Computer-Aided Design最新文献_第5页

Toward precise curve offsetting constrained to parametric surfaces 向着受参数曲面约束的精确曲线偏移

IF 3.1 3区计算机科学

Computer-Aided Design Pub Date : 2025-07-21 DOI: 10.1016/j.cad.2025.103916

Jin Zhao , Pengfei Wang , Shuangmin Chen , Jiong Guo , Shiqing Xin , Changhe Tu , Wenping Wang

{"title":"Toward precise curve offsetting constrained to parametric surfaces","authors":"Jin Zhao , Pengfei Wang , Shuangmin Chen , Jiong Guo , Shiqing Xin , Changhe Tu , Wenping Wang","doi":"10.1016/j.cad.2025.103916","DOIUrl":"10.1016/j.cad.2025.103916","url":null,"abstract":"<div><div>Computing offsets of curves on parametric surfaces is a fundamental yet challenging operation in computer-aided design and manufacturing. Traditional analytical approaches suffer from time-consuming geodesic distance queries and complex self-intersection handling, while discrete methods often struggle with precision. In this paper, we propose a totally different algorithm paradigm. Our key insight is that by representing the source curve as a sequence of line-segment primitives, the Voronoi decomposition constrained to the parametric surface enables localized offset computation. Specifically, the offsetting process can be efficiently traced by independently visiting the corresponding Voronoi cells. To address the challenge of computing the Voronoi decomposition on parametric surfaces, we introduce two key techniques. First, we employ intrinsic triangulation in the parameter space to accurately capture geodesic distances. Second, instead of directly computing the surface-constrained Voronoi decomposition, we decompose the triangulated parameter plane using a series of plane-cutting operations. Experimental results demonstrate that our algorithm achieves superior accuracy and runtime performance compared to existing methods. We also present several practical applications enabled by our approach.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"188 ","pages":"Article 103916"},"PeriodicalIF":3.1,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721019","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

UCSM: Dataset of U-shaped parametric CAD geometries and real-world sheet metal meshes for deep drawing UCSM: u形参数化CAD几何数据集和用于深拉深的真实金属板网格

IF 3 3区计算机科学

Computer-Aided Design Pub Date : 2025-07-18 DOI: 10.1016/j.cad.2025.103924

Tobias Lehrer , Philipp Stocker , Fabian Duddeck , Marcus Wagner

{"title":"UCSM: Dataset of U-shaped parametric CAD geometries and real-world sheet metal meshes for deep drawing","authors":"Tobias Lehrer , Philipp Stocker , Fabian Duddeck , Marcus Wagner","doi":"10.1016/j.cad.2025.103924","DOIUrl":"10.1016/j.cad.2025.103924","url":null,"abstract":"<div><div>The development of machine learning (ML) applications in deep drawing is hindered by limited data availability and the absence of open-access benchmarks for validating novel approaches, including domain generalization over distinct geometries. This paper addresses these challenges by introducing a comprehensive U-shaped dataset tailored to this manufacturing process. Our U-Channel sheet metal (UCSM) dataset combines 90 real-world meshes with an infinite number of synthetic geometry samples generated from four parametric Computer-Aided Design (CAD) models, ensuring extensive geometry variety and data quantity. Additionally, a ready-to-use dataset for drawability assessment and segmentation is provided. Leveraging CAD and mesh data sources bridges the gap between sparse data availability and ML requirements. Our analysis demonstrates that the proposed parametric models are geometrically valid, and real-world and synthetic data complement each other effectively, providing robust support for ML model development. While the dataset is confined to U-shaped, thin-walled, deep drawing scenarios, it considerably aids in overcoming data scarcity. Thereby, it facilitates the validation and comparison of new geometry-generalizing ML methodologies in this domain. By providing this benchmark dataset, we enhance the comparability and validation of emerging methods for ML advancements in sheet metal forming.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"188 ","pages":"Article 103924"},"PeriodicalIF":3.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713180","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

Computational design and fabrication of reusable multi-tangent bar structures 可重复使用多切线杆结构的计算设计与制造

