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Probabilistic Seismic Risk Assessment of a reinforced concrete building considering hazard level and the resulting vulnerability using Bayesian Belief Network

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Abstract

Seismic losses have significantly increased in size and frequency during the past few years, harming the economy and communities. Seismic Risk Assessment (SRA) requires integration of seismic hazard, building exposure and vulnerability, which entails many levels of complicated models, and necessitates taking uncertainties into account. The present study focuses on the probabilistic SRA of a single building, thereby excluding building exposure modelling and incorporating only seismic hazard and the resulting building vulnerability. In this study, the confidence level on probabilistic SRA is enhanced by considering a soft computing technique like Bayesian Belief Network (BBN) that makes use of the strength of Bayesian statistics to account for complicated connections and correlations amongst events at different levels of a network model of the system. This approach is based on developing a node-based model and assigning probabilities to each node by forming a Conditional Probability Table (CPT), which is based on both data as well as logically driven assumptions. The probabilistic seismic risk obtained has been represented in the form of three indices: low, medium and high. The established BBN model is next subjected to sensitivity analysis, which can help with the evaluation of updated data as new information from experimental observations or improved simulations is integrated. The application of the methodology is illustrated for a reinforced concrete (RC) hospital building located at Silchar city in northeast India, which is one of the most seismically active regions of the country. The developed model enables the identification of the seismic risk associated with a particular building which can be utilised to guide stakeholders, policymakers and designers in the efficient planning of emergency response, rescue operations and recovery activities.

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Acknowledgements

The first author (GR) acknowledges the students’ scholarship received from the Ministry of Human Resource and Development, Government of India.

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The authors declare that no funds, grants or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. Department of Civil Engineering, National Institute of Technology Silchar, Silchar, Assam, 788010, India

    Geetopriyo Roy, Abhilash Singh, Subhrajit Dutta & Satyabrata Choudhury

  2. Department of Civil Engineering, Assam Don Bosco University, Azara, Assam, 781017, India

    Mrinal Kanti Sen

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  1. Geetopriyo Roy
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  4. Subhrajit Dutta
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Geetopriyo Roy, Mrinal Kanti Sen and Abhilash Singh. The first draft of the manuscript was written by Geetopriyo Roy, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Mrinal Kanti Sen.

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Roy, G., Sen, M.K., Singh, A. et al. Probabilistic Seismic Risk Assessment of a reinforced concrete building considering hazard level and the resulting vulnerability using Bayesian Belief Network. Asian J Civ Eng 25, 2993–3009 (2024). https://doi.org/10.1007/s42107-023-00958-x

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