his study aimed to investigate the usability of Recycled Concrete Aggregate (RCA) in warm mix asphalt (WMA) as the implementation of sustainable construction technology. Five replacement rates (0%, 25%, 50%, 75%, and 100%) were tested for the coarse fraction of virgin aggregate (VA) with 3 types of RCA: untreated RCA, HL-treated RCA, and HCL-treated RCA. Scanning electron microscopy (SEM) analyses were performed to investigate the surface morphology for both treated and untreated RCA. The optimum asphalt cement content for every substitution rate was determined using Marshall mix design method. Thereafter, asphalt concrete specimens were prepared using the optimum asphalt cement content, followed by the evaluation of their performance prope

The durability of asphalt concrete is highly dependent on the geometry and mineralogy of coarse aggregates, yet their combined influence on mechanical and moisture resistance properties is still not fully understood. This study evaluates the effects of coarse aggregate geometry, specifically flat and elongated particle ratios and angularity, as well as mineral composition (quartz versus calcite), on asphalt mixture durability. The durability of mixtures was evaluated through Marshall properties as well as moisture susceptibility indicators, including the tensile strength ratio (TSR) and index of retained strength (IRS). Statistical analyses (ANOVA and t-tests) were also conducted to confirm the significance of the observed effects.

Tests were performed on Marshall samples and were implemented for permanent deformation and resilient modulus (Mr) under indirect tensile repeated loading (ITRL), with constant stress level. Two types of liquid asphalt (cutback and emulsion) were tried as recycling agents, aged materials that were reclaimed from field (100% RAP), samples were prepared from the aged mixture, and two types of liquid asphalt (cutback and emulsion) with a weight content of 0.5% were utilized to prepare a recycled mixture. A group of twelve samples was prepared for each mixture; six samples were tested directly for ITRL test (three samples at 25˚C and three samples at 40˚C), an average value for ITRL for every three samples was calculated (

Straight tendons in pretensioned members can cause high-tensile stresses in the concrete extreme fibers at end sections because of the absence of the bending stresses due to self-weight and superimposed loads and the dominance of the moment due to prestressing force alone. Accordingly, the concrete tensile stresses at the ends of a member prestressed with straight tendons may limit the service load capacity of the member. It is therefore important to establish limiting zone in the concrete section within which the prestressing force can be applied without causing tension in the extreme concrete fibers. Two practical methods are available to reduce the stresses at the end sections due to the prestressing force. The first method based

This paper reports on the experimental study, which conducted a series of triaxial tests for the asphalt concrete using hydrated lime as a mineral additive. Three HMA mixes, prepared by the specification for wearing, levelling and base layers, were studied under three different temperatures. The test results have demonstrated that, compared with the control mixes excluding HL, the permanent deformation resistance of the HL modified mixes has significant improvement. The deformation has been reduced at the same load repetition number, meanwhile the flow number has been considerably increased. The degree of improvement in permanent deformation resistance using HL is more pronounced at high stress deviation states and high temperature.

This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi