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Development of a Regional Wind Risk Assessment Framework for Wood-Frame Single-Family Residential Building Stock- [electronic resource]
Development of a Regional Wind Risk Assessment Framework for Wood-Frame Single-Family Residential Building Stock- [electronic resource]
상세정보
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214101211
- ISBN
- 9798379648213
- DDC
- 624
- 저자명
- Meng, Shuochuan.
- 서명/저자
- Development of a Regional Wind Risk Assessment Framework for Wood-Frame Single-Family Residential Building Stock - [electronic resource]
- 발행사항
- [S.l.]: : University of California, Los Angeles., 2023
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2023
- 형태사항
- 1 online resource(197 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 84-12, Section: B.
- 주기사항
- Advisor: Taciroglu, Ertugrul.
- 학위논문주기
- Thesis (Ph.D.)--University of California, Los Angeles, 2023.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약Over the past few decades, residential buildings along the coastal areas of the United States have suffered enormous structural damage and economic losses due to hurricane strikes. The significant variations in the building characteristics of residential buildings lead to distinctive building-level vulnerabilities under extreme winds. Therefore, an accurate representation of the building inventory is critical for quantifying regional hurricane risk. In this dissertation, a regional wind risk assessment framework is developed to evaluate hurricane-induced structural damage and economic losses for residential communities. Unlike existing loss models that represent the building stock by archetype models with limited variations in building characteristics, the proposed framework applies site-specific risk assessments on every house in the region of interest based on parcel-based building inventories. A sensitivity analysis is conducted to investigate the effects of different building features on building vulnerability to identify the most critical features and explore the means of simplifying the building modeling process. To apply site-specific damage assessments at regional level, an automatic building modeling workflow is integrated into the framework, which is supported by property-specific characteristics extracted through machine learning-aided data collection approaches. The framework is applied to residential communities in New Hanover County, North Carolina. Through site-specific risk assessments on 1,746 realistic building models, the overall variance in building-level damage and loss results among single-family houses is evaluated. The damage results reveal significant differences in wind vulnerability due to variations in architectural features. Furthermore, a comparative study shows that the aggregated regional loss calculated based on refined building models is substantially higher than that derived from building archetypes used in existing regional loss models. The building inventory generation and building modeling modules integrated into the framework largely reduce the inherent uncertainties of hurricane risk prediction. The high-resolution damage and loss results produced by the framework offer insights into local risk conditions, which facilitate the improvement of hazard risk mitigation and post-disaster management strategies.
- 일반주제명
- Civil engineering.
- 일반주제명
- Remote sensing.
- 키워드
- Data imputation
- 키워드
- Deep learning
- 키워드
- Hurricanes
- 키워드
- Machine learning
- 키워드
- Risk management
- 키워드
- Wood structures
- 기타저자
- University of California, Los Angeles Civil and Environmental Engineering 0300
- 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■001000016933164
■00520240214101211
■006m o d
■007cr#unu||||||||
■020 ▼a9798379648213
■035 ▼a(MiAaPQ)AAI30525539
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a624
■1001 ▼aMeng, Shuochuan.
■24510▼aDevelopment of a Regional Wind Risk Assessment Framework for Wood-Frame Single-Family Residential Building Stock▼h[electronic resource]
■260 ▼a[S.l.]:▼bUniversity of California, Los Angeles. ▼c2023
■260 1▼aAnn Arbor :▼bProQuest Dissertations & Theses, ▼c2023
■300 ▼a1 online resource(197 p.)
■500 ▼aSource: Dissertations Abstracts International, Volume: 84-12, Section: B.
■500 ▼aAdvisor: Taciroglu, Ertugrul.
■5021 ▼aThesis (Ph.D.)--University of California, Los Angeles, 2023.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aOver the past few decades, residential buildings along the coastal areas of the United States have suffered enormous structural damage and economic losses due to hurricane strikes. The significant variations in the building characteristics of residential buildings lead to distinctive building-level vulnerabilities under extreme winds. Therefore, an accurate representation of the building inventory is critical for quantifying regional hurricane risk. In this dissertation, a regional wind risk assessment framework is developed to evaluate hurricane-induced structural damage and economic losses for residential communities. Unlike existing loss models that represent the building stock by archetype models with limited variations in building characteristics, the proposed framework applies site-specific risk assessments on every house in the region of interest based on parcel-based building inventories. A sensitivity analysis is conducted to investigate the effects of different building features on building vulnerability to identify the most critical features and explore the means of simplifying the building modeling process. To apply site-specific damage assessments at regional level, an automatic building modeling workflow is integrated into the framework, which is supported by property-specific characteristics extracted through machine learning-aided data collection approaches. The framework is applied to residential communities in New Hanover County, North Carolina. Through site-specific risk assessments on 1,746 realistic building models, the overall variance in building-level damage and loss results among single-family houses is evaluated. The damage results reveal significant differences in wind vulnerability due to variations in architectural features. Furthermore, a comparative study shows that the aggregated regional loss calculated based on refined building models is substantially higher than that derived from building archetypes used in existing regional loss models. The building inventory generation and building modeling modules integrated into the framework largely reduce the inherent uncertainties of hurricane risk prediction. The high-resolution damage and loss results produced by the framework offer insights into local risk conditions, which facilitate the improvement of hazard risk mitigation and post-disaster management strategies.
■590 ▼aSchool code: 0031.
■650 4▼aCivil engineering.
■650 4▼aRemote sensing.
■650 4▼aArchitectural engineering.
■653 ▼aData imputation
■653 ▼aDeep learning
■653 ▼aHurricanes
■653 ▼aMachine learning
■653 ▼aRisk management
■653 ▼aWood structures
■690 ▼a0543
■690 ▼a0799
■690 ▼a0462
■71020▼aUniversity of California, Los Angeles▼bCivil and Environmental Engineering 0300.
■7730 ▼tDissertations Abstracts International▼g84-12B.
■773 ▼tDissertation Abstract International
■790 ▼a0031
■791 ▼aPh.D.
■792 ▼a2023
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16933164▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202402▼f2024
