QUANTIFYING UNCERTAINTY IN BRIDGE CONDITION ASSESSMENT DATA

The effectiveness of decisions in bridge management systems is based on the quality of data obtained regarding various processes in the systems. Hence, data play a crucial role in bridge management. In general, data collected has some amount of associated uncertainty. In order to assess the impact of this uncertainty on decisions, the uncertainty in the data should be quantified. In other words, by determining the level of uncertainty, we are judging the quality of the data, which is important for making effective decisions in bridge management systems. This paper describes a procedure for measuring the level of uncertainty in bridge condition assessment data. First, a bridge deterioration model was applied to historical data to estimate the current condition of a bridge and compared to current data. Next, reliability theory was applied to estimate the structural reliability of the bridge, again based on both historical and present data. Finally, the reliability of the bridge was compared to the results obtained from the deterioration model, using a coefficient of correlation. Because the deterioration model used Markov chains, which are probabilistic, and the reliability results are also reported as probabilities, the results can be compared.

• Record URL:
  http://www.ctre.iastate.edu/pubs/midcon/Deshmukh.pdf
• 
• Supplemental Notes:
  • The proceedings can be located on-line at www.ctre.iastate.edu/.
• Corporate Authors:

  Iowa State University, Ames

  Center for Transportation Research and Education, 2711 South Loop Drive
  Ames, IA  United States  50011-8664
• Authors:
  • Deshmukh, P
  • Bernhardt, KLS
• Conference:
  • Mid-Continent Transportation Symposium 2000
  • Location: Ames, Iowa
  • Date: 2000-5-15 to 2000-5-16
• Publication Date: 2000

Language

• English

Media Info

• Features: References; Tables;
• Pagination: p. 138-141

Subject/Index Terms

• TRT Terms: Bridge management systems; Condition surveys; Correlation analysis; Data collection; Data quality; Deterioration; Markov chains; Mathematical models; Measurement; Probability; Uncertainty
• Uncontrolled Terms: Structural reliability
• Subject Areas: Bridges and other structures; Data and Information Technology; Design; Highways; I24: Design of Bridges and Retaining Walls;

Filing Info

• Accession Number: 00793285
• Record Type: Publication
• ISBN: 0965231046
• Files: TRIS
• Created Date: May 25 2000 12:00AM