Computer-Aided Design最新文献

{"title":"Soap Film-Inspired Subdivisional Lattice Structure Construction","authors":"Guoyue Luo,&nbsp;Qiang Zou","doi":"10.1016/j.cad.2025.103950","DOIUrl":"10.1016/j.cad.2025.103950","url":null,"abstract":"<div><div>Lattice structures, distinguished by their customizable geometries at the microscale and outstanding mechanical performance, have found widespread application across various industries. One fundamental process in their design and manufacturing is constructing boundary representation (B-rep) models, which are essential for running advanced applications like simulation, optimization, and process planning. However, this construction process presents significant challenges due to the high complexity of lattice structures, particularly in generating nodal shapes where robustness and smoothness issues can arise from the complex intersections between struts. To address these challenges, this paper proposes a novel approach for lattice structure construction by cutting struts and filling void regions with subdivisional nodal shapes. Inspired by soap films, the method generates smooth, shape-preserving control meshes using Laplacian fairing and subdivides them through the point-normal Loop (PN-Loop) subdivision scheme to obtain subdivisional nodal shapes. The proposed method ensures robust model construction with reduced shape deviations, enhanced surface fairness, and smooth transitions between subdivisional nodal shapes and retained struts. The effectiveness of the method has been demonstrated by a series of examples and comparisons. The code and associated data have been made available at: <span><span>https://github.com/Qiang-Zou/Subdiv-Lattice</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"189 ","pages":"Article 103950"},"PeriodicalIF":3.1,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010589","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}

{"title":"A parallel multiscale FIM approach in solving the Eikonal equation on GPU","authors":"Jingqi Zhang ,&nbsp;Zihao Zhou ,&nbsp;Lixin Ren ,&nbsp;Junyuan Liu ,&nbsp;Ying Li ,&nbsp;Xiaowei He","doi":"10.1016/j.cad.2025.103949","DOIUrl":"10.1016/j.cad.2025.103949","url":null,"abstract":"<div><div>Signed Distance Fields (SDFs) are essential in various applications, particularly in level set problems, where computing the SDF is equivalent to solving the Eikonal equation. Common approaches to solving these equations include the Fast Marching Method (FMM), the Fast Sweeping Method (FSM), and the Fast Iterative Method (FIM). However, FMM and FSM face significant challenges in parallelization, increasing interest in developing FIM for GPU architectures. In this paper, we extend the innovative FIM algorithm (Huang, 2021), which is GPU-friendly but relies on a single uniform grid, by incorporating multiscale techniques to accelerate wavefront propagation from source points to infinity. Unlike the traditional Fast Iterative Method, which operates on a single uniform grid and propagates the wavefront at a constant speed of one grid spacing per iteration, our multiscale approach applies a hierarchy of varying propagation speeds to accelerate the convergence. Once all source and infinite points are properly initialized, only a few FIM iterations are required to refine the values of points near the source. A coarser-grained scale, with twice the spacing of the finer grid, is then used to propagate values from accepted and tentative points to the outer regions. This process is repeated until the top-level scale is reached. Subsequently, we reverse this process by performing FIM calculations from the coarsest scale until reaching the finest grid, thereby completing a V-cycle. With multiscale V-cycles, the solution progressively converges across the entire computational domain. Comparative experimental results show that our algorithm improves computational efficiency by approximately 128% over the GPU-based Fast Marching Method and by a factor of 23 compared to the improved FIM algorithm (Huang, 2021) at scale of <span><math><mrow><mi>N</mi><mo>=</mo><mn>2</mn><mi>E</mi><mn>8</mn></mrow></math></span>. This optimized approach applies to numerical simulations of multi-body systems, including fluid–structure interactions, as well as numerical analyses of flooding and earthquake scenarios.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"189 ","pages":"Article 103949"},"PeriodicalIF":3.1,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019267","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}

