Abstract
In this work, it is shown how fuzzy inference systems can be constructed to produce a global durability evaluation factor for concrete based on various performance criteria from accelerated tests. This can facilitate the decision-making process during the design stage by identifying optimum concrete mixtures proposed for specified field exposure. A fuzzy inference system was built for the specific case of various self-consolidating concrete mixtures subjected to ammonium sulfate attack. The performance of this model was compared with that of other models that enable decision making: the remaining service life model and compromise programming. Results of the fuzzy inference system had a better correlation with compromise programming (R2 = 0·7) than that with the remaining service life model (R2 = 0·5), and better represented the actual degradation observed in test specimens. It is shown that the proposed fuzzy inference model is rational, clear, reliable, versatile and flexible since it can be easily updated with new data or modified to accommodate future findings.
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