The increasing demand for cleaner and more efficient refining processes has driven the development of advanced upgrading technologies for heavy crude residues. This study investigates a novel Visbreaking-Supercritical Fluid Extraction (SFE) approach to upgrade the Merey vacuum residue (VR), integrating experimental analysis with molecular dynamics (MD) simulations for atomic-level mechanism exploration. The Visbreaking process is optimized at 400 °C for 40 min, achieving a viscosity reduction of 89.0 % while minimizing coke formation. The SFE process fractionates the visbroken VR, with total extraction yields ranging from 70.1 wt% to 70.7 wt%, demonstrating remarkable efficiency. Higher extraction pressures enhance deasphalted oil (DAO) yield but compromise its quality with higher metal and sulfur contents, while lower temperatures improve extraction selectivity. The integrated process effectively removes Fe, Ni, V, and Na, with demetalization efficiencies exceeding 62 %, 75 %, and 95 %, respectively. Molecular dynamics simulations provide atomic-scale insights into solubility mechanisms, revealing that higher pressures and lower temperatures enhance solvent compatibility with lighter visbroken VR fractions. The extracted DAO meets marine fuel oil blending specifications, while raffinates show potential for bitumen production and modification. These findings highlight the Visbreaking-SFE combination as a promising and sustainable upgrading strategy for heavy crude residues.

To increase the utilization of used tires, reduce carbon emissions and improve asphalt pavement performance, SBS/TB crumb rubber modified asphalt binder was designed, which was enhanced by SBS and terminal blend (TB) crumb rubber. SBS/TB crumb rubber modified asphalt binder was prepared by mixing 0 %, 10 %, and 15 % TB crumb rubber with 2 % and 3 % SBS, respectively. This study investigated the microstructure, thermal stability and rheological properties of SBS/TB crumb rubber modified asphalt binder. The Spearman correlation coefficient is introduced to analyze the correlation of microstructural, thermodynamic and rheological parameters. The results showed that SBS and TB crumb rubber were uniformly dispersed in asphalt binder without agglomeration phenomenon. In addition, the interaction between SBS and TB crumb rubber resulted in the formation of cross-links between the polymer and the asphalt binder, significantly improving the storage stability and the thermal stability of the modified asphalt binder. The pyrolysis mechanism of the modified asphalt binder is One-dimension diffusion or One-dimension phase boundary. With the addition of SBS and TB crumb rubber, the rheological, high-and-low temperature properties of modified asphalt binder are improved. Finally, microstructural, thermodynamic and rheological parameters have an extremely strong correlation by Spearman correlation coefficient analysis.

The chemo-mechanical properties of bitumen undergo significant alternations during aging and rejuvenation, posing challenges for accurately evaluating and enhancing rejuvenation efficiency in asphalt recycling. This study investigates how bitumen source, aging degree, rejuvenator type and dosage influence the chemical and rheological performance of rejuvenated bitumen. Comprehensive characterizations are performed using saturate, aromatic, resin, and asphaltene (SARA) fractionation, elemental analysis, gel permeation chromatography (GPC), and dynamic shear rheometer (DSR) tests. To elucidate chemo-rheological correlations, statistical techniques (Pearson correlation, analysis of variance (ANOVA), and Chi-square tests) are combined with artificial neural networks (ANN). Results indicate that the NB bitumen with more colloidal stability and less sulfur content exhibits the highest resistance to long-term aging. FB bitumen with 4.3 % sulfur achieves the best high-temperature deformation resistance with rutting failure temperature (RFT) higher than 80 °C, and TB bitumen exhibits the longest fatigue life. Rejuvenation using bio-oil is most effective on reducing relaxation time by up to 60 % and increasing creep compliance (Jnr3.2) by 1.7–2.5 times, depending on bitumen type. Rejuvenator dosage sensitivity for relaxation stress follows the trend: bio-oil < engine-oil < naphthenic-oil, while aromatic-oil shows variability depending on its source. Among the tested rejuvenators, bio-oil proves most effective, particularly for rejuvenating TB and FB bitumen. The ANN model demonstrates strong predictive performance for rheological properties, achieving R2 values between 0.90 and 0.98, with the highest accuracy observed for relaxation indices, followed by fatigue and rutting properties.

