Reliability Importance as a Measure of Bridge Element Condition Index for Deteriorating Bridges

2019 ◽  
Vol 2673 (12) ◽  
pp. 327-338
Author(s):  
Sylvester Inkoom ◽  
John O. Sobanjo
Keyword(s):  
Asset Management ◽  
Condition Index ◽  
Performance Measure ◽  
Cost Models ◽  
Bridge Management ◽  
Expansion Joints ◽  
State Highway ◽  
Optimal Resource ◽  
Inspection Data ◽  
Bridge System

As a concerted effort to improve the outcomes of bridge asset management, state highway agencies and Departments of Transportation (DOT) often improve their modes of bridge performance assessment using advanced deterioration models, optimized cost models, and other multi-objective preservation analysis in bridge monitoring processes. This paper attempts to utilize reliability importance index of a bridge component as a performance measure of the criticality of each element or subsystem to the entire bridge system. This paper investigates three major concepts regarding the importance of bridge elements: (i) the contribution of individual bridge elements to the overall reliability of the bridge system, (ii) the effect of critical elements on bridge deterioration, and (iii) the rank of the importance of elements and the potential economic consequence of their failure for optimal resource allocation. Computational methodologies are applied to legacy inspection data for bridges monitored over 20 years to evaluate the probability of failure of certain bridge elements. Based on the reliability importance criterion, the superstructure and substructure elements were considered to be critical to the survival of bridges. Bridge management and miscellaneous elements (such as expansion joints, railings, and sign structures), though important, did not generally contribute to the overall deterioration of the bridge.

Bridge Health Index: Study of Element Condition States and Importance Weights

2017 ◽  
Vol 2612 (1) ◽  
pp. 67-75 ◽  
Author(s):  
Sylvester Inkoom ◽  
John O. Sobanjo ◽  
Paul D. Thompson ◽  
Richard Kerr ◽  
Richard Twumasi-Boakye
Keyword(s):  
Management System ◽  
Support Network ◽  
Cost Models ◽  
Bridge Management ◽  
Health Index ◽  
Bridge Management System ◽  
Government Accounting ◽  
Index Study ◽  
Inspection Data ◽  
Condition State

The AASHTO Pontis bridge management system has been used to support network-level and project-level decision making on the condition and functional obsolescence of bridges. State departments of transportation often develop bridge inspection data collection methods, deterioration models, cost models, and other preservation analysis capabilities to comply with the requirements of the federal Government Accounting Standards Board. The bridge health index (BHI) in the Pontis bridge management system has been used in the evaluation of the condition of bridges and elements at the project and network levels. This paper investigates three issues in the computation of the BHI: the effects of using linear and nonlinear scales for the condition state weights when computing the element health index (EHI); the application of amplification weights to EHI values to emphasize bridge elements in bad condition; and the development of element weights based on element replacement costs, element long-term costs, element vulnerability to hazard risks, and a combination of these measures. Historical condition data from element-based inspection were used to evaluate these effects at the network level.

Statistical Analysis of Bridge Management System Inspection Data

2019 ◽  
Author(s):  
Ahmed M. Abdelmaksoud ◽  
Tracy C. Becker ◽  
Georgios P. Balomenos
Keyword(s):  
Statistical Analysis ◽  
Condition Index ◽  
Multivariate Regression Analysis ◽  
Prediction Equation ◽  
Maintenance Scheduling ◽  
Bridge Management ◽  
Bridge Inspection ◽  
Bridge Management System ◽  
Inspection And Maintenance ◽  
Inspection Data

<p>Bridge inspection is essential for sustaining safe and well-performing transportation networks. The Ministry of Transportation of Ontario (MTO) bi-yearly inspects over 2800 bridges in Ontario, Canada. Then assigns each bridge a Bridge Condition Index (BCI) representing its performance level and required rehabilitation<span>. </span>As this is a time and resources consuming practice, this study explores the BCI trends which can allow a better control on inspection and maintenance scheduling. First, statistical analysis is conducted to identify the correlation of the bridge parameters with the BCI. The analysis reveals that the main parameters associated with BCI are bridge age, and time since last major and minor maintenances. Then, multivariate regression analysis is performed to establish a BCI prediction equation function of these parameters. The proposed framework can supplement existing practices for smarter inspection and maintenance scheduling.</p>

Bridge Management for the 21st Century

2000 ◽  
Vol 1696 (1) ◽  
pp. 197-203 ◽  
Author(s):  
James E. Roberts ◽  
Richard Shepard
Keyword(s):  
Performance Measure ◽  
Bridge Management ◽  
Health Index ◽  
Element Level ◽  
The Past ◽  
Bridge Maintenance ◽  
Asset Value ◽  
Numerical Rating ◽  
Improved Performance ◽  
Inspection Data

