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Computational Framework to Evaluate the Relationships between Process Parameters, Grain Structure and Mechanical Properties of Additive Manufactured Materials

评估增材制造材料的工艺参数、晶粒结构和机械性能之间关系的计算框架

基本信息

批准号：
388878396
负责人：
Professor Dr.-Ing. Vasily Ploshikhin
金额：
--
依托单位：
Russian Foundation for Basic Research
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2017
资助国家：
德国
起止时间：
2016-12-31 至 2021-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/388878396?language=en
关键词：
Computational Framework Evaluate Relationships between

项目摘要

Additive manufacturing (AM) enabling metal products of highly complex shape to be created directly from CAD data has been gaining significant attention recently. Additive manufactured materials are characterized by complex inhomogeneous microstructure strongly affecting the material properties. In this connection, the prediction of microstructures and mechanical properties of additive manufactured materials is a significant research focus to face the challenge of producing tailored components. Moreover, it may play a key role in the AM process optimization. Modeling of grain structure evolution during AM and further implementation of the AM microstructures in the mechanical simulations will provide a scientific ground for optimization of the AM regimes to improve the microstructure and properties of the manufactured parts. Thus, the development of a reliable and efficient computational framework to evaluate the relationships between process parameters, grain structure and mechanical properties of additive manufactured materials is pursued.The project aims at development and application of a computational approach to the modeling of grain structure formation and evolution during AM of aluminum specimens (DFG) and subsequent simulation of their deformation behavior with an explicit account of the microstructure (RFBR). Selective laser melting (SLM), which involves sequential deposition of powder layers on a polycrystalline substrate followed by their melting, will be examined. The realized methodology will account for the mechanisms of microstructural development and the thermal processes during AM on the mesoscopic scale (DFG). Using the implemented cellular automata-finite difference method, the nature and mechanisms of grain structure evolution in aluminum alloy specimens processed by SLM will be investigated (DFG). Then a set of microstructure-based numerical calculations is planned to study the stress and strain patterns in additive manufactured aluminum specimens under loading on different length scales (RFBR).

能够直接从CAD数据生成高度复杂形状的金属产品的加法制造(AM)最近得到了极大的关注。添加剂制造的材料具有复杂的非均匀微观结构，对材料的性能有很大影响。在这方面，对添加剂制造材料的微观组织和力学性能的预测是面对定制部件制造挑战的一个重要研究重点。此外，它还可能在AM流程优化中起到关键作用。对AM过程中的晶粒组织演化进行建模，并在力学模拟中进一步实现AM的微观组织，将为优化AM制度以改善制件的组织和性能提供科学依据。因此，我们致力于开发一种可靠、高效的计算框架来评估添加材料的工艺参数、晶粒组织和力学性能之间的关系。该项目旨在开发和应用一种计算方法来模拟铝合金试件在变形过程中的组织形成和演化，并在此基础上模拟其变形行为，同时显式解释微观组织(RFBR)。将研究选择性激光熔化(SLM)，即在多晶衬底上顺序沉积粉末层，然后将其熔化。实现的方法将在介观尺度(DFG)上解释AM过程中的微观结构发展和热过程的机制。利用已实现的元胞自动机-有限差分方法，研究了铝合金SLM加工试件中晶界组织演变的本质和机理。在此基础上，设计了一套基于微观结构的数值计算方法，研究了不同长度尺度载荷作用下添加剂制造的铝试件的应力应变模式。