Flow–heat topology optimization of internally cooled high temperature applications using a voxelization approach for domain initialization

A method is presented for obtaining topology optimized designs for internally cooled high temperature applications, using a flexible geometry description, by means of a voxelization methodology and a novel boundary detection algorithm. A conjugate heat transfer approach is taken; the physics is described by a Stokes–Brinkman model for the flow, weakly coupled with a convection–diffusion model for the heat transfer. A practically relevant optimization formulation, consisting of a maximum temperature objective with a mass flow constraint, is used, and applied to an industrial-relevant non-trivial geometry resembling a guide vane in a gas turbine. Temperatures and velocities from the optimized design are compared with the response from a Stokes flow model with body-fitted mesh and a high-fidelity Reynolds-averaged Navier–Stokes model. A comparison of the performance from a mixed and a penalty approach for solving the flow problem is included. The voxelization approach shows good promise for handling complex design domains.

本文提出一种面向内部冷却高温应用的拓扑优化设计获取方法，该方法采用灵活的几何描述方式，结合体素化（voxelization）方法与新型边界检测算法实现。研究采用共轭传热（conjugate heat transfer）思路，流动物理场由斯托克斯-布林克曼（Stokes–Brinkman）模型描述，并与传热过程的对流扩散模型实现弱耦合。本文采用兼具工程实用性的优化构型：以最大温度为优化目标，同时施加质量流量约束，并将该优化框架应用于一类工业相关的非平凡几何模型——该模型模拟燃气轮机导叶结构。将优化后设计的温度场与速度场结果，分别与采用贴体网格（body-fitted mesh）的斯托克斯流动模型，以及高保真雷诺平均Navier-Stokes（Reynolds-averaged Navier–Stokes）模型的计算响应进行对比。此外，本文还对比了求解流动问题的混合法与惩罚法的性能差异。研究结果表明，体素化方法在处理复杂设计域方面展现出良好的应用前景。