Flood-induced disruption of urban road networks is an increasing threat in mountain-front cities, where river overflow, canal failure, and rapid urban expansion converge. This study integrates the Analytic Hierarchy Process (AHP) with Geographic Information Systems (GIS) to assess flood risk and prioritize climate-resilient road infrastructure in Almaty, the largest city of Kazakhstan. Five flood-conditioning criteria—distance to water, elevation, land use and land cover, rainfall, and slope—were classified into five susceptibility levels using the Jenks Natural Breaks method and combined through AHP-derived weights into a composite Flood Susceptibility Index. Distance to water received the highest weight (36.84
Recycled polyethylene terephthalate (PET) has been investigated as an asphalt modifier, although compatibility, storage stability, and performance optimization remain challenges. This study evaluated a ternary modification strategy combining micronized PET, ethylene–methyl acrylate–glycidyl methacrylate (EMA-GMA), and polyphosphoric acid (PPA) to improve the physical and rheological properties of asphalt binders. A control binder (AB 50/70, PG 64-22) was modified using three formulations: M1 (1.80
Open-graded friction course (OGFC) is gaining popularity due to economic, safety, and environmental benefits. It consists of coarse-grained aggregate skeleton, low quantity of fine aggregates and negligible filler. This study motivated to maximize the Reclaimed Asphalt Pavement (RAP) incorporation as aggregate along with Rice Husk Ash (RHA) as filler in OGFC. The conventional OGFC mix is designed for a fixed gradation using conventional aggregates and 2
The increasing demand for sustainable construction materials has encouraged the development and application of masonry units that can reduce resource consumption and environmental impacts while maintaining adequate engineering performance. Although AAC blocks, Fly Ash Bricks, Clay Bricks, and Compressed Stabilised Earth Blocks (CSEB) have been extensively investigated individually, comparatively fewer studies have evaluated these materials within a common framework integrating mechanical, physical, moisture-transport, microstructural, and data-driven analyses. The present study addresses this gap through a comparative experimental investigation of AAC blocks, Fly Ash Bricks, Clay Bricks, and CSEB using compressive strength, density, water absorption, initial rate of absorption (IRA), and sorptivity measurements, supplemented by Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD) characterization. An Artificial Neural Network (ANN) model was subsequently developed using experimentally measured density, water absorption, IRA, sorptivity, and material type as input variables to predict compressive strength, while SHAP analysis was employed to interpret the relative contribution of the input parameters. The experimental results showed that Fly Ash Bricks exhibited the highest average compressive strength of 10.06 MPa, whereas AAC blocks exhibited the lowest density of 649 kg/m3 and the highest moisture-transport characteristics. The correlation analysis indicated a strong positive relationship between density and compressive strength, whereas water absorption, IRA, and sorptivity exhibited negative relationships with strength. The ANN model demonstrated high predictive agreement with the experimental results, while SHAP analysis identified density and water absorption as the most influential variables. The contribution of the study lies in the comparative integration of experimental, microstructural, statistical, and explainable machine-learning analyses for evaluating diverse masonry materials using experimentally measured properties. The findings provide a systematic basis for comparing masonry performance and support data-driven assessment of sustainable masonry materials.
Textile Reinforced Concrete is widely used to strengthen Reinforced Concrete (RC) beams, an effective technique that optimizes the use of textile fibers by providing high ductility. The premature debonding of the TRC layer from the RC beam is the predominant failure that reduces the efficacy of the TRC-strengthened beam. TRC wrapping configurations control interfacial debonding and enable the effective utilization of additional TRC layers. Therefore, the influence of different TRC wrapping configurations and the number of textile layers on the flexural behavior and failure of strengthened RC beams requires further investigation. To this aim, the flexural performance of the U-shaped wrapping and the bottom wrapping of RC beams is investigated using a three-point bending test. Among the four strengthened specimens, two are bottom-wrapping with 2-layer and 4-layer arrangements. The remaining two specimens are U-shaped wrapping with corresponding 2-layer and 4-layer arrangements. The flexural analysis successfully reveals the impact of TRC wrapping pattern and the number of textile layers on load–deflection curves, stiffness, ductility, energy dissipation capacity, and failure modes. The U-shaped wrapping effectively increases both the ductility and the stiffness of the RC beam. The 4-layer U-shaped wrapping beam provides peak load and energy dissipation capacities that are 109
