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Efficient Solution of Inverse Thermal Problem via Parametric Model Order Reduction

机译:通过参数模型顺序减少高效解决逆热问题

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摘要

In this paper we present a novel approach to determine material thermal properties of thin film materials. As a testcase we have chosen silicon nitride employed in a micro-hotplate structure. We use ANSYS to build a three-dimensional finite element (FE) model of the test structure, which considers heat conduction and convection effects. It is further parameterized and subjected to parametric model order reduction (pMOR). The parameters of the reduced model are the unknown material thermal properties and the heat transfer coefficient, which are automatically adjusted within the optimization loop, so that the simulation results of the model are in agreement with the transient temperature measurements. The use of parameterized reduced order models within the optimization iterations speeds up the transient solution time by several orders of magnitude, while retaining almost the same precision as the full FE model.
机译:在本文中,我们提出了一种新颖的方法来确定薄膜材料的材料热性能。作为测试箱,我们选择了在微热板结构中使用的氮化硅。我们使用ANSYS构建测试结构的三维有限元(FE)模型,这考虑了热传导和对流效果。它进一步参数化并经受参数模型顺序减少(PMOR)。减少模型的参数是未知的材料热特性和传热系数,其在优化环内自动调节,因此模型的仿真结果与瞬态温度测量一致。在优化迭代中使用参数化减少订单模型将瞬态解决方案时间升高了几个数量级,同时将几乎与全FE模型保持几乎相同的精度。

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