A Review of Model Inaccuracy and Parameter Uncertainty in Laser Powder Bed Fusion Models and Simulations.

A Review of Model Inaccuracy and Parameter Uncertainty in Laser Powder Bed Fusion Models and Simulations.
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激光粉末床融合模型和模拟中的模型误差和参数不确定性的回顾。

DOI:
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发表时间:
2019
期刊:
Journal of manufacturing science and engineering
影响因子:
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通讯作者:
P. Witherell
P. Witherell
中科院分区:
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文献类型:
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作者:
Tesfaye Moges;G. Ameta;P. Witherell

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本文综述了金属激光粉末床熔合(L-PBF)过程中模型误差和参数不确定性的来源。金属增材制造(AM)涉及多种物理现象和参数,这些物理现象和参数可能会影响最终零件的质量。为了捕捉金属L-PBF过程中存在的热和相变的动力学和复杂性,已经开发了从低到高保真度的计算模型和模拟。由于很难纳入L-PBF过程中遇到的所有物理现象,计算模型依赖于可能忽略或简化过程中某些物理现象的假设。模型假设和不确定性对L-PBF模型的预测精度有重要影响。在本研究中,回顾了从粉末床形成到熔化和凝固过程的不同阶段建模不准确性的来源。对材料性能和工艺参数等参数不确定度的来源进行了综述。这篇综述的目的是支持未来在L-PBF模型中量化这些不确定性来源的方法的发展。不确定性源的量化对于理解模型保真度的权衡和指导选择适合其预期目的的模型是必要的。
This paper presents a comprehensive review on the sources of model inaccuracy and parameter uncertainty in metal laser powder bed fusion (L-PBF) process. Metal additive manufacturing (AM) involves multiple physical phenomena and parameters that potentially affect the quality of the final part. To capture the dynamics and complexity of heat and phase transformations that exist in the metal L-PBF process, computational models and simulations ranging from low to high fidelity have been developed. Since it is difficult to incorporate all the physical phenomena encountered in the L-PBF process, computational models rely on assumptions that may neglect or simplify some physics of the process. Modeling assumptions and uncertainty play significant role in the predictive accuracy of such L-PBF models. In this study, sources of modeling inaccuracy at different stages of the process from powder bed formation to melting and solidification are reviewed. The sources of parameter uncertainty related to material properties and process parameters are also reviewed. The aim of this review is to support the development of an approach to quantify these sources of uncertainty in L-PBF models in the future. The quantification of uncertainty sources is necessary for understanding the tradeoffs in model fidelity and guiding the selection of a model suitable for its intended purpose.
DOI: 10.1016/j.ijmachtools.2017.04.007
发表时间: 2017-08-01
影响因子: 14
作者:
Masoomi, Mohammad;Thompson, Scott M.;Shamsaei, Nima
通讯作者: Shamsaei, Nima