IF 3 3区计算机科学

Computer-Aided Design Pub Date : 2025-07-17 DOI: 10.1016/j.cad.2025.103907

Yijiang Huang , Ziqi Wang , Yi-Hsiu Hung , Chenming Jiang , Aurèle L. Gheyselinck , Stelian Coros

{"title":"Computational design and fabrication of reusable multi-tangent bar structures","authors":"Yijiang Huang , Ziqi Wang , Yi-Hsiu Hung , Chenming Jiang , Aurèle L. Gheyselinck , Stelian Coros","doi":"10.1016/j.cad.2025.103907","DOIUrl":"10.1016/j.cad.2025.103907","url":null,"abstract":"<div><div>Temporary bar structures made of reusable standardized components are widely used in construction, events, and exhibitions. They are economical, easy to assemble, and can be disassembled and reused in various structural arrangements for various purposes. However, existing reusable temporary structures are either limited to modular yet repetitive designs or require bespoke components, which restricts their reuse potential. Instead of designing bespoke kit of parts for limited reuse, this paper investigates how to design and build diverse freeform structures from one homogeneous kit of parts. We propose a computational framework to generate multi-tangent bar structures, a widely used jointing system, which allows bars to be joined at any point along their length with standard connectors. We present a mathematical formulation and a numerical scheme to optimize the bar spatial positions and contact assignment simultaneously, while ensuring that the constraints of tangency, collision, joint connectivity, and bar length are satisfied. Together with simulated case studies, we present two physical prototypes that reuse the same kit of parts using an augmented reality-guided assembly workflow.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"188 ","pages":"Article 103907"},"PeriodicalIF":3.0,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702899","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

CADInstruct: A multimodal dataset for natural language-guided CAD program synthesis 用于自然语言引导的CAD程序合成的多模态数据集

IF 3 3区计算机科学

Computer-Aided Design Pub Date : 2025-07-12 DOI: 10.1016/j.cad.2025.103926

Chaofan Lv, Jinsong Bao

{"title":"CADInstruct: A multimodal dataset for natural language-guided CAD program synthesis","authors":"Chaofan Lv, Jinsong Bao","doi":"10.1016/j.cad.2025.103926","DOIUrl":"10.1016/j.cad.2025.103926","url":null,"abstract":"<div><div>While large language models (LLMs) have demonstrated remarkable success in general-purpose code generation, their application in computer-aided design (CAD) program synthesis remains constrained by the scarcity of high-quality natural language-annotated datasets. To address this challenge, we propose CADInstruct, a novel approach aimed at constructing a multimodal CAD instruction dataset to enhance the CAD program synthesis capabilities of LLMs. First, we introduce a parametric modification module for modeling sequences, which extracts geometric constraints and critical dimensions from sketches, transforming CAD construction sequences into design-intent-oriented instructions. Second, we incorporate a shape semantic recognition module that leverages model names and visually enriched rendered views to generate precise shape descriptions using multimodal large models, enabling accurate semantic representation of complex geometries. Lastly, a modeling instruction semantic alignment module utilizes the extracted shape descriptions and modeling instructions to generate hierarchical natural language descriptions, encompassing geometric forms and detailed modeling steps, ensuring consistency between textual descriptions and CAD instructions. We fine-tuned the Qwen2.5-Coder-7B model using the CADInstruct dataset to evaluate the effectiveness of this framework. Experimental results demonstrated its capability to significantly enhance CAD program synthesis. The code and dataset will be made publicly available at <span><span>https://github.com/dxlcf/CADInstruct</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"188 ","pages":"Article 103926"},"PeriodicalIF":3.0,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679853","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

SDF-CWF: Consolidating Weak Features in High-Quality Mesh Extraction from Signed Distance Functions SDF-CWF：从带符号距离函数中提取高质量网格的弱特征整合

IF 3 3区计算机科学

Computer-Aided Design Pub Date : 2025-07-08 DOI: 10.1016/j.cad.2025.103912

Longdu Liu (Researcher) , Hao Yu , Shiqing Xin , Shuangmin Chen , Hongwei Lin , Wenping Wang , Changhe Tu

