A parametric study to improve suitability of micro-deval test to assess unbound base course aggregates

摘要

Micro-deval test provides a measure of resistance and durability of aggregates submerged in water through the actions of aggregate particles and abrasion from steel balls. The presence of water in the test chamber provides a more realistic assessment of field conditions when compared with Los Angeles (LA) abrasion test. Currently there is only one testing procedure in the United States (U.S.) to evaluate the coarse aggregates using micro-deval tests. Previous studies indicate that there has been significant interest in utilizing micro-deval test to assess the suitability coarse aggregates to be used in asphalt concrete and their field performance. However the studies related to evaluating coarse aggregates with microdeval test for base course applications are very limited. This study attempts to address how the microdeval testing procedure may be revised to better assess the performance of aggregates considered for the base course. Aggregates with seven different geological compositions were used in the study. Total of 250 micro-deval tests were performed and the results confirmed the repeatability and the suitability of the proposed method to all of the tested aggregates. As part of this study, a threshold is determined for the optimum amount of abrasive charge that should be used in the tests to obtain maximum material loss regardless of the geological make-up of the aggregate. If this approach is followed, a strong relationship between the number of revolutions and percent material loss is achieved. This relationship provides an opportunity to shorten the micro-deval tests and also an approach to assess durability of aggregates at number of revolutions significantly larger than what is prescribed in the existing micro-deval testing procedure. This ability may be used in the future to more realistically relate the long-term durability prediction of aggregates as it relates to field performance of base course. (C) 2017 Elsevier Ltd. All rights reserved.