Universidad Nacional Autónoma de Tayacaja Daniel Hernández Morillo - UNAT

Structural Evaluation and Predictive Modeling of Flexible Pavement in Rural Areas: A Case Study on the Puente Palca – Palca Road
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Keywords

Predictive model
Structural condition
Flexible pavement
Preventive maintenance
Pavement lifespan

How to Cite

Cárdenas Capcha, J. (2024). Structural Evaluation and Predictive Modeling of Flexible Pavement in Rural Areas: A Case Study on the Puente Palca – Palca Road. Llamkasun, 5(2), 02–12. https://doi.org/10.47797/llamkasun.v5i2.132

Abstract

This study aims to develop a predictive model for evaluating the structural condition of the asphalt layer and its impact on the serviceability of flexible pavement in the Puente Palca–Palca road, Huancavelica, Peru. The research focuses on 18 selected points along a 3-kilometer segment, employing techniques such as deflectometry, macrotexture analysis, skid resistance (CRD), degree of compaction, and the International Roughness Index (IRI). The study follows a quantitative, non-experimental, correlational-explanatory design, using non-linear regression models and multivariable analysis to predict the pavement's lifespan and functional capacity. The results indicate that compaction significantly affects deflectometry (R = 0.543), while asphalt content inversely influences macrotexture (R² = 0.5648). A critical reduction in surface texture (<1.0 mm) occurs when asphalt content exceeds 4.2%. Heavy traffic and climatic conditions further accelerate structural degradation, reducing pavement lifespan to 10-12 years without intervention. However, the predictive model extends this lifespan to 15 years, optimizing resources and lowering maintenance costs by 20%. The conclusion emphasizes that the developed predictive model for structural condition significantly impacts flexible pavement serviceability, improving its lifespan by 3-5 years and reducing repair costs, thereby enhancing safety and functionality in Huancavelica.

https://doi.org/10.47797/llamkasun.v5i2.132
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References

Ai, X., Cao, J., Feng, D., Gao, L., Hu, W., & Yi, J. (2022). Performance evaluation of recycled asphalt mixtures with various percentages of RAP from the rotary decomposition process. Construction and Building Materials, 321, 126406. https://doi.org/10.1016/j.conbuildmat.2022.126406

Aigner, E., Lackner, R., & Pichler, C. (2009). Multiscale Prediction of Viscoelastic Properties of Asphalt Concrete. Journal of Materials in Civil Engineering, 21(12), 771–780. https://doi.org/10.1061/(ASCE)0899-1561(2009)21:12(771)

Alamri, M., & Lu, Q. (2022). Investigation on the inclusion of reclaimed diluted epoxy asphalt pavement materials into hot mix asphalt. Construction and Building Materials, 361, 129710. https://doi.org/10.1016/j.conbuildmat.2022.129710

Amorim, S. I. R., Pais, J. C., Vale, A. C., & Minhoto, M. J. C. (2015). A model for equivalent axle load factors. International Journal of Pavement Engineering, 16(10), 881–893. https://doi.org/10.1080/10298436.2014.968570

Aroquipa, H. (2018). Project Management Model. Spanish Academy Editorial.

Aroquipa, H. (2024). Seismic resistance in structural systems: Analysis using PML and PAE (1st ed.). UNAT Editorial Fund. https://doi.org/https://doi.org/10.56224/ediunat.55

Aroquipa, H., Hurtado, A., Angel, C., Aroquipa, A., Gamarra, A., & Almeida Del Savio, A. (2023). A cost-benefit analysis for the appraisal of social and market prices in the probabilistic seismic risk assessment of building portfolios: A methodology for the evaluation of disaster risk reduction programs. International Journal of Disaster Risk Reduction, 90(October 2022), 103637. https://doi.org/10.1016/j.ijdrr.2023.103637

Aroquipa, H., Hurtado, A., Leon, F., Gamarra, A., Angel, C., Olivera, A., Massa, L. A., & Paz, R. (2023). Simplified methodological approach for estimating the mean repair time of building portfolios directed to the development of seismic resilience policies, based on the distribution of resources. Journal of Building Pathology and Rehabilitation, 8(2), 72. https://doi.org/10.1007/s41024-023-00321-2

Aroquipa Velásquez, H. (2014). Construction processes of buildings and their environmental impacts in relation to clean and sustainable production.

Bi, Y., Guo, F., Zhang, J., Pei, J., & Li, R. (2021). Correlation Analysis of asphalt binder/asphalt mastic properties and dynamic modulus of asphalt mixture. Construction and Building Materials, 276, 122256. https://doi.org/10.1016/j.conbuildmat.2021.122256

Dan, H.-C., Yang, D., Liu, X., Peng, A.-P., & Zhang, Z. (2020). Experimental investigation on dynamic response of asphalt pavement using SmartRock sensor under vibrating compaction loading. Construction and Building Materials, 247, 118592. https://doi.org/10.1016/j.conbuildmat.2020.118592

Higuera-Sandoval, C. H., & Pacheco-Merchan, O. F. (2008). Pathology of articulated pavements. Faculty of Engineering, 17(25), 7–26.

Huang, B., Shu, X., Li, G., & Chen, L. (2007). Analytical Modeling of Three-Layered HMA Mixtures. International Journal of Geomechanics, 7(2), 140–148. https://doi.org/10.1061/(ASCE)1532-3641(2007)7:2(140)

Huang, Y.H. (2004). Pavement Analysis and Design. Pearson Prentice Hall.

Kwigizile, V., Mussa, R. N., & Selekwa, M. (2005). Connectionist Approach to Improving Highway Vehicle Classification Schemes. Transportation Research Record: Journal of the Transportation Research Board, 1917(1), 182–189. https://doi.org/10.1177/0361198105191700120

Le Bastard, C., Baltazart, V., Yide Wang, & Saillard, J. (2007). Thin-Pavement Thickness Estimation Using GPR With High-Resolution and Superresolution Methods. IEEE Transactions on Geoscience and Remote Sensing, 45(8), 2511–2519. https://doi.org/10.1109/TGRS.2007.900982

Le Bastard, C., Yide Wang, Baltazart, V., & Derobert, X. (2014). Time Delay and Permittivity Estimation by Ground-Penetrating Radar With Support Vector Regression. IEEE Geoscience and Remote Sensing Letters, 11(4), 873–877. https://doi.org/10.1109/LGRS.2013.2280500

Marcelino, P., de Lurdes Antunes, M., Fortunato, E., & Gomes, M. C. (2021). Machine learning approach for pavement performance prediction. International Journal of Pavement Engineering, 22(3), 341–354. https://doi.org/10.1080/10298436.2019.1609673

Miquel, M. P. (2006). Surface regularity analysis in paved roads. Journal of Construction, 5(2), 16–22.

Pradena, M., & Wolf, E. (2006). Implementation and Control of Maintenance on Unpaved Roads Using Level of Service. Journal of Construction, 5(1), 21–29.

Rodríguez Moreno, M., Theboux Zeballos, G., & González Vaccarezza, A. (2013). Probabilistic evaluation of asphalt pavement cracking on roads in Chile. Journal of Construction, 12(2), 152–165.

Song, L., & Yang, L. (2021). Governance innovation of occupational safety and health in China under the background of industry 4.0. Industrial Safety and Envi

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Copyright (c) 2024 Jesús Cárdenas Capcha

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