Neural Estimation Of Seismic Resilience Of Transportation Networks

J. M. Mayoral

In the proceedings of: GeoVancouver 2016: 69th Canadian Geotechnical Conference

Session: CASE HISTORIES - II Seismic Design Aspects

ABSTRACT: Seismic resilience of transportation networks of densely populated cities, located in highly active earthquake regions, is studied using a neural procedure. A neural network (NN) is developed to assess major to extreme earthquakes effects through peak ground acceleration (PGA) at a given location. The neural method does not require a priori functional form and implicitly considers the influence of the spatial variability of the soil properties in the estimation of the seismic responses due to particular earthquake conditions (seismic source, epicentral distance, focal depth, and magnitude). Probability of major damage, and potential collapse, of buildings and critical infrastructure components of the transportation network, including urban overpasses, and metro lines, is obtained using appropriate fragility curves. A case study considering downtown Mexico City is included. For the transportation network simulation, a practice-oriented building collapse/road blockage model was used to account for connectivity loss estimation due to debris coming from buildings collapses, along with direct infrastructure failure. Thus, critical sectors from the network connectivity standpoint and potential traffic congestion areas due to earthquake damage, which can preclude rescue activities, were identified.

RÉSUMÉ: La résilience sismique des réseaux de transportation de villes densément peuplées, trouvées dans des régions séismiques très actives, est étudiée en utilisant une procédure neuronale. Un réseau neuronal est développé pour évaluer le dégât la variabilité spatiale (Réseau séismique, distance épicentrale, profondeur focale, et magnitude). Les chutes potentielles de bâtiments, et des lignes du métro, est effectué en utilisant des courbes de fragilité. Pour la simulation du réseau de transportation, on présente une modèle de bâtiment collapsé/route blocage (dégâts du bâtiment collapsé peuvent bloquer quelques routes), ssi vite que les mouvements de terre arrêtent, pour définir des secteurs critiques pour maintenir la connexion ininterrompue et que la capacité du réseau ajuste les fluxes quand la congestion du trafic provoquée par le dommage du séisme soit présente.

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