서브메뉴
검색
Enhancing Multidisciplinary Design Optimization Through Automated Computational Model Construction and Sensitivity Analysis- [electronic resource]
Enhancing Multidisciplinary Design Optimization Through Automated Computational Model Construction and Sensitivity Analysis- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214101522
- ISBN
- 9798380362368
- DDC
- 629.1
- 서명/저자
- Enhancing Multidisciplinary Design Optimization Through Automated Computational Model Construction and Sensitivity Analysis - [electronic resource]
- 발행사항
- [S.l.]: : University of California, San Diego., 2023
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- 형태사항
- 1 online resource(130 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-03, Section: B.
- 주기사항
- Advisor: Hwang, John T.
- 학위논문주기
- Thesis (Ph.D.)--University of California, San Diego, 2023.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약Multidisciplinary design optimization (MDO) is an approach that uses optimization methods to design complex engineering systems involving multiple disciplines simultaneously. The coupled nature of multidisciplinary systems and the large number of design variables involved in complex systems present unique challenges to solving MDO problems. One of these challenges is the implementation of software necessary to evaluate multidisciplinary models within an optimization framework. When gradient-based optimization approaches are used, efficient and accurate derivatives must be computed for each model evaluation. This dissertation presents an approach that significantly reduces the manual effort required to implement computational models for use within a gradient-based MDO framework, especially in large-scale problems. This dissertation introduces a novel approach to address these challenges and automate the process, enabling accurate and efficient adjoint-based sensitivity analysis for gradient-based MDO in particular. To address these challenges, a three-stage compiler methodology is proposed. The methodology centers around a graph representation that provides a foundation for automating sensitivity analysis in MDO. In addition, the Computational System Design Language (CSDL) is introduced, which allows for a concise description of the physical system. The adoption of CSDL demonstrates a twofold reduction in code complexity for engineering models, significantly reducing the barrier to entry for MDO practitioners. The three-stage compiler also provides users of CSDL with the ability to measure the effect of the model structure on run-time performance and memory complexity using the graph representation. Finally, the methodology developed in this dissertation is applied to the design of a space-based virtual telescope comprised of two spacecraft flying in formation. A reformulation of the orbit dynamics of the spacecraft is found to avoid the introduction of truncation errors due to tight formation constraints that render solving the optimization problem impossible. A sequential approach to applying MDO to the design of a space-based virtual telescope is also found to be more robust than solving the MDO problem where all disciplines are considered simultaneously.
- 일반주제명
- Aerospace engineering.
- 일반주제명
- Mechanical engineering.
- 기타저자
- University of California, San Diego Mechanical and Aerospace Engineering
- 기본자료저록
- Dissertations Abstracts International. 85-03B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008240612s2023 us |||||||||||||||c||eng d■001000016934047
■00520240214101522
■006m o d
■007cr#unu||||||||
■020 ▼a9798380362368
■035 ▼a(MiAaPQ)AAI30570208
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a629.1
■1001 ▼aGandarillas, Victor.
■24510▼aEnhancing Multidisciplinary Design Optimization Through Automated Computational Model Construction and Sensitivity Analysis▼h[electronic resource]
■260 ▼a[S.l.]:▼bUniversity of California, San Diego. ▼c2023
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2023
■300 ▼a1 online resource(130 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-03, Section: B.
■500 ▼aAdvisor: Hwang, John T.
■5021 ▼aThesis (Ph.D.)--University of California, San Diego, 2023.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aMultidisciplinary design optimization (MDO) is an approach that uses optimization methods to design complex engineering systems involving multiple disciplines simultaneously. The coupled nature of multidisciplinary systems and the large number of design variables involved in complex systems present unique challenges to solving MDO problems. One of these challenges is the implementation of software necessary to evaluate multidisciplinary models within an optimization framework. When gradient-based optimization approaches are used, efficient and accurate derivatives must be computed for each model evaluation. This dissertation presents an approach that significantly reduces the manual effort required to implement computational models for use within a gradient-based MDO framework, especially in large-scale problems. This dissertation introduces a novel approach to address these challenges and automate the process, enabling accurate and efficient adjoint-based sensitivity analysis for gradient-based MDO in particular. To address these challenges, a three-stage compiler methodology is proposed. The methodology centers around a graph representation that provides a foundation for automating sensitivity analysis in MDO. In addition, the Computational System Design Language (CSDL) is introduced, which allows for a concise description of the physical system. The adoption of CSDL demonstrates a twofold reduction in code complexity for engineering models, significantly reducing the barrier to entry for MDO practitioners. The three-stage compiler also provides users of CSDL with the ability to measure the effect of the model structure on run-time performance and memory complexity using the graph representation. Finally, the methodology developed in this dissertation is applied to the design of a space-based virtual telescope comprised of two spacecraft flying in formation. A reformulation of the orbit dynamics of the spacecraft is found to avoid the introduction of truncation errors due to tight formation constraints that render solving the optimization problem impossible. A sequential approach to applying MDO to the design of a space-based virtual telescope is also found to be more robust than solving the MDO problem where all disciplines are considered simultaneously.
■590 ▼aSchool code: 0033.
■650 4▼aAerospace engineering.
■650 4▼aMechanical engineering.
■653 ▼aMultidisciplinary design optimization
■653 ▼aOptimization methods
■653 ▼aMultidisciplinary systems
■653 ▼aComputational models
■690 ▼a0538
■690 ▼a0548
■71020▼aUniversity of California, San Diego▼bMechanical and Aerospace Engineering.
■7730 ▼tDissertations Abstracts International▼g85-03B.
■773 ▼tDissertation Abstract International
■790 ▼a0033
■791 ▼aPh.D.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16934047▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
