High-fidelity simulations and modeling of compressible reacting flows
- Scramjets are air-breathing propulsion devices and have long been recognized as suitable for hypersonic propulsion. Because of the high speed in scramjet combustors, the flow has a very short residence time before leaving the engine, during which air and fuel must mix on a molecular level and chemical reactions have to be completed. Although some ground and flight experiments have successfully demonstrated the feasibility of supersonic combustion, experimental testing requires a large investment and presents numerous difficulties. Computational tools are thus a key element toward the development of an efficient, high-performance scramjet engine, and because mixing and heat release are at the heart of a scramjet operation, the development and use of accurate combustion models for supersonic combustion are critical. The open questions in supersonic combustion span the spectrum from scientific pursuit, e.g., shock/flame interactions, to engineering applications like prediction of unstart phenomena in scramjets. In this study, direct numerical simulations (DNS) of a compressible reacting mixing layer with finite rate chemistry are performed. The DNS databases are used to explore the physics of supersonic combustion. An efficient combustion model based on the flamelet/progress variable is then introduced. In this approach, only two or three additional scalar transport equations need to be solved, independently of the complexity of the reaction mechanism. The proposed combustion model is validated using DNS databases. Finally, the compressible flamelet/progress variable model is applied to the case of an under-expanded hydrogen jet in a supersonic cross-flow and HIFiRE scramjet.
|Type of resource
|electronic; electronic resource; remote
|1 online resource.
|Stanford University, Department of Mechanical Engineering.
|Statement of responsibility
|Submitted to the Department of Mechanical Engineering.
|Thesis (Ph.D.)--Stanford University, 2014.
- © 2014 by Amirreza Saghafian
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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