서브메뉴
검색
Probabilistic Life Cycle Assessment as an Approach to Achieving Sustainable Building Design Benchmarks: Insights From Case Studies
Probabilistic Life Cycle Assessment as an Approach to Achieving Sustainable Building Design Benchmarks: Insights From Case Studies
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202104734
- ISBN
- 9798290649221
- DDC
- 378.1
- 서명/저자
- Probabilistic Life Cycle Assessment as an Approach to Achieving Sustainable Building Design Benchmarks: Insights From Case Studies
- 발행사항
- [Sl] : Stanford University, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 211 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-01, Section: A.
- 주기사항
- Advisor: Lepech, Michael.
- 학위논문주기
- Thesis (Ph.D.)--Stanford University, 2025.
- 초록/해제
- 요약This dissertation investigates the value proposition of probabilistic Life Cycle Assessment (pLCA) as a building design tool. While sustainable building design typically relies on deterministic approaches that fail to account for inherent uncertainties, this research develops and applies a detailed methodological framework for quantifying both the magnitude and uncertainty of environmental impacts across different construction methods and lifecycle stages. Through case studies across the spectrum of industrialized construction, this research demonstrates the value of additional insights enabled by bringing risk-based thinking to the sustainable building design arena.The research addresses three key questions: (1) How does the degree of industrialization influence the distribution of total building lifecycle impacts? (2) How do different levels of industrialization affect impacts across lifecycle stages? (3) How does incorporating uncertainty impact designers' ability to meet Sustainable Target Value (STV) targets? A novel methodological framework combines the Pedigree Matrix approach for uncertainty characterization with SIPmath Monte Carlo simulation, which is applied to multiple case studies of buildings with varying levels of industrialization. Each case study incorporates either a baseline for comparison or a STV target.Results from the analyzed case studies suggest shifts in the predictability of environmental performance can accompany selection of a specific industrialized construction approach. These case study results suggest that more established IC approaches may allow greater predictability, while novel IC approaches may demonstrate less predictability. Higher industrialization levels also appear to redistribute impacts across lifecycle stages, with the product stage potentially becoming more significant. The research indicates that industrialized construction buildings may benefit from reduced on-site activities and end-of-life impacts, while a small increase in transportation impacts was observed.Analysis of the case study data illustrates that deterministic methods can overstate designers' confidence in meeting sustainability targets. When uncertainty is incorporated into STV design, the probability of successfully meeting a target rarely reaches 100%, even for targets initially assessed as "met" by a significant margin in a deterministic analysis. This suggests the need for benchmarks that specify a level of confidence that the target will be met.This research contributes methodological advancements in uncertainty quantification for building LCA, practical tools for probabilistic sustainability assessment, and evidence-based insights into the potential environmental benefits of the specific industrialized construction approaches explored. By transforming sustainability assessment from deterministic pass/fail criteria to probability-based success rates, the framework enables more honest, risk-aware approaches to sustainable building design.
- 일반주제명
- Study abroad
- 일반주제명
- Construction
- 일반주제명
- Design thinking
- 일반주제명
- Environmental impact
- 일반주제명
- Student organizations
- 일반주제명
- Carbon
- 일반주제명
- Sustainability
- 기타저자
- Stanford University.
- 기본자료저록
- Dissertations Abstracts International. 87-01A.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008260126s2025 us c eng d■001000017358669
■00520260202104734
■006m o d
■007cr#unu||||||||
■020 ▼a9798290649221
■035 ▼a(MiAaPQ)AAI32149634
■035 ▼a(MiAaPQ)Stanfordct632jc7628
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a378.1
■1001 ▼aHegarty, Teresa Charlyn.
■24510▼aProbabilistic Life Cycle Assessment as an Approach to Achieving Sustainable Building Design Benchmarks: Insights From Case Studies
■260 ▼a[Sl]▼bStanford University▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a211 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-01, Section: A.
■500 ▼aAdvisor: Lepech, Michael.
■5021 ▼aThesis (Ph.D.)--Stanford University, 2025.
■520 ▼aThis dissertation investigates the value proposition of probabilistic Life Cycle Assessment (pLCA) as a building design tool. While sustainable building design typically relies on deterministic approaches that fail to account for inherent uncertainties, this research develops and applies a detailed methodological framework for quantifying both the magnitude and uncertainty of environmental impacts across different construction methods and lifecycle stages. Through case studies across the spectrum of industrialized construction, this research demonstrates the value of additional insights enabled by bringing risk-based thinking to the sustainable building design arena.The research addresses three key questions: (1) How does the degree of industrialization influence the distribution of total building lifecycle impacts? (2) How do different levels of industrialization affect impacts across lifecycle stages? (3) How does incorporating uncertainty impact designers' ability to meet Sustainable Target Value (STV) targets? A novel methodological framework combines the Pedigree Matrix approach for uncertainty characterization with SIPmath Monte Carlo simulation, which is applied to multiple case studies of buildings with varying levels of industrialization. Each case study incorporates either a baseline for comparison or a STV target.Results from the analyzed case studies suggest shifts in the predictability of environmental performance can accompany selection of a specific industrialized construction approach. These case study results suggest that more established IC approaches may allow greater predictability, while novel IC approaches may demonstrate less predictability. Higher industrialization levels also appear to redistribute impacts across lifecycle stages, with the product stage potentially becoming more significant. The research indicates that industrialized construction buildings may benefit from reduced on-site activities and end-of-life impacts, while a small increase in transportation impacts was observed.Analysis of the case study data illustrates that deterministic methods can overstate designers' confidence in meeting sustainability targets. When uncertainty is incorporated into STV design, the probability of successfully meeting a target rarely reaches 100%, even for targets initially assessed as "met" by a significant margin in a deterministic analysis. This suggests the need for benchmarks that specify a level of confidence that the target will be met.This research contributes methodological advancements in uncertainty quantification for building LCA, practical tools for probabilistic sustainability assessment, and evidence-based insights into the potential environmental benefits of the specific industrialized construction approaches explored. By transforming sustainability assessment from deterministic pass/fail criteria to probability-based success rates, the framework enables more honest, risk-aware approaches to sustainable building design.
■590 ▼aSchool code: 0212.
■650 4▼aStudy abroad
■650 4▼aConstruction
■650 4▼aDesign thinking
■650 4▼aEnvironmental impact
■650 4▼aStudent organizations
■650 4▼aCarbon
■650 4▼aSustainability
■690 ▼a0640
■71020▼aStanford University.
■7730 ▼tDissertations Abstracts International▼g87-01A.
■790 ▼a0212
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17358669▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
