Session: 07-04: Modeling of Thermal Energy Storage and Receiver Systems

Paper Number: 169965

169965 - Transient, Reduced-Order Heat and Mass Transfer Modeling of the Sandewirm, a Rotating Particle-Based Thermal Energy Storage System 

Abstract: 

A novel thermal energy storage device, Sandewirm, represents an approach to storing and managing thermal energy through an innovative particle-based mechanism. This system utilizes a combination of granular flow dynamics and thermal exchange principles to achieve energy storage and transfer capabilities. Sandewirm consists of opposing inner and outer helices and a particle heat exchange system. During rotation, particles flow down the outer helix through the exchanger and into the inner helix. The device stores thermal energy when rotating one way and releases it when rotating the other. This design leverages the advantages of existing pumped thermal energy storage technologies while potentially offering the capability of long duration energy storage (>8 hours) and storage temperatures up to 1000 ° C. A reduced-order thermal model characterizes system dynamics using a thermal resistor network (TRN). The model generalizes particle flow through an advective source term that represents the heat exchanger, while determining resistance values using effective thermal resistance approximations – including Zehner-Bauer-Schlunder (ZBS) resistance for particle-to-particle interactions in packed beds. With first-order accuracy, this model serves as a sizing tool to evaluate the device's effectiveness across different applications and varying design criteria. Machine learning (ML) and multi-objective optimization (MOO) techniques—including trained surrogate models and genetic algorithms – can be used to optimize key system design constraints. The models are trained using programmatically generated design criteria on the reduced-order thermal simulation to map diverse system behaviors. This optimization framework enables simultaneous evaluation of competing performance metrics, including system dimensions, thermal behavior, and cost considerations, while enhancing the framework's flexibility and fidelity.

Presenting Author: Dominic Lavigne University of Dayton

Presenting Author Biography: Dominic LaVigne is a mechanical engineer and clean energy innovator specializing in thermal energy storage solutions. With a B.S. in mechanical engineering and and M.S. in clean energy engineering, he is dedicated to advancing sustainable technology for grid-scale energy storage applications with both mechanical and electrical innovations.

Currently pursuing a PhD in mechanical engineering at the University of Dayton, his research focuses on developing pumped thermal energy storage and associated power cycles - a promising low-cost solution for grid-scale clean energy storage. Dominic also previously invented a novel micro-turbine (patent pending).

Dominic is a recipient of the Western New York Prosperity Fellowship, and is passionate about creating scalable, cost-effective energy storage solutions that can accelerate the global transition to renewable energy.