Adaptive hyper reduction for additive manufacturing thermal fluid analysis
Adaptive hyper reduction for additive manufacturing thermal fluid analysis
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DOI：
10.1016/j.cma.2020.113312
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发表时间：
2020-12-01
影响因子：
7.2
通讯作者：
Liu, Wing Kam
中科院分区：
文献类型：
--
作者：
Lu, Ye;Jones, Kevontrez Kyvon;Liu, Wing Kam
热流体耦合分析对于在增材制造中实现准确的温度预测至关重要。然而，这种类型的数值模拟是耗时的，由于高非线性，潜在的大网格尺寸和小的时间步长的限制。本文提出了一种新的自适应超简化方法，以加快这些模拟。与非线性项模型降阶的困难，解决了设计一个自适应减少的集成域。建议的在线基础自适应策略是基于一个基础映射，丰富的本地残差和间隙的基础重建技术的组合。所提出的方法的效率将通过增材制造模型的代表性3D示例来证明，包括单轨和多轨情况。(C)2020爱思唯尔B.V.保留所有权利。
Thermal fluid coupled analysis is essential to enable an accurate temperature prediction in additive manufacturing. However, numerical simulations of this type are time-consuming, due to the high non-linearity, the underlying large mesh size and the small time step constraints. This paper presents a novel adaptive hyper reduction method for speeding up these simulations. The difficulties associated with non-linear terms for model reduction are tackled by designing an adaptive reduced integration domain. The proposed online basis adaptation strategy is based on a combination of a basis mapping, enrichment by local residuals and a gappy basis reconstruction technique. The efficiency of the proposed method will be demonstrated by representative 3D examples of additive manufacturing models, including single-track and multi-track cases. (C) 2020 Elsevier B.V. All rights reserved.