Industrial waste has been rapidly increased day by day because of the fast-growing population which results environmental pollutions. It has been recommended that the disposal of industrial waste ...would be greatly reduced if it could be incorporated in concrete production. In cement concrete technology, there are many possibilities to use waste materials either as cement replacement or aggregate in concrete production. Two major industrials waste are glass and marble waste. The basic objective of this investigation is to examine the characteristics of concrete waste glass (WG) as binding material in proportions 10%, 20% and 30% by weight of cement. Furthermore, to obtain high strength concrete, waste marble in proportion of 40%, 50% and 60% by weight cement as fine aggregate were used as a filler material to fill the voids between concrete ingredients. Fresh properties were evaluated through slump cone test while mechanical performance was evaluated through compressive strength and split tensile strength which were performed after 7 days, 28 days and 56 days curing. Results show that, workability of concrete decreased with incorporation of waste glass and marble waste. Furthermore, mechanical performance improved considerably up 20% and 50% substitution of waste glass and waste marble respectively. Statistical approach of Response Surface Methodology (RSM) was used optimize both waste materials in concrete. Results indicate better agreement between statistical and experimental results.
The disposal of waste from coal plants and waste glass (WG) is causing significant environmental problems all around the planet. Currently, the amount of discarding of these wastes is increased. One ...possible option is to utilize fly ash (FA) from coal plants as a partial substitute for the cement and EG as a fractional substitute for sand in concrete, respectively. Besides, fibers can improve the strength and durability of concrete; explicitly speaking, using coconut fibers (CFs) is in trend due to their highest toughness among natural fibers making it suitable material as fiber reinforcement in concrete. This research studies the concrete behavior with 15% FA as a partial substitute of cement with 2% CFs and waste beverage glass as sand at various replacement levels (14%, 15%, 16%, 17%, 18%, 19%, and 20%). Mechanical and durability characteristics of concrete were assessed, such as compression strength, water absorption, flexural strength, density, workability, and water absorption. The current study results show that adding FA, CFs, and WG improved microstructure quality at 16% replacement of sand. The study showed that the M4 mix has enhanced the properties of concrete samples as compressive and flexural strength was improved to 47.2 and 6.2 MPa and improved apparent density by 20%. Adding more WGP than the optimal proportion (16%) led to detrimental effects on void ratio, permeability, and water absorption. Therefore, 16% of sand with WG and 15% of FA with cement can be substituted with 2% CFs to develop sustainable concrete.
The current practice of concrete is thought to be unsuitable because it consumes large amounts of cement, sand, and aggregate, which causes depletion of natural resources. In this study, a step ...towards sustainable concrete was made by utilizing recycled concrete aggregate (RCA) as a coarse aggregate. However, researchers show that RCA causes a decrease in the performance of concrete due to porous nature. In this study, waste glass (WG) was used as a filler material that filled the voids between RCA to offset its negative impact on concrete performance. The substitution ratio of WG was 10, 20, or 30% by weight of cement, and RCA was 20, 40, and 60% by weight of coarse aggregate. The slump cone test was used to assess the fresh property, while compressive, split tensile, and punching strength were used to assess the mechanical performance. Test results indicated that the workability of concrete decreased with substitution of WG and RCA while mechanical performance improved up to a certain limit and then decreased due to lack of workability. Furthermore, a statical tool response surface methodology was used to predict various strength properties and optimization of RCA and WG.
Because of the recent progress in materials properties, specifically high-strength concrete, further research is needed to evaluate its suitability, understanding, and performance in the modern-day ...world. This research aims to enhance the performance of ultra-high-strength geopolymer concrete (UHS-GPC) by adding nano-silica (NS) and polypropylene fibers (PPFs). Three 1%, 2%, and 3% different amounts of PPFs and three NS 5%, 10%, and 15% were utilized in the samples. Various performance parameters of UHS-GPC were evaluated, such as fresh property, compressive strength, modulus of elasticity split tensile, flexural and bonding strength, drying shrinkage, load-displacement test, fracture performance, and elevated temperature. The test outcomes showed that by raising the percentage of PPFs and NS to the allowable limit, the performance of UHS-GPC can be improved significantly. The most improved performance of UHS-GPC was obtained at 2% polypropylene fibers and 10% nano-silica, as the compressive, splitting tensile, flexural. Bond strength was improved by 17.07%, 47.1%, 36.52, and 37.58%, and the modulus of elasticity increased by 31.4% at 56 days. The study showed that the sample with 2% PPFs and 10% NS had excellent performance in the load-displacement test, drying shrinkage, fracture behavior, and elevated temperature. At 750°C elevated temperature, the samples' strength was reduced drastically, but at 250°C, the modified samples showed good resistance to heat by retaining their compressive strength to some degree. The present work showed the suitability of PPFs and NS to develop ultra-high-strength geopolymer concrete, which can be used as a possible alternate material for Portland cement-based concrete.
