Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

Piyatrapoomi, N and Kumar, Arun and Weligamage, Justin (2005) Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation. [Conference Paper]

Abstract

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

Additional Information

Item Type: Conference Paper
Collection: CRC for Construction Innovation
Keywords: CRC for Construction Innovation; Program C : Delivery Management of Built Assets; Project 2003-029-C : Maintenance Cost Prediction for Roads
Date Deposited: 11 Mar 2014 03:16
Last Modified: 11 Mar 2014 03:20
Copyright Owner: Copyright 2005 Icon.Net Pty Ltd
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URI: https://digitalcollections.qut.edu.au//id/eprint/1848
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