A Decision-Framework for Building Portfolios Towards Enhanced Resilience and Sustainability of Communities Under Natural Hazards

dc.contributor.advisorMuraleetharan, Kanthasamy
dc.contributor.authorWang, Yingjun
dc.contributor.committeeMemberCarlson, Deven
dc.contributor.committeeMemberHong, Yang
dc.contributor.committeeMemberHarvey, Philip
dc.contributor.committeeMemberSimonen, Kathrina
dc.contributor.committeeMemberWang, Naiyu
dc.date.accessioned2019-05-10T15:28:05Z
dc.date.available2019-05-10T15:28:05Z
dc.date.issued2019-05-10
dc.date.manuscript2019-05-09
dc.description.abstractIn recent years, communities in the U.S. and other countries have experienced several catastrophic natural hazards (e.g. Hurricane Katrina in 2005 and the Christchurch Earthquake in 2011). The unproportioned social, political impact and economic loss from these events and the fact that such events will continue to occur have highlighted the vulnerability of typical communities, and more importantly, emphasized the significance of considering the performance of communities as a whole under extreme natural and man-made events over a long-time horizon. The physical built environment and the decision-making on them plays a critical role in determining the extent to which the community will perform immediately after the hazard events, the recovery trajectory afterward as well as the long-term financial health, environmental protection, and prosperity. Some communities in the U.S. began or about to implement large-scale, community-level engineering strategies. However, such strategies generally suffer from lacking quantitative support. While some studies have been done to explore the large-scale decision-making, they might be not sufficient to address the problem systematically. A uniform decision support framework for various strategies across different stages of infrastructure systems must be developed. This dissertation focuses on developing a risk-informed decision-making framework for building portfolios under the threat of natural hazards, with particular emphasis on exploring optimal strategies supporting the engineering enhancement measures in different stages of building portfolios over their lifetime. In this study, three categories of large-scale engineering strategies are discussed in depth: new construction, pre-hazard retrofitting, and post-hazard reconstruction that communities may adopt to enhance the performance of the residential building cluster, and thus the whole community in future hazards. Decision-making is explored under seismic and tornado hazards as examples and reveals that communities can and must make engineering decisions from the perspective of the resilience performance of communities and simultaneously consider the sustainability requirements (by employing the economic metric of life-cycle cost as an example). The study demonstrates that the resilience and sustainability goals could be achieved at the same time without compromising one or the other. The proposed decision-making framework could assist community leaders in designing mandatory/voluntary policies or financial incentives to let owners invest in an organized manner and collectively enable the community to achieve its pre-defined resilience and sustainability goals in the long-term.en_US
dc.identifier.urihttps://hdl.handle.net/11244/319687
dc.languageen_USen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectPerformance-based designen_US
dc.subjectCommunity resilienceen_US
dc.subjectSustainabilityen_US
dc.subjectDecision-makingen_US
dc.thesis.degreePh.D.en_US
dc.titleA Decision-Framework for Building Portfolios Towards Enhanced Resilience and Sustainability of Communities Under Natural Hazardsen_US
ou.groupGallogly College of Engineering::School of Civil Engineering and Environmental Scienceen_US
shareok.nativefileaccessrestricteden_US
shareok.orcid0000-0001-6941-3426en_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
2019_Wang_Yingjun_Dissertation.pdf
Size:
11.77 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: