Browsing by Author "Adikariwattage V"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    Novel methodology for resilience assessment of critical infrastructure considering the interdependencies: A case study in water, transportation and electricity sector
    (Elsevier Ltd, 2025-03) Rathnayaka B; Robert D; Adikariwattage V; Siriwardana C; Kuligowski E; Setunge S; Amaratunga D
    Critical Infrastructures (CI) are vital for societal and economic stability, yet their resilience against disasters remains inadequately understood with the increasing interdependencies among the CIs. A better understanding of these interdependencies and the dynamic nature of CI functionalities is crucial for advancing disaster resilience assessment within engineering systems. This paper introduces a novel approach using a Dynamic Bayesian Network (DBN) to assess resilience in interdependent CI systems. The DBN method enables a probabilistic evaluation of system resilience by incorporating interdependencies and capturing the temporal dynamics of system capacities. This approach offers a more detailed perspective on resilience by modelling system functionality using expected values of different functionality states over time. Using a case study in Sri Lankan electricity, water distribution, and road infrastructure sectors and 34 experts, this study examines the complex network of CIs. It demonstrates the applicability of the proposed methodology. P-values of the Chi-Square test performed between the variation of model-predicted resilience and expert assessments are significantly less than 0.05, confirming the model's validity. Additionally, this study explores the expansion of the methodology for resilience assessment under multiple hazards, emphasizing its real-world effectiveness. The findings highlight the efficacy of the proposed methodology and its potential to assist asset managers, owners, and decision-makers in informed resilience planning and optimization strategies. This comprehensive approach fills critical gaps in existing methodologies, offering a robust framework for assessing CI resilience in a dynamic and systematic nature.