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Assessment of Maintenance Strategies and Performance Prediction for Urban Roads Using IRI and HDM-4 Models | ||
| Journal of Rehabilitation in Civil Engineering | ||
| مقاله 4، دوره 13، شماره 2 - شماره پیاپی 38، مرداد 2025، صفحه 64-74 اصل مقاله (772.86 K) | ||
| نوع مقاله: Regular Paper | ||
| شناسه دیجیتال (DOI): 10.22075/jrce.2024.32883.1968 | ||
| نویسندگان | ||
| Harinder D1؛ Yugendar Poojari* 2؛ Venkatesh Noolu3؛ Vamsi Dachepalli4 | ||
| 1Assistant Professor, Department of Civil Engineering, VNRVJIET-Hyderabad, India | ||
| 2Assistant Professor, Civil Engineering Department, Ghani Khan Choudhury Institute of Engineering and Technology, West Bengal, India | ||
| 3Assistant Professor, Sreenidhi Institute of Science and Technology, Hyderabad, India | ||
| 4PG Student, VNRVJIET-Hyderabad, Sweco India PVT Ltd. Road Engineering, Bangalore, India | ||
| تاریخ دریافت: 14 دی 1402، تاریخ بازنگری: 15 تیر 1403، تاریخ پذیرش: 25 مرداد 1403 | ||
| چکیده | ||
| Globally emerging markets need a well distributed, safe, and efficient transportation system. Analyzing, pavement management and maintaining such a dense highway networks and transportation systems comes with its own complications. Out of the many available techniques globally i.e. Highway Development and Management (HDM-4) can be adopted to achieve such a daunting task. In HDM-4, pavement distress initiation and progression can be predicted using HDM-4 pavement deterioration models using different parameters like traffic, climate, pavement structure, and composition combinations. However, before implementation, such HDM-4 model should be calibrated and validated. Since, in-situ variables greatly influence the rate at which each pavement distress initiates and propagates. The paper focuses on distress factors i.e. rutting, fatigue, pothole, and patching on a highway of two and four-lanes using HDM-4 model. International Roughness Index (IRI) values are computed using MERLIN instrument. The results are given as input to HDM-4 software for the predicting initiation and progression of discomfort for the present and future traffic. Based on the IRI values, priority ranking are given for road maintenance, higher the IRI value, higher is the priority for road maintenance and vice-versa. Findings from this study can be used to improve road networks, traffic safety, and applicability for comparable road conditions. | ||
تازه های تحقیق | ||
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| کلیدواژهها | ||
| Rutting؛ Fatigue؛ Pothole؛ Patching؛ IRI | ||
| مراجع | ||
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[1] Deori S, Choudhary R, Tiwari D, Gangopadhyay S. Calibration of HDM-4 models for Indian conditions of flexible pavement having modified bitumen in wearing course. Int J Pavement Eng 2018;19:772–85. https://doi.org/10.1080/10298436.2016.1208196.
[2] Jain SS, Aggarwal S, Parida M. HDM-4 Pavement Deterioration Models for Indian National Highway Network. J Transp Eng 2005;131:623–31. https://doi.org/10.1061/(ASCE)0733-947X(2005)131:8(623).
[3] Yildirim Y. Polymer modified asphalt binders. Constr Build Mater 2007;21:66–72. https://doi.org/10.1016/j.conbuildmat.2005.07.007.
[4] Čutura B, Mladenović G, Mazić B, Lovrić I. Application of the HDM-4 Model on Local Road Network: Case Study of the Herzegovina-Neretva Canton in Bosnia and Herzegovina. Transp Res Procedia 2016;14:3021–30. https://doi.org/10.1016/j.trpro.2016.05.441.
[5] Jiao X, Bienvenu M. Field Measurement and Calibration of HDM-4 Fuel Consumption Model on Interstate Highway in Florida. Int J Transp Sci Technol 2015;4:29–45. https://doi.org/10.1260/2046-0430.4.1.29.
[6] Ognjenovic S, Krakutovski Z, Vatin N. Calibration of the Crack Initiation Model in HDM 4 on the Highways and Primary Urban Streets Network in Macedonia. Procedia Eng 2015;117:559–67. https://doi.org/10.1016/j.proeng.2015.08.214.
