Life-Cycle Assessment of Apartment Buildings Based on Standard Quantities of Building Materials Using Probabilistic Analysis Technique
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Hyeonsuk | - |
dc.contributor.author | Jang, Hyeongjae | - |
dc.contributor.author | Tae, Sungho | - |
dc.contributor.author | Kim, Hyunsik | - |
dc.contributor.author | Jo, Kanghee | - |
dc.date.accessioned | 2022-12-20T05:53:19Z | - |
dc.date.available | 2022-12-20T05:53:19Z | - |
dc.date.issued | 2022-06 | - |
dc.identifier.issn | 1996-1944 | - |
dc.identifier.issn | 1996-1944 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/111365 | - |
dc.description.abstract | Given the increasingly serious nature of environmental problems, many countries have recently declared carbon neutrality policies and expended efforts to implement them. The domestic building industry aims to reduce its environmental impact using life-cycle assessments (LCAs) of buildings according to the Green Standard for Energy and Environmental Design. However, it is difficult to perform efficient LCAs because the required quantity takeoff process is complex, and the quantity takeoff sheet may not exist during the building's design phase. In this study, 21 building LCAs were used to simplify and improve the efficiency of the proposed method and enable building LCAs even when there was no quantity takeoff sheet. Furthermore, a standard quantity database of building materials was constructed based on the analysis of the input quantities of building materials per unit area, and the apartment buildings LCA method was proposed using this database. The input quantities of building materials were analyzed using the probabilistic analysis technique. The probability distribution was derived using Monte Carlo simulations, and the goodness-of-fit was verified. Finally, the reliability of the proposed building LCA method was verified using a case study. | - |
dc.format.extent | 12 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | MDPI Open Access Publishing | - |
dc.title | Life-Cycle Assessment of Apartment Buildings Based on Standard Quantities of Building Materials Using Probabilistic Analysis Technique | - |
dc.type | Article | - |
dc.publisher.location | 스위스 | - |
dc.identifier.doi | 10.3390/ma15124103 | - |
dc.identifier.scopusid | 2-s2.0-85132105524 | - |
dc.identifier.wosid | 000819057300001 | - |
dc.identifier.bibliographicCitation | Materials, v.15, no.12, pp 1 - 12 | - |
dc.citation.title | Materials | - |
dc.citation.volume | 15 | - |
dc.citation.number | 12 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 12 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Chemistry | - |
dc.relation.journalResearchArea | Materials Science | - |
dc.relation.journalResearchArea | Metallurgy & Metallurgical Engineering | - |
dc.relation.journalResearchArea | Physics | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Physical | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Multidisciplinary | - |
dc.relation.journalWebOfScienceCategory | Metallurgy & Metallurgical Engineering | - |
dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
dc.relation.journalWebOfScienceCategory | Physics, Condensed Matter | - |
dc.subject.keywordAuthor | probabilistic analysis techniques | - |
dc.subject.keywordAuthor | building material | - |
dc.subject.keywordAuthor | standard quantity | - |
dc.subject.keywordAuthor | life-cycle assessment | - |
dc.identifier.url | https://www.mdpi.com/1996-1944/15/12/4103 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.