ISSN オンライン: 2688-7231
ISBN 印刷: 978-1-56700-497-7 (Flash Drive)
ISBN オンライン: 978-1-56700-496-0
Proceedings of the 25th National and 3rd International ISHMT-ASTFE Heat and Mass Transfer Conference (IHMTC-2019)
Novel Modelling Approach and Stack Optimization for Recuperator in s-CO2 Brayton Cycle
Supercritical Carbon dioxide (s-CO2) Brayton cycle-based power plants are being extensively explored as a viable alternative to traditional Rankine based steam power plants. Higher temperatures at the turbine exit in a s-CO2 cycle provide a significant opportunity for heat recuperation, thus improving overall cycle efficiency. Compact Printed Circuit Heat Exchangers (PCHE's) are preferred in s-CO2 power plants. PCHE's are not only compact but offer higher heat transfer rates with smaller holdup mass of working fluid and hence, are ideally suited for high-pressure applications. The present paper describes a hybrid approach combining the advantages of traditional design using LMTD and modern CFD tools to design a PCHE for the s-CO2 application. Traditional design is facilitated by use of a Thermal Resistance Network (TRN) model, a quick tool which helps in providing the overall dimensions of the PCHE for a given heat load and pressure drop. This model represents the electrical analogy of heat transfer processes involved between hot and cold fluid streams of the heat exchanger. The TRN model accounts for the thermophysical property variations of CO2 along the length of the channel. This is achieved by discretizing the heat exchange domain of hot and cold streams into small resistances which effectively account for variations in properties, pressure drop, and local heat transfer coefficients. The effect of modelling higher number of rows (higher number of channels) on the performance of PCHE is investigated. Subsequently, the overall size is optimized for a given heat load and pressure drop. TRN model is coupled with a high fidelity CFD model which accounts for the exact cross-section and channel pattern which provide an accurate estimation of the local heat transfer coefficient and pressure drops.