Aug 2026· Academic Journal of International University of Erbil· Vol 3, pp. 176-184· 0 citations· 31 references
Abstract
Porous asphalt pavements play an important role in stormwater management while also providing structural integrity. Reliable permeability prediction is dynamic, allowing for better design optimization, long-term functioning evaluation, and effective maintenance planning. This work creates and evaluates artificial intelligence (AI) models for predicting the hydraulic permeability of porous asphalt pavements using a multi-regional dataset comprising 1,250 laboratory and field observations. The information included mix design parameters (air voids, D10/D50 ratio, binder concentration), compaction, construction, climate, and maintenance history. Machine-learning techniques such as artificial neural networks (ANN), support vector machines (SVM), random forest, and gradient boosting were trained and tested using 10-fold cross-validation and temporal validation (2010–2017 training; 2018–2021). ANN provided the greatest performance (R² = 0.91, RMSE ≈ 0.11 cm/s) with a
This study examined advanced machine learning models to predict key volumetric parameters of stone mastic asphalt (SMA) mixtures incorporating waste tire rubber. The input parameters were rubber aggregate and rubber modifier. The target outputs were air void, voids filled with asphalt, voids in mineral aggregate, and...
H. Çıtakoğlu, Ş. Aslan, Sevda Herdem· Scientific Reports· 0 citations
To ensure asphalt pavement durability under environmental and traffic loads, this study investigates permanent deformation caused by temperature changes and repeated axle loads. Based on long-term full-scale track monitoring, a feature fusion model integrating cumulative load passes and temperature was developed. We...
Mei-Yi Zhang, Gui-Yu Gan, Tai-Xin Fu et al.· Frontiers in Materials· 0 citations
An interpretable machine learning framework for predicting Va using 74 mixtures collected from 16 published studies and nine mixture-related variables is developed, which provides an interpretable tool for preliminary Va estimation and mixture screening, while independent laboratory and field validation remains necessa...
Thu-Hien Thi Hoang, H. Nguyen, H. Hoang et al.· Buildings· 0 citations
The results show that regularized models can support preliminary RAC mix evaluation and material assessment and show that regularized models can support preliminary RAC mix evaluation and material assessment.
Navin Kumar Gautam, Amrendra Kumar· Revista ALCONPAT· 0 citations
In Nigeria, buried steel infrastructure suffers premature failure due to soil-induced corrosion, yet existing degradation models rely on idealized laboratory simulations that ignore real-world soil heterogeneity and welding parameter interactions. This study addresses this critical gap by investigating mechanical prope...
L. M. Ebhota, O. Ogbeide, F. Uwoghiren et al.· International Journal of Phy...· 0 citations
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