Assessment of Rock Aggregate Quality Through Fuzzy Inference System

Abstract

In this study, Fuzzy Inference System (FIS) was adopted to evaluate the rock aggregate quality. For this purpose, some technical standards for coarse aggregates were integrated into the FIS analyses as threshold values. As a result, several membership functions were established using rock aggregate properties such as water absorption by weight (w(a)), flakiness index (FI), Los Angeles abrasion value (LAAV), and magnesium sulfate soundness (M-wl). Based on 48 if-then rules, the implementation and verification of the proposed FIS model were carried out using sixteen rock types whose field performances as coarse aggregate were previously evaluated [i.e., low quality (LQ), average quality (NQ), high quality (HQ), etc.] by field engineers. The results obtained from the FIS analyses were declared a Rock Aggregate Quality Assessment Rating (RQAR), where higher RQAR values indicate rock aggregates with higher quality. The results obtained from the FIS analyses are almost in good agreement with those obtained from the field performances of the investigated rocks. However, the number of cases should be increased to improve the proposed FIS model. In this context, the number of if-then rules membership functions can be rearranged according to the need. This study, in this manner, can be declared a case study indicating how to quantity rock aggregate quality based on FIS analyses.