Risk Identification and Assessment Methodology for Restoration Work Utilizing Unmanned Vehicles at Disaster Scenes
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Byeol | - |
dc.contributor.author | Lee, Joosung | - |
dc.contributor.author | Ueda, Jun | - |
dc.contributor.author | Cho, Yong Kwon | - |
dc.contributor.author | Han, Changsoo | - |
dc.contributor.author | Ahn, Yonghan | - |
dc.date.accessioned | 2021-06-22T11:03:01Z | - |
dc.date.available | 2021-06-22T11:03:01Z | - |
dc.date.issued | 2019-00 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/4688 | - |
dc.description.abstract | Nuclear power plant accidents such as those at Fukushima and Chernobyl release a significant amount of hazardous radiation. It takes a long time to recover from such an accident and the difficulty of the task is very high due to the many risks. Restoration work using unmanned vehicles protects workers from the risk of secondary accidents such as radiation exposure and building collapses. Unmanned tasks in high-risk environments should be performed in accordance with carefully planned and optimized work scenarios that prioritize specific tasks. This study examined the non-radiological and radiological risks, accessibility, task difficulty, and efficiency that determine work priorities in such cases and developed a methodology to assess the risks associated with specific unmanned restoration tasks. The proposed risk assessment methodology is based on a risk matrix that can be used to derive work priorities for each zone at a post-disaster nuclear site. © 2019 American Society of Civil Engineers. | - |
dc.format.extent | 8 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | American Society of Civil Engineers (ASCE) | - |
dc.title | Risk Identification and Assessment Methodology for Restoration Work Utilizing Unmanned Vehicles at Disaster Scenes | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1061/9780784482445.041 | - |
dc.identifier.scopusid | 2-s2.0-85068780964 | - |
dc.identifier.wosid | 000485354700041 | - |
dc.identifier.bibliographicCitation | Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019, pp 322 - 329 | - |
dc.citation.title | Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019 | - |
dc.citation.startPage | 322 | - |
dc.citation.endPage | 329 | - |
dc.type.docType | Conference Paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Engineering, Civil | - |
dc.subject.keywordPlus | Disasters | - |
dc.subject.keywordPlus | Nuclear fuels | - |
dc.subject.keywordPlus | Nuclear power plants | - |
dc.subject.keywordPlus | Nuclear reactor accidents | - |
dc.subject.keywordPlus | Restoration | - |
dc.subject.keywordPlus | Risk perception | - |
dc.subject.keywordPlus | Smart city | - |
dc.subject.keywordPlus | Sustainable development | - |
dc.subject.keywordPlus | Unmanned vehicles | - |
dc.subject.keywordPlus | Assessment methodologies | - |
dc.subject.keywordPlus | High risk environment | - |
dc.subject.keywordPlus | Nuclear power plant accident | - |
dc.subject.keywordPlus | Radiation Exposure | - |
dc.subject.keywordPlus | Radiological risks | - |
dc.subject.keywordPlus | Restoration works | - |
dc.subject.keywordPlus | Risk assessment methodologies | - |
dc.subject.keywordPlus | Risk Identification | - |
dc.subject.keywordPlus | Risk assessment | - |
dc.identifier.url | https://ascelibrary.org/doi/10.1061/9780784482445.041 | - |
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.