Bridge management has been a subject of intense interest and development for the past 10 years. In support of improved bridge management, FHWA funded the development of the Pontis bridge computer program, which is now in use by approximately 40 of the 50 states. In addition, many new guide specifications have been produced to assist bridge managers in their efforts to better manage the nation’s aging bridge inventory. The AASHTO Subcommittee on Bridges and Structures has taken the lead along with FHWA in implementing the improved bridge management systems. California and a few other states have been critical of the current ranking system for bridge maintenance and have been working to develop an improved performance measure. The bridge health index (HI), an improved and more comprehensive numerical rating system that uses the element inspection data to determine the remaining asset value of a bridge or network of bridges, is discussed. The HI is more consistent with the element-level evaluation data collected and reported in the Pontis program. Examples of the application of the HI are included.

scholarly journals Suggestions for improved reinforced concrete half-joint bridge inspection in England

2018 ◽  
Vol 199 ◽  
pp. 06004
Author(s):  
Pieter Desnerck ◽  
Pierfrancesco Valerio ◽  
Janet M Lees ◽  
Neil Loudon
Keyword(s):  
Reinforced Concrete ◽  
Asset Management ◽  
Data Gathering ◽  
Bridge Management ◽  
Additional Information ◽  
Current State ◽  
Defect Groups ◽  
Interim Management ◽  
History Of ◽  
Inspection Data

Asset management databases play a crucial role in the management of existing infrastructure assets. Highways England (HE) has a long history of using bridge management software to record the current state of bridges and to guide maintenance schemes and interventions. Reinforced concrete half-joints are amongst the most challenging structures to inspect and repair due to their susceptibility to deterioration and construction type. Hence, they require particular attention within asset management programmes. An Interim Management Strategy was developed by HE to identify all the structures on the Highways England road network with half-joint elements. These half-joint structures were then subjected to a special inspection regime. Out of the 428 half-joint structures with inspection data, 252 structures had defects associated with four existing HE defect classes. A review of the inspection database with a focus on half-joints led to an alternative classification of half-joint related defects based on a revised set of Defect Classes, the introduction of Defect Groups and the extraction of Defect Types specifically observed in half-joints. Using this new classification, the most common half-joint Defect Groups were found to be cracking, corrosion, spalling and deterioration mechanisms. In about half of the structures cracking and corrosion tended to be observed together. Correlations were also shown to exist between structural and deterioration, and constructional Defect Classes, emphasising the need for quality control and proper workmanship. Recommendations to address shortcomings in current inspection practice are proposed. Clearer defect definitions and decision-tree guidance for inspectors could enhance the consistency and repeatability of inspection data gathering thereby overcoming some of the limitations of subjective classifications. Acquiring additional information about the observed crack details including zonal information, crack patterns, crack extent, crack orientations and widths combined with local and global pictorial evidence would also be advantageous. This could then provide the basis for the automatic processing and identification of structures with specific half-joint related defects. In this way, asset managers would be better able to allocate limited resources to the most critical structures.

Development of Structural Condition Index to Support Pavement Maintenance and Rehabilitation Decisions at Network Level

2003 ◽  
Vol 1827 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Zhanmin Zhang ◽  
German Claros ◽  
Lance Manuel ◽  
Ivan Damnjanovic
Keyword(s):  
Evaluation Method ◽  
Surface Condition ◽  
Condition Index ◽  
Structural Condition ◽  
Pavement Management ◽  
Structural Deformation ◽  
Pavement Maintenance ◽  
State Highway ◽  
Structural Reinforcement ◽  
Maintenance And Rehabilitation

Every year, state highway agencies apply large amounts of seal coats and thin overlays to pavements to improve the surface condition, but these measures do not successfully address the problem. Overall pavement condition continues to deteriorate because of the structural deformation of pavement layers and the subgrade. To make effective decisions about the type of treatment needed, one should take into consideration the structural condition of a pavement. Several different structural estimators can be calculated by using falling weight deflectometer data and information stored in the Pavement Management Information System (PMIS) at the Texas Department of Transportation. The analysis considers pavement modulus and structural number as the structural estimators of a pavement. The evaluation method is based on the sensitivity of the structural estimators to deterioration descriptors. The deterioration per equivalent single-axle load of all major scores stored in the Texas PMIS is proposed as the primary indicator of pavement deterioration. In addition, the use of the structural condition index is recommended as a screening tool to discriminate between pavements that need structural reinforcement and those that do not. This index is calibrated for use in maintenance and rehabilitation analysis at the network level.

