{"title":"基于复合块划分的复杂Dexel模型重构算法","authors":"Haiwen Yu, Dianliang Wu, Xu Hanzhong","doi":"10.1115/1.4063955","DOIUrl":null,"url":null,"abstract":"Abstract In machining simulations, dexel models are often used to represent objects to achieve high accuracy and real-time performance. However, this approach leads to the loss of original surface information and topological relationships, thereby affecting the visualization effect of simulations. Furthermore, existing reconstruction methods have the drawbacks of generalization or redundancy. To reconstruct the surface of dexel models efficiently and accurately, this paper proposes an algorithm based on “composite block” partition, which converts the dexel model into a polyhedral model. The algorithm begins by partitioning the entire dexel model within the grids into several composite blocks based on the “Connectivity Principle” and generating their end faces. Subsequently, the transitional zone's surface is reconstructed based on the connectivity relationships of the boundaries of composite blocks. Finally, an optimization process refines the boundaries to generate smoother side faces at a low computational cost. The paper first validates the algorithm's reconstruction capability and the effectiveness of edge refinement through the reconstruction of various dexel models with different precision levels. It's observed that edge refinement doesn't introduce excessive additional computation, doubling the overall efficiency compared to existing algorithms. Furthermore, by changing model volumes and performing separate reconstructions, it's noted that as the volume increases, the incremental growth in conversion time gradually decreases. This makes the algorithm particularly suitable for reconstructing large-scale complex dexel models. Finally, the application of this algorithm in virtual-real simulation system and industrial digital twin system is briefly introduced.","PeriodicalId":54856,"journal":{"name":"Journal of Computing and Information Science in Engineering","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reconstruction Algorithm for Complex Dexel Models Based on Composite Block Partition\",\"authors\":\"Haiwen Yu, Dianliang Wu, Xu Hanzhong\",\"doi\":\"10.1115/1.4063955\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract In machining simulations, dexel models are often used to represent objects to achieve high accuracy and real-time performance. However, this approach leads to the loss of original surface information and topological relationships, thereby affecting the visualization effect of simulations. Furthermore, existing reconstruction methods have the drawbacks of generalization or redundancy. To reconstruct the surface of dexel models efficiently and accurately, this paper proposes an algorithm based on “composite block” partition, which converts the dexel model into a polyhedral model. The algorithm begins by partitioning the entire dexel model within the grids into several composite blocks based on the “Connectivity Principle” and generating their end faces. Subsequently, the transitional zone's surface is reconstructed based on the connectivity relationships of the boundaries of composite blocks. Finally, an optimization process refines the boundaries to generate smoother side faces at a low computational cost. The paper first validates the algorithm's reconstruction capability and the effectiveness of edge refinement through the reconstruction of various dexel models with different precision levels. It's observed that edge refinement doesn't introduce excessive additional computation, doubling the overall efficiency compared to existing algorithms. Furthermore, by changing model volumes and performing separate reconstructions, it's noted that as the volume increases, the incremental growth in conversion time gradually decreases. This makes the algorithm particularly suitable for reconstructing large-scale complex dexel models. Finally, the application of this algorithm in virtual-real simulation system and industrial digital twin system is briefly introduced.\",\"PeriodicalId\":54856,\"journal\":{\"name\":\"Journal of Computing and Information Science in Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computing and Information Science in Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4063955\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computing and Information Science in Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4063955","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Reconstruction Algorithm for Complex Dexel Models Based on Composite Block Partition
Abstract In machining simulations, dexel models are often used to represent objects to achieve high accuracy and real-time performance. However, this approach leads to the loss of original surface information and topological relationships, thereby affecting the visualization effect of simulations. Furthermore, existing reconstruction methods have the drawbacks of generalization or redundancy. To reconstruct the surface of dexel models efficiently and accurately, this paper proposes an algorithm based on “composite block” partition, which converts the dexel model into a polyhedral model. The algorithm begins by partitioning the entire dexel model within the grids into several composite blocks based on the “Connectivity Principle” and generating their end faces. Subsequently, the transitional zone's surface is reconstructed based on the connectivity relationships of the boundaries of composite blocks. Finally, an optimization process refines the boundaries to generate smoother side faces at a low computational cost. The paper first validates the algorithm's reconstruction capability and the effectiveness of edge refinement through the reconstruction of various dexel models with different precision levels. It's observed that edge refinement doesn't introduce excessive additional computation, doubling the overall efficiency compared to existing algorithms. Furthermore, by changing model volumes and performing separate reconstructions, it's noted that as the volume increases, the incremental growth in conversion time gradually decreases. This makes the algorithm particularly suitable for reconstructing large-scale complex dexel models. Finally, the application of this algorithm in virtual-real simulation system and industrial digital twin system is briefly introduced.
期刊介绍:
The ASME Journal of Computing and Information Science in Engineering (JCISE) publishes articles related to Algorithms, Computational Methods, Computing Infrastructure, Computer-Interpretable Representations, Human-Computer Interfaces, Information Science, and/or System Architectures that aim to improve some aspect of product and system lifecycle (e.g., design, manufacturing, operation, maintenance, disposal, recycling etc.). Applications considered in JCISE manuscripts should be relevant to the mechanical engineering discipline. Papers can be focused on fundamental research leading to new methods, or adaptation of existing methods for new applications.
Scope: Advanced Computing Infrastructure; Artificial Intelligence; Big Data and Analytics; Collaborative Design; Computer Aided Design; Computer Aided Engineering; Computer Aided Manufacturing; Computational Foundations for Additive Manufacturing; Computational Foundations for Engineering Optimization; Computational Geometry; Computational Metrology; Computational Synthesis; Conceptual Design; Cybermanufacturing; Cyber Physical Security for Factories; Cyber Physical System Design and Operation; Data-Driven Engineering Applications; Engineering Informatics; Geometric Reasoning; GPU Computing for Design and Manufacturing; Human Computer Interfaces/Interactions; Industrial Internet of Things; Knowledge Engineering; Information Management; Inverse Methods for Engineering Applications; Machine Learning for Engineering Applications; Manufacturing Planning; Manufacturing Automation; Model-based Systems Engineering; Multiphysics Modeling and Simulation; Multiscale Modeling and Simulation; Multidisciplinary Optimization; Physics-Based Simulations; Process Modeling for Engineering Applications; Qualification, Verification and Validation of Computational Models; Symbolic Computing for Engineering Applications; Tolerance Modeling; Topology and Shape Optimization; Virtual and Augmented Reality Environments; Virtual Prototyping