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Accelerating the Simulation of Chemically Reacting Turbulent Flows via Machine Learning Techniques
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Accelerating the Simulation of Chemically Reacting Turbulent Flows via Machine Learning Techniques. |
| 개인저자 | Owoyele, Opeoluwa. |
| 단체저자명 | North Carolina State University. Mechanical Engineering. |
| 발행사항 | [S.l.]: North Carolina State University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 223 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
| ISBN | 9780438283886 |
| 학위논문주기 | Thesis (Ph.D.)--North Carolina State University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Tarek Echekki. |
| 요약 | Turbulent reacting flows constitute one of the most complex classes of engineering problems because they combine the chaotic process of turbulence with stiff, highly nonlinear chemical kinetics. The presence of a large number of species -- leadi |
| 일반주제명 | Mechanical engineering. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
