A COMPARATIVE EVALUATION ON THE PROPERTIES OF HMA WITH VARIATIONS IN AGGREGATE GRADATION OF LABORATORY AND FIELD PRODUCED MIXES

India is having a road network of about 4.69 million Km with majority of roads as flexible pavement of having black top surface.These black top surfaces are constructed mainly with the use of naturally available local aggregates and asphalt binder, where aggregates are dried and mixed with hot bitumen to produce the Hot Mix Asphalt (HMA).For a given aggregate gradation, the optimum binder content is important and it is estimated by satisfying various mix design parameters.Even designing a bituminous mix to meet the desired requirements of a particular paving project also requires careful selection of the compatible aggregate source, aggregate gradation and bitumen grade to sustain till its design life.Hence, it is essential to understand how aggregate gradation affects the performance of HMA.The present study was taken up with the objective of evaluating the properties of HMA mixtures designed using bituminous concrete (BC)-I gradation and compared with conventional method of gradation used in the field or batch mix plant.For the preparation of bituminous mixes, five types of aggregate gradation (upper limit, mid-point range, fuller-thompson maximum density gradation, HMA plant mix gradation and lower limit aggregate gradation) were used as per the specification of Ministry of Road Transport and Highways (Fifth revision)-2013 and mix design evaluation is done by using Marshall method.By evaluating the volumetric and Marshall properties of the bituminous mixes with five different gradations, results indicate that the performance of mixes made with mid-point of gradation range shows higher stability value than other mixes and the optimum binder content increases form coarser gradation to finer gradation.Finally, a parameter called Gradation ratio (GR) is also evaluated to indicate the type of aggregate grading and to correlate it with various mix design parameters with the variations in aggregate grading.