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One of the often-employed building constituents in the construction sector is concrete, which involves hydration of cement, leading to the generation of carbon footprints during its production. Also, massive amount of natural aggregate is illegally mined, which poses serious environmental issues along with ecological misbalance. Researchers are in continuous search of appropriate substitutes to mitigate those challenges and develop innovative concrete mix. Consequently, depletion of natural resources, the disturbances to the environmental and ecological imbalance will reduce. The purpose of this study is to develop a Portland Slag Cement based novel sustainable concrete incorporating Alccofine and Recycled Refractory Brick as fractional replacement of cement and fine aggregate, respectively and evaluate its destructive, non-destructive and microstructural properties.

M25 grade of concrete adopting 0.45 water-binder proportion, with diverse percentage of Alccofine as fractional substitution of cement and 20% of recycled refractory brick (RRB) as fine aggregate, has been cast and evaluated for diverse mechanical strength following a curing of 7, 14 and 28 days. Scanning electron microscopic analysis has been carried out to study the microstructural changes in the specimens.

Supplementary use of Alccofine enhanced normal compressive strength of sustainable concrete mix blended with Portland Slag Cement by a large amount at all levels of 7, 14 and 28 days of curing. Test results indicated development of a favourable high-strength sustainable concrete mix by substituting cement with Alccofine.

This manuscript has demonstrated the possibility of developing sustainable concrete blends by incorporating Alccofine 1203 and RRB as partial replacement of Portland Slag Cement and natural fine aggregate, respectively. The strength and potential of concrete incorporating RRB for wider and special application in adverse environmental conditions having higher thermal gradient, as RRB is a valuable waste from high temperature kiln and furnaces. Alccofine 1203 has been included in the concrete mix as an alternative to Portland Slag Cement to improve the mechanical strength properties and durability of concrete intended for adverse environmental application.

Accurate predictions of the steady-state corrosion phase and service life to achieve specific safety limits are crucial for assessing the service of reinforced concrete (RC) structures. Forecasting the service life (SL) of structures is imperative for devising maintenance and repair strategy plans. The optimization of maintenance strategies serves to prolong asset life, mitigate asset failures, minimize repair costs and enhance health and safety standards for society.

The well-known empirical conventional (traditional) approaches and machine learning (ML)-based SL prediction models were presented and compared. A comprehensive parametric study was conducted on existing models, considering real-world conditions as reported in the literature. The analysis of traditional and ML models underscored their respective limitations.

Empirical models have been developed by considering simplified assumptions and relying on factors such as corrosion rate, steel reinforcement diameter and concrete cover depth, utilizing fundamental mathematical formulas. The growth of ML in the structural domain has been identified and highlighted. The ML can capture complex relationships between input and output variables. The performance of ML in corrosion and service life evaluation has been satisfactory. The limitations of ML techniques are discussed, and its open challenges are identified, along with insights into the future direction to develop more accurate and reliable models.

To enhance the traditional modeling of service life, key areas for future research have been highlighted. These include addressing the heterogeneous properties of concrete, the permeability of concrete and incorporating the interaction between temperature and bond-slip effect, which has been overlooked in existing models. Though the performance of the ML model in service life assessment is satisfactory, models overlooked some parameters, such as the material characterization and chemical composition of individual parameters, which play a significant role. As a recommendation, further research should take these factors into account as input parameters and strive to develop models with superior predictive capabilities.

Recent deployment has revealed that ML algorithms can grasp complex relationships among key factors impacting deterioration and offer precise evaluations of remaining SL without relying on traditional models. Incorporation of more comprehensive and diverse data sources toward potential future directions in the RC structural domain can provide valuable insights to decision-makers, guiding their efforts toward the creation of even more resilient, reliable, cost-efficient and eco-friendly RC structures.

This study aims to investigate the mechanical properties of sustainable recycled polypropylene (rPP) composite materials integrated with spherical silicon carbide (SiC) particles.

A representative volume element (RVE) analysis is employed to predict the Young’s modulus of rPP filled with spherical-shaped SiC at varying volume percentages (i.e. 10, 20 and 30%).

The investigation reveals that the highest values of Young’s modulus, tensile strength, flexural strength and mode 1 frequency are observed for the 30% rPP/SiC samples, exhibiting increases of 115, 116, 62 and 15%, respectively, compared to pure rPP. Fractography analysis confirms the ductile nature of pure rPP and the brittle behavior of the 30% rPP/SiC composite. Moreover, the RVE method predicts Young’s modulus more accurate than micromechanical models, aligning closely with experimental results. Additionally, results from ANSYS simulation tests show tensile strength, flexural strength and frequency within a 10% error range when compared to experimental data.

This study contributes to the field by demonstrating the mechanical enhancements achievable through the incorporation of sustainable materials like rPP/SiC, thereby promoting environmentally friendly engineering solutions.