This study aimed to explore the long-term aging influence on chemo-rheological properties and develop novel consecutive models for the long-term aging reaction kinetics of bitumen. The results revealed that the aging index was significantly dependent on the types of selected parameters. The Zero-order model was suitable to describe the long-term aging reaction kinetics of bitumen based on the oxygen-containing functional groups with the reaction rate constants in 0.7–3.3*10⁻⁴ (mol L⁻¹·h⁻¹). In the SARA-based consecutive reaction model, the most optimum kinetics model for aromatic fraction was the Third-order reaction model and the corresponding reaction kinetics constant (k₁) was 0.02 (mol·L⁻¹)⁻²(h)⁻¹. The Zero-order model could well fit the generation kinetics of asphaltene molecules with the reaction rate constant k₂ of 3.85*10⁻⁴ mol·(L·h)⁻¹. Further, the transformation reaction from the resin to asphaltene molecules was the control step of the whole consecutive reaction model. In this study, when one-unit resin fraction was generated, the consumption amount of aromatic fraction was about 2.82 units. Meanwhile, when one-unit resin fraction was consumed, only 0.58-unit asphaltene could be generated. The developed reaction kinetics models could be beneficial to predict the functional groups distribution and SARA fractions in aged bitumen with different aging degrees.

A styrene-butadiene-styrene (SBS) latex modifier can be used for asphalt modification due to the fact of its energy-saving, construction convenience, and economic advantages. The objective of this study was to investigate the influence of asphalt type and SBS latex dosage on the rheological properties, compatibility, and storage stability of asphalt through temperature and frequency sweep, steady-state flow, multiple stress creep and recovery (MSCR) tests, Cole-Cole plots and thermal storage tests. The results indicated that high SBS latex content is beneficial for improving anti-rutting, anti-fatigue, viscous flow resistance, and elastic recovery abilities of modified asphalt. The chemical composition of asphalt had a significant effect on the properties of the SBS latex-modified asphalt. High asphaltenes and low resins were favorable to enhancing anti-rutting and recovery properties but weakened the anti-fatigue, compatibility, and storage stability of modified asphalt. Furthermore, compared to SBS particle-modified asphalt, SBS latex-modified asphalt had greater rutting and fatigue resistance. However, SBS latex-modified asphalt had some disadvantages in compatibility and storage stability. Comprehensively considering the balance of viscoelastic properties, compatibility, and storage stability of SBS latex-modified asphalt, the mixing dosage of SBS latex modifier is recommended at 4.0 wt% which could feasibly replace SBS particle in asphalt modification.

