Jayaprakash Sridhar

Pervious concrete is a special type of concrete being used in construction industry and offering a sustainable solution for storm water management and ground water recharge. This research focuses on Response Surface Methodology (RSM) with a Box- Behnken design to systematically evaluate different parameters such as aggregate size, quantities of ordinary Portland cement (OPC), Portland Pozzolana Cement (PPC) and coarse aggregate content for analysing the influence the mechanical performance of pervious concrete mixes. Through comprehensive testing and statistical analysis, the study uncovers complex interactions of the mix components, facilitating the identification of optimal formulations to achieve a balance between strength and sustainability for diverse applications. In this present study, nine mixes were performed with varying Aggregate Binder (A/B) and Water Binder (W/B) ratio ranging from 3 - 2.9 and 0.3 - 0.35. All the mixes were tried with OPC and PPC binders using aggregate sizes viz. 6.3 mm, 9.4mm and 12.5 mm respectively. Test results proved that, mix containing more binder content with higher water cement ratio (M9) showcased higher mechanical strength properties than other mixes (M1-M8) due to enriched paste coating around the aggregate surface. Mix M1 has shown higher permeability and porosity due to lesser binder quantity and the adequate water-cement ratio results in slower rate of hydration process resulting in more void formation. Better strength properties are observed in smaller size aggregates which attributed to a dense microstructure. Increase in aggregate size results in decrease in strength whereas permeability and porosity increase.

The construction industry significantly contributes to global CO ₂ emissions, with cement production being a major factor. Concurrently, large quantities of crushed fly ash brick (CFAB) waste accumulate due to manufacturing defects. In this study, CFAB powder was developed as a supplementary cementitious material (SCM) by partially replacing cement in concrete mixes at 5%, 10%, and 15% by weight. Mechanical testing revealed that 5% CFAB replacement improved 28‐day compressive and flexural strengths by 21% and 33%, respectively, which was attributed to enhanced pozzolanic activity and the formation of calcium silicate hydrate (C–S–H) phases, as confirmed by scanning electron microscopy (SEM), energy‐dispersive X‐ray spectroscopy (EDAX), X‐ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) analyses. Higher replacement levels reduced strength due to dilution effects. These findings demonstrate that CFAB can serve as a reactive low‐carbon binder, promoting sustainable concrete production and waste valorization aligned with circular economy goals.

Amidst escalating concerns about global climate change, the construction industry emerges as a significant contributor to environmental degradation, primarily due to its extensive resource and energy utilization. To address this gap, this study adopts a Building Information Modeling (BIM)-enabled Life Cycle Assessment (LCA) approach to quantify the Global Warming Potential (GWP) and embodied carbon of key construction materials ready-mix concrete, steel, and bricks. Four residential building models of varying scales were developed in Autodesk Revit Architecture and analyzed using the One-Click LCA tool. The results reveal that steel exhibits the highest GWP (3.2–3.6 t.CO ₂ e per tonne), followed by bricks (0.24–0.28 t.CO ₂ e per tonne) and ready-mix concrete (0.11–0.15 t.CO ₂ e per tonne). On average, steel accounts for 34% of the total embodied carbon in buildings, making it the most carbon-intensive material. The embodied carbon benchmarks for the case studies range from 507 to 5176 kg.CO ₂ e m ⁻² , placing all models in the high-emission (red band) category. These findings underscore the crucial need for material optimization and sustainable design strategies at early project stages. The integration of BIM with LCA thus provides a powerful decision-support tool to understand the material impact on environment and advance carbon-conscious construction practices.

Ultra high performance engineered cementitious composites (UHP-ECCs) are advanced cementitious materials that exhibit exceptional strength, durability, and ductility. This chapter reviews the corrosion resistance and permeability properties of UHP-ECCs, which are critical factors in determining their suitability for various applications. UHP-ECCs have been shown to exhibit excellent resistance to corrosion in harsh environments due to their high cement content, low water-to-cement ratio, and the incorporation of various fibers. Additionally, UHP-ECCs exhibit extremely low permeability to liquids, gases, and ions, which makes them suitable for a wide range of applications, including water storage, wastewater treatment, and transportation infrastructure. The chapter concludes that UHP-ECCs are a highly desirable material for applications where corrosion resistance and low permeability properties are essential. Request access from your librarian to read this chapter's full text.

