Browse > Article
http://dx.doi.org/10.12652/Ksce.2021.41.4.0417

Prediction of Life Expectancy of Asphalt Road Pavement by Region  

Song, Hyun Yeop (Hanbat National University)
Choi, Seung Hyun (Hanbat National University)
Han, Dae Seok (Korea Institute of Civil Engineering and Building Technology ․)
Do, Myung Sik (Hanbat National University)
Publication Information
KSCE Journal of Civil and Environmental Engineering Research / v.41, no.4, 2021 , pp. 417-428 More about this Journal
Abstract
Since future maintenance cost estimation of infrastructure involves uncertainty, it is important to make use of a failure prediction model. However, it is difficult for local governments to develop accurate failure prediction models applicable to infrastructure due to a lack of budget and expertise. Therefore, this study estimated the life expectancy of asphalt road pavement of national highways using the Bayesian Markov Mixture Hazard model. In addition, in order to accurately estimate life expectancy, environmental variables such as traffic volume, ESAL (Equivalent Single Axle Loads), SNP (Structural Number of Pavement), meteorological conditions, and de-icing material usage were applied to retain reliability of the estimation results. As a result, life expectancy was estimated from at least 13.09 to 19.61 years by region. By using this approach, it is expected that it will be possible to estimate future maintenance cost considering local failure characteristics.
Keywords
Bayesian Markov Mixture Hazard model; Road pavements; Life expectancy; Environmental variable;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Bayes, T. and Price, R. (1763). "An essay towards solving a problem in the doctrine of chance." By the late Revision. Bayes, F.R.S. communicated by Mr. Price, in a letter to John Canton, A.M.F.R.S., Philosophical Transactions of the Royal Society of London, Vol. 53, pp. 370-418.   DOI
2 Geweke, J. (1992). Evaluating the accuracy of sampling-based approaches to calculating posterior moments, Handbook of Bayesian Statistics 4, eds. Bernardo, J. M., Berger, J. O., Dawid, A. P. and Smith, A. F. M., Clarendon Press, Oxford, UK, pp. 169-193.
3 Han, D. S., Kaito, K., Kobayashi, K. and Aoki, K. (2016). "Performance evaluation of advanced pavement materials by bayesian markov mixture hazard model." KSCE Journal of Civil Engineering, KSCE, Vol. 20, No. 2, pp. 729-737.   DOI
4 Han, D. S., Kobayashi, K. and Do, M. S. (2013). "Section-based multifunctional calibration method for pavement deterioration forecasting model." KSCE Journal of Civil Engineering, KSCE, Vol. 17, No. 2, pp. 386-394.   DOI
5 Kim, S. H. and Kim, N. S. (2006). "Development of performance prediction models in flexible pavement using regression analysis method." KSCE Journal of Civil Engineering, KSCE, Vol. 10, No. 2, pp. 91-96.   DOI
6 Lancaster, T. (1990). The econometric analysis of transition data, Cambridge University Press, N.Y., USA.
7 Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. and Teller, H. (1953). "Equations of state calculations by fast computing machines." Journal of Chemical Physics, Vol. 21, No. 6, pp. 1087-1091.   DOI
8 Do, M. S. (2011). "Comparative analysis on mean life reliability with functionally classified pavement sections." KSCE Journal of Civil Engineering, KSCE, Vol. 15, No. 2, pp. 261-270.   DOI
9 Train, K. E. (2009). Discrete choice methods with simulation (Second edition), Cambridge University Press, N.Y., USA.
10 Choi, S. H., Do, M. S., Han, D. S., Sim, H. J. and Chae, C. D. (2019). "Estimation of road pavements life expectancy by bayesian markov mixture hazard model." International Journal of Highway Engineering, Vol. 21, No. 6, pp. 57-67 (in Korean).   DOI
11 Han, D. S., Kaito, K. and Kobayashi, K. (2014). "Application of Bayesian estimation method with Markov hazard model to improve deterioration forecasts for infrastructure asset management." KSCE Journal of Civil Engineering, KSCE, Vol. 18, No. 7, pp. 2107-2119.   DOI
12 Hastings, W. K. (1970). "Monte Carlo sampling methods using Markov chains and their applications." Biometrika, Vol. 57, No. 1, pp. 97-109.   DOI
13 Obama, K., Okada, K., Kaito, K. and Kobayashi, K. (2008). "Disaggregated hazard rates evaluation and bench-marking." Journal of Civil Engineering, JSCE, Vol. 64, No. 4, pp. 857-874. (in Japanese).
14 Tsuda, Y., Kaito, K., Aoki, K. and Kobayashi, K. (2006). "Estimating markovian transition probabilities for bridge deterioration forecasting." Journal of Structural Engineering and Earthquake Engineering, JSCE, Vol. 23, No. 2, pp. 241-256.
15 Prozzi, J. A. and Madanat, S. M. (2004). "Development of pavement performance models by combining experimental and field data." Journal of Infrastructure Systems, Vol. 10, No. 1, pp. 9-22.   DOI
16 Kaito, K., Kobayashi, K., Aoki, K. and Matsuoka, K. (2012). "Hierarchical Bayesian estimation of mixed hazard models." Journal of Civil Engineering, JSCE, Vol. 68, No. 4, pp. 255-271 (in Japanese).
17 Kobayashi, K., Kaito, K. and Nam, L. T. (2012). "A bayesian estimation method to improve deterioration prediction for infrastructure system with Markov chain model." International Journal of Architecture, Engineering and Construction, Vol. 1, No. 1, pp. 1-13.   DOI
18 Han, D. S. and Do, M. S. (2016). "Evaluation of Socio-environmental effects considering road service levels for transportation asset management." Journal of Testing and Evaluation, Vol. 44, No. 1, pp. 679-691.