Seismic Reliability Assessment of Aging Highway Bridge Networks with Field Instrumentation Data and Correlated Failures, I: Methodology

The state-of-the-practice in seismic network reliability assessment of highway bridges often ignores bridge failure correlations imposed by factors such as the network topology, construction methods, and present-day condition of bridges, among others. Additionally, aging bridge seismic fragilities are typically determined simply using historical estimates of deterioration parameters. This research presents a methodology to estimate bridge fragilities using spatially interpolated and updated deterioration parameters from a limited set of instrumented bridges in the network, while incorporating the impacts of overlooked correlation factors in bridge fragility estimates. Simulated samples of correlated bridge failures are used in an enhanced Monte Carlo method to assess bridge network reliability, and the impact of different correlation structures on the network reliability is discussed. The presented methodology aims to provide more realistic estimates of seismic reliability of aging transportation networks and to potentially help network stakeholders to more accurately identify critical bridges for maintenance and retrofit prioritization.

[1]  Mark G. Stewart,et al.  Structural reliability of concrete bridges including improved chloride-induced corrosion models , 2000 .

[2]  C. Park,et al.  A Simple Method for Generating Correlated Binary Variates , 1996 .

[3]  Stephen J. Ganocy,et al.  Bayesian Statistical Modelling , 2002, Technometrics.

[4]  Dan M. Frangopol,et al.  Generalized bridge network performance analysis with correlation and time-variant reliability , 2011 .

[5]  Julian J. Bommer,et al.  The Influence of Ground-Motion Variability in Earthquake Loss Modelling , 2006 .

[6]  David M. Perkins,et al.  Spatial Correlation of Probabilistic Earthquake Ground Motion and Loss , 2001 .

[7]  Daniel Straub,et al.  Bayesian Network Enhanced with Structural Reliability Methods: Methodology , 2010, 1203.5986.

[8]  C. Allin Cornell,et al.  Probabilistic Basis for 2000 SAC Federal Emergency Management Agency Steel Moment Frame Guidelines , 2002 .

[9]  Reginald DesRoches,et al.  Bridge Functionality Relationships for Improved Seismic Risk Assessment of Transportation Networks , 2007 .

[10]  J. Baker,et al.  Correlation model for spatially distributed ground‐motion intensities , 2009 .

[11]  J. Baker,et al.  A vector‐valued ground motion intensity measure consisting of spectral acceleration and epsilon , 2005 .

[12]  David Kazmer,et al.  Plastics Manufacturing Systems Engineering , 2009 .

[13]  Paolo Gardoni,et al.  Matrix-based system reliability method and applications to bridge networks , 2008, Reliab. Eng. Syst. Saf..

[14]  Jianfeng Zhao,et al.  Seismic damage of highway bridges during the 2008 Wenchuan earthquake , 2009 .

[15]  Mark G. Stewart,et al.  Spatial variability of pitting corrosion and its influence on structural fragility and reliability of RC beams in flexure , 2004 .

[16]  Sarah L. Gassman,et al.  Nondestructive Assessment of Damage in Concrete Bridge Decks , 2004 .

[17]  Phadeon-Stelios Koutsourelakis,et al.  Assessing structural vulnerability against earthquakes using multi-dimensional fragility surfaces: A Bayesian framework , 2010 .

[18]  Stephanie E. Chang,et al.  Disasters and transport systems: loss, recovery and competition at the Port of Kobe after the 1995 earthquake , 2000 .

[19]  C. Allin Cornell,et al.  Probabilistic seismic demand analysis of nonlinear structures , 1999 .

[20]  Dan M. Frangopol,et al.  A stochastic computational framework for the joint transportation network fragility analysis and traffic flow distribution under extreme events , 2011 .

[21]  Terje Haukaas,et al.  Seismic fragility estimates for reinforced concrete bridges subject to corrosion , 2009 .

[22]  K. M. Yusof,et al.  Atmospheric chloride penetration into concrete in semitropical marine environment , 1994 .

[23]  M. Piedmonte,et al.  A Method for Generating High-Dimensional Multivariate Binary Variates , 1991 .

