Potential damage, eventually demonstrated as moisture damage on inner and in-situ road structures, is the most complex problem to predict, which costs lots of money, time, and natural resources for maintenance and even leads to safety problems. Traditional linear regression analysis cannot fit well with this multi-factor task in such in-field circumstances. Random Forest (RF) is a progressive nonlinear algorithm, which can combine all relative factors to gain accurate prediction and good explanation. In this study, an RF model is constructed for the prediction of potential damage. In addition, relative variable importance is analyzed to obtain the correlations between factors and potential damage separately. The results show that, through the optimization, the model achieved a good average accuracy of 83.33%. Finally, the controlling method for moisture damage is provided by combining the traditional analysis method and the RF model. In a word, RF is a prospective method in predictions and data mining for highway engineering. Trained with effective data, it can be multifunctional and powerful to solve hard problems.

The chemical compositions of asphalt and mineral type are always related to interface adhesion performance, and further affect the field performance of asphalt mixture. This study aims to evaluate the effects of mineral type as well as bitumen types experiencing different ageing process on the adhesion property of interface. Adhesion energy and adhesion work of different bitumen and mineral combinations were calculated in dry or wet condition. Results show that different asphalt ageing mechanisms have significantly different effects on bitumen–mineral interface adhesion performance. Interfacial adhesion work increases with the increase of asphaltene and resin fractions in bitumen. Both sulfoxide and ketone can effectively improve the interface adhesion between bitumen and mineral. Water adversely affects the adhesion of asphalt–mineral interface. Calcite-bitumen has excellent resistance to water stripping for lower adhesion work loss rate than quartz-bitumen combination no matter what SARA or chemical structure of bitumen.

Grouted Semi-flexible Pavement (GSP) is a novel pavement composed of open-graded asphalt concrete grouted with high-fluidity cement mortar. Due to its excellent load-bearing and anti-rutting performance, it has great potential as anti-rutting overlay and surface in road construction. However, the understanding of GSP performance remains limited and pertinent findings are inconsistent. This article aims to provide a systematic literature review for the articles which were published between 2000 and 2020 on GSP, explore the problems in the recent research, identify knowledge gaps, and deliver recommendations for future research. The influential factors and the relative evaluation methods of GSP performance are summarized and discussed in this article.

With the aim of improving the asphalt and asphalt mixture performance at high and low temperatures, polyphosphoric acid (PPA) and styrene butadiene rubber (SBR) were added to achieve a modification in this study. The effects of PPA and SBR compound modifiers on the rheological and mechanical properties of asphalt and asphalt mixture were characterised by conventional and novelty tests. It was demonstrated that PPA can dramatically improve the anti-rutting performance of base and SBR-modified asphalt and mixture. In addition, resistance against low-temperature cracking of PPA/SBR compound-modified asphalt and mixture was also desirable. Furthermore, the performance indicators were ranked and analysed. As a consequence, 0.75%PPA/2.5%SBR is beneficial to achieve the desired properties comprehensively. The novel tests mentioned in the paper are proper and recommended. Effective indicators have been proposed for their potential to characterise the performance of asphalt and mixture.