{"title":"Matrix representation and GPU-optimized parallel B-spline computing","authors":"Jiayu Wu ,&nbsp;Zhengwen Feng ,&nbsp;Qiang Zou","doi":"10.1016/j.cad.2025.103948","DOIUrl":"10.1016/j.cad.2025.103948","url":null,"abstract":"<div><div>B-spline modeling is fundamental to CAD systems, and its evaluation and manipulation algorithms currently in use were developed decades ago, specifically for CPU architectures. While remaining effective for many applications, these algorithms become increasingly inadequate as CAD models grow more complex, such as large-scale assemblies and microstructures. GPU acceleration offers a promising solution, but most existing GPU B-spline algorithms simply adapt CPU counterparts without accounting for the mismatch between the unstructured, recursive nature of B-splines and the structured nature of GPU kernels, ultimately failing to fully leverage GPU capabilities. This paper presents a novel approach that transforms B-spline representations into regular matrix structures, reducing all evaluation and manipulation computations to matrix addition and multiplication, thus better aligning with GPU architecture. By combining this matrix representation with GPU-optimized task scheduling and memory access patterns, the paper demonstrates significant performance improvements in the key B-spline operations of inversion and projection. Experimental results show an improvement of about two orders of magnitude in computational speed compared to existing methods.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"189 ","pages":"Article 103948"},"PeriodicalIF":3.1,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144933023","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}

{"title":"On tool wear optimized motion planning for 5-axis CNC machining of free-form surfaces using toroidal cutting tools","authors":"Kinga Kruppa ,&nbsp;Juan Zaragoza Chichell ,&nbsp;Michal Bizzarri ,&nbsp;Michael Bartoň","doi":"10.1016/j.cad.2025.103952","DOIUrl":"10.1016/j.cad.2025.103952","url":null,"abstract":"<div><div>We propose a computational framework for motion planning for 5-axis CNC machining of free-form surfaces. Given a reference surface, a set of contact paths on it, and a shape of a toroidal cutting tool as input, the proposed algorithm designs the tool motions that are by construction locally and globally collision-free, and offers a trade-off between approximation quality and tool wear using an optimization-based framework. The proposed algorithm first quickly constructs 2D time-tilt configuration spaces along each contact path, detecting regions that are collision-free. The configuration spaces are then merged into a single time-tilt configuration space to find a global tilt function to control the overall motion of the tool. An initial collision-free tilt function in B-spline form is first estimated and then optimized to minimize the machining error while distributing the tool wear as uniformly as possible along the entire cutting edge of the tool while staying in the collision-free region. Our algorithm is validated on both synthetic free-form surfaces and industrial benchmarks, showing that one can considerably reduce the tool wear without degrading the machining accuracy.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"189 ","pages":"Article 103952"},"PeriodicalIF":3.1,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010590","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}

{"title":"AIXD: AI-eXtended Design Toolbox for data-driven and inverse design","authors":"Alessandro Maissen ,&nbsp;Aleksandra Anna Apolinarska ,&nbsp;Sophia V. Kuhn ,&nbsp;Luis Salamanca ,&nbsp;Michael A. Kraus ,&nbsp;Konstantinos Tatsis ,&nbsp;Gonzalo Casas ,&nbsp;Rafael Bischof ,&nbsp;Romana Rust ,&nbsp;Walter Kaufmann ,&nbsp;Fernando Pérez-Cruz ,&nbsp;Matthias Kohler","doi":"10.1016/j.cad.2025.103945","DOIUrl":"10.1016/j.cad.2025.103945","url":null,"abstract":"<div><div>Design processes, in many disciplines like architecture, civil engineering or mechanical engineering, involve navigating large, high-dimensional and heterogeneous data. While AI-driven approaches like inverse design and surrogate modeling can enhance design exploration, their adoption is hindered by complex workflows and the need for coding and machine learning expertise. To address this, we introduce AI-eXtended Design (AIXD): a low-code, open-source toolbox that integrates AI into computational design. AIXD simplifies handling of mixed data types, as well as the analysis, training, and deployment of machine learning models for inverse design, surrogate modeling, and sensitivity analysis, enabling domain experts to rapidly explore diverse solutions with minimal coding. In this paper, we show the functionalities of the toolbox, and we demonstrate AIXD’s capabilities in architectural and engineering design applications, showing how it accelerates performance evaluation, generates high-performing alternatives, and improves design understanding by delivering new insights. By bridging AI and design practice, AIXD lowers the entry barrier to data-driven methods, making AI-extended design more accessible and efficient.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"189 ","pages":"Article 103945"},"PeriodicalIF":3.1,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145003999","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}

