Search for: All records

Natural disasters devastate property and infrastructure systems, impeding sustainable development. Low-income communities, due to economic, physical, and social disparities, face heightened exposure and vulnerability. These communities endure severe and long-lasting infrastructure damage, experiencing a fourfold increase in deaths per disaster and delayed recovery efforts. Consequently, they resort to constructing informal housing and infrastructure, worsening post-disaster challenges and vulnerabilities. This study aims to address post-disaster challenges in low-income communities by proposing two novel approaches that remain understudied despite their significant potential: (1) a short-term solution of origami temporary emergency housing for swift shelter post-disaster, enabling a return to routine activities while homes and infrastructure systems are being repaired or rebuilt; and (2) a long-term solution, including effective pedagogy, such as teaching methods and instructional tools, to educate and train low-income individuals to aid in sustainable post-disaster reconstruction while providing the added benefit of social mobility. To validate the feasibility of origami TEH and the need and effectiveness of the pedagogy, a survey among architecture, engineering, and construction experts in Puerto Rico, a region prone to natural disasters, was conducted. The results, analyzed using statistical measures including descriptive statistics and ordered probit regression analysis, emphasize the urgent need for sustainable TEH that can be quickly assembled and education for low-income individuals in construction trades. Implementing these solutions will significantly impact communities by addressing post-disaster challenges and promoting social mobility and job equity. 

Post-disaster reconnaissance is vital for assessing the impact of a natural disaster on the built environment and informing improvements in design, construction, risk mitigation, and our understanding of extreme events. The data obtained from reconnaissance can also be utilized to improve disaster recovery planning by maximizing resource efficiency, minimizing waste, and promoting resilience in future disasters. This paper aims to investigate existing reconnaissance reports and datasets to identify the factors that impact the reusability of buildings post-disaster and to recommend strategies that align with circular economy goals. The study adopted a three-step research methodology to attain the proposed goals: (1) thematic analysis was used to evaluate types of damages reported in the reconnaissance reports; (2) a supervised machine-learning algorithm was employed to analyze reconnaissance datasets; and (3) a concept map was developed based on interviews of 109 stakeholders in disaster-prone communities to recommend strategies to adopt circular economy practices post-disaster. The study results highlight the recurring risks of damage to different parts of the building and how circular economy resilience practices like deconstruction can minimize waste and maximize resource efficiency during post-disaster recovery. The findings of the study promote a more regenerative economy to build resilience to the challenges of future extreme weather events.