Heat Transfer Models of Moving Packed-Bed Particle-to-sCO2 Heat Exchangers

[+] Author and Article Information
Kevin Albrecht

Concentrating Solar Technologies Department, Sandia National Laboratories, 3212 Black Hills Dr. NE, Albuquerque, NM 87111

Clifford K. Ho

Concentrating Solar Technologies Department, Sandia National Laboratories, 6324 Elk Horn Dr. NE, Albuquerque, NM 87111

1Corresponding author.

ASME doi:10.1115/1.4041546 History: Received July 20, 2017; Revised September 17, 2018


Particle-based concentrating solar power (CSP) plants have been proposed to increase operating temperature for integration with higher efficiency power cycles using supercritical carbon dioxide (sCO2). The majority of research to date has focused on the development of high-efficiency and high-temperature particle solar thermal receivers. However, system realization will require the design of a particle/sCO2 heat exchanger as well for delivering thermal energy to the power-cycle working fluid. Recent work has identified moving packed-bed heat exchangers as low-cost alternatives to fluidized-bed heat exchangers, which require additional pumps to fluidize the particles and recuperators to capture the lost heat. However, the reduced heat transfer between the particles and the walls of moving packed-bed heat exchangers, compared to fluidized beds, causes concern with adequately sizing components to meet the thermal duty. Models of moving packed-bed heat exchangers are not currently capable of exploring the design trade-offs in particle size, operating temperature, and residence time. The present work provides a predictive numerical model based on literature correlations capable of designing moving packed-bed heat exchangers as well as investigating the effects of particle size, operating temperature, and particle velocity (residence time). Furthermore, the development of a reliable design tool for moving packed-bed heat exchangers must be validated by predicting experimental results in the operating regime of interest. An experimental system is designed to provide the data necessary for model validation and/or to identify where deficiencies or new constitutive relations are needed.

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