This study investigates the effects of warm-mix asphalt (WMA) additives and bio-oil on the rheological and chemical properties of virgin bitumen (VB) and polymer-modified bitumen (PMB) under varying aging conditions. The workability, viscoelasticity, and chemical characteristic of warm-mix bio-rejuvenated bitumen are assessed using a rotational viscometer, dynamic shear rheometer, Fourier Transform Infrared Spectroscopy. Results show that PMB has superior aging resistance than VB. The wax-based additive exponentially reduces viscosity of VB, while the chemical-based additive decreases viscosity linearly and performs better in PMB due to improved polymer-bitumen interfacial lubrication. The wax-based additive enhances high-temperature elasticity and rutting resistance, whereas adding 0.9 wt% chemical-based additive declines the rutting failure temperature (RFT) of VB by 3.3°C and PMB by 2.3°C. However, the wax-based additive lowers the fatigue life of VB, while the chemical-based additive extends the fatigue life. The fatigue failure temperature (FFT) value increases by 2.3°C for VB and 3.4°C for PMB after adding 4 % wax-based additive. The optimal dosage of the chemical-based additive for PMB is determined to be 0.6 %. The bio-rejuvenator significantly enhances the fatigue performance of aged VB, but has limited impact on aged PMB. Both WMA additives reduce aromaticity and alter aliphatic content, with the chemical-based one showing a stronger dilutive effect, particularly in PMB. Additionally, a warm-mix bio-rejuvenated bitumen with higher aliphatic index (AII) and carbonyl index (CI) shows better deformation resistance and longer fatigue life.

This study explores the use of chemical descriptors derived from force field atom types to predict Fickian diffusion coefficients of rejuvenators in bitumen, utilizing machine learning models trained on data from 240 non-equilibrium molecular dynamics simulations. The simulations cover three bitumen types (NO, TO, FO), five aging degrees, and four temperatures (60 °C, 120 °C, 160 °C, 200 °C), capturing diffusion coefficients ranging from 0.0068e-10 m2/s in highly aged bitumens at 60 °C to 4.35e-10 m2/s in fresher samples at 200 °C. The MLM, built with 18 chemical descriptors for bitumen and rejuvenator sides, achieves an R2 of 0.97, accurately predicting diffusion across varied conditions. This approach abstracts away from the need for repeated MD simulations, enabling diffusion predictions even for systems outside the original dataset. The manuscript presents three case studies to illustrate how the model can be used for the iterative design of rejuvenators by optimizing molecular structures based on critical chemical features, such as rejuvenator oxygen content, bitumen sulfur content, and molecular weights. It also demonstrates how the model offers a practical framework for understanding the diffusion and performance of rejuvenators by linking time-dependent factors—such as concentration, depth, and rejuvenation time—with the bulk properties of bitumen-rejuvenator systems, facilitating industrial applications.

This study implements molecular dynamics (MD) simulations to explore the atomic-level energy properties of rejuvenated bitumen, considering the influence of different recycling agent (RA) types, dosages and aging levels of bitumen. Moreover, the potential correlations between energy indices and high-temperature performance of rejuvenated bitumen are explored. Our findings show that recycling agents can effectively reinstate the cohesive energy density (CED) values of aged bitumen, correlating well with their high-temperature rheological properties. The results reveal that the energy parameters of potential energy (UVEP), kinetic energy (UWEK), non-bond energy (EN), total energy (UVET), diagonal energy (UNED), and cross-terms energy (ECT) can reflect the restoration level of recycling agents (RAs) on atomic-level energy characteristics of aged bitumen. Compared to rutting failure temperature (RFT), elastic recovery (R3.2), and creep compliance (Jnr3.2), the zero-shear viscosity (ZSV) greatly correlates with CED. Meanwhile, the UWEK index from MD simulations demonstrates a strong correlation with high-temperature rheological indicators of rejuvenated bitumen. With the rise in UWEK, there is a linear decrease in the RFT, Log(ZSV), and R3.2 values of rejuvenated bitumen. Conversely, the Log(Jnr3.2) exhibits a linear increasing trend. However, the correlation patterns between rheological indicators and either EN or ECT are contingent on the aging degree of bitumen. Based on the correlation coefficient, the UWEK stands out as the primary choice among all energy indices for predicting high-temperature rheological performance of rejuvenated bitumen.

