Mining multiple association rules in LTPP database: An analysis of asphalt pavement thermal cracking distress

摘要

Thermal cracking is one of the most noteworthy distresses in asphalt concrete (AC) pavements. It is caused by the thermal stress in pavement layers, when air temperatures are extremely low or change rapidly. This paper aims to mine multiple association rules for thermal cracking in seasonal freezing zones. Relevant data on thermal cracking, including 36 potential influence factors, were collected from 339 samples from 46 Long-Term Pavement Performance (LTPP) sections in 6 US states and 3 Canadian provinces. Grey Relational Analysis was used to identify the most significant elements among these 36 factors as inputs for an Apriori algorithm, which was implemented to explore the association rules among the key influence factors. Results showed that the asphalt binder percentage, measured stiffness (PG + 4 240s) from BBR testing, monthly freezing index, AC layer thickness, service age and Annual Average Daily Traffic (AADT) all exhibited significant influences on thermal cracking, and the proposed indicator, the thermal cracking development rate (TCDR), had different levels of strong associations with these significant influence factors. All six factors were taken into account for mining association rules. Based on these association rules, recommendations for pavement design, construction and management are provided to prolong the service life of pavements. (C) 2018 Elsevier Ltd. All rights reserved.