Computer-Aided Design最新文献_第10页

Taming Connectedness in Machine-Learning-Based Topology Optimization with Connectivity Graphs 基于连通性图的机器学习拓扑优化中的连通性

IF 4.3 3区计算机科学

Computer-Aided Design Pub Date : 2023-10-26 DOI: 10.1016/j.cad.2023.103634

Mohammad Mahdi Behzadi , Jiangce Chen , Horea T. Ilies

{"title":"Taming Connectedness in Machine-Learning-Based Topology Optimization with Connectivity Graphs","authors":"Mohammad Mahdi Behzadi , Jiangce Chen , Horea T. Ilies","doi":"10.1016/j.cad.2023.103634","DOIUrl":"10.1016/j.cad.2023.103634","url":null,"abstract":"<div><p>Despite the remarkable advancements in machine learning (ML) techniques for topology optimization<span>, the predicted solutions often overlook the necessary structural connectivity required to meet the load-carrying demands of the resulting designs. Consequently, these predicted solutions exhibit subpar structural performance because disconnected components are unable to bear loads effectively and significantly compromise the manufacturability of the designs.</span></p><p>In this paper, we propose an approach to enhance the topological accuracy of ML-based topology optimization methods by employing a predicted dual connectivity graph<span><span><span>. We show that the tangency graph of the Maximal Disjoint Ball Decomposition (MDBD), which accurately captures the topology of the optimal design, can be used in conjunction with a point transformer network to improve the connectivity of the design predicted by Generative Adversarial Networks and </span>Convolutional Neural Networks<span>. Our experiments show that the proposed method can significantly improve the connectivity of the final predicted structures. Specifically, in our experiments the error in the number of disconnected components was reduced by a factor of 4 or more without any loss of accuracy. We demonstrate the flexibility of our approach by presenting examples including various boundary conditions (both seen and unseen), domain resolutions, and initial design domains. Importantly, our method can seamlessly integrate with other existing deep learning-based optimization algorithms, utilize training datasets with models using any valid </span></span>geometric representations, and naturally extend to three-dimensional applications.</span></p></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"168 ","pages":"Article 103634"},"PeriodicalIF":4.3,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136093489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reducing the Number of Different Faces in Free-Form Surface Approximations Through Clustering and Optimization 通过聚类和优化减少自由曲面逼近中不同面的数量

IF 4.3 3区计算机科学

Computer-Aided Design Pub Date : 2023-10-21 DOI: 10.1016/j.cad.2023.103633

Yuanpeng Liu , Ting-Uei Lee , Anooshe Rezaee Javan , Nico Pietroni , Yi Min Xie

{"title":"Reducing the Number of Different Faces in Free-Form Surface Approximations Through Clustering and Optimization","authors":"Yuanpeng Liu , Ting-Uei Lee , Anooshe Rezaee Javan , Nico Pietroni , Yi Min Xie","doi":"10.1016/j.cad.2023.103633","DOIUrl":"https://doi.org/10.1016/j.cad.2023.103633","url":null,"abstract":"<div><p>Free-form structures are highly valued for their aesthetic appeal in architecture, but they typically comprise panels of many different shapes, which can pose great challenges for building construction. In this study, we aim to address this issue by proposing a novel clustering–optimization method to reduce the number of different <span><math><mi>n</mi></math></span>-gonal faces in free-form surface approximations. The method partitions the faces into several groups of similar shapes through clustering and transforms the ones within each group toward congruent forms through optimization. By utilizing this approach, the number of geometrically different panels can be reduced while also satisfying a user-specified error threshold. The potential practical application of this method is demonstrated by redesigning the façade of a real architectural project to achieve cost-effective solutions.</p></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"166 ","pages":"Article 103633"},"PeriodicalIF":4.3,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010448523001653/pdfft?md5=4ee1082f40b2dd0482dd49485d1d919d&pid=1-s2.0-S0010448523001653-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91987319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Shape Derivative Approach to Domain Simplification 一种区域简化的形状导数方法