Several types of research currently use machine learning (ML) methods to estimate the mechanical characteristics of concrete. This study aimed to compare the capacities of four ML methods: eXtreme ...gradient boosting (XG Boost), gradient boosting (GB), Cat boosting (CB), and extra trees regressor (ETR), to predict the splitting tensile strength of 28-day-old self-compacting concrete (SCC) made from recycled aggregates (RA), using data obtained from the literature. A database of 381 samples from literature published in scientific journals was used to develop the models. The samples were randomly divided into three sets: training, validation, and test, with each having 267 (70%), 57 (15%), and 57 (15%) samples, respectively. The coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE) metrics were used to evaluate the models. For the training data set, the results showed that all four models could predict the splitting tensile strength of SCC made with RA because the R2 values for each model had significance higher than 0.75. XG Boost was the model with the best performance, showing the highest R2 value of R2 = 0.8423, as well as the lowest values of RMSE (=0.0581) and MAE (=0.0443), when compared with the GB, CB, and ETR models. Therefore, XG Boost was considered the best model for predicting the splitting tensile strength of 28-day-old SCC made with RA. Sensitivity analysis revealed that the variable contributing the most to the split tensile strength of this material after 28 days was cement.
Reprocessing solid waste materials is a low-cost method of preserving the environment, conserving natural resources, and reducing raw material consumption. Developing ultra-high-performance concrete ...materials requires an immense quantity of natural raw materials. The current study seeks to tackle this issue by evaluating the effect of various discarded materials, waste glass (GW), marble waste (MW), and waste rubber powder (WRP) as a partial replacement of fine aggregates on the engineering properties of sustainable ultra-high-performance fiber-reinforced geopolymer concrete (UHPGPC). Ten different mixtures were developed as a partial substitute for fine aggregate, each containing 2% double-hooked end steel fibers, 5%, 10%, and 15% GW, MW, and WRP. The present study assessed the fresh, mechanical, and durability properties of UHPGPC. In addition, to evaluate concrete development at the microscopic level due to the addition of GW, MW, and WRP. Spectra of X-ray diffraction (XRD), thermogravimetric analysis (TGA), and mercury intrusion (MIP) tests were conducted. The test results were compared to current trends and procedures identified in the literature. According to the study, adding 15% marble waste and 15% waste rubber powder reduced ultra-high-performance geopolymer concrete's strength, durability, and microstructure properties. Even so, adding glass waste improved the properties, as the sample with 15% GW had the highest compressive strength of 179 MPa after 90 days. Furthermore, incorporating glass waste into the UHPGPC resulted in a good reaction between the geopolymerization gel and the waste glass particles, enhancing strength properties and a packed microstructure. The inclusion of glass waste in the mix resulted in the control of crystal-shaped humps of quartz and calcite, according to XRD spectra. During the TGA analysis, the UHPGPC with 15% glass waste had the minimum weight loss (5.64%) compared to other modified samples.
A main global challenge is finding an alternative material for cement, which is a major source of pollution to the environment because it emits greenhouse gases. Investigators play a significant role ...in global waste disposal by developing appropriate methods for its effective utilization. Geopolymers are one of the best options for reusing all industrial wastes containing aluminosilicate and the best alternative materials for concrete applications. Waste wood ash (WWA) is used with other waste materials in geopolymer production and is found in pulp and paper, wood-burning industrial facilities, and wood-fired plants. On the other hand, the WWA manufacturing industry necessitates the acquisition of large tracts of land in rural areas, while some industries use incinerators to burn wood waste, which contributes to air pollution, a significant environmental problem. This review paper offers a comprehensive review of the current utilization of WWA with the partial replacement with other mineral materials, such as fly ash, as a base for geopolymer concrete and mortar production. A review of the usage of waste wood ash in the construction sector is offered, and development tendencies are assessed about mechanical, durability, and microstructural characteristics. The impacts of waste wood ash as a pozzolanic base for eco-concreting usages are summarized. According to the findings, incorporating WWA into concrete is useful to sustainable progress and waste reduction as the WWA mostly behaves as a filler in filling action and moderate amounts of WWA offer a fairly higher compressive strength to concrete. A detail study on the source of WWA on concrete mineralogy and properties must be performed to fill the potential research gap.