[24]  Robert E. Melchers,et al.  Effect of reinforcement corrosion on reliability of highway bridges , 1998 .

[25]  Anshel J. Schiff,et al.  Northridge earthquake : lifeline performance and post-earthquake response , 1995 .

[26]  C. Bucher,et al.  A fast and efficient response surface approach for structural reliability problems , 1990 .

[27]  Jack W. Baker,et al.  Efficient sampling and data reduction techniques for probabilistic seismic lifeline risk assessment , 2010 .

[28]  J. C. Myers,et al.  Geostatistical Error Management: Quantifying Uncertainty for Environmental Sampling and Mapping , 1997 .

[29]  G. R. Toro,et al.  Model of Strong Ground Motions from Earthquakes in Central and Eastern North America: Best Estimates and Uncertainties , 1997 .

[30]  S. Harmsen,et al.  Documentation for the 2002 update of the national seismic hazard maps , 2002 .

[31]  Behrouz Shafei,et al.  Performance Evaluation of Deteriorating Highway Bridges Located in High Seismic Areas , 2011 .

[32]  Reginald DesRoches,et al.  Seismic fragility of typical bridges in moderate seismic zones , 2004 .

[33]  A. Kiremidjian,et al.  Uncertainty and Correlation for Loss Assessment of Spatially Distributed Systems , 2007 .

[34]  Martin H. Trauth,et al.  MATLAB® Recipes for Earth Sciences , 2021, Springer Textbooks in Earth Sciences, Geography and Environment.

[35]  Kevin R. Mackie,et al.  Post‐earthquake functionality of highway overpass bridges , 2006 .

[36]  Mark G. Stewart,et al.  Extent of spatially variable corrosion damage as an indicator of strength and time-dependent reliability of RC beams , 2009 .

[37]  Anne S. Kiremidjian,et al.  Issues in Seismic Risk Assessment of Transportation Networks , 2007 .

[38]  K. C. Liam,et al.  Chloride ingress measurements and corrosion potential mapping study of a 24-year-old reinforced concrete jetty structure in a tropical marine environment , 1992 .

[39]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[40]  Robert E. Melchers,et al.  Effect of response surface parameter variation on structural reliability estimates , 2001 .

[41]  Kazuaki Zen Corrosion and life cycle management of port structures , 2005 .

[42]  Dan M. Frangopol,et al.  Reinforced concrete bridge deck reliability model incorporating temporal and spatial variations of probabilistic corrosion rate sensor data , 2008, Reliab. Eng. Syst. Saf..

[43]  R. Caflisch,et al.  Quasi-Monte Carlo integration , 1995 .

[44]  Michael P. Enright,et al.  Probabilistic analysis of resistance degradation of reinforced concrete bridge beams under corrosion , 1998 .

[45]  B. G. Nielson Analytical Fragility Curves for Highway Bridges in Moderate Seismic Zones , 2005 .

[46]  Reginald DesRoches,et al.  Analytical Seismic Fragility Curves for Typical Bridges in the Central and Southeastern United States , 2007 .

[47]  Michael P. Enright,et al.  Condition Prediction of Deteriorating Concrete Bridges Using Bayesian Updating , 1999 .

[48]  Reginald DesRoches,et al.  Retrofitted Bridge Fragility Analysis for Typical Classes of Multispan Bridges , 2009 .

[49]  Peeranan Towashiraporn,et al.  Building Seismic Fragilities Using Response Surface Metamodels , 2004 .

[50]  A. Moncmanova,et al.  Environmental Deterioration of Materials , 2007 .

[51]  Terje Haukaas,et al.  Probabilistic capacity models and seismic fragility estimates for RC columns subject to corrosion , 2008, Reliab. Eng. Syst. Saf..

[52]  Kurt Hornik,et al.  On the generation of correlated artificial binary data , 1998 .

[53]  P. Filzmoser,et al.  Statistical Data Analysis Explained , 2008 .

[54]  Wei Liu,et al.  An improved cut-based recursive decomposition algorithm for reliability analysis of networks , 2012, Earthquake Engineering and Engineering Vibration.

[55]  C. Page,et al.  Corrosion of reinforcement in concrete , 1990 .