Newly developed high-performance concrete (HPC) is a revolutionary building material with superior mechanical properties and enhanced durability. Researchers have optimized HPC by incorporating industrial byproducts like modified ferro slag, silica fume, and fly ash, promoting sustainability and reducing carbon emissions. This paper analyzes the mechanical characteristics of HPC using the American Concrete Institute (ACI-211.1-91) guidelines, substituting cement with 17% fly ash (FA) and 10% silica fume (SF), and replacing coarse aggregate with up to 40% modified ferro slag. M60 grade was adopted for all mixes. Experimental tests assessed compressive strength (CS), split tensile strength (STS), and flexural strength (FS). Results showed significant improvements, with CS surpassing conventional HPC mixes by up to 25%. The highest CS, STS, and FS were observed with 30% modified ferro slag, achieving 10%, 6%, and 9% increases, respectively, at 28 days. These improvements indicate enhanced structural integrity and resistance to cracking. Utilizing industrial byproducts in HPC not only boosts performance but also supports sustainable construction by reducing waste and conserving natural resources.

In the present study, Response Surface Methodology model (RSM) and Artificial Neural Network model (ANN) is presented to forecast the ultimate moment capacity of ferrocement using 2 variable process modelling (volume fraction and steel slag replacement). The RSM and ANN model’s outcomes are contrasted with those of other existing models, like plastic analysis, mechnaism approcah, simplified method, group method of data handling, the results shows that ferrocement with steel slag replacement of 25% and chicken mesh volume fraction (V_r) of 4.35% has maximum experimental moment capacity of 253.33 kN-mm and predicted moment capacity using RSM and ANN is 244.70 kNmm and 255.88 kNmm respectively. The adopted ANN have a regression value of 0.9882 and 0.98863 for training and testing respectively. The outcomes of the analysis of variance show that the provided models are very suitable since the p value is less than 0.005, the projected R2 and the adjustable R2 is less than 20%. Moreover, the flexural moment of ferrocement composites is more significantly affected by the V_r. According to the findings of the surface plot, Pareto chart, and regression analysis, the V_r is the most important and crucial factor for the flexural moment of ferrocement composites.

This study aimed to develop accurate models for estimating the compressive strength (CS) of concrete using a combination of experimental testing and different machine learning (ML) approaches: baseline regression models, boosting model, bagging model, tree‐based ensemble models, and average voting regression (VR). The research utilized an extensive experimental dataset with 14 input variables, including cement, limestone powder, fly ash, granulated glass blast furnace slag, silica fume, rice husk ash, marble powder, brick powder, coarse aggregate, fine aggregate, recycled coarse aggregate, water, superplasticizer, and voids in mineral aggregate. To evaluate the performance of each ML model, five metrics were used: mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), coefficient of determination (R²‐score), and relative root mean squared error (RRMSE). The comparative analysis revealed that the VR model exhibited the highest effectiveness, displaying a strong correlation between actual and estimated outcomes. The boosting, bagging, and VR models achieved impressive R²‐scores in the range of 86.69%–92.43%, with MAE ranging from 3.87 to 4.87, MSE from 21.74 to 38.37, RMSE from 4.66 to 4.87, and RRMSE between 8% and 11%. Particularly, the VR model outperformed all other models with the highest R²‐score (92.43%) and the lowest error rate. The developed models demonstrated excellent generalization and prediction capabilities, providing valuable tools for practitioners, researchers, and designers to efficiently evaluate the CS of concrete. By mitigating environmental vulnerabilities and associated impacts, this research can significantly contribute to enhancing the quality and sustainability of concrete construction practices.

