The built environment, particularly buildings, is susceptible to both structural and economic damage from catastrophic events triggered by various natural hazards, including earthquakes, floods, and landslides. The increasing intensity and frequency of certain natural hazards, driven by ongoing climate change, underscore the necessity of adopting a multi-risk perspective. However, current risk assessments often employ metrics that are not directly comparable, hindering comprehensive multi-risk evaluations. To address this gap, a multilayer assessment framework integrating different risks represents a significant step forward. In general, the risk factor can be defined as a function of the probability that a certain event may occur in relation to the extent of damage to people, environment, buildings, and goods. While the full integration of probabilistic hazard, vulnerability, and value at risk has been extensively applied to seismic risk, similar methodologies are less developed for climate-related hazards. This Thesis introduces an innovative approach to structural vulnerability modelling for assessing climate change impacts on the built environment. The research extends traditional seismic risk assessment methods to derive fragility models for climate-induced hazards, such as severe flash floods and debris flows. Central to this work is an analytical structural model employing incremental displacements to simulate the out-of-plane behaviour of load-bearing walls and infill panels subjected to horizontal pressures of different shapes and heights. This model allows incorporating key structural uncertainties through a Monte Carlo simulation and computing hydrogeological fragility models through a parametric definition. This framework provides a robust, integrated and comprehensive approach, crucial for enhancing disaster resilience in the context of climate change.

CLIMATE CHANGE IMPACT ON BUILT ENVIRONMENT: STRUCTURAL VULNERABILITY MODELS FOR FLOOD AND DEBRIS FLOW ACTIONS

MOZZON, SARA
2025

Abstract

The built environment, particularly buildings, is susceptible to both structural and economic damage from catastrophic events triggered by various natural hazards, including earthquakes, floods, and landslides. The increasing intensity and frequency of certain natural hazards, driven by ongoing climate change, underscore the necessity of adopting a multi-risk perspective. However, current risk assessments often employ metrics that are not directly comparable, hindering comprehensive multi-risk evaluations. To address this gap, a multilayer assessment framework integrating different risks represents a significant step forward. In general, the risk factor can be defined as a function of the probability that a certain event may occur in relation to the extent of damage to people, environment, buildings, and goods. While the full integration of probabilistic hazard, vulnerability, and value at risk has been extensively applied to seismic risk, similar methodologies are less developed for climate-related hazards. This Thesis introduces an innovative approach to structural vulnerability modelling for assessing climate change impacts on the built environment. The research extends traditional seismic risk assessment methods to derive fragility models for climate-induced hazards, such as severe flash floods and debris flows. Central to this work is an analytical structural model employing incremental displacements to simulate the out-of-plane behaviour of load-bearing walls and infill panels subjected to horizontal pressures of different shapes and heights. This model allows incorporating key structural uncertainties through a Monte Carlo simulation and computing hydrogeological fragility models through a parametric definition. This framework provides a robust, integrated and comprehensive approach, crucial for enhancing disaster resilience in the context of climate change.
20-mag-2025
Inglese
DA PORTO, FRANCESCA
Università degli studi di Padova
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/213691
Il codice NBN di questa tesi è URN:NBN:IT:UNIPD-213691