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It is commonly known that mineral fillers significantly affect the asphalt mixture's performance. Superior flexible pavement performance can be ensured by gaining a deeper understanding of the function of filler. This research investigates the influence of three different fillers: granite dust, cement, and hydrated lime, at Australian asphalt mixtures. The testing program includes Marshall testing, moisture damage resistance, indirect tensile strength (ITS), and indirect tensile stiffness modulus (ITSM) tests of asphalt mixtures. Analysis of variance (ANOVA) was used to statistically assess the results obtained, besides damage analysis. The results indicate that using natural granite dust yields the highest resistance to moisture, while cement produces the highest stability, ITS, and ITSM. Unexpectedly, using hydrated lime filler decreases the stability/stiffness and moisture resistance of asphalt mixtures. ANOVA tests indicate that the type of filler affects ITS, TSR, and ITSM results (i.e., the p-value

Recognizing material waste as a significant global concern has influenced both the environment and the construction industry. The utilization of ceramic waste as a recycled material in construction projects has gained attention as an effective and sustainable approach to address environmental issues. This study examines the use of waste ceramic tile powder (WCTP) as a supplementary material in cement mortars to decrease the amount of cement required. WCTP was used in place of cement at percentages of 5%, 10%, and 20%. Four different mix designs were created and tested for the study, yielding a total of 48 specimens. Numerous investigations were carried out, including flow table evaluations, measures of dry density, assessments of compressive and flexural strengths, X-ray diffraction, and SEM-EDX testing. The objective of these investigations was to evaluate the specimens' mechanical and physical characteristics as a whole. The findings showed that using ceramic powder in place of some cement might enhance the properties of the mortar. The compressive and flexural strengths of the mortar were notably impacted by replacing 10% of the cement content with ceramic powder. The inclusion of ceramic powder significantly enhanced the mortar's microstructure interface, according to SEM-EDX studies. In the end, the utilization of ceramic powder was found to have a substantial positive impact on the environment by reducing waste. [ABSTRACT FROM AUTHOR]

Conventional concrete causes significant environmental problems, including resource depletion, high CO2 emissions, and high energy consumption. Steel slag aggregate (SSA), a by-product of the steelmaking industry, offers a sustainable alternative due to its environmental benefits and improved mechanical properties. This study examined the predictive power of four modeling techniques—Gene Expression Programming (GEP), an Artificial Neural Network (ANN), Random Forest Regression (RFR), and Gradient Boosting (GB)—to predict the compressive strength (CS) of SSA concrete. Using 367 datasets from the literature, six input variables (cement, water, granulated furnace slag, superplasticizer, coarse aggregate, fine aggregate, and age) were utilized to predict compressive strength. The models' performance was evaluated using statistical measures such as the mean absolute error (MAE), root mean squared error (RMSE), mean values, and coefficient of determination (R2). Results indicated that the GB model consistently outperformed RFR, GEP, and the ANN, achieving the highest R2 values of 0.99 and 0.96 for the training and testing dataset, respectively, followed by RFR with R2 values of 0.97 (training) and 0.93 (testing), GEP with R2 values of 0.85 (training) and 0.87 (testing), and ANN with R2 values of 0.61 (training) and 0.82 (testing). Additionally, the GB model had the lowest MAE values of 0.79 MPa (training) and 2.61 MPa (testing) and RMSE values of 1.90 MPa (training) and 3.95 MPa (testing). This research aims to advance predictive modeling in sustainable construction through analysis and well-defined conclusions. [ABSTRACT FROM AUTHOR]

This paper assesses the capability of using a new data‐driven approach to predict the bond strength between steel rebar and concrete subjected to high temperatures. The analysis has been conducted using a novel evolutionary polynomial regression analysis (EPR‐MOGA) that employs soft computing techniques, and new correlations have been proposed. The proposed correlations provide better predictions and enhanced accuracy than existing approaches, such as classical regression analysis. Based on this novel approach, the resulting correlations have achieved a lower mean absolute error (MAE), and root mean square error (RMSE), a mean (μ) close to the optimum value (1.0) and a higher coefficient of determination (R2) compared to available correlations, which use classical regression analysis. Based on their enhanced performance, the proposed correlations can be used to obtain better optimised and more robust design calculations. [ABSTRACT FROM AUTHOR]

Porous materials play an important role in creating a sustainable environment by improving wastewater treatment's efficacy. Porous materials, including adsorbents or ion exchangers, catalysts, metal–organic frameworks, composites, carbon materials, and membranes, have widespread applications in treating wastewater and air pollution. This review examines recent developments in porous materials, focusing on their effectiveness for different wastewater pollutants. Specifically, they can treat a wide range of water contaminants, and many remove over 95% of targeted contaminants. Recent advancements include a wider range of adsorption options, heterogeneous catalysis, a new UV/H2O2 procedure, ion exchange, Fenton oxidation, membrane activities, ozonation, membrane bioreactor, electrochemical treatment, wet air oxidation, and a carbon capture methodology utilizing various porous materials. A particular focus for innovative research is on developing technologies to synthesize porous materials and assess their performance in removing various pollutants from wastewater at varying experimental conditions. Porous materials can be essential in designing wastewater treatment systems to address the critical environmental issues of water stress and safe drinking water worldwide. [ABSTRACT FROM AUTHOR]

Material processing, using water contact laser technology, can enhance the machining, welding, or cutting quality. In this paper, we explore the alteration of Titanium alloy (Ti6Al4V) surface properties by nanosecond-pulsed laser-processing method in water and air, under various conditions. In this work, we adopt several analysis approaches, such as crater width, surface morphology, oxidation, and wettability. The results show that, in the case of laser processing in the air up to 500 mJ with 50 pulses, the laser parameters enhance the hydrophilicity. The processing environment would also impact the crater width, shape, and distribution of the created surface structures. Conversely, the surface oxygen content significantly raises on the laser-irradiated surfaces. According to these results, it is more logical to conclude that all of these cooperative chemical and physical changes increase the surface wettability and cause it to be more hydrophilic. [ABSTRACT FROM AUTHOR]