A Bayesian approach to rapid seismic vulnerability assessment at urban scale

ABSTRACT The seismic vulnerability of city centers is commonly assessed by extending the study methods applied to single buildings to urban aggregations. This approach is not always applicable at territorial scale, as it is uneconomical in terms of time and costs. An innovative method provides reasonable large-scale a priori estimation of parameters not directly evaluable from the exterior of buildings by elaborating values which can be measured from the outside. Those parameters are treated as continuous variables, by assigning them a suitable probability density function. The Bayesian approach is adopted, which allows the update of initial hypotheses by using new data gathered during on-site surveys. In this regard, a rapid survey form for the on-site data collection is proposed. An example of its application to a façade of a building structural unit in Santo Stefano di Sessanio in L’Aquila province (Italy) is proposed, showing promising preliminary results for buildings belonging to Italian historical centers.

[1]  Stephen N. Luko,et al.  Risk Management Principles and Guidelines , 2013 .

[2]  Sergio Lagomarsino,et al.  Performance-based assessment of cultural heritage assets: outcomes of the European FP7 PERPETUATE project , 2014, Bulletin of Earthquake Engineering.

[3]  Francisco Javier,et al.  The "parallel" and the comparative method in Jean Rondelet Traité théorique et pratique de l'art de bâtir , 2015 .

[4]  F. da Porto,et al.  Analysis and repair of clustered buildings: Case study of a block in the historic city centre of L’Aquila (Central Italy) , 2013 .

[5]  Jie Shan,et al.  A comprehensive review of earthquake-induced building damage detection with remote sensing techniques , 2013 .

[6]  S. Cattari,et al.  Urban risk assessment : fragility functions for masonry buildings , 2015 .

[7]  John Aitchison,et al.  The Statistical Analysis of Compositional Data , 1986 .

[8]  Aníbal Costa,et al.  Seismic vulnerability assessment and characterisation of the buildings on Faial Island, Azores , 2011, Bulletin of Earthquake Engineering.

[9]  Simon Jackman,et al.  Bayesian Analysis for the Social Sciences , 2009 .

[10]  M. Pittore,et al.  Toward a rapid probabilistic seismic vulnerability assessment using satellite and ground-based remote sensing , 2013, Natural Hazards.

[11]  N. Pletneva.  COMMENTARY ON THE INTERNATIONAL STANDARD ISO 31000–2009 “RISK MANAGEMENT. PRINCIPLES AND GUIDELINES” , 2014 .

[12]  S. E. Ahmed,et al.  Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference , 2008, Technometrics.

[13]  Maria Rosa Valluzzi,et al.  Structural Aspects of The Conservation of Historic Masonry Constructions in Seismic Areas: Remedial Measures and Emergency Actions , 2011 .

[14]  Guido Magenes,et al.  DEVELOPMENT OF SEISMIC VULNERABILITY ASSESSMENT METHODOLOGIES OVER THE PAST 30 YEARS , 2006 .

[15]  Peter D. Hoff,et al.  A First Course in Bayesian Statistical Methods , 2009 .

[16]  F. da Porto,et al.  Damage and vulnerability assessment of URM buildings after the 2012 Northern Italy earthquakes , 2016 .

[17]  James H. Lambert,et al.  A Methodology for , 2000 .

[18]  A. Penna,et al.  A methodology for deriving analytical fragility curves for masonry buildings based on stochastic nonlinear analyses , 2010 .