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A comprehensive benchmark of fixed-grid methods for the modeling of melting

机译:一种熔化建模固定网格方法的全面基准

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摘要

Numerical simulation of melting processes is known to be tricky yet due to new application fields they raise again the attention of both, researchers and engineers. Several approaches were developed to solve this moving boundary problem, fixed grid methods being the most widespread ones. However, up to now no holistic and quantitative comparison, even of the most common enthalpy methods (some of these being included in famous commercial software), exists. Therefore, within this work, an exhaustive study is performed to evaluate the corresponding accuracy of the five most used macroscopic energy formulations with a strong coupling between temperature and enthalpy. In addition to pure conductive cases with analytical solution, an experimental test including natural convection is considered. Thus, the influence of the time step, of the grid and of the tolerance within the energy equation are investigated. In the same way several thermodynamical modelings are considered: either isothermal or non-isothermal phase change, several temperature ranges being used in this later case. From the more than 2500 simulations obtained, painstaking quantitative error analysis are conducted and quality thresholds are defined. Generally, approaches formulated in terms of enthalpy appear to be more robust than the ones using temperature formulations instead. The popular effective heat capacity method (with iterative correction) leads to the largest errors when considering the complete enthalpy in the convection term. (C) 2017 Elsevier Masson SAS. All rights reserved.
机译:已知熔化过程的数值模拟尚令人棘手令人棘手,因为新的应用领域他们再次引起,研究人员和工程师的注意。开发了几种方法来解决这个移动的边界问题,固定网格方法是最广泛的网格方法。然而,现在,甚至没有整体和量化的比较,即使是最常见的焓方法(其中一些被包括在着名的商业软件中)。因此,在这项工作中,进行详尽的研究以评估五种最常用的宏观能量配方的相应精度,其温度和焓之间的强耦合。除了具有分析解决方案的纯导电情况外,还考虑了包括自然对流的实验测试。因此,研究了时间步骤,网格的影响和能量方程内的公差的影响。以相同的方式考虑多个热力学建模:等温或非等温相变,在此后来使用的几个温度范围。从2500多种模拟中,进行了艰苦的定量误差分析,并定义了质量阈值。通常,在焓方面配制的方法看起来比使用温度配方的温度更强。当考虑对流项中完全焓时,流行的有效热容量方法(具有迭代校正)导致最大的错误。 (c)2017年Elsevier Masson SAS。版权所有。

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