Use of Relational Database Management Systems Principles in Reliable Prediction of Pavement Skid Resistance

Findings are presented from a research study conducted at Texas Tech University on the skid resistance of hot-mix asphalt concrete surfaces. The background on problems of evaluating aggregate sources using the results of laboratory tests and field skid resistance history is presented, and the methodology adopted by researchers is discussed briefly. The study findings indicate that by using a combination of tests, such as acid-insoluble residue (AIR) and petrography analysis, aggregates can be classified into three major groups: low AIR carbonates, high AIR carbonates, and noncarbonates. Skid performance rating (SPR) values were used to correlate the laboratory test results. It was found that laboratory test results of high AIR carbonates and noncarbonates provide good correlation with SPR values. However, the laboratory tests of low AIR carbonates show poor correlation with SPR values. The problems of implementing the results are discussed from the viewpoint of a pavement engineer. An entity-relationship (ER) modeling technique was used to analyze and design a database application specifically created as a tool to assist pavement materials engineers. The database application, SKIDRATE, combines relational database management principles and the results of statistical regression models obtained in this study. Thus, SKIDRATE serves the dual objective of effective data management and data processing. Essential features of the application and its use to evaluate field skid performance of aggregates are briefly explained.