Modeling radiation transport in turbulent particle-laden media
Abstract/Contents
- Abstract
- Particle-based solar receivers are a promising device for efficient renewable energy systems. In these systems, an array of mirrors focuses sunlight onto a falling curtain of particles that absorbs the light. The heated particles are stored for later energy extraction. In this work I consider a design concept in which the particles and air are in a co-flowing configuration; as the particles are heated they conduct the energy to the surrounding air, which may be used directly in a power plant. The formulation of the governing equations to encompass the full physics of the problem will be presented. The impact of turbulence on the opacity of the particle cloud is analyzed. Using results from direct numerical simulations of particle-laden turbulence and ray tracing, this work will demonstrate that turbulence can substantially decrease the opacity of a particle cloud. The homogenization of the particles to a concentration field recovers an acceptable representation of radiation transport with the caveat that over-refining the grid can lead to numerical artifacts. The particle homogenization technique is then applied to a novel simulation of a particle-laden turbulent duct flow exposed to high intensity radiation to parallel ongoing experiments of a lab-scale solar receiver. These simulations provide design guidelines by examining the thermal efficiency and flow physics in particle-based solar receivers. The choice of radiation model to capture the heat transfer in the simulations can have a substantial impact on the computed temperature profiles. Initial comparisons between the computations and experiments at higher Reynolds number are also discussed. Finally, the application of the multi-fidelity Monte Carlo method for uncertainty quantification to radiation transport will be shown, along with a method for evaluating effective variance reduction techniques and its use for treating the uncertainty in the particle radiative properties.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2017 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Frankel, Ari |
|---|---|
| Associated with | Stanford University, Department of Mechanical Engineering. |
| Primary advisor | Iaccarino, Gianluca |
| Primary advisor | Mani, Ali, (Professor of mechanical engineering) |
| Thesis advisor | Iaccarino, Gianluca |
| Thesis advisor | Mani, Ali, (Professor of mechanical engineering) |
| Thesis advisor | Eaton, John K |
| Advisor | Eaton, John K |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Ari Frankel. |
|---|---|
| Note | Submitted to the Department of Mechanical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2017. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2017 by Ari Louis Frankel
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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