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Adjoint Lattice Boltzmann for topology optimization on multi-GPU architecture

机译:伴随的Lattice Boltzmann在多GPU架构上进行拓扑优化

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In this paper we present a topology optimization technique applicable to a broad range of flow design problems. We propose also a discrete adjoint formulation effective for a wide class of Lattice Boltzmann Methods (LBM). This adjoint formulation is used to calculate sensitivity of the LBM solution to several type of parameters, both global and local. The numerical scheme for solving the adjoint problem has many properties of the original system, including locality and explicit time-stepping. Thus it is possible to integrate it with the standard LBM solver, allowing for straightforward and efficient parallelization (overcoming limitations typical for the discrete adjoint solvers). This approach is successfully used for the channel flow to design a free-topology mixer and a heat exchanger. Both resulting geometries being very complex maximize their objective functions, while keeping viscous losses at acceptable level. (C) 2016 Elsevier Ltd. All rights reserved.
机译:在本文中,我们提出了一种拓扑优化技术,适用于广泛的流程设计问题。我们还提出了适用于多种格子Boltzmann方法(LBM)的离散伴随配方。该辅助公式用于计算LBM解决方案对几种类型的参数(全局和局部)的敏感性。解决伴随问题的数值方案具有原始系统的许多特性,包括局部性和明确的时间步长。因此,可以将其与标准LBM求解器集成,从而实现直接有效的并行化(克服离散伴随求解器的典型限制)。此方法已成功用于通道流动,以设计自由拓扑混合器和热交换器。这两个非常复杂的几何形状都将其目标函数最大化,同时将粘性损失保持在可接受的水平。 (C)2016 Elsevier Ltd.保留所有权利。

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