Implementation of Virtual Reality in Routine Bridge Inspection

2003 ◽  
Vol 1827 (1) ◽  
pp. 29-35 ◽  
Author(s):  
David V. Jáuregui ◽  
Kenneth R. White
Keyword(s):  
Virtual Reality ◽  
Easy Access ◽  
Bridge Management ◽  
Bridge Inspection ◽  
Image Creation ◽  
Bridge Inspections ◽  
Recorded Data ◽  
Media Types ◽  
Inspection Data ◽  
Selection Of

The innovative use of QuickTime Virtual Reality (QTVR) and panoramic image–creation utilities for recording field observations and measurements during routine bridge inspections is reported. A virtual reality approach provides the ability to document a bridge’s physical condition by using different media types at a significantly higher level of detail than is possible in a written bridge inspection report. Digitally recorded data can be stored on compact disc for easy access before, during, or after an inspection. The development of a QTVR bridge record consists of four major steps: selection of the camera stations, acquisition of the digital images, creation of cylindrical or cubic panoramas, and rendering of the QTVR file. Specific details related to these steps are provided, as applied to various bridge inspection projects. The potential impact of QTVR on bridge management—in which routine inspection data are a factor in making decisions regarding the future maintenance, rehabilitation, or replacement of a bridge—is discussed.

The Executive Support System of Ontario, Canada

2005 ◽  
Vol 1933 (1) ◽  
pp. 26-34
Author(s):  
Joseph A. Guerre ◽  
William E. Robert ◽  
Alison Bradbury ◽  
Michael Goodale
Keyword(s):  
Support System ◽  
Asset Management ◽  
System Integration ◽  
Network Performance ◽  
Business Processes ◽  
Functional Class ◽  
Management Systems ◽  
Analysis Tool ◽  
Bridge Management ◽  
Management Concepts

The Ministry of Transportation of Ontario (MTO), Canada, is currently implementing an asset management business framework (AMBF). The AMBF provides the ministry with an ambitious blueprint for incorporating asset management concepts into its existing business processes. A key component in the AMBF is the ability to integrate results from the ministry's existing management systems. In support of the AMBF, MTO has developed a prototype executive support system (ESS). The ESS is a what-if analysis tool that predicts network performance over time using data from the ministry's pavement and bridge management systems. It enables decision makers to evaluate the relationship between performance and budget and to view results by region, corridor, or functional class. This paper presents the analytical approach used to develop the ESS and describes how it was implemented by MTO. The ESS uses a candidate-based approach to system integration, which enables the integration of any management system capable of generating work candidates and estimating their impact on a defined set of performance measures. The ESS brings together data from these systems and performs an additional level of cross-asset economic optimizations, taking into account user-defined operating assumptions. Although much work has recently been done on the integration of pavement and bridge systems, the objective of this paper is to present a practical example implemented by MTO.

Quality of Element-Level Bridge Inspection Data

2020 ◽  
Vol 2674 (2) ◽  
pp. 252-261
Author(s):  
Glenn A. Washer ◽  
Mohammad M. Hammed ◽  
Paul Jensen ◽  
Robert J. Connor
Keyword(s):  
Load Capacity ◽  
Field Trials ◽  
Bridge Management ◽  
Bridge Inspection ◽  
Element Level ◽  
Level Data ◽  
Truck Load ◽  
Inspection Data ◽  
Highway System

Bridge inspection results provide input for several important functions such as maintenance, repair, and rehabilitation, bridge load capacity ratings, truck load routing/permitting, and future safety/condition predictions. As a result, the quality and reliability of inspection data are important for bridge management and to ensure the safety and serviceability of bridges. Element-level data collection has been required nationwide for bridges on the National Highway System since 2014, and therefore is relatively new to some bridge owners. The objective of the research reported here was to assess the quality of element-level bridge inspection data by comparing bridge inspection results between different bridge inspectors assessing the same bridges. This paper reports results from two research studies completed to collect data on the quality (i.e., variability) of element-level inspection data. Results of field trials indicated that there was significant variability in the data for bridge elements reported in the study. Based on these data, the element-level inspection results were widely dispersed—the smallest coefficient of variation calculated from the current studies was 18%, but typical values were found to be greater than 50% in most cases, and often greater than 100%. These data provide examples from a series of field trials that illustrate the need for improving the quality of element-level inspections to ensure the reliability of the data provided.

The Information System for Bridge Networks Condition Monitoring and Prediction

2012 ◽  
Vol 5 (1) ◽  
pp. 1-18
Author(s):  
Khalid Aboura ◽  
Bijan Samali
Keyword(s):  
Information System ◽  
Condition Monitoring ◽  
New South ◽  
Management Systems ◽  
Maintenance Optimization ◽  
Bridge Management ◽  
Bridge Inspection ◽  
South Wales ◽  
Bridge Networks ◽  
Inspection Data

This paper introduces an information system for estimating lifetime characteristics of elements of bridges and predicting the future conditions of networks of bridges. The Information System for Bridge Networks Condition Monitoring and Prediction was developed for the Roads and Traffic Authority of the state of New South Wales, Australia. The conceptual departure from the standard bridge management systems is the use of a novel stochastic process built out of the gamma process. The statistical model was designed for the estimation of infrastructure lifetime, based on the analysis of more than 15 years of bridge inspection data. The predictive curve provides a coherent mathematical model for conducting target level constrained and funding based maintenance optimization.

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