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.

Establishing MR&R Costs for a Network-Level Bridge Management System

1998 ◽  
Vol 1642 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Teresa M. Adams ◽  
Joseph F. Barut
Keyword(s):  
Management System ◽  
Multiple Comparisons ◽  
Cost Data ◽  
Bridge Management ◽  
Bridge Management System ◽  
Historical Cost ◽  
Bridge Maintenance ◽  
The Cost ◽  
Condition State ◽  
Relative Variability

The development of standardized maintenance, repair, and rehabilitation (MR&R) cost data for a network-level bridge management system (BMS) is presented. The Pontis BMS requires several data inputs, including the agency’s costs to perform bridge maintenance actions. Most states that are implementing Pontis do not have historical cost data standardized according to MR&R action, element, and condition state as required. The development of a questionnaire for collecting MR&R costs is described. The questionnaire was used to collect the estimated costs of MR&R actions on 25 bridge elements. Standard definitions of the physical characteristics for the elements were developed. Direct and indirect factors that influence MR&R costs were identified and organized into scenarios corresponding to the extreme minimum and maximum costs. The cost data collected by the questionnaire were analyzed. Procedures for assessing the variability of the estimated costs are presented. The coefficient of variation was used to measure the relative variability of estimated costs. One-way analysis of variance was used to assess the variation in estimated costs among the elements and MR&R actions. A multiple comparisons with the best analysis was used to identify certain elements and MR&R actions with greatest and least variations in cost. The results of this paper include recommended costs for the MR&R actions on 25 elements for the state of Wisconsin.

Indices for Fast Assessment of Bridge Condition in Taiwan

2015 ◽  
Vol 752-753 ◽  
pp. 689-697
Author(s):  
Nie Jia Yau ◽  
Hsien Ke Liao
Keyword(s):  
Natural Disasters ◽  
Management System ◽  
Visual Inspection ◽  
Site Investigation ◽  
Bridge Management ◽  
Bridge Management System ◽  
Traffic Loads ◽  
Collapse Resistance ◽  
Flood Resistance ◽  
Inspection Data

Developed in 2000, the Taiwan Bridge Management System (TBMS) is an internet-based, nation-wide bridge management system used by all of the bridge management agencies in Taiwan. Currently, the TBMS has an inventory of more than 24,300 bridges with 14 years of visual inspection data and maintenance records. The inspection data of each bridge are input into the TBMS at least once per two years. In order to have a fast assessment of bridge condition in resisting natural disasters and traffic loads, five indices are established in this research: (1) Degree of flood resistance (DF), (2) Degree of mudflow resistance (DM), (3) Degree of earthquake resistance (DE), (4) Degree of loads resistance (DL), and (5) Degree of collapse resistance (DC). Calculation of these five indices is based on the inventory and visual inspection data of each bridge without further thorough site investigation. These indices are used for screening or sieving bridges out of the TBMS inventory that are potentially vulnerable to natural disasters or traffic loads, thus maintenance efforts can be put on such bridges to improve the efficiency of bridge management.

OPERATIONAL STATE OF BRIDGES OF UKRAINE

2019 ◽  
pp. 57-68
Author(s):  
Larysa Bodnar ◽  
Petro Koval ◽  
Sergii Stepanov ◽  
Liudmyla Panibratets
Keyword(s):  
Management System ◽  
The State ◽  
Operating Conditions ◽  
Bridge Management ◽  
Bridge Management System ◽  
Program Complex ◽  
Operating Condition ◽  
Software Complex ◽  
Automatic Mode ◽  
The Status

A significant part of Ukrainian bridges on public roads is operated for more than 30 years (94 %). At the same time, the traffic volume and the weight of vehicles has increased significantly. Insufficient level of bridges maintenance funding leads to the deterioration of their technical state. The ways to ensure reliable and safe operation of bridges are considered. The procedure for determining the predicted operational status of the elements and the bridge in general, which has a scientific novelty, is proposed. In the software complex, Analytical Expert Bridges Management System (AESUM), is a function that allows tracking the changes in the operational status of bridges both in Ukraine and in each region separately. The given algorithm of the procedure for determining the predicted state of the bridge using a degradation model is described using the Nassie-Schneidermann diagram. The model of the degradation of the bridge performance which is adopted in Ukraine as a normative one, and the algorithm for its adaptation to the AESUM program complex with the function to ensure the probabilistic predicted operating condition of the bridges in the automatic mode is presented. This makes it possible, even in case of unsatisfactory performance of surveys, to have the predicted lifetime of bridges at the required time. For each bridge element it is possible to determine the residual time of operation that will allow predict the state of the elements of the structure for a certain period of time in the future. Significant interest for specialists calls for the approaches to the development of orientated perspective plans for bridge inspection and monitoring of changes in the operational status of bridges for 2009-2018 in Ukraine. For the analysis of the state of the bridge economy, the information is available on the distribution of bridges by operating state related to the administrative significance of roads, by road categories and by materials of the structures. Determining the operating state of the bridge is an important condition for making the qualified decisions as regards its maintenance. The Analytical Expert Bridges Management System (AESUM) which is implemented in Ukraine, stores the data on the monitoring the status of bridges and performs the necessary procedures to maintain them in a reliable and safe operating condition. An important result of the work is the ability to determine the distribution of bridges on the public roads of Ukraine, according to operating conditions established in the program complex of AESUM, which is presented in accordance with the data of the current year. In conditions of limited funding and in case of unsatisfactory performance of surveys, it is possible to make the reasonable management decisions regarding the repair and the reconstruction of bridges. Keywords: bridge management system, operating condition, predicted operating condition, model of degradation, bridge survey plan, highway bridge.

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