Analysis of the brazilian federal bridge inventory

Bridge Management has been extensively investigated and extended by researchers and engineers around the world. The main goal is to provide an appropriate support to decision-making regarding risk identification, required maintenance, strengthening, rehabilitation or element replacement under the constraint of limited budgets. To achieve this objective, the Federal Brazilian Department of Transportation (DNIT) has promoted the most comprehensive road bridge inventory under its direct administration. The present article analyzes and presents the inventory findings with the intention of disseminating the information necessary to provide input data for research projects in the areas of degradation, inspection and maintenance of bridges. The main construction characteristics of the Brazilian road bridges, the condition state of these structures as well as the type and frequency of damages detected are related. A specific analysis comparing the results for different inspectors is presented to try to identify some bias. The appropriate consideration of these biases is an important issue to be addressed in the future in order to have a more balanced and equilibrated evaluation of the condition of these bridges.

[1]  George Morcous,et al.  Performance Prediction of Bridge Deck Systems Using Markov Chains , 2006 .

[2]  Giovanni Pais Pellizzer,et al.  Influence of reinforcement's corrosion into hyperstatic reinforced concrete beams: a probabilistic failure scenarios analysis , 2015 .

[3]  C. F. Kossack,et al.  Rank Correlation Methods , 1949 .

[4]  Samer Madanat,et al.  Computation of Infrastructure Transition Probabilities using Stochastic Duration Models , 2002 .

[5]  Anil K. Agrawal,et al.  Bridge Element Deterioration Rates , 2009 .

[6]  Ronaldo C. Battista,et al.  Towards actual brazilian traffic load models for short span highway bridges , 2015 .

[7]  Brett Tempest,et al.  Determination of Bridge Deterioration Models and Bridge User Costs for the NCDOT Bridge Management System , 2015 .

[8]  Hasan,et al.  Concrete bridge deterioration prediction using Markov chain approach , 2013 .

[9]  Paul D. Thompson.  Decision Support Analysis in Ontario's New Bridge Management System , 2001 .

[10]  Glenn Washer,et al.  Estimating Inspection Intervals for Bridges Based on Statistical Analysis of National Bridge Inventory Data , 2015 .

[11]  Luís C. Neves,et al.  Incorporating local environmental factors into railway bridge asset management , 2016 .

[12]  Jamshid Mohammadi,et al.  ESTIMATING THE FUTURE CONDITION OF HIGHWAY BRIDGE COMPONENTS USING NATIONAL BRIDGE INVENTORY DATA , 2004 .

[13]  Yi Jiang.  Application and Comparison of Regression and Markov Chain Methods in Bridge Condition Prediction and System Benefit Optimization , 2010 .

[14]  Xi-la Liu,et al.  Shear behaviour of RC beams with corrosion damaged partial length , 2012 .

[15]  R. Marques,et al.  Road-Network Development in Quickly Growing Economies: Brazilian Case Study MG-050 , 2015 .

[16]  George Morcous,et al.  LIFE-CYCLE ASSESSMENT OF HIGHWAY BRIDGES , 2002 .

[17]  W. Hyman,et al.  Bridge Management Systems for Transportation Agency Decision Making , 2009 .

[18]  Hongwei Lin,et al.  The bond behavior between concrete and corroded steel bar under repeated loading , 2017 .

[19]  Yew-Chaye Loo,et al.  Typical deterministic and stochastic bridge deterioration modelling incorporating backward prediction model , 2013 .

[20]  Alexander Paz,et al.  Estimating Bridge Deterioration for Small Data Sets Using Regression and Markov Models , 2016 .