X. Liu
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178 records found
1
Chemo-physical rejuvenation of aged SBS-modified bitumen
Multiscale effects of oils, polymer replenishment, and reactive chain extender
Styrene-butadiene-styrene (SBS)-modified binders in porous asphalt age rapidly, degrading both the viscoelastic bitumen phase and the crosslinked polymer network, hindering high-value recycling of reclaimed asphalt pavement (RAP). Conventional rejuvenation predominantly softens bitumen while overlooking polymer restoration. This study separates rejuvenation into two categories, what is repaired (bitumen vs SBS) and how it is repaired (physical vs chemical), to develop and compare four families: (1) oils targeting the bitumen phase, (2) oil–SBS blends supplying fresh polymer, (3) methylene diphenyl diisocyanate (MDI) promoting chemical reconnection of SBS chains, and (4) chemo-physical systems combining MDI with oil–SBS. Chemical properties were linked to performance using Fourier-Transformation Infrared (FTIR) spectroscopy, Gas Chromatography-Flame Ionization Detection (GC-FID), Dynamic Shear Rheometer (DSR) master curves, Multiple Stress Creep and Recovery Test (MSCRT), creep-relaxation, Linear Amplitude Sweep (LAS), fluorescence microscopy, and Environmental Scanning Electron Microscopy (ESEM). Results show that oils softened the binder and improved fatigue and low-temperature properties but diluted the SBS signal and failed to restore elasticity. Oil–SBS raised the SBS index and partially recovered elasticity, though microscopy revealed only discrete polymer domains. MDI on its own enhanced stiffness and elastic recovery but caused brittleness. Chemo-physical rejuvenators reconciled these trade-offs, yielding elasticity comparable to the unaged binder, creep-relaxation and LAS fatigue resistance approaching or exceeding the reference, and dense, well-dispersed polymer-rich domains. These findings highlight the need to combine bitumen softening, polymer replenishment, and chemical chain reconnection for effective SBS restoration and high-quality recycling of SBS-modified RAP, thereby advancing cleaner, resource-efficient pavement material systems.
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.
This study advances that foundation by employing Artificial Neural Networks (ANNs), which—when properly trained—can capture complex relationships with greater continuity and generalizability. Beyond simply replacing RFRs, we develop a fully automated framework for constructing Machine Learning Models (MLMs) to predict density and thermal expansion coefficients of bitumen. Using Optuna for hyperparameter optimization, we ensure that the information extracted from MD simulations is utilized effectively.
The resulting ANN models accurately reproduce MD-predicted densities, achieving R2>0.99, MSEs below 0.1 %, and maximum absolute errors below 5 % on test data. In addition to reducing computational cost, the models exhibit improved interpolation and extrapolation capabilities, enabling reliable predictions for properties, ranges, and compositions not explicitly simulated.
Key aspects of our approach include:
• Transitioning from RFRs to ANNs, improving generalization, interpolation, and predictive accuracy.
• Automated hyperparameter optimization, leveraging Optuna to maximize model efficiency.
• Expanding applicability, enabling property prediction for unseen compositions without additional MD simulations. ...
This study advances that foundation by employing Artificial Neural Networks (ANNs), which—when properly trained—can capture complex relationships with greater continuity and generalizability. Beyond simply replacing RFRs, we develop a fully automated framework for constructing Machine Learning Models (MLMs) to predict density and thermal expansion coefficients of bitumen. Using Optuna for hyperparameter optimization, we ensure that the information extracted from MD simulations is utilized effectively.
The resulting ANN models accurately reproduce MD-predicted densities, achieving R2>0.99, MSEs below 0.1 %, and maximum absolute errors below 5 % on test data. In addition to reducing computational cost, the models exhibit improved interpolation and extrapolation capabilities, enabling reliable predictions for properties, ranges, and compositions not explicitly simulated.
Key aspects of our approach include:
• Transitioning from RFRs to ANNs, improving generalization, interpolation, and predictive accuracy.
• Automated hyperparameter optimization, leveraging Optuna to maximize model efficiency.
• Expanding applicability, enabling property prediction for unseen compositions without additional MD simulations.
Scymol
A python-based software package for initializing and running molecular dynamics simulations using LAMMPS
Fatigue cracking is one of the most notable distresses in steel bridge deck pavement (SBDP), necessitating the development of high performance pavement materials to extend service life. In this paper, the fatigue resistance characteristics of natural rock asphalt (NRA)/SBS systematically evaluated. Twelve types of composite-modified asphalt binders were prepared by incorporating Iranian rock asphalt (IRA), Buton rock asphalt (BRA), and SBS as modifiers. IRA and BRA were added at 5 wt%, 10 wt%, and 15 wt%, while SBS was introduced at 2 wt% and 3 wt%. The modified asphalt binders subjected to time sweep (TS) test and linear amplitude sweep (LAS) test to comparatively analyze fatigue damage and fatigue life. DSR-C model was applied to calculate the fatigue crack length. The research also comparative evaluate differences and correlations between fatigue crack length indexes and conventional fatigue life indexes. The results showed that NRA enhanced the fatigue performance of modified asphalt binders. With the increase of NRA content, the fatigue properties of modified asphalt also become better. S3I15 is better than other composite modified asphalt binders in both fatigue life and fatigue cracking indexes, demonstrating that it offers the best resistance to fatigue damage. The fatigue cracking index calculated by the DSR-based cracking (DSR-C) model could effectively evaluate the fatigue performance of NRA/SBS composite modified asphalt binders. NRA/SBS composite modified asphalt could be widely used in steel bridge deck pavement.