{"title":"SDF-CWF: Consolidating Weak Features in High-Quality Mesh Extraction from Signed Distance Functions","authors":"Longdu Liu (Researcher) , Hao Yu , Shiqing Xin , Shuangmin Chen , Hongwei Lin , Wenping Wang , Changhe Tu","doi":"10.1016/j.cad.2025.103912","DOIUrl":"10.1016/j.cad.2025.103912","url":null,"abstract":"<div><div>With advancements in geometric deep learning techniques, neural signed distance functions (SDFs) have gained popularity for their flexibility. Recent studies show that neural SDFs can retain geometric details and encode sharp features. However, during the mesh extraction stage, methods like marching cubes may degrade these geometric details and sharp features, thus compromising the expressiveness of neural SDFs.</div><div>In this paper, we aim to develop a general-purpose mesh extraction method for both freeform and CAD models, assuming the availability of a SDF. Our goal is to produce a well-triangulated, resolution-adjustable mesh surface that preserves rich geometric details and distinct feature lines. Our approach is inspired by Centroidal Voronoi Tessellation (CVT) but introduces two key modifications. First, we extend CVT computation to implicit representations, where explicit surface decomposition is not available. Second, we propose a measure for estimating the likelihood that a point lies on feature lines, enabling the extraction of feature-aligned triangle meshes using power diagrams (with site weights positively correlated to the likelihood values). Comprehensive comparisons with state-of-the-art methods demonstrate the superiority of our approach in both feature alignment and triangulation quality.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"188 ","pages":"Article 103912"},"PeriodicalIF":3.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144596859","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

High-resolution fiber-level simulation of knitted patterns 高分辨率纤维级针织图案模拟

IF 3 3区计算机科学

Computer-Aided Design Pub Date : 2025-06-30 DOI: 10.1016/j.cad.2025.103913

Xin Yang , Cheng Lu , Huiqi Shao , Guangwei Shao , Jinhua Jiang , Siyi Bi , Nanliang Chen

{"title":"High-resolution fiber-level simulation of knitted patterns","authors":"Xin Yang , Cheng Lu , Huiqi Shao , Guangwei Shao , Jinhua Jiang , Siyi Bi , Nanliang Chen","doi":"10.1016/j.cad.2025.103913","DOIUrl":"10.1016/j.cad.2025.103913","url":null,"abstract":"<div><div>Knitted fabrics, characterized by intricate patterns, vibrant colors, and soft tactile properties, have long served as a source of inspiration in textile design. Leveraging digital technology to translate these design concepts into realistic models, this paper proposes a fiber-level 3D simulation framework for complex knitted structures, inspired by the digital element methodology. In this approach, yarns are discretized into fiber assemblies represented by sequences of control points. Improved beam elements connect adjacent points to model bending behavior, while rod elements simulate inter-fiber interactions. To improve structural controllability, dynamic boundary conditions and variable driving forces are introduced, enabling accurate capture of both global and local deformations. An efficient Array operation is developed to support scalable generation of fabric patterns under a modified periodic boundary condition. Experimental evaluations demonstrate that the proposed method achieves visually and structurally accurate simulations within a limited number of iterations. Comparative analysis with real fabric samples validates the effectiveness and fidelity of the simulation framework, making it suitable for applications in virtual textile design and performance prediction.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"188 ","pages":"Article 103913"},"PeriodicalIF":3.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144571347","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

DNN-based Parameterization for B-Spline Curve Approximation 基于dnn的b样条曲线逼近参数化

IF 3 3区计算机科学

Computer-Aided Design Pub Date : 2025-06-18 DOI: 10.1016/j.cad.2025.103897

Wenqiang Tang , Zhouwang Yang

引用次数: 0

Two-stage physics-informed deep neural networks framework for form-finding of tensegrity structures 张拉整体结构寻形的两阶段物理信息深度神经网络框架

