Abstract
This study aims at developing pay adjustments for initial smoothness of asphalt pavement overlay using life-cycle cost analysis (LCCA). The relationship between the initial International Roughness Index (IRI) and pavement life based on the threshold of surface distress index (SDI) was developed to calculate the pay adjustment using LCCA. It was found that the terminal IRI values when pavement overlay life was reached based on the SDI threshold of poor condition had an average value of 128 in./mile (2.02 m/km) with standard deviation of 15 in./mile (0.24 m/km). The pay adjustments were significantly affected by the assumption of analysis period in LCCA considering single or successive overlay applications. The Bayesian approach with Markov Chain Monte Carlo (MCMC) methods was used to develop the probabilistic model between the expected pavement life and the initial IRI. The probabilistic distribution of pay adjustments was presented when the uncertainty was considered with respect to the effect of initial IRI on pavement life and the assumption of overlay sequence. Compared with the pay adjustment obtained from the deterministic approach, the probabilistic analysis resulted in a similar pay adjustment for the case of single overlay but a greater pay adjustment for the case of successive overlays. The proposed analysis approach can be implemented by agencies in decision making of quality assurance based on actual practice of maintenance strategy.
| Original language | English (US) |
|---|---|
| Journal | Journal of Testing and Evaluation |
| Volume | 48 |
| Issue number | 2 |
| DOIs | |
| State | Published - Mar 1 2020 |
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All Science Journal Classification (ASJC) codes
- Mechanics of Materials
- Mechanical Engineering
- Materials Science(all)
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Life-cycle cost analysis of pay adjustment for initial smoothness of asphalt pavement overlay. / Wang, Hao; Wang, Zilong; Zhao, Jingnan; Qian, Junyu.
In: Journal of Testing and Evaluation, Vol. 48, No. 2, 01.03.2020.Research output: Contribution to journal › Article
TY - JOUR
T1 - Life-cycle cost analysis of pay adjustment for initial smoothness of asphalt pavement overlay
AU - Wang, Hao
AU - Wang, Zilong
AU - Zhao, Jingnan
AU - Qian, Junyu
PY - 2020/3/1
Y1 - 2020/3/1
N2 - This study aims at developing pay adjustments for initial smoothness of asphalt pavement overlay using life-cycle cost analysis (LCCA). The relationship between the initial International Roughness Index (IRI) and pavement life based on the threshold of surface distress index (SDI) was developed to calculate the pay adjustment using LCCA. It was found that the terminal IRI values when pavement overlay life was reached based on the SDI threshold of poor condition had an average value of 128 in./mile (2.02 m/km) with standard deviation of 15 in./mile (0.24 m/km). The pay adjustments were significantly affected by the assumption of analysis period in LCCA considering single or successive overlay applications. The Bayesian approach with Markov Chain Monte Carlo (MCMC) methods was used to develop the probabilistic model between the expected pavement life and the initial IRI. The probabilistic distribution of pay adjustments was presented when the uncertainty was considered with respect to the effect of initial IRI on pavement life and the assumption of overlay sequence. Compared with the pay adjustment obtained from the deterministic approach, the probabilistic analysis resulted in a similar pay adjustment for the case of single overlay but a greater pay adjustment for the case of successive overlays. The proposed analysis approach can be implemented by agencies in decision making of quality assurance based on actual practice of maintenance strategy.
AB - This study aims at developing pay adjustments for initial smoothness of asphalt pavement overlay using life-cycle cost analysis (LCCA). The relationship between the initial International Roughness Index (IRI) and pavement life based on the threshold of surface distress index (SDI) was developed to calculate the pay adjustment using LCCA. It was found that the terminal IRI values when pavement overlay life was reached based on the SDI threshold of poor condition had an average value of 128 in./mile (2.02 m/km) with standard deviation of 15 in./mile (0.24 m/km). The pay adjustments were significantly affected by the assumption of analysis period in LCCA considering single or successive overlay applications. The Bayesian approach with Markov Chain Monte Carlo (MCMC) methods was used to develop the probabilistic model between the expected pavement life and the initial IRI. The probabilistic distribution of pay adjustments was presented when the uncertainty was considered with respect to the effect of initial IRI on pavement life and the assumption of overlay sequence. Compared with the pay adjustment obtained from the deterministic approach, the probabilistic analysis resulted in a similar pay adjustment for the case of single overlay but a greater pay adjustment for the case of successive overlays. The proposed analysis approach can be implemented by agencies in decision making of quality assurance based on actual practice of maintenance strategy.
UR - http://www.scopus.com/inward/record.url?scp=85065133456&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85065133456&partnerID=8YFLogxK
U2 - https://doi.org/10.1520/JTE20170529
DO - https://doi.org/10.1520/JTE20170529
M3 - Article
VL - 48
JO - Journal of Testing and Evaluation
JF - Journal of Testing and Evaluation
SN - 0090-3973
IS - 2
ER -