Bayesian networks for assessment of disruption to school systems under combined hazards
Bibliographic Data
| ID | 22028992 |
|---|---|
| Authors | Ahsana P Vatteri (0000-0003-3864-324X, University College London), Dina D’Ayala (0000-0003-3864-2052, University College London, corresponding author), Pierre Gehl (0000-0002-1225-9621, Bureau de Recherches Géologiques et Minières) |
| Year | 2022 |
| Volume | 74 |
| Pages | 102924 |
| Publication date | 2022-05-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Disaster Risk Reduction (JOURNAL) |
| Journal identifiers | ISSN: 2212-4209 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ijdrr.2022.102924 |
| OpenAlex | W4220926308 |
| Language | EN |
| Citations received | 5 |
| References cited | 45 |
Exposure of school buildings to floods and earthquakes poses significant risk to the vulnerable population of students and their education process. 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. The socio-economic condition of the users-community also plays a role in the extent of such disruption. A complex problem of this nature demands consideration of a large number of dimensions, to estimate the impact to the school system infrastructure in a locality. To handle the qualitative and quantitative nature of these variables, a Bayesian network (BN) model is proposed representing multiple schools in a locality as a system. Three dimensions are considered to contribute to the system disruption, namely, schools’ physical functionality loss, accessibility and use loss, and social vulnerability. The impact is quantified through the probability of the system being in various states of disruption. The BN also explores mitigating measures, such as the mobility of students between schools in the system. The general methodology is illustrated by a case-study of school buildings in Guwahati, India, whereby the majority of buildings is constructed in confined masonry with varying level of seismic performance. The physical effects of combined flood and seismic action on confined masonry buildings is assessed by nonlinear numerical modelling, and their probabilistic occurrence is expressed in terms of fragility functions corresponding to varying flood depth and peak ground acceleration
Bayesian network · Bayesian probability · Business · Forensic engineering · Computer Science · Engineering · Environmental Science · Infrastructure Resilience and Vulnerability Analysis · Occupational Health and Safety Research · Risk and Safety Analysis · Artificial Intelligence
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Poverty and Disasters in the United States
Probabilistic earthquake and flood loss assessment in the Middle East
A prioritization RVS methodology for the seismic risk assessment of RC school buildings
Reconnoitering school children vulnerability and its determinants
Learning from past earthquake disasters
Resilient communities through safer schools
Vulnerability of schools to floods in Nyando River catchment, Kenya
| Citations per year | 1.67 |
|---|---|
| Citation span | 2023 - 2026 (4) |
| Highly cited | No |