/j.compstruc.2024.107527","DOIUrl":"10.1016/j.compstruc.2024.107527","url":null,"abstract":"<div><p>Topology optimization (TO) is a pivotal technique for generative design of high-performance structures. Practical designs often face complex boundary conditions and require non-gradient optimizers for solving TO with thousands of design variables or more. This paper presents the Adaptive Deep Learning (ADL) which supports both gradient-based topology optimization (GTO) and non-gradient-based topology optimization (NGTO). The ADL roots in convolutional neural network to link material layouts with structural compliance. A small number of training data is generated dynamically based on the ADL’s prediction of the optimum. The ADL explores the region of interest in a probabilistic setup and evolves with increased data. The presented ADL has been evaluated on four cases including beam design, heat dissipation structure design, three-dimensional machine tool column design and heat transfer enhancement optimization. The ADL achieved 0.04 % to 4.08 % increasement of structural performance compared to GTO algorithm, and 0.88 % to 81.98 % increasement compared to NGTO algorithms.</p></div>","PeriodicalId":50626,"journal":{"name":"Computers & Structures","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243536","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}

{"title":"Variational damage model: A novel consistent approach to fracture","authors":"","doi":"10.1016/j.compstruc.2024.107518","DOIUrl":"10.1016/j.compstruc.2024.107518","url":null,"abstract":"<div><p>The computational modeling of fractures in solids using damage mechanics faces challenge when dealing with complex crack topologies. One effective approach to address this challenge is by reformulating damage mechanics within a variational framework. In this paper, we present a novel variational damage model that incorporates a threshold value to prevent damage initiation at low energy levels. The proposed model defines fracture energy density (<span><math><mover><mrow><mi>ϕ</mi></mrow><mrow><mo>˜</mo></mrow></mover></math></span>) and damage field (<em>s</em>) based on the energy density (<em>ϕ</em>), crack energy release rate (<span><math><msub><mrow><mi>G</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span>), and crack length scale (<em>ℓ</em>). Specifically, if <span><math><mi>ϕ</mi><mo>≤</mo><mfrac><mrow><msub><mrow><mi>G</mi></mrow><mrow><mi>c</mi></mrow></msub></mrow><mrow><mn>2</mn><mi>ℓ</mi></mrow></mfrac></math></span>, then <span><math><mover><mrow><mi>ϕ</mi></mrow><mrow><mo>˜</mo></mrow></mover><mo>=</mo><mi>ϕ</mi></math></span> and <span><math><mi>s</mi><mo>=</mo><mn>0</mn></math></span>; otherwise, <span><math><mover><mrow><mi>ϕ</mi></mrow><mrow><mo>˜</mo></mrow></mover><mo>=</mo><mo>−</mo><mfrac><mrow><msubsup><mrow><mi>G</mi></mrow><mrow><mi>c</mi></mrow><mrow><mn>2</mn></mrow></msubsup></mrow><mrow><mn>4</mn><msup><mrow><mi>ℓ</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></mfrac><mfrac><mrow><mn>1</mn></mrow><mrow><mi>ϕ</mi></mrow></mfrac><mo>+</mo><mfrac><mrow><msub><mrow><mi>G</mi></mrow><mrow><mi>c</mi></mrow></msub></mrow><mrow><mi>ℓ</mi></mrow></mfrac></math></span> and <span><math><mi>s</mi><mo>=</mo><mn>1</mn><mo>−</mo><mfrac><mrow><msub><mrow><mi>G</mi></mrow><mrow><mi>c</mi></mrow></msub></mrow><mrow><mn>2</mn><mi>ℓ</mi></mrow></mfrac><mfrac><mrow><mn>1</mn></mrow><mrow><mi>ϕ</mi></mrow></mfrac></math></span>. Furthermore, we extend the model with a threshold value to a higher-order version. Utilizing this functional, we derive the governing equation for fractures that evolve automatically with ease. The formulation can be seamlessly integrated into conventional finite element methods for elastic solids with minimal modifications. The proposed formulation offers sharper crack interfaces compared to phase field methods using the same mesh density. We demonstrate the capabilities of our approach through representative numerical examples in both 2D and 3D, including static fracture problems, cohesive fractures, and dynamic fractures. The open-source code is available on GitHub via the link <span><span>https://github.com/hl-ren/vdm</span><svg><path></path></svg></span>.</p></div>","PeriodicalId":50626,"journal":{"name":"Computers & Structures","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0045794924002475/pdfft?md5=0b234ac467f002675d6571c60839763f&pid=1-s2.0-S0045794924002475-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243539","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}

