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首页> 外文期刊>International journal of numerical methods for heat & fluid flow >Efficient automatic discrete adjoint sensitivity computation for topology optimization - heat conduction applications
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Efficient automatic discrete adjoint sensitivity computation for topology optimization - heat conduction applications

机译：用于拓扑优化的高效自动离散伴随灵敏度计算-导热应用

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Purpose - Topology optimization is a method used for developing optimized geometric designs by distributing material pixels in a given design space that maximizes a chosen quantity of interest (Qol) subject to constraints. The purpose of this study is to develop a problem-agnostic automatic differentiation (AD) framework to compute sensitivities of the QoI required for density distribution-based topology optimization in an unstructured co-located cell-centered finite volume framework. Using this AD framework, the authors develop and demonstrate the topology optimization procedure for multi-dimensional steady-state heat conduction problems. Design/methodology/approach - Topology optimization is performed using the well-established solid isotropic material with penalization approach. The method of moving asymptotes, a gradient-based optimization algorithm, is used to perform the optimization. The sensitivities of the Qol with respect to design variables, required for optimization algorithm, are computed using a discrete adjoint method with a novel AD library named residual automatic partial differentiator (Rapid). Findings - Topologies that maximize or minimize relevant quantities of interest in heat conduction applications are presented. The efficacy of the technique is demonstrated using a variety of realistic heat transfer applications in both two and three dimensions, in conjugate heat transfer problems with finite conductivity ratios and in non-rectangularon-cuboidal domains. Originality/value - fa contrast to most published work which has either finite volume methods for transport applications, the topology optimization procedure is developed in a general unstructured finite volume framework. This permits topology optimization for flow and heat transfer applications in complex design domains such as those encountered in industry. In addition, the Rapid library is designed to provide a problem-agnostic pathway to automatically compute all required derivatives to machine accuracy. This obviates the necessity to write new code for finding sensitivities when new physics are added or new cost functions are considered and permits general-purpose implementations of topology optimization for complex industrial applications.
机译：目的-拓扑优化是一种用于通过在给定的设计空间中分配材料像素来开发优化的几何设计的方法，该方法可以使受约束的选定感兴趣量（Qol）最大化。这项研究的目的是开发一个与问题无关的自动差分（AD）框架，以计算非结构化位于同一位置的以细胞为中心的有限体积框架中基于密度分布的拓扑优化所需的QoI敏感性。使用该AD框架，作者开发并演示了多维稳态导热问题的拓扑优化程序。设计/方法/方法-使用完善的固体各向同性材料并采用惩罚方法进行拓扑优化。移动渐近线的方法（基于梯度的优化算法）用于执行优化。优化算法所需的Qol对设计变量的敏感度是使用具有新的AD库（称为残差自动偏微分器（Rapid））的离散伴随方法计算的。发现-提出了在导热应用中最大化或最小化相关关注量的拓扑。在二维和三维中，在具有有限电导率的共轭传热问题中以及在非矩形/非立方域中，使用了各种实际的传热应用，证明了该技术的有效性。原创性/价值-与大多数已发表的具有运输应用的有限体积方法的工作形成对比，拓扑优化过程是在通用的非结构化有限体积框架中开发的。这允许在复杂设计领域（如工业界遇到的领域）中的流量和传热应用进行拓扑优化。此外，Rapid库旨在提供与问题无关的途径，以自动计算所有必需的导数以提高机器精度。这样就避免了在添加新物理或考虑新成本函数时编写新代码以查找敏感度的必要性，并允许针对复杂工业应用的拓扑优化的通用实现。

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