The design of geopolymer concrete must meet more stringent requirements for the landscape, so understanding and designing geopolymer concrete with a higher compressive strength challenging. In the performance prediction of geopolymer concrete compressive strength, machine learning models have the advantage of being more accurate and faster. However, only a single machine learning model is usually used at present, there are few applications of ensemble learning models, and model optimization processes is lacking. Therefore, this paper proposes to use the Firefly Algorithm (AF) as an optimization tool to perform hyperparameter tuning on Logistic Regression (LR), Multiple Logistic Regression (MLR), decision tree (DT), and Random Forest (RF) models. At the same time, the reliability and efficiency of four integrated learning models were analyzed. The model was used to analyze the influencing factors of geopolymer concrete and determine the strength of their influencing ability. According to the experimental data, the RF-AF model had the lowest RMSE value. The RMSE value of the training set and test set were 4.0364 and 8.7202, respectively. The R value of the training set and test set were 0.9774 and 0.8915, respectively. Therefore, compared with the other three models, RF-AF has a stronger generalization ability and higher prediction accuracy. In addition, the molar concentration of NaOH was the most important influencing factors, and its influence was far greater than the other possible factors including NaOH content. Therefore, it is necessary to pay more attention to NaOH molarity when designing geopolymer concrete.

Bitumen fatigue resistance is critical to determine the overall fatigue performance and service life of asphalt pavements. However, the mechanisms responsible for fatigue damage of bitumen have previously not been well understood. Molecular dynamics (MD) simulation has recently emerged as a powerful computer-aided numerical technique to model the microscopic failure behaviours in materials. This study aims to use the MD method to investigate the molecular origin of bitumen fatigue damage. The molecular models of the virgin and aged PEN70/100 bitumen were firstly constructed based on their saturate, aromatic, resin and asphaltene (SARA) four fractions. An MD equilibrium was run on the developed bitumen models with the assigned interatomic potentials. Following an MD-based tensile simulation, a strain-controlled fatigue simulation was performed to study the nanostructure and damage behaviours of the virgin and aged bitumen under fatigue loading by calculating the stress-strain response, potential energy, molecular structure and nanovoid volumes. Furthermore, a rheometer measurement was also conducted to characterise the fatigue damage of the bitumen directly by a crack length at the macroscale. Results indicate that the bitumen molecules become unfolded and tend to align along the loading direction when fatigue loading was applied. The change in the molecular configuration helped the molecular chains move closer together and thus contributed to the reduction of the intermolecular interactions including the van der Waals and Coulombic energies. With the increasing load cycles, nanovoids were formed and grew in the bitumen through molecular rearrangement and movement, leading to microscopic fatigue damage of the bitumen. It was found that the aged bitumen produced more severe fatigue damage than the virgin bitumen, which was indicated by the MD-based nanovoid volume at the molecular scale and the DSR-based crack length at the macroscale. The findings from MD simulation provide a fundamental understanding of the molecular origin of fatigue damage, that cannot be experimentally detected for bitumen materials.

Developed by Delft University of Technology, the tri-component polyurethane modified cold binder (PMCB) displays impressive durability and strength in asphalt mixtures, showing promise as a reliable binder for cold in-place recycling. However, when applying PMCB for rapid, in-situ recycling, the presence of moisture in reclaimed asphalt pavement (RAP) poses a significant challenge. To address this, an innovative approach involving treatment of the wet RAP with Calcium dioxide (CaO) prior to the integration of PMCB was tested. Evaluation methods used included the Indirect Tensile Test (ITT), followed by the calculation of the Indirect Tensile Strength Ratio (ITSR) to assess moisture susceptibility. Furthermore, Cantabro tests were performed to determine the material loss under abrasion and weathering conditions. These assessments underscored the feasibility of this approach. The treatment of wet RAP with CaO has proven a viable strategy for rapid in-situ recycling with PMCB, contributing to sustainable pavement construction. In addition, the research identified that a 5.5% concentration of the PMCB binder maximizes structural integrity and performance in the considered RAP.

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.

