LDR | | 02052nmm uu200409 4500 |
001 | | 000000332214 |
005 | | 20240805170409 |
008 | | 181129s2018 |||||||||||||||||c||eng d |
020 | |
▼a 9780438283503 |
035 | |
▼a (MiAaPQ)AAI10969835 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
082 | 0 |
▼a 539.76 |
100 | 1 |
▼a Liu, Yang. |
245 | 10 |
▼a Development of a Data-Driven Analysis Framework for Boiling Problems with Multiphase-CFD Solver. |
260 | |
▼a [S.l.] :
▼b North Carolina State University.,
▼c 2018 |
260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
300 | |
▼a 153 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
500 | |
▼a Adviser: Nam Dinh. |
502 | 1 |
▼a Thesis (Ph.D.)--North Carolina State University, 2018. |
520 | |
▼a Flow boiling is a highly efficient heat transfer regime, which is used for thermal management in various engineered systems. Among the modeling tools for boiling, the Multiphase Computational Fluid Dynamics (MCFD) solver based on Eulerian-Euleri |
520 | |
▼a This dissertation presents a data-driven analysis framework to address this open issue. The framework aims to leverage state of the art statistical methods and the increasingly affluent boiling data, from both high-resolution experimental measur |
520 | |
▼a First, a boiling data processing and storage procedure is developed for high-resolution experiments and high-fidelity simulations. The extracted data are stored in a structured manner to ensure the flexibility for multipurpose usage. Second, a c |
590 | |
▼a School code: 0155. |
650 | 4 |
▼a Nuclear engineering. |
650 | 4 |
▼a Statistics. |
690 | |
▼a 0552 |
690 | |
▼a 0463 |
710 | 20 |
▼a North Carolina State University.
▼b Nuclear Engineering. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0155 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15001278
▼n KERIS |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a 관리자 |