IF 3 3区计算机科学

Computer-Aided Design Pub Date : 2025-06-04 DOI: 10.1016/j.cad.2025.103898

Jin Wang, Mingliang Zhu, Zhiwei Miao

{"title":"Two-stage physics-informed deep neural networks framework for form-finding of tensegrity structures","authors":"Jin Wang, Mingliang Zhu, Zhiwei Miao","doi":"10.1016/j.cad.2025.103898","DOIUrl":"10.1016/j.cad.2025.103898","url":null,"abstract":"<div><div>This paper proposes a two-stage optimization deep neural network method for form-finding of tensegrity structures, based on physical information. The total loss function of the neural network is constructed by comprehensively considering the physical information, including nodal residual forces, element length constraints, and minimum node distance. To enhance the learning ability of the neural network, a two-stage optimization model is adopted. In the first stage, the AdamW optimizer is employed for preliminary training of the network's hyperparameters, quickly reducing the loss values. Following the preliminary training, the l-BFGS optimizer is utilized in the second stage to refine the optimization and converge toward the optimal solution, resulting in the nodal coordinates that satisfy the structural equilibrium. The paper includes case studies on five different tensegrity models. The results show that the proposed two-stage physics-informed deep neural network (PIDNN) approach, utilizing dual optimizers, can efficiently and accurately perform form-finding for various tensegrity structures, including both single- and multi-stable models. The method provides reliable results, avoids complex finite element computations, and offers high computational efficiency.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"186 ","pages":"Article 103898"},"PeriodicalIF":3.0,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243171","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

Parametric generators of geometric models and computational meshes of Francis turbines runners 混流式水轮机流道几何模型的参数化生成器及计算网格

IF 3 3区计算机科学

Computer-Aided Design Pub Date : 2025-04-21 DOI: 10.1016/j.cad.2025.103886

Bohumír Bastl

引用次数: 0

Augmented Sphere Tracing for Real-time Editing Mega-scale Periodic Shell-lattice Structures 实时编辑超大规模周期壳晶格结构的增强球面跟踪

IF 3 3区计算机科学

Computer-Aided Design Pub Date : 2025-04-02 DOI: 10.1016/j.cad.2025.103876

Jiajie Guo, Ming Li

{"title":"Augmented Sphere Tracing for Real-time Editing Mega-scale Periodic Shell-lattice Structures","authors":"Jiajie Guo, Ming Li","doi":"10.1016/j.cad.2025.103876","DOIUrl":"10.1016/j.cad.2025.103876","url":null,"abstract":"<div><div>We propose an augmented sphere tracing (AST) pipeline that seamlessly integrates editing, rendering, and slicing of mega-scale periodic shell-lattice structures. Traditional STL-based pipelines face challenges such as time-consuming format conversions, high storage requirements, and complex blending issues between discrete lattice and shell components, often resulting in a loss of geometric accuracy. Alternatively, implicit-based pipelines excel at smooth modeling and robust Boolean operations but require inefficient and error-prone conversions of STL shells into implicit forms, complicating the rendering process. To address these issues, AST combines hybrid implicit lattice and mesh shell representations, eliminating the need for explicit 3D model construction and unnecessary geometric format conversions. It overcomes the major challenges of hybrid forms and mega-scale rendering by using an augmented tracing distance query that avoids costly signed distance field (SDF) calculations while preserving geometric details. Additionally, it employs a local tracing distance query within a single cell, leveraging lattice periodicity for efficiency. The pipeline also supports various types of shell-lattices in industrial applications, including blending, warping, field-directed distributions, region-specific cell types, and produces arbitrary directional slicing for manufacturing. As demonstrated by various examples implemented in WebGPU, AST archives high efficiency and accuracy in real-time rendering of shell-lattices with billions of beams on an RTX 3090, outperforming traditional pipelines in storage, frame time, and detail preservation.</div></div>","PeriodicalId":50632,"journal":{"name":"Computer-Aided Design","volume":"184 ","pages":"Article 103876"},"PeriodicalIF":3.0,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776638","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