{"title":"Control of geometry and stability of tensegrities in the Octahedron and X-Octahedron families","authors":"","doi":"10.1016/j.compstruc.2024.107547","DOIUrl":"10.1016/j.compstruc.2024.107547","url":null,"abstract":"<div><p>Tensegrity structures obtained from the same connectivity patterns are said to belong to families. The Octahedron and X-Octahedron families are examples of these. In the literature, little attention has been paid to how the final geometries of the equilibrium forms of the members of both families are obtained. A compact formulation for controlling the equilibrium shapes of members of the Octahedron and X-Octahedron families is proposed in this article allowing the designer to get any geometry for the super-stable members of both families. Controlling the stability of folded forms is achieved by using the shape of the structure, and a detailed explanation of the formulation is provided here, as well as several examples that clarify the formulation. The geometrical control of the equilibrium shape is fundamental when applying it to tensegrity structures in an engineering context.</p></div>","PeriodicalId":50626,"journal":{"name":"Computers & Structures","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243755","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}

{"title":"Topology optimization of active tensegrity structures","authors":"","doi":"10.1016/j.compstruc.2024.107513","DOIUrl":"10.1016/j.compstruc.2024.107513","url":null,"abstract":"<div><p>Existing studies on active tensegrity structure optimum design only focus on sizing and/or shape optimization i.e., the structural element topology does not change during the design process, which vastly limits the design space and further improvement of mass-saving performance. This study investigates the optimum design of active tensegrity structures through topology optimization, which has never been done to the best of the authors’ knowledge. Structural member topology and actuator layout are considered as binary design variables and their coupling relation is handled by auxiliary constraints. Member cross-sectional areas are treated as discrete design variables considering practical availability. Member prestress, actuator length changes, and other necessary auxiliary parameters are defined as continuous variables and designed simultaneously. Equilibrium conditions, member yielding, cable slackness, strut buckling, and the limitations on the nodal displacements as well as other design requirements are formulated as constraints. Linearization algorithm is proposed to transform the bilinear expressions in the objective and constraint functions to allow the problem to be solved to global optimum. Typical benchmark examples indicate that the topology-optimized active designs obtained through the proposed approach can further decrease the material consumption compared with sizing-optimized active tensegrity designs hence leading to more lightweight structures.</p></div>","PeriodicalId":50626,"journal":{"name":"Computers & Structures","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142233805","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}

{"title":"Vertex-based graph neural network classification model considering structural topological features for structural optimization","authors":"","doi":"10.1016/j.compstruc.2024.107542","DOIUrl":"10.1016/j.compstruc.2024.107542","url":null,"abstract":"<div><p>Traditional surrogate models always face the challenge of low accuracy when dealing with high-dimensional problems in structural optimization, this study aims to overcome this problem and proposes a vertex-based graph neural network (GNN) classification model. In contrast to conventional machine learning models that treat design variables as independent inputs, the proposed model develops a vertex-based graph representation to transform structural topological features and critical physical information into the graph data. According to a message passing mechanism based on the graph convolutional, it can extract the correlations among design variables and enhance its capability in handling high-dimensional structural optimization problems. Three truss examples, including a 10-bar with 10 variables, a 600-bar with 25 variables, and a 942-bar with 59 variables, are utilized to investigate the performance of the proposed surrogate model. The results demonstrate that the GNN-based surrogate model outperforms traditional machine learning approaches, particularly in the two high-dimensional problems, showcasing its superior ability to capture complex variable correlations and handle high-dimensional structural optimization tasks. Moreover, the proposed method significantly reduces the computational expenses by over 60% compared to conventional metaheuristic algorithms, while yielding optimal designs with comparable quality. These results demonstrate the efficiency and effectiveness of the GNN-based surrogate model in tackling complex, high-dimensional structural optimization problems.</p></div>","PeriodicalId":50626,"journal":{"name":"Computers & Structures","volume":null,"pages":null},"PeriodicalIF":4.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142230210","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}