Pavement materials that could enhance the mechanical properties of open-graded porous asphalt mixtures in long-term service periods could offer a solution to produce long-life pavements, causing a reduction of interventions' needs, as well as the associated disruptions to road users and user costs. One option to improve the longevity of open-graded porous mixtures is with the use of epoxy asphalt that, despite its high initial cost, offers enhanced longevity that might offset any future user and intervention costs. This study aimed to evaluate the durability of plant-produced epoxy-modified open-graded porous asphalt mixtures. A batch production plant was employed to produce loose mixtures, which were used to pave a test road in the Province of Gelderland, the Netherlands, and compact specimens in the laboratory. Control mixtures with a non-epoxy-modified asphalt binder were also produced in the same plant. The durability of laboratory- and field-compacted mixtures was evaluated by conducting indirect tensile tests before and after oven conditioning. Results illustrated that the epoxy-modified asphalt demonstrated the highest strength and stiffness values, while the strength was reduced after conditioning in a water bath with the retained strength within the allowable specification limits. This attribute was confirmed from drill cores obtained from the test road after one year in service. Also, the materials compacted in the field had slightly higher strength and stiffness values than the laboratory-produced mixtures. Although the results provided have illustrated the improvement of durability of open-graded porous asphalt with implementing epoxy modification, further evidence from the test road over the years is needed for validation.
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.
An asphalt joint is formed when a fresh mix is laid and compacted next to an existing layer, brings about temperature difference during compaction, and therefore requires extra care in quality control and expose to higher cracking risks. Self-healing asphalt aims to stimulate the healing capacity of asphalt mixture and prolong its service life. The main objective of this study is to develop and optimize a calcium alginate capsules healing system for an asphalt joint mix. Capsules following two different self-healing concepts were prepared, namely conventional alginate capsules and conductive alginate capsules. Microscopy, Computed Tomography (CT) and Thermogravimetry analysis (TGA) were used to investigate the performance of alginate capsules. The results show that both types of capsules have a porous structure and a stable performance under high temperature, and therefore potentially survive from the asphalt mixing and production process. These capsules will be implemented and evaluated in full asphalt mix in future research.
AA2UA
Converting all-atom models into their united atom coarse grained counterparts for use in LAMMPS
This study employs strain-controlled oscillatory deformations in Molecular Dynamics (MD) simulations to evaluate the dynamic properties of all-atom molecular systems, specifically targeting the SARA fractions of bitumen. Twelve molecular systems representing these fractions were modeled using the PCFF force field. The simulations effectively captured their viscoelastic properties across multiple frequency domains, including Elastic, Glassy, Rubbery, and Viscous responses. Reported storage and loss moduli range from thousands to tens of megapascals, with viscosities from tens to near-zero Pascal-seconds across various frequencies and temperatures, aligning well with experimental observations. Saturates and Aromatics were identified as the softest and most thermally susceptible fractions, while Resins and Asphaltenes were the stiffest and least susceptible. The study reveals that the relaxation time of all-atom molecular systems is significantly shorter than in experimental setups, necessitating careful comparison of stress-related phenomena across equivalent relaxation times. Although this allows for the exploration of response profiles in computationally tractable simulations, the nature of all-atom force fields and simulation algorithms introduces spatiotemporal scale discrepancies that must be addressed in future simulations involving the study of stress-related phenomena using MD.
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.
SMI2PDB
A self-contained Python tool to generate atomistic systems of organic molecules using their SMILES notations
This paper presents a United Atom (UA) force field for simulating hydrocarbon molecules in bituminous materials, integrating explicit hydrogens into beads with their parent atom. This method simplifies all-atom molecular models, significantly accelerating Molecular Dynamics (MD) simulations of bitumen by 10 to 100 times. Key advantages include halving the particle count, eliminating complex hydrogen interactions, and decreasing the degrees of freedom of the molecules. Developed by mapping forces from an all-atom model to the centers of mass of UA model beads, the force field ensures accurate replication of energies, forces, and molecular conformations, mirroring properties like pressure and density. It features 17 bead types and 287 interaction types, encompassing various hydrocarbon molecules. The UA force field's stability, surpassing all-atom models, is a notable achievement. This stability, stemming from smoother potential energy surfaces, leads to consistent property measurements and improved stress tensor accuracy. It enables the extension of MD simulations to larger spatiotemporal scales, crucial for understanding complex phenomena such as phase separation in bituminous materials. This foundational work sets the stage for future developments, including refining parameters and introducing new bead types, to enhance the modeling capabilities of the force field, thereby advancing the application and understanding of bituminous materials.