The low-temperature relaxation and fatigue cracking performance are two essential aspects in estimating the rejuvenation efficiency of recycling agents (RAs). This study aims to fundamentally investigate the effects of recycling agent type/dosage and aging degree of bitumen on thermodynamic and rheological properties of rejuvenated bitumen at low and intermediate temperatures. Molecular dynamics (MD) simulations are utilized to predict thermodynamic indices of rejuvenated bitumen, further linked to critical low-temperature and fatigue indicators from experiments. The results reveal that all RAs show a regeneration effect on fractional free volume (FFV), self-diffusion coefficient (DS), glass transition temperature (Tg), and surface free energy (γ). Bio-oil and engine-oil exhibit higher rejuvenation efficiency on these thermodynamic properties than naphthenic-oil and aromatic-oil. The aging degree of bitumen and temperature show significant effects on rejuvenation efficiency. It is recommended to use the FFV parameter to predict the relaxation properties of rejuvenated bitumen. However, these thermodynamic indicators inadequately differentiate between rejuvenators and softeners. Based on crossover parameter results, most recycling agents (bio-oil, engine oil, and naphthenic oil) in this study display softening characteristics. Only aromatic oil effectively rejuvenates the crossover modulus (Gc) of aged binder. Notably, engine oil demonstrates the least rejuvenation in crossover parameters for the recovery of aged bitumen. Further, γ demonstrates a strong association with both Glover-Rowe (G-R) and fatigue crack width C500 indices across all cases involving rejuvenated bitumen. This work will build a multi-scale evaluation framework on the rejuvenation effectiveness of recycling agents on low-temperature and fatigue performance of aged bitumen.

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.

Attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR) is an essential tool for the analysis of bituminous binders due to its cost-effectiveness, user-friendliness, and non-destructive nature. However, its effectiveness is often hampered by challenges such as non-informative regions, lack of standardized analysis methods, and inconsistent baselines in spectral data. Addressing these challenges, this study aims to comprehensively evaluate the impact of various data pre-processing (DP) methods on ATR-FTIR spectra from diverse bituminous binder types, sources, and aging conditions. Using partial least squares discriminant analysis (PLSDA) classification, the study assesses the effectiveness of baseline correction, normalization, and their combinations. The methodology involves analyzing peak areas, indices, entire spectra, and first derivative spectra to determine the most effective pre-processing strategies. Key findings reveal that the effectiveness of DP methods is influenced by the classification goals, characteristics of the spectral dataset, and the specific methods employed for input data preparation. The study demonstrates that using entire spectra or their first derivatives leads to higher classification accuracy compared to indices or specific spectral peak areas. The choice between peak area and indices calculation methods should align with the study’s objectives. For efficient and rapid selection of DP methods, tools like PLSDA are recommended. Among the normalization methods, normalization to constant vector length (NCV), normalization to change the maximum to 1 (NMO), robust scaling (RS), and normalization to sum (NTS) are suitable for peak area or indices-based classification. For entire spectra and their first derivatives, NTS, NCV, autoscaling (AS), pareto scaling (PS), and standard normal variate (SNV) methods are recommended. Regarding baseline correction, Adaptive Smoothness Penalized Least Squares (aspls) is suitable for studies focusing on gradual material changes, such as multi-level aging studies, but not for additive
detection studies. The findings of this study provide valuable insights and practical recommendations for selecting appropriate DP methods, thereby enhancing the classification accuracy and reliability of ATR-FTIR spectral analysis of bituminous binders. This contributes significantly to the design of experiments, reduces operational risks, and optimizes resource utilization in the field.

