서브메뉴
검색
Shape and Divertor Control in Tokamaks- [electronic resource]
![Shape and Divertor Control in Tokamaks - [electronic resource]](/Users/Baul/Images/book.png)
Shape and Divertor Control in Tokamaks- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214100439
- ISBN
- 9798379718497
- DDC
- 530
- 서명/저자
- Shape and Divertor Control in Tokamaks - [electronic resource]
- 발행사항
- [S.l.]: : Princeton University., 2023
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- 형태사항
- 1 online resource(241 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 84-12, Section: B.
- 주기사항
- Advisor: Kolemen, Egemen.
- 학위논문주기
- Thesis (Ph.D.)--Princeton University, 2023.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약As tokamak fusion reactors increase in size and power, robust and high performance technologies will be needed to perform tasks of magnetic control and high heat flux power exhaust. Advanced divertor strategies such as the X-divertor, snowflake, and X-point target divertor have been proposed as candidate solutions for mitigating the enormous power levels experienced in reactors. These advanced divertors are created in part through modification of the magnetic field structure to create and control additional magnetic field nulls. Additionally, the startup, shaping, and vertical control tasks of future reactors will be pushed to hardware limits as machine size and complexity increase. Control techniques that can effectively use the available hardware and optimize performance while satisfying constraints are necessary. Measurement and estimation of various parameters will be more difficult suggesting the usage of models that use inputs from multiple diagnostics or employ neural networks. This thesis explores the physics and engineering challenges of these magnetic control and estimation problems in detail for applications of shape and divertor control in tokamaks.
- 일반주제명
- Plasma physics.
- 일반주제명
- Mechanical engineering.
- 일반주제명
- Applied physics.
- 키워드
- Divertor
- 키워드
- Feedback control
- 키워드
- Neural nets
- 키워드
- Nuclear fusion
- 키워드
- Shape control
- 키워드
- Tokamaks
- 기타저자
- Princeton University Mechanical and Aerospace Engineering
- 기본자료저록
- Dissertations Abstracts International. 84-12B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008240612s2023 us |||||||||||||||c||eng d■001000016932296
■00520240214100439
■006m o d
■007cr#unu||||||||
■020 ▼a9798379718497
■035 ▼a(MiAaPQ)AAI30491141
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a530
■1001 ▼aWai, Josiah Titus.
■24510▼aShape and Divertor Control in Tokamaks▼h[electronic resource]
■260 ▼a[S.l.]:▼bPrinceton University. ▼c2023
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2023
■300 ▼a1 online resource(241 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 84-12, Section: B.
■500 ▼aAdvisor: Kolemen, Egemen.
■5021 ▼aThesis (Ph.D.)--Princeton University, 2023.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aAs tokamak fusion reactors increase in size and power, robust and high performance technologies will be needed to perform tasks of magnetic control and high heat flux power exhaust. Advanced divertor strategies such as the X-divertor, snowflake, and X-point target divertor have been proposed as candidate solutions for mitigating the enormous power levels experienced in reactors. These advanced divertors are created in part through modification of the magnetic field structure to create and control additional magnetic field nulls. Additionally, the startup, shaping, and vertical control tasks of future reactors will be pushed to hardware limits as machine size and complexity increase. Control techniques that can effectively use the available hardware and optimize performance while satisfying constraints are necessary. Measurement and estimation of various parameters will be more difficult suggesting the usage of models that use inputs from multiple diagnostics or employ neural networks. This thesis explores the physics and engineering challenges of these magnetic control and estimation problems in detail for applications of shape and divertor control in tokamaks.
■590 ▼aSchool code: 0181.
■650 4▼aPlasma physics.
■650 4▼aMechanical engineering.
■650 4▼aApplied physics.
■653 ▼aDivertor
■653 ▼aFeedback control
■653 ▼aNeural nets
■653 ▼aNuclear fusion
■653 ▼aShape control
■653 ▼aTokamaks
■690 ▼a0759
■690 ▼a0548
■690 ▼a0215
■71020▼aPrinceton University▼bMechanical and Aerospace Engineering.
■7730 ▼tDissertations Abstracts International▼g84-12B.
■773 ▼tDissertation Abstract International
■790 ▼a0181
■791 ▼aPh.D.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16932296▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
