Parammal Vatteri, Ahsana; (2022) Performance Assessment of Masonry School Buildings to Seismic and Flood Hazards Using Bayesian Networks. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Performance assessment of schools is an integral part of disaster risk reduction of communities from natural hazards such as earthquakes and floods. In regions of high exposure, these hazards may often act concurrently, whereby yearly flood events weaken masonry school buildings, rendering them more vulnerable to frequent earthquake shaking. This recurring damage, combined with other functional losses, ultimately result in disruption to education delivery, affecting vulnerable schoolchildren. This project examines behaviour of school buildings to seismic and flood loading, and associated disruption to education from a structural and functional perspective. The study is based on a case study of school buildings in Guwahati, India, where the majority of the buildings can be classified into confined masonry (CM) typology. This project presents three stages of analyses to study the performance of these CM school buildings and the system of schools, as summarised in the following. The first stage of the study involves refinement of the World Bank’s Global Library of School Infrastructure taxonomy to widen its scope and to fit the CM school typology. This leads to the identification of index buildings, which are single-story buildings with flexible diaphragms differing mainly in the level of seismic design. In the second stage, a novel numerical modelling platform based on Applied Element Method is used to analyse the index buildings for simplified lateral loads from both the aforementioned hazards. Seismic loading is applied in the form of ground acceleration, while flood loading is applied as hydrostatic pressure. Sequential scenarios are simulated by subjecting the building to varying flood depths followed by lateral ground acceleration, after accounting for the material degradation due to past flooding. Analytical fragility curves are derived for each case of analysis to quantify their physical performance, using a non-linear static procedure (N2 method) and least square error regression. The third stage of the study employs a Bayesian network (BN) based methodology to model the education disruption at the school system level, from exposure of schools to flood and seismic hazards. The methodology integrates the qualitative and quantitative nature of system variables, such as the physical fragility of school buildings (derived in the second stage), accessibility loss, change of use as shelters and socio-economic condition of the users-community. The performance of the education system impacted by the sequential hazards is quantified through the probability of the various states of disruption duration. The BN also explores the effectiveness of non-structural mitigating measures, such as the transfer of students between schools in the system. The framework proves to be a useful tool to assist decision-making, with regard to disaster preparedness and recovery, hence, contributing to the development of resilient education systems.

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