Evaluating the substitution potential of SBS with crumb rubber-polypropylene blends as asphalt binder and mixture modifiers

D Nasr, R Babagoli, M Rezaei, PR Borujeni - Construction and Building …, 2022 - Elsevier
The study aimed to assess the suitability of substituting styrene–butadienestyrene with
waste crumb rubber-polypropylene blends as modifiers to enhance the performance …

The influencing factors of evaporation residue of emulsified modified asphalt to optimize the environmental adaptability

Y Lin, C Qian, J Shi, Y Zhang, S Ren, G Nan… - … and Building Materials, 2022 - Elsevier
Compared with traditional asphalt, emulsified asphalt occurs to be a better low-temperature
usability and environmental adaptability, which can reduce environmental pollution and …

[HTML][HTML] Modelling of Marshall stability of polypropylene fibre reinforced asphalt concrete using support vector machine and artificial neural network

S Jalota, M Suthar - International Journal of Transportation Science and …, 2024 - Elsevier
The present study assesses the proficiency of support vector machine (SVM) models
utilizing four kernel functions namely normalized polynomial kernel function (SVM …

Evaluation of asphalt mixtures modified with low-density polyethylene and high-density polyethylene using experimental results and machine learning models

M Junaid, C Jiang, U Gazder, I Hafeez, D Khan - Scientific Reports, 2024 - nature.com
The widespread use of low-density polyethylene (LDPE) and high-density polyethylene
(HDPE) plastics has resulted in a large amount of waste plastic that requires appropriate …

Prediction and evaluation the moisture damage resistance of rejuvenated asphalt mixtures based on neural network

Y Luo, P Guo, J Gao, Y Chen, D Zhou, JY Hu - Construction and Building …, 2023 - Elsevier
The aim of this paper is to establish a model for predicting the moisture damage resistance
of the rejuvenated asphalt mixture. Based on the surface free energy theory, the contact …

Prediction of Marshall stability of asphalt concrete reinforced with polypropylene fibre using different soft computing techniques

S Jalota, M Suthar - Soft Computing, 2024 - Springer
In the present study, various soft computing techniques were employed for predicting the
Marshall stability (MS) of asphalt concrete reinforced with polypropylene fibre, namely …

Marshall Stability Prediction with Glass and Carbon Fiber Modified Asphalt Mix Using Machine Learning Techniques

A Upadhya, MS Thakur, MS Al Ansari, MA Malik… - Materials, 2022 - mdpi.com
Pavement design is a long-term structural analysis that is required to distribute traffic loads
throughout all road levels. To construct roads for rising traffic volumes while preserving …

Prediction of Compressive Strength of Fly Ash-Slag Based Geopolymer Paste Based on Multi-Optimized Artificial Neural Network

M Bai, Z Zhang, K Cao, H Li, C He - Materials, 2023 - mdpi.com
The fly ash-slag geopolymer is regarded as one of the new green cementitious materials
that can replace cement, but it is difficult to predict its mechanical properties by conventional …

[HTML][HTML] Macro-microscopic study on the crack resistance of polyester fiber asphalt mixture under dry-wet cycling and neural network prediction

J Wu, Y Hu, Q Jin, H Ren - Case Studies in Construction Materials, 2024 - Elsevier
Asphalt mixture is a composite material with a complex multiphase dispersed system, and its
macroscopic mechanical behavior is inherently related to the microstructure characteristics …

[PDF][PDF] Benchmarking Classical and Deep Machine Learning Models for Predicting Hot Mix Asphalt Dynamic Modulus

W Zeiada, L Obaid, S El-Badawy… - Civil Engineering …, 2025 - researchgate.net
Abstract The dynamic modulus (| E*|) of hot-mix asphalt (HMA) is a crucial mechanistic
characteristic essential in defining the strain response of asphalt concrete (AC) mixtures …