IF 4.3 3区计算机科学

Computer-Aided Design Pub Date : 2023-10-21 DOI: 10.1016/j.cad.2023.103636

J. Hinz , O. Chanon , A. Arrigoni , A. Buffa

{"title":"A Shape Derivative Approach to Domain Simplification","authors":"J. Hinz , O. Chanon , A. Arrigoni , A. Buffa","doi":"10.1016/j.cad.2023.103636","DOIUrl":"https://doi.org/10.1016/j.cad.2023.103636","url":null,"abstract":"<div><p>The objective of this study is to address the difficulty of simplifying the geometric model in which a differential problem is formulated, also called defeaturing, while simultaneously ensuring that the accuracy of the solution is maintained under control. This enables faster and more efficient simulations, without sacrificing accuracy in the regions of interest. More precisely, we consider an isogeometric discretisation of an elliptic model problem defined on a two-dimensional simply connected hierarchical B-spline physical domain with a complex boundary. Starting with an oversimplification of the geometry, we build a goal-oriented adaptive strategy that adaptively reintroduces continuous geometrical features in regions where the analysis suggests a large impact on the quantity of interest. This strategy is driven by an <em>a posteriori</em> estimator of the defeaturing error based on first-order shape sensitivity analysis, and it profits from the local refinement properties of hierarchical B-splines. The adaptive algorithm is described together with a procedure to generate (partially) simplified hierarchical B-spline geometrical domains. Numerical experiments are presented to illustrate the proposed strategy and its limitations.</p></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"167 ","pages":"Article 103636"},"PeriodicalIF":4.3,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71768994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fast Reconstruction of Microstructures with Ellipsoidal Inclusions Using Analytical Descriptors 利用解析描述子快速重建椭球夹杂微观结构

IF 4.3 3区计算机科学

Computer-Aided Design Pub Date : 2023-10-20 DOI: 10.1016/j.cad.2023.103635

Paul Seibert , Markus Husert , Maximilian P. Wollner , Karl A. Kalina , Markus Kästner

{"title":"Fast Reconstruction of Microstructures with Ellipsoidal Inclusions Using Analytical Descriptors","authors":"Paul Seibert , Markus Husert , Maximilian P. Wollner , Karl A. Kalina , Markus Kästner","doi":"10.1016/j.cad.2023.103635","DOIUrl":"https://doi.org/10.1016/j.cad.2023.103635","url":null,"abstract":"<div><p>Microstructure reconstruction is an important and emerging aspect of computational materials engineering and multiscale modeling and simulation. Despite extensive research and fast progress in the field, the application of descriptor-based reconstruction remains limited by computational resources. Common methods for increasing the computational feasibility of descriptor-based microstructure reconstruction lie in approximating the microstructure by simple geometrical shapes and by utilizing differentiable descriptors to enable gradient-based optimization. The present work combines these two ideas for structures composed of non-overlapping ellipsoidal inclusions such as magnetorheological elastomers. This requires to express the descriptors as a function of the microstructure parametrization. Deriving these relations leads to analytical solutions that further speed up the reconstruction procedure. Based on these descriptors, microstructure reconstruction is formulated as a multi-stage optimization procedure. The developed algorithm is validated by means of different numerical experiments and advantages and limitations are discussed in detail.</p></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"166 ","pages":"Article 103635"},"PeriodicalIF":4.3,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010448523001677/pdfft?md5=2f1cf9313dca3d0de81488f37ae4a7ec&pid=1-s2.0-S0010448523001677-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92101163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A compact yet flexible design space for large-scale nonperiodic 3D woven composites based on a weighted game for generating candidate tow architectures 一种基于加权博弈的大型非周期三维编织复合材料候选拖曳结构的紧凑而灵活的设计空间

IF 4.3 3区计算机科学

Computer-Aided Design Pub Date : 2023-10-20 DOI: 10.1016/j.cad.2023.103637

Zhen-Pei Wang , Brian N. Cox , Shemuel Joash Kuehsamy , Mark Hyunpong Jhon , Olivier Sudre , N. Sridhar , Gareth J. Conduit

{"title":"A compact yet flexible design space for large-scale nonperiodic 3D woven composites based on a weighted game for generating candidate tow architectures","authors":"Zhen-Pei Wang , Brian N. Cox , Shemuel Joash Kuehsamy , Mark Hyunpong Jhon , Olivier Sudre , N. Sridhar , Gareth J. Conduit","doi":"10.1016/j.cad.2023.103637","DOIUrl":"https://doi.org/10.1016/j.cad.2023.103637","url":null,"abstract":"<div><p>Three-dimensional non-periodic woven composite preforms have sufficient design flexibility that tows can be aligned along principal loading paths even in shaped structural components with detailed local features. While this promises competitive performance, the feasible design space is combinatorially large, far beyond exhaustive search. Seeking a design space that is compact and easily searched yet can span the full potential of 3D weaving, we propose a method for generating candidate designs called the Background Vector Method (BVM) which treats weaving tows as agents in a game competing to match background vectors derived from different design requirements. The BVM generates candidate designs that adapt local architecture to global design goals by adjusting scalar weights. A manufacturing-based parameterization assures fabricability. The scope of possible designs and the speed of the BVM are illustrated by re-creating common periodic 3D weaving patterns and novel complex non-periodic architectures, with a route demonstrated to forming cavities, ducts, and other open volumes. How the BVM might be incorporated within an optimization algorithm is outlined and pathways are shown for systematically enlarging the design space as individual design problems may require.</p></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"167 ","pages":"Article 103637"},"PeriodicalIF":4.3,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91999406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gradient design and fabrication methodology for interleaved self-locking kirigami panels 交错自锁基利米板的梯度设计和制造方法

