LAUSR

Abstract A key challenge in the development of a practical thermal storage device (TSD) is the low thermal conductivity of common phase change materials (PCM). This low conductivity impedes both heat input and extraction. The most common solution is to use conductive metal fins to spread heat through the device. However, optimizing the effectiveness of the container and the fin arrangement is difficult due to the large number of potential design parameters. This paper develops a strategy to make simulation-based optimization process affordable and accurate. First, numerical techniques are designed to accurately and efficiently compute heat and mass transport in a variety of geometries without generating grids to conform to each geometry. This facilitates rapid prototyping and mitigates the expense of individual simulations. Second, a pre-screening process identifies the independent variables with the largest and most nonlinear effect on the objective function in the optimization process, thus narrowing the parameter space. Finally, a dynamic Kriging-based optimization approach constructs a multidimensional response surface using sparse input datasets; the response surface is then used to identify an optimal design. The combination of the above three strategies is shown to result in an approach that can aid in the design of optimal thermal storage devices that rely on a mixture of PCM and metal fins.