Geopolymer, a novel binder material, possesses the potential to replace conventional cement completely. Recent studies have investigated the incorporation of various nanomaterials (NMs) into ...geopolymer concrete (GPC) to enhance its properties. Nanotechnology, an emerging field of study, has garnered significant attention in recent decades due to its groundbreaking research and practical applications. This comprehensive review aims to elucidate the effects of nanomaterial inclusion on the workability, strength, durability, and physical and microstructural characteristics of GPC. The properties have been meticulously examined, reviewed, and discussed. Over 190 research and review articles were reviewed, analyzed, and presented to develop a database containing critical properties of GPC modified with different doses and types of NMs. The influence of introducing diverse kinds and doses of NMs on GPC behavior was assessed. Historical trends, current tendencies, challenges, and the benefits and limitations of NM-modified GPC were explored. According to this review, incorporating NMs is promising for developing high-strength or high-performance GPC. It significantly improves mechanical, microstructural, and durability properties by providing additional calcium-silicate-hydrate, calcium-aluminate-silicate-hydrate gel, and nano-filling effects in the GPC matrix. This advancement will enable the construction industry to realize the potential of NM-enhanced GPC successfully. The present review demonstrated that the geopolymer concrete showed enhancements in engineering properties and effectiveness when modified with different types of nanomaterials and tested under different conditions. The current study also presented some challenges and research gaps that should be addressed in future research studies.
A considerable amount of discarded building materials are produced each year worldwide, resulting in ecosystem degradation. Self-compacting concrete (SCC) has 60–70% coarse and fine particles in its ...composition, so replacing this material with another waste material, such as recycled aggregate (RA), reduces the cost of SCC. This study compares novel Artificial Neural Network algorithm techniques—Levenberg–Marquardt (LM), Bayesian regularization (BR), and Scaled Conjugate Gradient Backpropagation (SCGB)—to estimate the 28-day compressive strength (f’c) of SCC with RA. A total of 515 samples were collected from various published papers, randomly splitting into training, validation, and testing with percentages of 70, 10 and 20. Two statistical indicators, correlation coefficient (R) and mean squared error (MSE), were used to assess the models; the greater the R and lower the MSE, the more accurate the algorithm. The findings demonstrate the higher accuracy of the three models. The best result is achieved by BR (R = 0.91 and MSE = 43.755), while the accuracy of LM is nearly the same (R = 0.90 and MSE = 48.14). LM processes the network in a much shorter time than BR. As a result, LM and BR are the best models in forecasting the 28 days f’c of SCC having RA. The sensitivity analysis showed that cement (28.39%) and water (23.47%) are the most critical variables for predicting the 28-day compressive strength of SCC with RA, while coarse aggregate contributes the least (9.23%).
The requirement of the construction sector pushes researchers and academicians to determine the 28-day concrete compressive strength due to less consumption of natural products and reduced cost. One ...recommended method to reduce the cost and simultaneously adopt sustainability is introducing recycled aggregates in concrete. Most typical structures require concrete, which is self-flowable and compactable; specific structures require concrete, which is self-flowable and compactable; one such concrete is self-compacting concrete (SCC). 515 mix design samples for SCC with recycled aggregates are collected from the literature and used for training, validation, and testing to create the model using machine learning techniques (Extra Gradient (XG) Boosting, Ada Boosting, Gradient Boosting, Light Gradient Boosting, Category Boosting, K Nearest Neighbors, Extra Trees, Decision Trees, Random Forest, and Support Vector Machine). The correlation between input and output variables is analyzed using ANOVA and is indicated that data can be used to develop machine learning models successfully. Sensitive analysis and error assessment are performed to choose the best machine learning methods, and it found that CB, KNN, and ERT have the highest R2 value and lowest MSE.
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