IF 4.3 3区计算机科学

Computer-Aided Design Pub Date : 2023-10-13 DOI: 10.1016/j.cad.2023.103632

Hao Qiu , Yixiong Feng , Yicong Gao , Zhaoxi Hong , Jianrong Tan

{"title":"Gradient design and fabrication methodology for interleaved self-locking kirigami panels","authors":"Hao Qiu , Yixiong Feng , Yicong Gao , Zhaoxi Hong , Jianrong Tan","doi":"10.1016/j.cad.2023.103632","DOIUrl":"https://doi.org/10.1016/j.cad.2023.103632","url":null,"abstract":"<div><p>Sandwich panels with excellent mechanical properties are widely used in the aerospace, architecture, and automobile industries. Kirigami-inspired structural designs are receiving increasing attention owing to the shape-induced functions and novel properties imparted by their folds and cuts. In this study, novel graded self-locking kirigami panels based on a tucked-interleaved pattern are developed and analyzed under quasi-static loading. The proposed tucked-interleaved pattern can be assembled to form freely supported self-locking polyhedral structures. The self-locking property is ensured by the interleaved flaps, which create in-plane compression to hold the structure in place. In particular, we analyze the effects of geometric variations in kirigami panels fabricated using a CO<sub>2</sub> laser machining system. The experimental data under quasi-static compression and simulation results both indicate that the proposed kirigami panels have outstanding load-to-weight ratios on the order of 10<sup>5</sup>. It appears that the introduction of a graded design can generate graded stiffness as well as superior specific energy absorption with an appropriate introduction of geometric gradients. These results show that the proposed kirigami panels combining self-locking and programmable non-uniform stiffness have great potential for non-uniform engineering applications.</p></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"166 ","pages":"Article 103632"},"PeriodicalIF":4.3,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0010448523001641/pdfft?md5=70fa5e265ba9c95a37e880f44d35416f&pid=1-s2.0-S0010448523001641-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91987318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning-driven optimization design of hydrogel-based negative hydration expansion metamaterials 基于机器学习的水凝胶负水化膨胀超材料优化设计

IF 4.3 3区计算机科学

Computer-Aided Design Pub Date : 2023-10-11 DOI: 10.1016/j.cad.2023.103631

Yisong Qiu, Hongfei Ye, Hongwu Zhang, Yonggang Zheng

{"title":"Machine learning-driven optimization design of hydrogel-based negative hydration expansion metamaterials","authors":"Yisong Qiu, Hongfei Ye, Hongwu Zhang, Yonggang Zheng","doi":"10.1016/j.cad.2023.103631","DOIUrl":"https://doi.org/10.1016/j.cad.2023.103631","url":null,"abstract":"<div><p>Hydrogel-based negative hydration expansion (NHE) metamaterials are composite structures composed of responsive hydrogels and polymers, and their properties depend on their unique structures. In this paper, an optimization method based on the combination of the back-propagation neural network (BPNN) and the multi-population genetic algorithm (MPGA) is developed to rapidly design isotropic and anisotropic hydrogel-based metamaterials with specific NHE effects. In this method, several dimensionless design parameters are introduced to describe the structural characteristics of the metamaterial. The initial dataset is constructed based on the finite element method simulation results, and the mapping relationship between the design parameters and the equivalent linear strain is constructed by the BPNN, and the metamaterial with specific effect is efficiently optimized by combining the MPGA. The method is proved to have high accuracy and efficiency, and is applied to design many novel 2D and 3D metamaterials. The 3D metamaterial designed by this method has an ultra-large NHE ratio about 82 %. Compared with the topology optimization method, this method can significantly reduce the amount of computation, and can effectively avoid falling into the local optimum. The results show that the optimization method based on machine learning is an efficient means to design hydrogel-based metamaterials.</p></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"166 ","pages":"Article 103631"},"PeriodicalIF":4.3,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S001044852300163X/pdfft?md5=f22de6c63d7148c72cfbfaf0f89db584&pid=1-s2.0-S001044852300163X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92061976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extending Point-Based Deep Learning Approaches for Better Semantic Segmentation in CAD 基于扩展点的深度学习方法在CAD中实现更好的语义分割

