Thermal energy storage (TES) systems based on renewable energy sources (concentrated solar, wind, and photovoltaic etc.) are crucial to reducing dependence on conventional energy generation systems and reducing renewable energy’s intermittent nature. TES can be utilized in conjunction with concentrated solar power (CSP) in particle-based power cycles where the particles can be charged (heat addition) using solar energy and then discharged (heat extraction) using particle-based heat exchangers (HX). Efficient particle based HXs are vital in coupling heat transfer fluid (HTF) from thermal receivers to power cycle working fluid (WF). Heat transfer enhancement is essential for adopting particle-based moving packed-bed heat exchangers (MPBHXs) in next-generation TES systems, as MPBHXs usually exhibit low particle bed-to-wall heat transfer coefficients and total heat transfer rate. This dissertation focuses on addressing the limitations of MPBHXs by computationally studying the heat transfer performance enhancement due to granular flows in metal foam-based MPBHXs and reactive flow-based MPBHXs. Comprehensive multidimensional, multiscale, and multiphysics models are developed to predict the TES/TCES (Thermochemical energy storage) performance accurately. First, the flow properties through metal foams are determined, followed by granular flow through metal foam-based particle-to-sCO2 HXs to predict the heat transfer enhancement. Then, granular flows with reactive and sensible heat-only particles are studied in particle-to-sCO2 HXs to predict the heat transfer enhancement, followed by the development of discrete element models (DEM) in inclined moving bed granular flows to study particle-scale heat and mass transfer. Overall, this study provides valuable insights into effective modeling of granular flows from continuum to discrete scales and improved design and operation of particle-based heat exchangers and thermochemical reactors.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-7152 |
| Date | 10 May 2024 |
| Creators | Mishra, Ashreet |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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