The increasing popularity of sustainable asphalt pavement stems from its advantageous attributes, such as cost-saving, environmental protection, and reductions in energy and material consumption. Although there is a desire to maximize the reuse of reclaimed asphalt (RA) waste materials in road construction, this is hindered by the poor performance of aged bitumen. In response, rejuvenation technology has been developed to restore the cohesive and adhesive properties of aged binders. To effectively select appropriate rejuvenators for aged bitumen derived from diverse RA sources and showing varying chemo-mechanical properties, it is crucial to establish an evaluation method that can assess and differentiate the rejuvenation efficiency of different rejuvenator-aged bitumen blends. Furthermore, it is essential to gain a fundamental understanding of the underlying mechanisms responsible for the variations.
This dissertation aims to develop a comprehensive and multi-scale approach for assessing the rejuvenation efficiency and mechanisms of various rejuvenator-aged bitumen blends. The combination of molecular dynamics (MD) simulations prediction and experimental validation is throughout the whole thesis to evaluate the compatibility potential and diffusive capacity of rejuvenators within aged bitumen, as well as their rejuvenation effectiveness in the chemo-thermodynamic-rheological performance. Additionally, the intermolecular interactions occurring between the rejuvenator and aged bitumen molecules are visualized and quantified by MD simulations.
The accurate construction of molecular models for aged bitumen is crucial for investigating the fundamental effects of aging on bitumen behavior at the molecular scale. To accomplish this, the long-term aging influence on the chemical characteristics of bitumen was assessed through Saturate, Aromatic, Resin, and Asphaltene (SARA) fractionation, Fourier Transform Infrared Spectroscopy (FTIR) test and element analysis method. The chemical information obtained served as a foundation for determining the molecular structures of bitumen models. Various thermodynamic parameters of both virgin and aged bitumen were predicted to fundamentally evaluate the aging effect on bitumen properties. Lastly, functional group and SARA-based long-term aging reaction kinetics models were proposed to anticipate the chemical characteristics of aged bitumen with different aging degrees, thereby establishing the corresponding molecular models without the need for additional experimental procedures.
Simultaneously, novel average and multi-component molecular models for various rejuvenators (bio-oil BO, engine-oil EO, naphthenic-oil NO, aromatic-oil AO) were established. The average models were based on the average chemical characteristics, such as functional group distribution, element component, and average molecular weight. On the other hand, multi-component models were derived from molecular component distribution in rejuvenators through Gas Chromatography-Mass spectrometry (GC-MS) analysis. Both models were validated by comparing MD outputs with experimental results. It was found that the average models provided more accurate predictions regarding the glass transition temperatures, especially for the aromatic-oil. Additionally, a range of thermodynamic parameters for the rejuvenators were predicted and compared. Finally, the average structures of rejuvenators were adopted to construct subsequent molecular models of rejuvenated binders.
The consideration of compatibility between the rejuvenator and aged bitumen is crucial due to the potential phase separation. In this thesis, different thermodynamic parameters, such as solubility parameter difference Δδ, Flory-Huggins parameter\chi, and mixing free energy ΔGm were predicted and calculated using MD simulations for various rejuvenated bitumen systems. The predicted compatibility ranking for four rejuvenators was AO > BO > NO > EO, aligned with the experimentally measured thermal stability results. Moreover, separation index (SI) parameters based on rheological and chemical indices were available to assess the thermal stability of rejuvenated bitumen.
Furthermore, a comprehensive investigation was implemented to explore the effects of rejuvenator type, temperature, and aging degree of bitumen on the diffusion behavior of rejuvenators in aged binders at multiple scales. The molecular dynamics (MD) simulation method was employed to detect the molecular-level diffusion characteristics of rejuvenators and predict their diffusion coefficient (D) parameters. At the atomic scale, it was observed that there was a mutual but partial interfacial diffusion feature between rejuvenators and aged bitumen molecules. Meanwhile, the concentration distribution of rejuvenator molecules in aged bitumen was well described by Fick's Second Law. The calculated D values for the four rejuvenators ranged from 10-11 to 10-10 m2/s, and the diffusive capacities followed the order of BO > EO > NO > AO. To verify the MD simulation outputs, diffusion tests and dynamic shear rheometer (DSR) characterizations were conducted. The experimental results regarding the magnitude and order of the D values were in good agreement with the MD simulation findings. Lastly, it was observed that an increased aging degree of bitumen had a negative impact on the molecular diffusivity of BO, EO, and NO rejuvenators, whereas the D value of AO molecules enlarged as the aging level deepened.
A series of measurements were conducted to estimate the combined effects of rejuvenator type/dosage and aging degree of bitumen on the rheological properties of rejuvenated bitumen. Importantly, several critical indicators were identified that effectively assess and differentiate the rejuvenation efficiency of different rejuvenators on aged bitumen performance. In terms of high-temperature performance, parameters rutting failure temperature (RFT) and zero-shear viscosity (ZSV) from the linear viscoelastic (LVE) and flow tests were found to be useful. Additionally, parameters R3.2, Jnr0.1 or Jnr3.2, and Jnrslope were recommended for estimating the elastic performance, creep potential, and stress sensitivity of rejuvenated bitumen. Among these, the RFT parameter played a crucial role in evaluating and distinguishing the rejuvenation effectiveness of various rejuvenators on the high-temperature performance of aged bitumen. For the low-temperature relaxation property, parameters τ50s, t25%, and A were proposed as critical indicators. Regarding fatigue life improvement, BO demonstrated the highest rejuvenation effectiveness, followed by EO, NO, and AO rejuvenators. The fatigue failure temperature (FFT) parameter was identified as an effective indicator for fatigue performance evaluation in LVE tests. In linear amplitude sweep (LAS) tests, the fatigue life (Nf5), peak strain (ɛsr), and elastic modulus (E) parameters were optimized as effective fatigue indicators. Nonetheless, crack width (C) results were consistent with conclusions drawn from LVE and LAS tests. Particularly, the crack width C500 parameter showed strong correlations with other critical fatigue indicators, and its prediction could be achieved using correlation equations without the need for time-consuming TS tests.
At the atomic-level evaluation, several key thermodynamic properties of variable rejuvenated bitumen models were outputted by molecular dynamics (MD) simulation. The rejuvenation effectiveness of different rejuvenators on the thermodynamic indices of aged bitumen was estimated and compared. Importantly, the potential connections between these essential nanoscale parameters and critical macroscale indicators in terms of high-and-low temperature performance and fatigue behaviors of rejuvenated binders were explored. It was revealed that the addition of rejuvenators inherently catalysed a restoration of density and cohesive energy density (CED) values toward those of virgin bitumen. A suite of indicators, including UVEP, UWEK, EN, UVET, UNED, and ECT, are introduced as critical energetic parameters, each reflecting rejuvenator efficacy on atomic-level energetic features, except for specific cases involving aromatic-oil rejuvenated binders. Meanwhile, it is recommended to predict the relaxation properties of different rejuvenated bitumen by the fractional free volume parameter from MD simulation. The surface free energy (γ) emerges as a dependable index for assessing the rejuvenation efficacy of the cohesive cracking potential of aged bitumen.
In summary, a multiscale evaluation framework of rejuvenated bitumen was proposed and developed in this dissertation, together with a full understanding of the difference in rejuvenation efficiency and mechanism between various rejuvenators on chemo-thermodynamic-rheological performance restoration of aged bitumen. The outcomes of this thesis would be beneficial to promoting the formation of classification standards of rejuvenator additives, development of advanced multifunctional rejuvenators, and improvement of all-round evaluation method on rejuvenated binder.