IF 4.3 3区计算机科学

Computer-Aided Design Pub Date : 2023-10-10 DOI: 10.1016/j.cad.2023.103629

Gerico Vidanes , David Toal , Xu Zhang , Andy Keane , Jon Gregory , Marco Nunez

{"title":"Extending Point-Based Deep Learning Approaches for Better Semantic Segmentation in CAD","authors":"Gerico Vidanes , David Toal , Xu Zhang , Andy Keane , Jon Gregory , Marco Nunez","doi":"10.1016/j.cad.2023.103629","DOIUrl":"https://doi.org/10.1016/j.cad.2023.103629","url":null,"abstract":"<div><p>Geometry understanding is a core concept of computer-aided design and engineering (CAD/CAE). Deep neural networks have increasingly shown success as a method of processing complex inputs to achieve abstract tasks. This work revisits a generic and relatively simple approach to 3D deep learning – a point-based graph neural network – and develops best-practices and modifications to alleviate traditional drawbacks. It is shown that these methods should not be discounted for CAD tasks; with proper implementation, they can be competitive with more specifically designed approaches. Through an additive study, this work investigates how the boundary representation data can be fully utilised by leveraging the flexibility of point-based graph networks. The final configuration significantly improves on the predictive accuracy of a standard <em>PointNet++</em> network across multiple CAD model segmentation datasets and achieves state-of-the-art performance on the <em>MFCAD++</em> machining features dataset. The proposed modifications leave the core neural network unchanged and results also suggest that they can be applied to other point-based approaches.</p></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"166 ","pages":"Article 103629"},"PeriodicalIF":4.3,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49711218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multicomponent Topology Optimization Method Considering Stepwise Linear Assemblability with a Fictitious Physical Model 考虑虚拟物理模型分步线性可装配性的多部件拓扑优化方法

IF 4.3 3区计算机科学

Computer-Aided Design Pub Date : 2023-10-06 DOI: 10.1016/j.cad.2023.103628

R. Hirosawa , M. Noda , K. Matsushima , Y. Noguchi , T. Yamada

引用次数: 0

Simplification of 3D CAD Model in Voxel Form for Mechanical Parts Using Generative Adversarial Networks 用生成对抗性网络简化机械零件的体素形式三维CAD模型

IF 4.3 3区计算机科学

Computer-Aided Design Pub Date : 2023-10-01 DOI: 10.1016/j.cad.2023.103577

Hyunoh Lee , Jinwon Lee , Soonjo Kwon , Karthik Ramani , Hyung-gun Chi , Duhwan Mun

{"title":"Simplification of 3D CAD Model in Voxel Form for Mechanical Parts Using Generative Adversarial Networks","authors":"Hyunoh Lee , Jinwon Lee , Soonjo Kwon , Karthik Ramani , Hyung-gun Chi , Duhwan Mun","doi":"10.1016/j.cad.2023.103577","DOIUrl":"https://doi.org/10.1016/j.cad.2023.103577","url":null,"abstract":"<div><p>Most three-dimensional (3D) computer-aided design (CAD) models of mechanical parts, created during the design stage, have high shape complexity. The shape complexity required of CAD models reduces according to the field of application. Therefore, it is necessary to simplify the shapes of 3D CAD models, depending on their applications. Traditional simplification methods recognize simplification target shape based on a pre-defined algorithm. Such algorithm-based methods have difficulty processing unusual partial shapes not considered in the CAD model. This paper proposes a method that uses a network based on a generative adversarial network (GAN) to simplify the 3D CAD models of mechanical parts. The proposed network recognizes and removes simplification target shapes included in the 3D CAD models of mechanical parts. A 3D CAD model dataset was constructed to train the 3D CAD model simplification network. 3D CAD models are represented in voxel form in the dataset. Next, the constructed training dataset was used to train the proposed network. Finally, a 3D voxel simplification experiment was performed to evaluate the performance of the trained network. The experiment results showed that the network had an average error rate of 3.38% for the total area of the mechanical part and an average error rate of 14.61% for the simplification target area.</p></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"163 ","pages":"Article 103577"},"PeriodicalIF":4.3,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49711094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1