As an environmentally responsible alternative to conventional concrete, geopolymer concrete recycles previously used resources to prepare the cementitious component of the product. The challenging issue with employing geopolymer concrete in the building business is the absence of a standard mix design. According to the chemical composition of its components, this work proposes a thorough system or framework for estimating the compressive strength of fly ash-based geopolymer concrete (FAGC). It could be possible to construct a system for predicting the compressive strength of FAGC using soft computing methods, thereby avoiding the requirement for time-consuming and expensive experimental tests. A complete database of 162 compressive strength datasets was gathered from the research papers that were published between the years 2000 and 2020 and prepared to develop proposed models. To address the relationships between inputs and output variables, long short-term memory networks were deployed. Notably, the proposed model was examined using several soft computing methods. The modeling process incorporated 17 variables that affect the CSFAG, such as percentage of SiO₂ (SiO₂), percentage of Na₂O (Na₂O), percentage of CaO (CaO), percentage of Al₂O₃ (Al₂O₃), percentage of Fe₂O₃ (Fe₂O₃), fly ash (FA), coarse aggregate (CAgg), fine aggregate (FAgg), Sodium Hydroxide solution (SH), Sodium Silicate solution (SS), extra water (EW), superplasticizer (SP), SH concentration, percentage of SiO₂ in SS, percentage of Na₂O in SS, curing time, curing temperature that the proposed model was examined to several soft computing methods such as multi-layer perception neural network (MLPNN), Bayesian regularized neural network (BRNN), generalized feed-forward neural networks (GFNN), support vector regression (SVR), decision tree (DT), random forest (RF), and LSTM. Three main innovations of this study are using the LSTM model for predicting FAGC, optimizing the LSTM model by a new evolutionary algorithm called the marine predators algorithm (MPA), and considering the six new inputs in the modeling process, such as aggregate to total mass ratio, fine aggregate to total aggregate mass ratio, FASiO₂:Al₂O₃ molar ratio, FA SiO₂:Fe₂O₃ molar ratio, AA Na₂O:SiO₂ molar ratio, and the sum of SiO₂, Al₂O₃, and Fe₂O₃ percent in FA. The performance capacity of LSTM-MPA was evaluated with other artificial intelligence models. The results indicate that the R² and RMSE values for the proposed LSTM-MPA model were as follows: MLPNN (R² = 0.896, RMSE = 3.745), BRNN (R² = 0.931, RMSE = 2.785), GFFNN (R² = 0.926, RMSE = 2.926), SVR-L (R² = 0.921, RMSE = 3.017), SVR-P (R² = 0.920, RMSE = 3.291), SVR-S (R² = 0.934, RMSE = 2.823), SVR-RBF (R² = 0.916, RMSE = 3.114), DT (R² = 0.934, RMSE = 2.711), RF (R² = 0.938, RMSE = 2.892), LSTM (R² = 0.9725, RMSE = 1.7816), LSTM-MPA (R² = 0.9940, RMSE = 0.8332), and LSTM-PSO (R² = 0.9804, RMSE = 1.5221). Therefore, the proposed LSTM-MPA model can be employed as a reliable and accurate model for predicting CSFAG. Noteworthy, the results demonstrated the significance and influence of fly ash and sodium silicate solution chemical compositions on the compressive strength of FAGC. These variables could adequately present variations in the best mix designs discovered in earlier investigations. The suggested approach may also save time and money by accurately estimating the compressive strength of FAGC with low calcium content.

Generally, rejuvenators are used to supply missing components of aged asphalt, reverse the aging process, and are widely used in asphalt maintenance and recycling. However, compared with traditional rejuvenators, bio-oil rejuvenators are environmentally friendly, economical and efficient. This study looks into the effect of the three different bio-oils, namely sunflower oil, soybean oil, and palm oil, on the physical properties, rheological properties and chemical components of aged asphalt at different dosages. The asphalt physical properties and Dynamic Shear Rheological (DSR) test results show that with the increase in bio-oil, the physical properties and rheological properties of rejuvenated asphalt are close to those of virgin asphalt, but the high-temperature rutting resistance needs to be further improved. The results of Fourier Transform Infrared Spectroscopy (FTIR) show that the carbonyl and sulfoxide indices of rejuvenated asphalt are much lower than those of aged asphalt. Moreover, the rejuvenation efficiency of aged asphalt mixed with sunflower oil is better than that with soybean oil and palm oil at the same dosage.

The film thickness of asphalt mixtures is critical for determining their performance and aging durability. However, understanding of the appropriate film thickness and its influence on performance and aging behavior for high-content polymer-modified asphalt (HCPMA) mixtures is still limited. This research aims to examine the relationship between film thickness, performance, and aging behavior of HCPMA mixtures in order to establish an optimal film thickness that ensures satisfactory performance and aging durability. HCPMA specimens with film thicknesses ranging from 6.9 μm to 17 μm were prepared using a 7.5% SBS-content-modified bitumen. Various tests, including Cantabro, SCB, SCB fatigue, and Hamburg wheel-tracking tests, were conducted to evaluate raveling, cracking, fatigue, and rutting resistance before and after aging. The key findings indicate that insufficient film thickness negatively affects aggregate bonding and performance, while excessive thickness reduces mixture stiffness and resistance to cracking and fatigue. A parabolic relationship between the aging index and film thickness was observed, suggesting that increasing film thickness improves aging durability up to a point, beyond which excessive thickness adversely impacts aging durability. The optimal film thickness for HCPMA mixtures, considering performance before and after aging and aging durability, falls within the 12.9 to 14.9 µm range. This range ensures the best balance between performance and aging durability, offering valuable insights for the pavement industry in designing and utilizing HCPMA mixtures.