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首页> 外文期刊>Journal of thermal stresses >A NEW REDUCTION TECHNIQUE FOR THERMAL MODELS WITH FLUID NETWORKS
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A NEW REDUCTION TECHNIQUE FOR THERMAL MODELS WITH FLUID NETWORKS

机译：流体网络热模型的一种新的降阶技术

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摘要

Thermal finite element models are used to simulate the temperature distribution of a body under a certain set of boundary conditions. When short calculation times are necessary (i.e., for parametric study, active control loops, temperature monitoring algorithms, etc.) detailed FE models cannot be used and reduced-order models must be developed. Reduced-order models may have both generalized and physical degrees of freedom (dofs), according to the scope of the reduction. The use of generalized dofs is more suitable to simulate full-field temperature distribution of the body, while inclusion of physical dofs can be advantageous when temperature must be only computed at a small number of locations. In this paper a new reduction technique is proposed for applications where only a small set of temperatures must be computed; it is based on the Guyan reduction method and overcomes the limitations of the original Guyan reduction when applied to thermal models with a fluid network, characterized by non-symmetric matrices. The new technique is applied to a case study, consisting of a dummy turbine disk and its secondary air system in order to show the improvement with respect to the original Guyan approach.
机译：热有限元模型用于模拟在特定边界条件下的物体温度分布。当需要较短的计算时间时（例如，对于参数研究，主动控制回路，温度监控算法等），无法使用详细的有限元模型，必须开发降阶模型。根据缩减的范围，降阶模型可能同时具有广义和物理自由度（dofs）。广义自由度的使用更适合于模拟人体的全场温度分布，而当必须仅在少数几个位置计算温度时，包含物理自由度可能是有利的。在本文中，针对仅需计算少量温度的应用提出了一种新的还原技术。它基于Guyan约简方法，并且在应用于具有非对称矩阵特征的带有流体网络的热模型时，克服了原始Guyan约简的局限性。这项新技术被应用到一个案例研究中，该案例包括一个虚拟涡轮盘及其二次空气系统，以显示相对于原始Guyan方法的改进。

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