Browsing by Author "Setunge S"

Now showing 1 - 3 of 3
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    A unified framework for evaluating the resilience of critical infrastructure: Delphi survey approach
    (Elsevier B.V., 2024-06-26) Rathnayaka B; Robert D; Adikariwattage V; Siriwardana C; Meegahapola L; Setunge S; Amaratunga D
    This study advocates establishing an indicator system for Critical Infrastructure (CI) resilience assessment to ensure consistency and comparability in future endeavors. Resilience has emerged as a fundamental framework for effectively managing the performance of CIs in response to the challenges posed by disaster events. However, it is evident that a lack of uniformity exists in the choice and standardization of resilience assessment across the identified frameworks. This paper proposes key attributes for facilitating resilience assessment of CIs using an in-depth literature survey for identification and two rounds of Delphi survey in the Sri Lankan context for their verification. The literature survey has analyzed the resilience assessment attributes under four types of capacities: planning (anticipative), absorptive, restorative, and adaptive. Twenty-seven resilience attributes (Planning: 6; Absorptive: 12; Restorative: 6; Adaptive: 3) under different capacities were identified, including sub-indicators for evaluating each resilience attribute. Outcomes of the Delphi survey were analyzed through descriptive statistics. The proposed attributes received high levels of agreement from the experts, indicating their suitability and applicability for assessing the resilience of the CIs. The mean ratings of the attributes varied from 4.0 to 5.0, with the majority exceeding 4.5 out of 5. The evaluation of these attributes will be useful for assessing the resilience capacity of the CIs and thereby to model the overall resilience of the CIs. The results of this study will provide a solid basis for formulating hypotheses in future research aimed at assessing CI resilience.
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    Identifying and prioritizing climate change adaptation measures in the context of electricity, transportation and water infrastructure: A case study
    (Elsevier B.V., 2023-11-17) Rathnayaka B; Robert D; Siriwardana C; Adikariwattage VV; Pasindu HR; Setunge S; Amaratunga D
    Climate Change Adaptation (CCA) has become a vital measure within every nation due to the significant impacts posed by climate change on Critical Infrastructures (CIs) and human lives. Despite scholars' identification of possible impacts on CIs, a lack of consideration for CCA measures to mitigate these impacts can be observed. This study aims to identify and prioritize CCA measures in the assets and infrastructure of critical sectors; electricity, transportation, and water supply considering Sri Lanka as a case study. The present study employed an Analytical Hierarchical Process (AHP) to prioritize CCA measures of these three infrastructure sectors as a system considering their interconnected and systematic nature. The prioritization process was informed by 42 open-ended expert interviews, and these interviews were also instrumental in validating the criteria used to evaluate the CCA measures. The study identified and discussed several CCA measures for different stages of the infrastructure life cycle, including planning, design and construction, and maintenance and retrofitting. The CCA measures were prioritized based on eight criteria obtained from a detailed review analysis. The results revealed that an asset management system at the planning stage is the most significant CCA measure for CIs. Furthermore, the study emphasizes that proper planning of evacuation routes, consideration of operational loads imposed by climate change, and nature-based solutions are significant CCA measures that need to be incorporated during infrastructure development. The outcome from this study provides insights for built environment professionals to adapt infrastructures to climate change. Additionally, the results of the study can be integrated into the rules and regulations of the developing countries to enhance climate resilience within the built environment.
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    Systematic Mapping of Global Research on Disaster Damage Estimation for Buildings: A Machine Learning-Aided Study
    (MDPI (Basel, Switzerland), 2024-06-20) Rajapaksha D; Siriwardana C; Ruparathna R; Maqsood T; Setunge S; Rajapakse L; De Silva S; Witt E; Bilau AA; Sun B
    Research on disaster damage estimation for buildings has gained extensive attention due to the increased number of disastrous events, facilitating risk assessment, the effective integration of disaster resilience measures, and policy development. A systematic mapping study has been conducted, focusing on disaster damage estimation studies to identify trends, relationships, and gaps in this large and exponentially growing subject area. A novel approach using machine learning algorithms to screen, categorise, and map the articles was adopted to mitigate the constraints of manual handling. Out of 8608 articles from major scientific databases, the most relevant 2186 were used in the analysis. These articles were classified based on the hazard, geographical location, damage function properties, and building properties. Key observations reveal an emerging trend in publications, with most studies concentrated in developed and severely disaster-affected countries in America, Europe, and Asia. A significant portion (68%) of the relevant articles focus on earthquakes. However, as the key research opportunities, a notable research gap exists in studies focusing on the African and South American continents despite the significant damage caused by disasters there. Additionally, studies on floods, hurricanes, and tsunamis are minimal compared to those on earthquakes. Further trends and relationships in current studies were analysed to convey insights from the literature, identifying research gaps in terms of hazards, geographical locations, and other relevant parameters. These insights aim to effectively guide future research in disaster damage estimation for buildings.