Thermal Modeling in Metal Additive Manufacturing Using Graph Theory
Thermal Modeling in Metal Additive Manufacturing Using Graph Theory
复制标题
使用图论进行金属增材制造的热建模
DOI：
10.1115/1.4043648
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Rao, Prahalada
中科院分区：
文献类型：
--
作者：
Yavari, M. Reza;Cole, Kevin D.;Rao, Prahalada
这项工作的目标是预测零件几何形状和工艺参数对金属零件中温度瞬时时空分布的影响，也称为热场或温度历史，因为它们正在使用增材制造（AM）工艺逐层构建。在追求这一目标，这项工作的目标是开发和验证基于图论的方法来预测金属AM部件的温度分布。这一目标是为了克服目前AM中工艺一致性和零件质量差的问题。金属AM工艺中零件质量差的主要原因之一归因于零件中温度分布的性质。例如，在打印期间在部件中产生的陡峭的热梯度会导致缺陷，例如翘曲和热应力引起的开裂。现有的非专有方法来预测AM部件中的温度分布主要使用基于网格的有限元分析，该有限元分析在计算上是曲折的-几层的模拟通常需要几个小时，如果不是几天的话。因此，为了缓解金属AM工艺中的这些挑战，需要有效的计算模型来预测温度分布，从而指导零件设计和工艺参数的选择，而不是昂贵的经验测试。与有限元分析技术相比，所提出的无网格基于图论的方法便于在台式计算机上几分钟内预测温度分布。为了探索这些断言，我们进行了以下两项研究：（1）将使用图论方法预测的热扩散趋势与有限元分析进行比较，和基于绿色函数的基本长方体几何形状的分析传热计算，该长方体几何形状在其体积的某一部分中经受脉冲热输入，以及（2）模拟三个-（a）Goldak的移动热源有限元法，（B）提出的图论方法，以及（c）进一步比较从最后两种方法预测的热趋势与商业解决方案。从第一项研究中，我们报告说，热趋势近似的图论方法被发现是准确的绿色的功能为基础的分析解决方案（对称平均绝对百分比误差）的5%以内。第二项研究的结果表明，使用图论方法预测的AM部件的热趋势与有限元分析一致，并且使用图论预测温度分布的计算时间显着减少。例如，对于所研究的AM部件几何形状之一，使用图论方法在不到18分钟内预测温度趋势，误差在10%以内，而使用有限元分析超过180分钟。虽然本文仅限于理论发展和验证的图论方法，我们即将进行的研究将集中在实验验证，通过过程中的热测量。
The goal of this work is to predict the effect of part geometry and process parameters on the instantaneous spatiotemporal distribution of temperature, also called the thermal field or temperature history, in metal parts as they are being built layer-by-layer using additive manufacturing (AM) processes. In pursuit of this goal, the objective of this work is to develop and verify a graph theory-based approach for predicting the temperature distribution in metal AM parts. This objective is consequential to overcome the current poor process consistency and part quality in AM. One of the main reasons for poor part quality in metal AM processes is ascribed to the nature of temperature distribution in the part. For instance, steep thermal gradients created in the part during printing leads to defects, such as warping and thermal stress-induced cracking. Existing nonproprietary approaches to predict the temperature distribution in AM parts predominantly use mesh-based finite element analyses that are computationally tortuous—the simulation of a few layers typically requires several hours, if not days. Hence, to alleviate these challenges in metal AM processes, there is a need for efficient computational models to predict the temperature distribution, and thereby guide part design and selection of process parameters instead of expensive empirical testing. Compared with finite element analyses techniques, the proposed mesh-free graph theory-based approach facilitates prediction of the temperature distribution within a few minutes on a desktop computer. To explore these assertions, we conducted the following two studies: (1) comparing the heat diffusion trends predicted using the graph theory approach with finite element analysis, and analytical heat transfer calculations based on Green’s functions for an elementary cuboid geometry which is subjected to an impulse heat input in a certain part of its volume and (2) simulating the laser powder bed fusion metal AM of three-part geometries with (a) Goldak’s moving heat source finite element method, (b) the proposed graph theory approach, and (c) further comparing the thermal trends predicted from the last two approaches with a commercial solution. From the first study, we report that the thermal trends approximated by the graph theory approach are found to be accurate within 5% of the Green’s functions-based analytical solution (in terms of the symmetric mean absolute percentage error). Results from the second study show that the thermal trends predicted for the AM parts using graph theory approach agree with finite element analyses, and the computational time for predicting the temperature distribution was significantly reduced with graph theory. For instance, for one of the AM part geometries studied, the temperature trends were predicted in less than 18 min within 10% error using the graph theory approach compared with over 180 min with finite element analyses. Although this paper is restricted to theoretical development and verification of the graph theory approach, our forthcoming research will focus on experimental validation through in-process thermal measurements.
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DOI：
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发表时间：
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期刊：
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发表时间：
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影响因子：
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