[7] Thube DT. Highway Development and Management Model (HDM-4): calibration and adoption for low-volume roads in local conditions. Int J Pavement Eng 2013;14:50–9. https://doi.org/10.1080/10298436.2011.606320.
[8] Vamsi D, Harinder D. Assessment of Performance and Maintenance of Flexible Pavement Using KENLAYER and HDM-4. IOP Conf Ser Earth Environ Sci 2022;982:012055. https://doi.org/10.1088/1755-1315/982/1/012055.
[9] Kumar JA, Harinder D, Vamshi D. Evaluation of flexible pavement overlay using highway development and management (HDM-4), 2023, p. 020009. https://doi.org/10.1063/5.0132942.
[10] Al‐Mansour AI, Sinha KC, Kuczek T. Effects of Routine Maintenance on Flexible Pavement Condition. J Transp Eng 1994;120:65–73. https://doi.org/10.1061/(ASCE)0733-947X(1994)120:1(65).
[11] Hall KT, Simpson AL, Correa CE. LTPP data analysis: Effectiveness of maintenance and rehabilitation options. National Cooperative Highway Research Program Washington, DC; 2002.
[12] Yogesh US, Jain SS, Devesh T. Adaptation of HDM-4 Tool for Strategic Analysis of Urban Roads Network. Transp Res Procedia 2016;17:71–80. https://doi.org/10.1016/j.trpro.2016.11.062.
[13] Chatti K, Lee D. Development of a Preventive Maintenance Strategy for Minimizing Roughness-Related Pavement Damage. Transp Res Rec J Transp Res Board 2001;1769:39–45. https://doi.org/10.3141/1769-05.
[14] Ningyuan L, Kazmierowski T, Sharma B. Verification of Network-Level Pavement Roughness Measurements. Transp Res Rec J Transp Res Board 2001;1764:128–38. https://doi.org/10.3141/1764-14.
[15] Aultman-Hall L, Jackson E, Dougan CE, Choi S-N. Models Relating Pavement Quality Measures. Transp Res Rec J Transp Res Board 2004;1869:119–25. https://doi.org/10.3141/1869-14.
[16] Harinder D, Anusha P, Ramesh A, Kamatalam KMP. Evaluation of flexible pavement performance based on HDM-4 and international roughness index. E3S Web Conf 2023;391:01202. https://doi.org/10.1051/e3sconf/202339101202.
[17] Asadi S, Shafabakhsh G. Presenting a Statistical Model of Fatigue Prediction for the Effect of Loading Frequency on Reflective Cracks Propagation on Asphalt Layers Improved by Geosynthetics. J Rehabil Civ Eng 2024;12:18–33.
[18] Jafari Ani O, Shafabakhsh G, Mirabdolazimi SM. Investigation of Rheological Characteristics of Powdered Activated Carbon Modified Bitumen for Use in Self-Healing Mechanism of Asphalt Concrete. J Rehabil Civ Eng 2024;12:58–68.
[19] Teymouri E, Noraziemah Mohd Pauzi N, Kwong Soon W, Salari M, Forouzan M. Effects of Water, Cement, and Superplasticizer Content on the Mechanical, Physical, and Cementitious Paste Thickness of Pervious Concrete. J Rehabil Civ Eng 2024;12.
[20] Afrazi M, Lin Q, Fakhimi A. Physical and numerical evaluation of mode II fracture of quasi-brittle materials. Int J Civ Eng 2022;20:993–1007.
[21] Sultana S, Najjar Y, Yasarer H, Uddin W, Barros R. International roughness index model for jointed reinforced concrete highway pavements: An artificial neural network application. Elev. Int. Conf. Bear. Capacit. Roads, Railw. Airfields, CRC Press; 2022, p. 246–55.
[22] Arrivabeni BS, Machado CC, Gomes RRM, Teixeira APM. Technical, economical, and socio-environmental analysis of forest road maintenance using the HDM-4 software. TRANSPORTES 2023;31:e2699–e2699.
[23] Gharieb M, Nishikawa T. Development of roughness prediction models for Laos national road network. CivilEng 2021;2:158–73.
[24] Arifin MZ, Prabowo P, Wicaksono AD. Modeling of road damage prediction due to overload using HDM-4 method. EUREKA Phys Eng 2024:70–81. | ||
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