[56]  D G Krige,et al.  A statistical approach to some mine valuation and allied problems on the Witwatersrand , 2015 .

[57]  G. Atkinson,et al.  Ground-motion relations for eastern North America , 1995, Bulletin of the Seismological Society of America.

[58]  Michael F. Goodchild Representing, Modeling, and Visualizing the Natural Environment , 2010 .

[59]  Clemens Reimann,et al.  Statistical data analysis explained : applied environmental statics with R , 2008 .

[60]  K. Campbell PREDICTION OF STRONG GROUND MOTION USING THE HYBRID EMPIRICAL METHOD AND ITS USE IN THE DEVELOPMENT OF GROUND-MOTION (ATTENUATION) RELATIONS IN EASTERN NORTH AMERICA , 2003 .

[61]  Jamie E. Padgett,et al.  Aging Considerations in the Development of Time-Dependent Seismic Fragility Curves , 2010 .

[62]  Ricardo A. Olea,et al.  Geostatistics for Engineers and Earth Scientists , 1999, Technometrics.

[63]  Stefan Hurlebaus,et al.  Probabilistic Capacity Models and Fragility Estimates for Reinforced Concrete Columns Incorporating NDT Data , 2009 .

[64]  MikiI Funahashi Predicting Corrosion-Free Service Life of a Concrete Structure in a Chloride Environment , 1990 .

[65]  Palle Thoft-Christensen,et al.  Advanced bridge management systems , 1995 .

[66]  Timothy W. Simpson,et al.  Metamodels for Computer-based Engineering Design: Survey and recommendations , 2001, Engineering with Computers.

[67]  Y. K. Wen,et al.  Uniform Hazard Ground Motions for Mid-America Cities , 2001 .

[68]  Masanobu Shinozuka,et al.  Development of fragility curves of bridges retrofitted by column jacketing , 2004 .

[69]  R. Reese Geostatistics for Environmental Scientists , 2001 .

[70]  A. D. Lunn,et al.  A note on generating correlated binary variables , 1998 .

[71]  Bruce R. Ellingwood,et al.  A new look at the response surface approach for reliability analysis , 1993 .

[72]  Leonardo Dueñas-Osorio,et al.  Bridge retrofit prioritisation for ageing transportation networks subject to seismic hazards , 2013 .

[73]  Dan M. Frangopol,et al.  Reliability of Reinforced Concrete Girders Under Corrosion Attack , 1997 .

[74]  C. V. Anderson,et al.  The Federal Emergency Management Agency (FEMA) , 2002 .

[75]  J. Kiefer,et al.  Optimum Designs in Regression Problems , 1959 .

[76]  W. Mackaness,et al.  VISUALIZATION OF INTERPOLATION ACCURACY , 2008 .

[77]  Peter Goos,et al.  Optimal Design of Experiments: A Case Study Approach , 2011 .

[78]  William Graf,et al.  Potential Losses in a Repeat of the 1886 Charleston, South Carolina, Earthquake , 2005 .

[79]  Reginald DesRoches,et al.  Regional Seismic Risk Assessment of Bridge Network in Charleston, South Carolina , 2010 .

[80]  Robert Haining,et al.  Statistics for spatial data: by Noel Cressie, 1991, John Wiley & Sons, New York, 900 p., ISBN 0-471-84336-9, US $89.95 , 1993 .

[81]  Daniel Straub,et al.  Bayesian Network Enhanced with Structural Reliability Methods: Application , 2010, 1203.5985.

[82]  Nicolas Luco,et al.  Direct Calculation of the Probability Distribution for Earthquake Losses to a Portfolio , 2009 .

[83]  Dan M. Frangopol,et al.  Use of monitoring extreme data for the performance prediction of structures: Bayesian updating , 2008 .

[84]  G. Box,et al.  On the Experimental Attainment of Optimum Conditions , 1951 .

[85]  P. Glasserman,et al.  Monte Carlo methods for security pricing , 1997 .

[86]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[87]  Jamie E. Padgett,et al.  Impact of multiple component deterioration and exposure conditions on seismic vulnerability of concrete bridges , 2012 .