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Given the defects of bitumen in asphalt mixtures particularly exposed to moisture, this study mainly aims to investigate the relationship between qualitative and quantitative results of moisture susceptibility tests on asphalt mixtures modified by ZycoTherm, nanoclay, nanosilica and SBS. The Marshall stability, modulus of resilience and indirect tensile strength tests are carried out. Boiling water and SEM qualitative tests are also used. Eventually, the qualitative tests results are digitalized through image processing by MATLAB and compared with the moisture susceptibility results of indirect tensile strength test. For modulus of resilience testing, the results show that this modifier has the maximum impact on Marshall stability, improving it by about 23%. For moisture susceptibility testing, the nanosilica-modified mixture has the maximum effect among anti-stripping additives, with an improvement by about 20%. An investigation into the results of SEM images and boiling water test via MATLAB indicates the high accuracy of SEM images and their results show the most compatibility with the results of quantitative data.

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In the recent decades, different kinds of fiber materials are used for improving the asphalt mixture performance. Meanwhile, different kinds of fiber are used excessively due to their desirable physical and chemical properties and their easier application. The main purpose of this research is to evaluate the characteristics of the asphalt mixture while using basalt fiber and glass fiber. In order to provide asphalt samples, these two types of fibers are used in different percentages. In this way, 42 samples (with different percentages of fiber and bitumen) were made using Marshal Hammer. In the next step, while constructing 63 asphalt samples using a gyratory device, then mix asphalt conventional tests include the determination of indirect tensile strength, moisture sensitivity test, and resilient modulus and creep tests performed. The results of this research indicate that using these two types of fibers increased the percentage of optimum bitumen and marshal resistance. At best, adding 0.1% glass fiber resulted in 13% increase in marshal resistance. Finally, ANFIS-GUI was used to estimate the experimental result and the feasibility of employing neural fuzzy network to predict the laboratory data have been evaluated.

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