Rutting Resistance of HMA Rehabilitated with Micro-Surfacing
Rutting Resistance of HMA Rehabilitated with Micro-Surfacing作者机构：école de Technologie Supérieure ETS Montréal Canada Ecole Spécial des travaux publics ESTP Paris France
出 版 物：《Open Journal of Civil Engineering》 (土木工程期刊（英文）)
年 卷 期：2018年第8卷第2期
页 面：245-255页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：HMA RAP Micro-Surfacing Rutting Aging
摘 要：The work presented here is a study on the measurement and prediction of the rutting resistance of previously rutted asphalt mixes rehabilitated with a layer of micro-surfacing manufactured with virgin and recycled aggregates at different stages of aging. The experimental procedure consisted of rutting tests on hot mix asphalt slabs already degraded and repaired with virgin and recycled micro-surfacing. Then, the evolution of the behavior of micro-surfacing cast on the hot mix asphalt slabs is observed according to loading cycles of the pavement rutting tester MLPC. Before rutting tests, slabs are subjected to 24 hours at 50°C and aged for 2 days and 5 days at 85°C in the oven. The results showed rutting percentages of 6.3% for hot mix asphalt slabs aged for 2 days and 7.2% for 5 days. These hot mix slabs repaired with virgin micro-surfacing have rutting percentage of about 9.2 % for 2 days of aging and 6.5% for 5 days of aging. While, the HMA slabs repaired with recycled micro-surfacing have rutting percentage of about 8.1% for 2 days of aging and 5.9% for 5 days of aging. These results allowed the development of a prediction model based essentially on three predictor variables including cycle number, rutting state and percentage of water in the micro-surfacing material. The developed model shows a strong correlation between the predicted rutting values and the rutting values measured with the MLPC rut tester. Thermal aging in oven has a positive impact on the resistance to permanent deformation of new asphalt mixes and those rehabilitated with micro-surfacing. The parameters of rutting state and contribution water are significant in the rutting prediction model, while the cycle number remains a non-significant parameter in the model but determinant.
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