Topology design of two-fluid heat exchange

This paper presents a density-based topology optimization method for designing three-dimensional (3D) compliant mechanisms and loadbearing structures with design-dependent pressure loading. Instead of interface-tracking techniques, the Darcy law in conjunction with a drainage term is employed to obtain pressure field as a function of the design vector. To ensure continuous transition of pressure loads as the design evolves, the flow coefficient of a finite element is defined ...

Inverse design arises in a variety of areas in engineering such as acoustic, mechanics, thermal/electronic transport, electromagnetism, and optics. Topology optimization is a major form of inverse design, where we optimize a designed geometry to achieve targeted properties and the geometry is parameterized by a density function. This optimization is challenging, because it has a very high dimensionality and is usually constrained by partial differential equations (PDEs) and a...

This paper presents a density-based topology optimization method for designing 3D thin-walled structures with adaptive meshing. Uniform wall thickness is achieved by simultaneously constraining the minimum and maximum feature sizes using Helmholtz partial differential equations (PDE). The PDE-based constraints do not require information about neighbor cells and therefore can readily be integrated with an adaptive meshing scheme. This effectively enables the 3D topology optimi...

Topology optimization (TO) is a popular and powerful computational approach for designing novel structures, materials, and devices. Two computational challenges have limited the applicability of TO to a variety of industrial applications. First, a TO problem often involves a large number of design variables to guarantee sufficient expressive power. Second, many TO problems require a large number of expensive physical model simulations, and those simulations cannot be parallel...

We present a robust and efficient algorithm for solving large-scale three-dimensional structural topology optimization problems, in which the optimization problem is solved by a globally convergent sequential linear programming (SLP) method with a stopping criterion based on first-order optimality conditions. The SLP approach is combined with a multiresolution scheme, that employs different discretizations to deal with displacement, design and density variables, allowing high...

This report details the design and optimisation of a water-cooled forced convection heat dissipation system for use in high-temperature applications (ranges between 700 degrees - 1000 degrees K). A hollow cuboid vapour chamber model was investigated. The space within the hollow cuboid was used as the design space. COMSOL, a FEM software product was used to solve for the physical parameters of each geometry for the heat dissipation system design space. COMSOL in conjunction wi...

Topology optimization by optimally distributing materials in a given domain requires non-gradient optimizers to solve highly complicated problems. However, with hundreds of design variables or more involved, solving such problems would require millions of Finite Element Method (FEM) calculations whose computational cost is huge and impractical. Here we report Self-directed Online Learning Optimization (SOLO) which integrates Deep Neural Network (DNN) with FEM calculations. A ...

Topology optimization methods face serious challenges when applied to structural design with fluid-structure interaction (FSI) loads, specially for high Reynolds fluid flow. This paper devises an explicit boundary method that employs separate analysis and optimization grids in FSI systems. A geometry file is created after extracting a smooth contour from a set of binary design variables that defines the structural design. The FSI problem can then be modeled with accurate phys...

Engineering structures must often be designed to resist thermally induced stresses. Significant progress has been made on the design of such structures through thermo-elastic topology optimization. However, a computationally efficient framework to handle stress-constrained large-scale problems is lacking. The main contribution of this paper is to address this limitation. In particular, a unified topological-sensitivity (TS) based level-set approach is presented in this paper ...

Generative design has been growing across the design community as a viable method for design space exploration. Thermal design is more complex than mechanical or aerodynamic design because of the additional convection-diffusion equation and its pertinent boundary interaction. We present a generative thermal design using cooperative multi-agent deep reinforcement learning and continuous geometric representation of the fluid and solid domain. The proposed framework consists of ...