Date of Degree
PhD (Doctor of Philosophy)
Udaykumar, H S
First Committee Member
Buchholz, James H J
Second Committee Member
Third Committee Member
Fourth Committee Member
Choi, K K
The high energy density and stable temperature fields of latent heat thermal storage devices (LHTSD) make them promising in a range of applications, including solar energy storage, solar cooking, home heating and cooling, and thermal buffering. The chief engineering challenge in building an effective LHTSD is to find a way to complement the storage capabilities provided by the low-conductivity phase-change material with a suitable enhanced heat transfer mechanism.
The principal aim of this project is to develop a tool to improve the design of a small-scale LHTSD, such as one that might be used in solar cooking for a family. An effective small-scale storage device would need to absorb solar energy quickly, release the energy at a high temperature, be affordable, and be manageable within a small household. An LHTSD using solar salts fulfills the latter two requirements: solar salts, a near-eutectic mixture of NaNO3 and KNO3 (60/40% by mass) commonly used in thermal storage applications, are inexpensive and widely available, and the use of latent heat storage means a relatively small chamber can hold enough energy to cook a family meal. The challenge, however, is to design a device that absorbs and releases energy from the solar salts, which have a very low thermal conductivity. The most practical tool to improve the spread of heat through the salts is a finned metal core within the LHTSD.
This project uses numerical simulation to determine the most effective design of this finned core. A Cartesian grid solver is developed that is capable of simulating the convection-dominated melting processes within the storage device. The phase boundary is tracked using the enthalpy method, and conjugate heat transfer is calculated with a strongly coupled implicit scheme.
A number of techniques are then used to with this solver in order to better understand the factors that affect the performance of a LHTSD and to improve the design of such devices. The thesis is organized as an introductory section followed by three case studies. In the first section, the project is introduced, and the governing equations and core numerical methods are described. In addition, a set of test simulations demonstrate that results using the developed numerical scheme match those of a range of experimental and numerical benchmarks.
Each of the case studies aims to adapt the numerical scheme to a more specific problem concerning LHTSDs. In the first, the performance of four fin designs are compared over long-term (48 hour) simulations; the aim is to test the potential performance of the four LHTSDs given realistic solar conditions in New Delhi, India. In the second case study, a set of physical experiments are performed in an empty and a finned LHTSD, and matched 3-dimensional numerical simulations are used to explore the thermal, melt, and flow behavior of the solar salts with the chambers. The final study uses the computational scheme to optimize the design of the finned core of an LHTSD over a large parameter space. To optimize the best design, the key parameters are first prescreened to find which three parameters have the largest effect on the objective equation. A machine-learning optimization code using the dynamic Kriging method (DKG) is then used to build a response surface from which the optimized design can be determined.
These three cases demonstrate the potential of the numerical scheme to explore the performance of finned LHTSD designs in a range of ways: the scheme can be used to predict behavior of devices in realistic conditions, to explore the behavior of solar salts during the melting and solidification process, and to determine an optimal design within a large parameter space. In doing so, they show the potential of this tool to help improve the performance and practicality of small-scale LHTSDs.
fins, optimization, phase change, solar cooker, thermal storage
xiv, 162 pages
Includes bibliographical references (pages 155-162).
Copyright © 2018 Michael Augspurger
Augspurger, Michael. "Improving the performance of finned latent heat thermal storage devices using a Cartesian grid solver and machine-learning optimization techniques." PhD (Doctor of Philosophy) thesis, University of Iowa, 2018.