This study enhances the molecular analysis of bitumen by transitioning from traditional chemical descriptors, such as SARA (Saturates, Aromatics, Resins, and Asphaltenes) fractions and elemental compositions, to specific force field atom types in Molecular Dynamics (MD) models. This shift improves the precision in predicting material properties critical for bituminous material characterization. Machine Learning Models (MLMs) were developed to use these atom types as input features, inherently reflecting fundamental chemical characteristics. Trained on data from over 1,770 LAMMPS simulations of diverse bitumen types and conditions, these MLMs enable the prediction of properties like density, heat capacity, solubility parameters, and thermal expansion coefficients without the need for additional MD simulations. The models utilize 30 chemical descriptors corresponding to specific atom types in the PCFF force field, which collectively account for over 95% of the influence on these properties. By accurately predicting fundamental, thermodynamic, and kinetic properties, the use of MLMs and force field atom types allows researchers to efficiently tweak the chemical nature of organic molecules and mixtures to achieve desired properties. With near-instantaneous prediction times, these MLMs offer valuable insights for advancing bitumen research in the construction and petroleum industries, reducing the need for more intensive simulation techniques.

Elastomer/plastic compound-modified bitumen was created by adding reactive elastomeric terpolymer (RET) to plastic-modified bitumen, made of either high-density polyethylene (HDPE) or recycled polyethylene (RPE). The rheological properties of the modified bitumen were analyzed. The results indicated that RET elastomer improved high-temperature modulus, temperature insensitivity, anti-rutting properties, elastic recovery, and shear-resistance of both HDPE and RPE-modified bitumen. A high dosage of RET had a negative impact on the cracking resistance of plastic-modified bitumen, thus it is recommended to use 1wt% for optimal results. The increased elasticity in the bitumen was attributed to the creation of a polymer network by RET.

