MARC보기
LDR02619nmm uu200457 4500
001000000332194
00520240805170226
008181129s2018 |||||||||||||||||c||eng d
020 ▼a 9780438282834
035 ▼a (MiAaPQ)AAI10969768
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 539.76
1001 ▼a Chang, Chih-Wei.
24510 ▼a Data-Driven Modeling of Nuclear System Thermal-Hydraulics.
260 ▼a [S.l.] : ▼b North Carolina State University., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 184 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Adviser: Nam T. Dinh.
5021 ▼a Thesis (Ph.D.)--North Carolina State University, 2018.
520 ▼a The goal of this work is to develop a methodology to enhance predictive power of datadriven nuclear system thermal-hydraulics (NSTH) simulation using machine learning. NSTH simulation is instrumental for reactor design, safety analysis, and oper
520 ▼a The technical approach of the dissertation consists of three components. First, the technical background overview navigates the essential knowledge from related disciplines, including thermal-hydraulics models, system simulation, and machine lea
520 ▼a Five machine learning frameworks for NSTH have been introduced in the dissertation including physics-separated ML (PSML or Type I ML), physics-evaluated ML (PEML or Type II ML), physics-integrated ML (PIML or Type III ML), physics-recovered (PRM
520 ▼a Various numerical experiments are formulated ranging from system-level simulation to computational fluid dynamics (CFD) to exhibit the advantage of deep learning (DL) for model development. The case studies of system-level simulation using Type
520 ▼a The CFD case study exhibits that the DL-based Reynolds stress model can assimilate millions of data points to reduce forecast error. Performance of the DL-based stress can be quantified by flow features coverage mapping. The results show that Re
590 ▼a School code: 0155.
650 4 ▼a Nuclear engineering.
650 4 ▼a Mechanical engineering.
650 4 ▼a Aerospace engineering.
690 ▼a 0552
690 ▼a 0548
690 ▼a 0538
71020 ▼a North Carolina State University. ▼b Nuclear Engineering.
7730 ▼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
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15001259 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자