Examinando por Materia "Fragility curves"

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    Development of structural debris flow fragility curves (debris flow buildings resistance) using momentum flux rate as a hazard parameter
    (Elsevier B.V., 2018-05-18) Prieto, Jorge Alonso; Journeay, Murray; Acevedo A.B.; Arbelaez, Juan; Ulmi, Malaika; Mecánica Aplicada
    Societal risks associated with debris flow hazards are significant and likely to escalate due to global population growth trends and the compounding effects of climate change. Quantitative risk assessment methods (QRA) provide a means of anticipating the likely impacts and consequences of settlement in areas susceptible to landslide activity and are increasingly being used to inform land use decisions that seek to increase disaster resilience through mitigation and/or adaptation. Current QRA methods for debris flow hazards are based primarily on empirical vulnerability functions that relate hazard intensity (depth, velocity, etc.) to expected levels of loss for a given asset of concern, i.e. most of current methods are dedicated to loss-intensity relations. Though grounded in observed cause-effect relationships, empirical vulnerability functions are not designed to predict the capacity of a building to withstand the physical impacts of a debris flow event, or the related uncertainties associated with modelling building performance as a function of variable debris flow parameters. This paper describes a methodology for developing functions that relate hazard intensity to probability of structural damage, i.e., fragility functions, rather than vulnerability functions, based on the combined hydrodynamic forces of a debris flow event (hazard level) and the inherent structural resistance of building typologies that are common in rural mountainous settings (building performance). Hazard level includes a hydrodynamic force variable (FDF), which accounts for the combined effects of debris flow depth and velocity, i.e. momentum flux (hv2), material density (?) and related flow characteristics including drag (Cd) and impact coefficient (Kd). Building performance is measured in terms of yield strength (Ay), ultimate lateral capacity (AU) and weight to breadth ratios (W/B) defined for a portfolio building types that are common in mountain settlements. Collectively, these model parameters are combined using probabilistic methods to produce building-specific fragility functions that describe the probability of reaching or exceeding successive thresholds of structural damage over a range of hazard intensity values, expressed in terms of momentum flux. Validation of the proposed fragility model is based on a comparison between model outputs and observed cause-effect relationships for recent debris flow events in South Korea and in Colombia. Debris flow impact momentum fluxes, capable of resulting in complete damage to unreinforced masonry buildings (URM) in those regions are estimated to be on the order of 24 m3/s2, consistent with field-based observations. Results of our study offer additional capabilities for assessing risks associated with urban growth and development in areas exposed to debris flow hazards. © 2018 Elsevier B.V.
  • No hay miniatura disponible
    Publicación
    Development of structural debris flow fragility curves (debris flow buildings resistance) using momentum flux rate as a hazard parameter
    (Elsevier B.V., 2018-05-18) Prieto, Jorge Alonso; Journeay, Murray; Acevedo A.B.; Arbelaez, Juan; Ulmi, Malaika; Universidad EAFIT. Departamento de Ingeniería de Producción; Materiales de Ingeniería
    Societal risks associated with debris flow hazards are significant and likely to escalate due to global population growth trends and the compounding effects of climate change. Quantitative risk assessment methods (QRA) provide a means of anticipating the likely impacts and consequences of settlement in areas susceptible to landslide activity and are increasingly being used to inform land use decisions that seek to increase disaster resilience through mitigation and/or adaptation. Current QRA methods for debris flow hazards are based primarily on empirical vulnerability functions that relate hazard intensity (depth, velocity, etc.) to expected levels of loss for a given asset of concern, i.e. most of current methods are dedicated to loss-intensity relations. Though grounded in observed cause-effect relationships, empirical vulnerability functions are not designed to predict the capacity of a building to withstand the physical impacts of a debris flow event, or the related uncertainties associated with modelling building performance as a function of variable debris flow parameters. This paper describes a methodology for developing functions that relate hazard intensity to probability of structural damage, i.e., fragility functions, rather than vulnerability functions, based on the combined hydrodynamic forces of a debris flow event (hazard level) and the inherent structural resistance of building typologies that are common in rural mountainous settings (building performance). Hazard level includes a hydrodynamic force variable (FDF), which accounts for the combined effects of debris flow depth and velocity, i.e. momentum flux (hv2), material density (?) and related flow characteristics including drag (Cd) and impact coefficient (Kd). Building performance is measured in terms of yield strength (Ay), ultimate lateral capacity (AU) and weight to breadth ratios (W/B) defined for a portfolio building types that are common in mountain settlements. Collectively, these model parameters are combined using probabilistic methods to produce building-specific fragility functions that describe the probability of reaching or exceeding successive thresholds of structural damage over a range of hazard intensity values, expressed in terms of momentum flux. Validation of the proposed fragility model is based on a comparison between model outputs and observed cause-effect relationships for recent debris flow events in South Korea and in Colombia. Debris flow impact momentum fluxes, capable of resulting in complete damage to unreinforced masonry buildings (URM) in those regions are estimated to be on the order of 24 m3/s2, consistent with field-based observations. Results of our study offer additional capabilities for assessing risks associated with urban growth and development in areas exposed to debris flow hazards. © 2018 Elsevier B.V.
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    Publicación
    Performance-based seismic landslide hazard assessment : numerical frameworks for regional and local-scale applications
    (Universidad EAFIT, 2025-12-09) Montoya Araque, Exneyder Andrés; Montoya-Noguera, Silvana; López-Caballero, Fernando; Esta investigación se realizó bajo un acuerdo de supervisión internacional conjunta de doctorado bajo la modalidad de cotutela entre la Universidad EAFIT (Medellín, Colombia) y la Université Paris-Saclay (Francia), dentro de la unidad de investigación Laboratoire de Mécanique Paris-Saclay (LMPS) (Université Paris-Saclay, CentraleSupélec, ENS Paris-Saclay, CNRS). A continuación, se detallan las fuentes de patrocinio/financiación y otros recursos: - Financiación principal: Esta investigación contó con el apoyo financiero principal de: (i) la Vicerrectoría de Ciencia, Tecnología e Innovación (CTeI) de la Universidad EAFIT, a través del proyecto interno No. 817898, "Amenaza sísmica de deslizamientos en el Valle de Aburrá"; (ii) la iniciativa IDEX Paris-Saclay (ANR-11-IDEX-0003-02), a través del programa de financiación ADI 2022 para proyectos de doctorado en cotutela internacional; y (iii) el Proyecto ECOS-NORD 008-2023 (Colombia) – C23U01 (Francia), "Evaluación de la amenaza por deslizamientos detonados por sismos y lluvia – Medellín, Colombia". - Instalaciones y financiación complementaria: Esta investigación hizo uso de las instalaciones y el apoyo económico complementario brindado por el Laboratoire de Mécanique Paris-Saclay (LMPS), así como por el Grupo de Investigación Naturaleza y Ciudades y del antiguo Grupo de Investigación en Mecánica Aplicada de la Universidad EAFIT. - Recursos computacionales: Las simulaciones numéricas y los cálculos a gran escala contaron con el apoyo del Centro de Computación Científica APOLO de la Universidad EAFIT (Medellín, Colombia), y del centro de computación Mésocentre de la Université Paris-Saclay, CentraleSupélec y École Normale Supérieure Paris-Saclay, con el respaldo del CNRS y la Région Île-de-France.