The impact of integrating Nano Silica (NS) on mechanical characteristics, resistance towards impact, and chloride penetration on concrete having Fly Ash (FA) are investigated in this research. The NS particles are subsequently mixed into concrete at one, two, three, four, and five percent of the binder’s mass, respectively. The performance of the specimens under an impact load is assessed by utilizing the drop weight impact technique, frequency on strikes, and impact force variation has been used to evaluate the specimen's impact resistance. The concrete's ability to withstand damage from chloride penetration was evaluated by determining the chloride diffusion coefficient of the samples. The test findings demonstrated that adding NS to concrete may significantly increase its mechanical characteristics as well as chloride penetration resistance. The optimum amount of NS substitution in concrete is two to three percent and it is discovered that if the proportion of NS is too large, the benefits of incorporating NS into the characteristics of the concrete are diminished, and might even have a detrimental effect on the resistance towards impact and durability of the concrete. Moreover, the experimental compressive strength and split tensile is compared with existing gene expression programming model.

The performance of structural composites during loading has always been a concern for the designers and construction industry since the reinforced concrete structure was discovered. In this study, lateral loaddisplacement behavior of beamcolumn joints wrapped with aramid fiber is evaluated using both experimental and numerical analysis subjected to torsional moment (beam-eccentric loading). Three categories of reinforcement concepts are adopted for the preparation of the beamcolumn joints, where members are wrapped with aramid fiber at the joints, and others are not fortified with aramid fibers. Prior to testing, the structural composites are cured for maximum 28 days into water. The beamcolumn joints are subjected to lateral load at a point near the column end of the beamcolumn connection, and the corresponding deflections are measured until the member fails. Based on the test results, ductility and energy absorption capacity are evaluated. The findings of the numerical investigation of beamcolumn joint show there is not much variation in the experimental and numerical analysis; it is clearly found that aramid fiber wrapping provided large rigidity in the joint, and it is also prolonged the final failure of the joints. This study shows that in addition to the conventional reinforcement, providing the hanger reinforcement and the diagonal reinforcement improves the rigidity of the beamcolumn joints during severe loadings, as this study described.

High-performance concrete (HPC) is obtained by inclusion of mineral admixtures like silica fumes and fly ash to the normal concrete. Consumption of natural materials such as sand, natural aggregates, and limestone produces environmental degradation. Similarly, industrial by-products such as fly ash, silica fume, and ferro slag need to be safely disposed of without negatively impacting the environment. The problem being addressed in this study is the need to develop high-performance concrete (HPC) that is durable and environmentally friendly. In recent years, the use of natural aggregates and ferro slag as partial replacements for traditional aggregates has gained attention as a sustainable alternative in the production of concrete. However, there is limited research on the effect of these materials on the mechanical and durability properties of HPC under varied curing conditions. In this current research, high-performance concrete of M60 grade with partial substitution of coarse aggregate with ferro slag aggregate was formed as per the recommendations of the American Concrete Institute with the inclusion of fly ash and silica fume. Natural coarse aggregate was partly substituted by ferro slag aggregate in proportions from 0% to 40%. Partial substitution of cement was made with 15% of fly ash and 10% of silica fumes. Specimens of normal concrete mix (MF0) and modified ferro slag aggregate concrete mix (MF20, MF30, and MF40) were prepared and subjected to acid test, sulphate test, and alternate wet and drying tests to assess the compressive strength of the concrete mixes. Central composite design (CCD) of RSM modelling was adopted to recommend a regression model to forecast the compressive strength of concrete under wetting drying test, acid test, and sulphate attack. Further, natural aggregate, ferro slag, and duration of curing were considered as basic variables to suggest the model. Regression models for response data were evaluated using analysis of variance (ANOVA) and Pareto charts. The results show that the mix MF30 (30% substitution of natural aggregate by ferro slag aggregate) had higher compressive strength. The residual compressive strength at 270 days under alternate wetting and drying, acid attack, and sulphate attack was obtained as 62 MPa, 62.50 MPa, and 66.50 MPa, respectively. Similarly, the percentage loss of weight was obtained as 12.92%, 12.22%, and 6.60% for alternate wetting and drying, acid attack, and sulphate attack, respectively. The findings of the analysis of variance (ANOVA) indicate that the most significant factors influencing the variables and are natural aggregate, ferro slag, and curing period. The regression models for and are extremely significant, as shown by the ANOVA and Pareto chart analyses.