{"title":"B-spline curve interpolation to ordered points through shape quality optimization","authors":"Jingyu Zhang ,&nbsp;Qiuyang Song ,&nbsp;Pengbo Bo ,&nbsp;Jianrui Ding ,&nbsp;Caiming Zhang","doi":"10.1016/j.cad.2025.103942","DOIUrl":"10.1016/j.cad.2025.103942","url":null,"abstract":"<div><div>B-spline curve interpolation to sequential data points is a fundamental problem in various applications and has been extensively studied. However, little attention has been given to optimizing the shape quality of the interpolation curve for each specific dataset. In this paper, we propose a novel approach to B-spline curve interpolation that directly enhances shape quality by minimizing a curve-quality evaluation function, jointly optimizing the control points, location parameters, and knot vectors. The key challenge lies in satisfying the necessary constraints to ensure the existence of a B-spline interpolation curve. To address this, we reformulate the problem as an unconstrained optimization, which inherently enforces these constraints. The interpolation curve is derived by perturbing an approximation curve to eliminate its distance error while preserving its optimized shape quality. To theoretically justify this process, we establish a formal connection between the approximation and interpolation curves, proving that the distance error between them is bounded by a factor of the approximation error with respect to the data points. Experimental results and comparisons with existing methods demonstrate the effectiveness and robustness of our approach in producing high-quality interpolation curves.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"189 ","pages":"Article 103942"},"PeriodicalIF":3.1,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908388","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}

{"title":"Bringing Attention to CAD: Boundary Representation Learning via Transformer","authors":"Qiang Zou,&nbsp;Lizhen Zhu","doi":"10.1016/j.cad.2025.103940","DOIUrl":"10.1016/j.cad.2025.103940","url":null,"abstract":"<div><div>The recent rise of generative artificial intelligence (AI), powered by Transformer networks, has achieved remarkable success in natural language processing, computer vision, and graphics. However, the application of Transformers in computer-aided design (CAD), particularly for processing boundary representation (B-rep) models, remains largely unexplored. To bridge this gap, we propose a novel approach for adapting Transformers to B-rep learning, called the Boundary Representation Transformer (BRT). B-rep models pose unique challenges due to their irregular topology and continuous geometric definitions, which are fundamentally different from the structured and discrete data Transformers are designed for. To address this, BRT proposes a continuous geometric embedding method that encodes B-rep surfaces (trimmed and untrimmed) into Bézier triangles, preserving their shape and continuity without discretization. Additionally, BRT employs a topology-aware embedding method that organizes these geometric embeddings into a sequence of discrete tokens suitable for Transformers, capturing both geometric and topological characteristics within B-rep models. This enables the Transformer’s attention mechanism to effectively learn shape patterns and contextual semantics of boundary elements in a B-rep model. Extensive experiments demonstrate that BRT achieves state-of-the-art performance in part classification and feature recognition tasks.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"189 ","pages":"Article 103940"},"PeriodicalIF":3.1,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144912961","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}

{"title":"Self-supervised representation of non-standard mechanical parts and fine-tuning method integrating macro process knowledge","authors":"Zirui Li ,&nbsp;Maolin Cai ,&nbsp;Jiaxin Chen ,&nbsp;Fangwei Ning ,&nbsp;Zhongliang Xie ,&nbsp;Xiaomeng Tong","doi":"10.1016/j.cad.2025.103954","DOIUrl":"10.1016/j.cad.2025.103954","url":null,"abstract":"<div><div>In the context of the geometric complexity and process knowledge diversity of non-standard mechanical parts (NSMPs), conventional structured data representation methods cannot effectively express the features of parts. This results in difficulty of part retrieval and low efficiency of process knowledge reuse. To address this problem, we established a multi-layer attributed graph that integrated geometric structure and macro process knowledge to represent NSMPs, and proposed methods for generating geometrically similar samples as well as macro process similar samples. Then, we proposed a pre-training model based on a graph convolutional encoder to embed the geometric structure of parts, which was transferred to supervised classification tasks. In addition, a fine-tuning model incorporating a graph pooling encoder is further introduced, integrating macro process knowledge. This approach enables users to efficiently retrieve parts suitable for design and process reuse through the cosine similarity of embedding, thereby improving the efficiency and accuracy of part retrieval and process reuse. The experimental results show that the pre-training model excels in embedding representation and sample differentiation. Specifically, its transfer learning accuracy in classification tasks reaches 92.6%. Furthermore, we applied fine-tuning to macro process reuse, where the experimentally determined similarity threshold is 0.952, achieving a judgment accuracy of 94.1%.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"189 ","pages":"Article 103954"},"PeriodicalIF":3.1,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908389","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}

