STL-Free Adaptive Slicing Scheme for Additive Manufacturing of Cellular Materials

IF 2.6 3区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Sina Rastegarzadeh, Jida Huang
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引用次数: 0

Abstract

In recent years, advances in additive manufacturing (AM) techniques have called for a scalable fabrication framework for high-resolution designs. Despite several process-specific handful design approaches, there is a gap to fill between computer-aided design (CAD) and the manufacturing of highly detailed multi-scale materials, especially for delicate cellular materials design. This gap ought to be filled with an avenue capable of efficiently slicing multi-scale intricate designs. Most existing methods depend on the mesh representation, which is time-consuming and memory-hogging to generate. This paper proposes an adaptive direct slicing (mesh-free) pipeline that exploits the function representation (FRep) for hierarchical architected cellular materials design. To explore the capabilities of the presented approach, several sample structures with delicate architectures are fabricated using a stereolithography (SLA) printer. The computational efficiency of the proposed slicing algorithm is studied. Furthermore, the geometry frustration problem brought by the connection of distinct structures between functionally graded unit cells at the micro-scale level is also investigated.
用于细胞材料增材制造的无STL自适应切片方案
近年来,增材制造(AM)技术的进步要求为高分辨率设计提供可扩展的制造框架。尽管有几种特定于工艺的设计方法,但计算机辅助设计(CAD)和高度精细的多尺度材料的制造之间仍存在差距,尤其是对于精细的蜂窝材料设计。应该用一种能够有效分割多尺度复杂设计的方法来填补这一空白。大多数现有的方法都依赖于网格表示,这是一种耗时且占用内存的生成方法。本文提出了一种自适应直接切片(无网格)流水线,该流水线利用函数表示(FRep)进行分层结构的蜂窝材料设计。为了探索所提出的方法的能力,使用立体光刻(SLA)打印机制造了几个具有精细结构的样品结构。研究了所提出的切片算法的计算效率。此外,还在微观尺度上研究了功能梯度单元之间不同结构的连接所带来的几何挫折问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.30
自引率
12.90%
发文量
100
审稿时长
6 months
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
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