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Development of a Novel Multiscale Fatigue Model for Laminated Composites
Development of a Novel Multiscale Fatigue Model for Laminated Composites
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211153017
- ISBN
- 9798384045915
- DDC
- 629.1
- 서명/저자
- Development of a Novel Multiscale Fatigue Model for Laminated Composites
- 발행사항
- [Sl] : University of Michigan, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 280 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
- 주기사항
- Advisor: Waas, Anthony.
- 학위논문주기
- Thesis (Ph.D.)--University of Michigan, 2024.
- 초록/해제
- 요약Fatigue in laminated composite structures can be caused by cyclic loading below the pristine static limit. It is detrimental to the structural performance and can lead to early catastrophic failure. Fatigue damage primarily manifests as intraply micro and macrocracks as well as interface delaminations, but can also manifest as fiber failure. These damage modes develop over multiple spatial and temporal scales, which make it challenging to model accurately and efficiently. State of the art models either fail at capturing important physics of the problem and therefore lack accuracy, or fail at being computationally efficient and therefore are impractical for use in engineering applications. In this research, a model that offers the ability to capture the important damage modes that develop during fatigue loading at different scales in a computationally efficient way is proposed, based on experimental observations at multiple length scales. Diffused microscale cracking is captured using a multiscale analytical method, while macroscale matrix cracking, delamination, and fiber failure are captured using a combination of a fiber-aligned meshing approach and cohesive zone models. Temporal multiscale aspects of the problem are captured using a cycle jumping approach. Computational performance of the model was boosted through the use of data science and machine learning. To develop the model, the problem of a single-edge notched cross-ply [90/0/90] specimen subjected to tensile quasi-static loading and fatigue loading was analyzed based on experimental results. The model was based on a series of high resolution experimental data. This data included synchrotron computed tomography in-situ scans that were used in a digital volume correlation analysis at the microscale, as well as digital image correlation and thermography images collected during fatigue tests at the macroscale. Model predictions demonstrated good agreement with experimental data regarding damage initiation mechanisms, damage progression under quasi-static loading, and damage initiation and progression under fatigue loading. It was concluded that the proposed modeling approach is capable of efficiently capturing fatigue damage growth in laminated composites with sufficient accuracy and therefore it is suitable for engineering applications. Future suggested work includes the validation of the model for additional laminate stacking sequences and loading scenarios.
- 일반주제명
- Aerospace engineering
- 일반주제명
- Computer engineering
- 일반주제명
- Materials science
- 일반주제명
- Mechanical engineering
- 키워드
- Fatigue
- 키워드
- Thermography
- 키워드
- Machine learning
- 기타저자
- University of Michigan Aerospace Engineering
- 기본자료저록
- Dissertations Abstracts International. 86-03B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520250211153017
■006m o d
■007cr#unu||||||||
■020 ▼a9798384045915
■035 ▼a(MiAaPQ)AAI31631538
■035 ▼a(MiAaPQ)umichrackham005694
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a629.1
■1001 ▼aRojas Sanchez, Jose Fernando.
■24510▼aDevelopment of a Novel Multiscale Fatigue Model for Laminated Composites
■260 ▼a[Sl]▼bUniversity of Michigan▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a280 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-03, Section: B.
■500 ▼aAdvisor: Waas, Anthony.
■5021 ▼aThesis (Ph.D.)--University of Michigan, 2024.
■520 ▼aFatigue in laminated composite structures can be caused by cyclic loading below the pristine static limit. It is detrimental to the structural performance and can lead to early catastrophic failure. Fatigue damage primarily manifests as intraply micro and macrocracks as well as interface delaminations, but can also manifest as fiber failure. These damage modes develop over multiple spatial and temporal scales, which make it challenging to model accurately and efficiently. State of the art models either fail at capturing important physics of the problem and therefore lack accuracy, or fail at being computationally efficient and therefore are impractical for use in engineering applications. In this research, a model that offers the ability to capture the important damage modes that develop during fatigue loading at different scales in a computationally efficient way is proposed, based on experimental observations at multiple length scales. Diffused microscale cracking is captured using a multiscale analytical method, while macroscale matrix cracking, delamination, and fiber failure are captured using a combination of a fiber-aligned meshing approach and cohesive zone models. Temporal multiscale aspects of the problem are captured using a cycle jumping approach. Computational performance of the model was boosted through the use of data science and machine learning. To develop the model, the problem of a single-edge notched cross-ply [90/0/90] specimen subjected to tensile quasi-static loading and fatigue loading was analyzed based on experimental results. The model was based on a series of high resolution experimental data. This data included synchrotron computed tomography in-situ scans that were used in a digital volume correlation analysis at the microscale, as well as digital image correlation and thermography images collected during fatigue tests at the macroscale. Model predictions demonstrated good agreement with experimental data regarding damage initiation mechanisms, damage progression under quasi-static loading, and damage initiation and progression under fatigue loading. It was concluded that the proposed modeling approach is capable of efficiently capturing fatigue damage growth in laminated composites with sufficient accuracy and therefore it is suitable for engineering applications. Future suggested work includes the validation of the model for additional laminate stacking sequences and loading scenarios.
■590 ▼aSchool code: 0127.
■650 4▼aAerospace engineering
■650 4▼aComputer engineering
■650 4▼aMaterials science
■650 4▼aMechanical engineering
■653 ▼aComposite structures
■653 ▼aFatigue
■653 ▼aProgressive failure modeling
■653 ▼aComputed tomography
■653 ▼aThermography
■653 ▼aMachine learning
■690 ▼a0538
■690 ▼a0464
■690 ▼a0794
■690 ▼a0800
■690 ▼a0548
■71020▼aUniversity of Michigan▼bAerospace Engineering.
■7730 ▼tDissertations Abstracts International▼g86-03B.
■790 ▼a0127
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17164562▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
