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Computational Geometry for Design Optimization
Computational Geometry for Design Optimization
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202103649
- ISBN
- 9798314875551
- DDC
- 629.1
- 서명/저자
- Computational Geometry for Design Optimization
- 발행사항
- [Sl] : University of Michigan, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 177 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-11, Section: B.
- 주기사항
- Advisor: Martins, Joaquim R. R. A.
- 학위논문주기
- Thesis (Ph.D.)--University of Michigan, 2025.
- 초록/해제
- 요약As the aviation industry faces emissions requirements and expands into new markets, aircraft design is tasked with meeting the technical challenges that arise. Numerous solutions are being explored to address aviation's impact and advance aircraft design, from new airframes to new energy sources. These options pose significant changes to aircraft designs and their subsystems, requiring the creation and integration of new technologies.The lack of historical data and designer intuition behind these new designs and technologies will make computational models and optimization increasingly important, especially high-fidelity, gradient-based optimization. Design optimization is already a valuable tool for aircraft design, but geometry continues to be a bottleneck for more complex designs. To address this, this work focuses on gaps in knowledge of geometric parameterization and constraints and methods for intersection handling.The choice of geometric parameterization is important to an optimization because it determines how the design changes and how the final result can be used. Typical parameterization methods are not always intuitive for designers and might not fit well with the rest of the design process. A new CAD-based parameterization is compared with an established method, free-form deformation, to evaluate its potential to address these issues. This new parameterization is found to be sufficient for aerodynamic shape optimization, performing as well as the established method and producing a usable model as the final design.Spatial integration is a core problem in aircraft design but complicated to include in optimization due to the lack of constraints to capture geometry of internal components. One such constraint is used here to explore the effects of spatial integration in optimization of a full aircraft configuration. This investigation explores the benefits of combining spatial integration and aerodynamic shape optimization. Optimizations with more freedom in the spatial integration are found to result in performance improvements at a range of system requirements.Intersections are everywhere in aircraft but often overlooked in optimization due to the difficulty in keeping topologies consistent as the geometry changes. Designing these intersection areas has added importance, such as aerodynamic design where careful shaping is necessary to avoid additional drag. Two methods for updating a mesh that treats intersections in a smooth and topologically consistent way are presented here. The first focuses on the aerodynamics of a fillet between two components and is demonstrated on an optimization of a fuselage-fillet-wing system. This optimization shows a drag reduction from optimizing with the intersection method versus constraining the intersection to optimize without. The second is a general method for optimizing designs with large numbers of intersections and is shown on a structural optimization with moving panels. This optimization demonstrates a greater mass reduction when the optimization uses this method than with the conventional optimization. Both of these sets of optimizations show that treating intersections in designs adds design freedom that enables optimizations to find better designs.
- 일반주제명
- Aerospace engineering
- 일반주제명
- Applied physics
- 일반주제명
- Engineering
- 일반주제명
- Aeronomy
- 키워드
- Aircraft design
- 기타저자
- University of Michigan Aerospace Engineering
- 기본자료저록
- Dissertations Abstracts International. 86-11B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■006m o d
■007cr#unu||||||||
■020 ▼a9798314875551
■035 ▼a(MiAaPQ)AAI32092665
■035 ▼a(MiAaPQ)umichrackham006049
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a629.1
■1001 ▼aHajdik, Hannah M.
■24510▼aComputational Geometry for Design Optimization
■260 ▼a[Sl]▼bUniversity of Michigan▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a177 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-11, Section: B.
■500 ▼aAdvisor: Martins, Joaquim R. R. A.
■5021 ▼aThesis (Ph.D.)--University of Michigan, 2025.
■520 ▼aAs the aviation industry faces emissions requirements and expands into new markets, aircraft design is tasked with meeting the technical challenges that arise. Numerous solutions are being explored to address aviation's impact and advance aircraft design, from new airframes to new energy sources. These options pose significant changes to aircraft designs and their subsystems, requiring the creation and integration of new technologies.The lack of historical data and designer intuition behind these new designs and technologies will make computational models and optimization increasingly important, especially high-fidelity, gradient-based optimization. Design optimization is already a valuable tool for aircraft design, but geometry continues to be a bottleneck for more complex designs. To address this, this work focuses on gaps in knowledge of geometric parameterization and constraints and methods for intersection handling.The choice of geometric parameterization is important to an optimization because it determines how the design changes and how the final result can be used. Typical parameterization methods are not always intuitive for designers and might not fit well with the rest of the design process. A new CAD-based parameterization is compared with an established method, free-form deformation, to evaluate its potential to address these issues. This new parameterization is found to be sufficient for aerodynamic shape optimization, performing as well as the established method and producing a usable model as the final design.Spatial integration is a core problem in aircraft design but complicated to include in optimization due to the lack of constraints to capture geometry of internal components. One such constraint is used here to explore the effects of spatial integration in optimization of a full aircraft configuration. This investigation explores the benefits of combining spatial integration and aerodynamic shape optimization. Optimizations with more freedom in the spatial integration are found to result in performance improvements at a range of system requirements.Intersections are everywhere in aircraft but often overlooked in optimization due to the difficulty in keeping topologies consistent as the geometry changes. Designing these intersection areas has added importance, such as aerodynamic design where careful shaping is necessary to avoid additional drag. Two methods for updating a mesh that treats intersections in a smooth and topologically consistent way are presented here. The first focuses on the aerodynamics of a fillet between two components and is demonstrated on an optimization of a fuselage-fillet-wing system. This optimization shows a drag reduction from optimizing with the intersection method versus constraining the intersection to optimize without. The second is a general method for optimizing designs with large numbers of intersections and is shown on a structural optimization with moving panels. This optimization demonstrates a greater mass reduction when the optimization uses this method than with the conventional optimization. Both of these sets of optimizations show that treating intersections in designs adds design freedom that enables optimizations to find better designs.
■590 ▼aSchool code: 0127.
■650 4▼aAerospace engineering
■650 4▼aApplied physics
■650 4▼aEngineering
■650 4▼aAeronomy
■653 ▼aDesign optimization
■653 ▼aAircraft design
■653 ▼aGradient-based optimization
■653 ▼aAerodynamic shape optimization
■653 ▼aStructural optimization
■653 ▼aComputational geometry
■690 ▼a0538
■690 ▼a0367
■690 ▼a0537
■690 ▼a0215
■71020▼aUniversity of Michigan▼bAerospace Engineering.
■7730 ▼tDissertations Abstracts International▼g86-11B.
■790 ▼a0127
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17358136▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