High-viscosity modified asphalt (HVMA) is the most commonly applied method in drainage asphalt pavements. However, some disadvantages of hot-mix HVMA, including high energy consumption and unavoidable environmental pollution, should be improved. Therefore, warm-mix additive (WMA) was introduced. In this paper, the effects of WMA on the rheological and microstructural properties of HVMA were studied to select optimum WMA conditions. WMAs mainly include foam warm mix (1%, 3%, and 5%), Sasobit (1%, 3%, and 5%), Evotherm (0.4%, 0.8%, and 1.2%), and the newly introduced warm additive glow brand (GLWBR) (0.4%, 0.8%, and 1.2%). Dynamic shear rheometer (DSR) and bending beam rheometer (BBR) tests were performed on HVMA after rheological processes. Also, microstructural properties were examined by Fourier transform infrared spectroscopy and scanning electron microscopy methods. Based on the obtained results, all WMAs reduced the viscosity (135°C) of HVMA and achieved warm mixing effects. However, absolute viscosity (60°C) was enhanced by Sasobit and GLWBR. In addition, GLWBR improved high-temperature rheological performance and had no significant effect on the low-temperature and aging performance of HVMA. These findings were further verified by morphological observations.

This study investigates the impacts of rejuvenator type/dosage and the aging degree of bitumen on the chemical and rheological properties of rejuvenated bitumen, and propose critical chemo-rheological indicators for evaluating rejuvenation efficiency. Moreover, the potential connections between essential chemical and rheological indices of rejuvenator-aged bitumen blends are explored. Results indicate that chemical indices show linear relationships with rejuvenator dosage and vary depending on the rejuvenator type and aging level of bitumen. All rejuvenators can regenerate certain rheological parameters of aged bitumen to varying degrees, but cannot restore the crossover modulus (Gc). Various rheological indices exhibit different correlations with rejuvenator dosage and sensitivity degrees to the discrepancy in rejuvenator type and aging degree of bitumen. Critical chemical and rheological indicators are proposed based on their sensitivity levels to influence factors, with the aromaticity index (AI), carbonyl index (CI), and sulfoxide index (SI) as effective chemical indices and the complex modulus (G*), crossover frequency (fc), and high-temperature master curve area (AMH) as critical rheological indices for rejuvenation efficiency evaluation. The study finds that the magnitude of rejuvenation efficiency for four rejuvenators is Bio-oil > Engine-oil > Naphthenic-oil > Aromatic-oil, and the linear correlations between the critical chemical and rheological indices, together with their rejuvenation percentages, are significantly affected by the rejuvenator type and aging level of bitumen.

The rejuvenation efficiency of aged bitumen is the main concern when developing rejuvenating agents. It is necessary to develop a method to assess the efficiency of rejuvenators using rheological parameters in the whole frequency region. To this end, the 2S2P1D micromechanics model is adopted to fit the entire G∗ master curves of various rejuvenated bitumen, and the influence of rejuvenator type/dosage and aging grade of bitumen on the whole G∗ master curve and chemical indices are investigated. Critical parameters for evaluating rejuvenation efficiency derived from viscoelastic models and chemical characterizations are proposed. Furthermore, the potential relationships between the rheological model-based parameters (E _∞, δ, β, and τ) and chemical indices (carbonyl index CI and sulfoxide index SI) are explored. The results indicate that rejuvenators restore the δ, τ, CI, and SI values of aged bitumen towards the virgin bitumen level. The E _∞ parameter is not applicable to evaluate the rejuvenation efficiency of engine-oil and naphthenic-oil rejuvenators, but the positive E _∞R values of bio-oil and aromatic-oil rejuvenated bitumen are detected. All rejuvenators fail to restore the β parameter of aged bitumen. The τ and CI parameters are selected as critical evaluation indicators from the perspective of viscoelastic models and chemical characteristics. Linear correlations between all rheological parameters and chemical indices are observed and established.