{"title":"Optimized PHT-to-NURBS conversion: A weighted rectangle partition approach","authors":"Xinyu Wu,&nbsp;Jiansong Deng,&nbsp;Zhouwang Yang","doi":"10.1016/j.cad.2025.103915","DOIUrl":"10.1016/j.cad.2025.103915","url":null,"abstract":"<div><div>This study addresses the conversion of Polynomial Splines over Hierarchical T-meshes (PHT-splines) to Non-Uniform Rational B-Splines (NURBS). We reformulate this conversion as a weighted rectangle partition problem, introducing a coarser grid, referred to as base rectangles, to minimize the search space while ensuring optimal solutions. Our systematic framework facilitates the lossless conversion of PHT-splines to NURBS, effectively balancing the number of patches and control points. Extensive experiments on 109 2D and 118 3D subjects demonstrate reductions in control points by up to 48.94% for 2D cases and 78.35% for 3D cases. Moreover, our approach is versatile and adaptable to fixed-patch partition scenarios, highlighting its potential to bridge PHT-splines and NURBS.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"189 ","pages":"Article 103915"},"PeriodicalIF":3.1,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144892729","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}

{"title":"P2Seg: Distance query from point to segments","authors":"Jiantao Song ,&nbsp;Rui Xu ,&nbsp;Wensong Wang ,&nbsp;Shiqing Xin ,&nbsp;Shuangmin Chen ,&nbsp;Jiaye Wang ,&nbsp;Taku Komura ,&nbsp;Wenping Wang ,&nbsp;Changhe Tu","doi":"10.1016/j.cad.2025.103947","DOIUrl":"10.1016/j.cad.2025.103947","url":null,"abstract":"<div><div>Querying the nearest distance from a point to <span><math><mi>n</mi></math></span> line segments in 2D is a textbook problem in computational geometry. This paper presents P2Seg, a novel algorithmic strategy that transforms the intricate problem into an accessible linear traversal. Our method precomputes a KD tree and a Voronoi diagram for the site collection <span><math><mi>S</mi></math></span>, where <span><math><mi>S</mi></math></span> refers to the endpoints of all line segments. Obviously, for a query point <span><math><mi>q</mi></math></span>, the nearest site <span><math><msub><mrow><mi>s</mi></mrow><mrow><mi>i</mi></mrow></msub></math></span> provides a crucial clue for pinpointing the nearest line segment, i.e., the pairing <span><math><mrow><mo>(</mo><mi>q</mi><mo>,</mo><msub><mrow><mi>s</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>)</mo></mrow></math></span> effectively reduces the search from <span><math><mi>n</mi></math></span> line segments to a limited number, represented as <span><math><mrow><mi>L</mi><mrow><mo>(</mo><mi>q</mi><mo>,</mo><msub><mrow><mi>s</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>)</mo></mrow></mrow></math></span>. The key idea of this paper is driven by an insightful observation: if the ray <span><math><mrow><msub><mrow><mi>s</mi></mrow><mrow><mi>i</mi></mrow></msub><mi>q</mi></mrow></math></span> intersects with <span><math><msub><mrow><mi>s</mi></mrow><mrow><mi>i</mi></mrow></msub></math></span>’s Voronoi cell at a point, say <span><math><msup><mrow><mi>q</mi></mrow><mrow><mo>′</mo></mrow></msup></math></span>, then <span><math><mrow><mi>L</mi><mrow><mo>(</mo><mi>q</mi><mo>,</mo><msub><mrow><mi>s</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>)</mo></mrow></mrow></math></span> is a subset of <span><math><mrow><mi>L</mi><mrow><mo>(</mo><msup><mrow><mi>q</mi></mrow><mrow><mo>′</mo></mrow></msup><mo>,</mo><msub><mrow><mi>s</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>)</mo></mrow></mrow></math></span>. This suggests that preprocessing efforts can be substantially minimized by focusing solely on scenarios where the query point lies on the Voronoi edges, which are fundamentally one-dimensional. We further prove that the challenge of locating the nearest line segment from <span><math><mrow><mi>L</mi><mrow><mo>(</mo><msup><mrow><mi>q</mi></mrow><mrow><mo>′</mo></mrow></msup><mo>,</mo><msub><mrow><mi>s</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>)</mo></mrow></mrow></math></span> can be distilled down to a simple linear traversal. Testing on datasets of varying complexities shows that P2Seg significantly outperforms state-of-the-art techniques. For example, in scenarios involving 10K segments with an average length of 0.5, our method runs 2.2 times faster than P2M and 60 times faster than AABB, as illustrated in the teaser figure.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"189 ","pages":"Article 103947"},"PeriodicalIF":3.1,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896242","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}