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The properties of asphalt mastic are crucial in determining the moisture sensitivity of asphalt mixtures, but the adhesion performance of the mastic has not been quantitatively described. To address this gap, this study calculated the asphalt mastic surface energy using the equation-of-state method, and established a moisture sensitivity (𝑀𝑆) index based on it. The effectiveness of this index was verified through Marshall testing. First, the surface energy of asphalt and filler was measured, and the critical volume fraction of the mastic was determined using the two-point method. Second, the interaction parameters of asphalt and filler were calculated using the equation-of-state method, and the surface energy of the mastic was obtained. Then the 𝑀𝑆 index was established to evaluate the moisture sensitivity of asphalt mixtures. This new index utilizes the surface energy and aggregate to quantitatively evaluate adhesion, considering the specific surface area of the aggregate and the thickness of asphalt film. Finally, the 𝑀𝑆 was validated through Marshall tests of asphalt mixtures. The results demonstrated that the 𝑀𝑆 obtained by the calculated surface energy exhibits a strong linear correlation with the moisture sensitivity of asphalt mixtures. The goodness of fit reached above 0.90 and the highest was 0.965. This study provided a novel approach to characterize the moisture sensitivity of asphalt mixtures.

Question

The properties of asphalt mastic are crucial in determining the moisture sensitivity of asphalt mixtures, but the adhesion performance of the mastic has not been quantitatively described. To address this gap, this study calculated the asphalt mastic surface energy using the equation-of-state method, and established a moisture sensitivity (𝑀𝑆) index based on it. The effectiveness of this index was verified through Marshall testing. First, the surface energy of asphalt and filler was measured, and the critical volume fraction of the mastic was determined using the two-point method. Second, the interaction parameters of asphalt and filler were calculated using the equation-of-state method, and the surface energy of the mastic was obtained. Then the 𝑀𝑆 index was established to evaluate the moisture sensitivity of asphalt mixtures. This new index utilizes the surface energy and aggregate to quantitatively evaluate adhesion, considering the specific surface area of the aggregate and the thickness of asphalt film. Finally, the 𝑀𝑆 was validated through Marshall tests of asphalt mixtures. The results demonstrated that the 𝑀𝑆 obtained by the calculated surface energy exhibits a strong linear correlation with the moisture sensitivity of asphalt mixtures. The goodness of fit reached above 0.90 and the highest was 0.965. This study provided a novel approach to characterize the moisture sensitivity of asphalt mixtures.

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Solution

The text you provided is in English, so I will continue to respond in English.

The study you mentioned aimed to quantitatively describe the adhesion performance of asphalt mastic, which is crucial in determining the moisture sensitivity of asphalt mixtures. The researchers calculated the asphalt mastic surface energy using the equation-of-state method and established a moisture sensitivity (MS) index based on it.

The process was as follows:

  1. The surface energy of asphalt and filler was measured.
  2. The critical volume fraction of the mastic was determined using the two-point method.
  3. The interaction parameters of asphalt and filler were calculated using the equation-of-state method, and the surface energy of the mastic was obtained.
  4. The MS index was established to evaluate the moisture sensitivity of asphalt mixtures. This new index uses the surface energy and aggregate to quantitatively evaluate adhesion, considering the specific surface area of the aggregate and the thickness of the asphalt film.
  5. The MS index was validated through Marshall tests of asphalt mixtures.

The results showed a strong linear correlation between the MS obtained by the calculated surface energy and the moisture sensitivity of asphalt mixtures. The goodness of fit was above 0.90, with the highest being 0.965. This study provided a new approach to characterizing the moisture sensitivity of asphalt mixtures.

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