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Structural lightweight concrete (SLWC) is crucial for reducing building weight, reducing structural loads, and enhancing energy efficiency through lower thermal conductivity. This study explores the effects of incorporating silica fume (SF), micro-polypropylene (micro-PP), and macro-PP fibers on the workability, thermal properties, and strength of SLWC. SF was added to all mixtures, substituting 10% of the Portland cement (PC), except for the control mixture. Macro-PP fibers were introduced alone or in combination with micro-PP fibers at volumetric ratios of 0.3% and 0.6%. The study evaluated various parameters, including slump, Vebe time, density, water absorption (WA), ultrasonic pulse velocity (UPV), thermal conductivity coefficients (k), compressive strength (CS), and splitting tensile strength (STS) across six different SLWC formulations. The results indicate that while SF negatively impacted the workability of SLWC mortars, it improved CS and STS due to the formation of calcium silicate hydrate (C-S-H) gels from SF's high pozzolanic activity. Additionally, using micro-PP fibers in combination with macro-PP fibers rather than solely macro-PP fibers enhanced the workability, CS, and STS of the SLWC samples. Although SF had a minor effect on reducing thermal conductivity, the use of macro-PP fibers alone was more effective for improving thermal properties by creating a more porous structure compared to the hybrid use of micro-PP fibers. Moreover, increasing the ratio of micro- and macro-PP fibers from 0.3% to 0.6% resulted in lower CS values but a significant increase in STS values. [ABSTRACT FROM AUTHOR]

Abstract\nHIGHLIGHTSThe aggregate size and particle-size distribution (PSD) can change the packing density, slump, and strength of concrete. The micromechanical effects of aggregate size on the slump and strength remain unclear. The current numerical study examined concrete behavior using slump and uniaxial compressive strength (UCS) tests considering the aggregate size distribution using the discrete element method. The effect of the aggregate size on the packing density, UCS, and slump of the concrete was analyzed. To accomplish this, we evaluated how variations in the uniformity and curvature coefficients of the PSD, as well as the specific surface area of the samples, were affected by changes in aggregate size. Although the simulations were based on standard specimens from the laboratory, the results showed good agreement with the documented experimental results. Briefly, at a 40–60% fine aggregate content, the packing density and compressive strength of the concrete reached their peaks and caused a decrease in the height of the slump. The uniformity and curvature coefficients did not influence the slump height. The induced shear band could be tracked during the UCS tests and the crack angles could be measured. At the optimum fine content (40–60%), the shear bands were primarily localized and propagated through the samples having different fine contents.The use of the optimum level of the concrete fine aggregate content ensured its workability and strength.This optimum level of fine aggregate was 40–60%.The discrete element method can be used to evaluate the role of particle size on the performance of concrete.The particle size distribution changed the macro-parameters of the concrete.The maximum packing density was determined to be 40–60% of fine aggregates.The use of the optimum level of the concrete fine aggregate content ensured its workability and strength.This optimum level of fine aggregate was 40–60%.The discrete element method can be used to evaluate the role of particle size on the performance of concrete.The particle size distribution changed the macro-parameters of the concrete.The maximum packing density was determined to be 40–60% of fine aggregates. [ABSTRACT FROM AUTHOR]

The main focus of this study is to assess the slump characteristics of high‐performance concrete (HPC) using decision tree (DT) and support vector regression (SVR) models. In the first step, the models were solely fed via HPC samples to reproduce the slump rates. By coupling phasor particle swarm optimization (PPSO) to main models, hybrid DT‐PPSO and SVR‐PPSO frameworks, simulate the slump rates accurately. Using the correlation of determination and root mean square error (MAE) metrics for the DT, 96.04 and 5.097 were computed, respectively. SVR was obtained at 92.62 and 6.965, alternatively. In the hybrid approach, DT‐PPSO could improve by 3% and 55% in terms of correlation of determination and root MAE, respectively. DT‐PPSO appeared high‐accuracy model compared to others; however, a single DT had more desirable results than SVR. Overall, the advantages of this study encompass its methodological approach, comparative insights, and practical relevance, offering valuable contributions to the understanding and prediction of mechanical slump in HPC. [ABSTRACT FROM AUTHOR]

Direct Contact Membrane Distillation (DCMD) uses low heat sources to separate water from urea, which was then used as a plasticizer in regolith-based cement to make it more workable. The work investigated separating potable water and urea from artificial urine using DCMD and then characterizing the products. Water was successfully separated from the artificial urine solution as characterized by density, conductivity, pH, and substance concentrations. The concentrated urine solution was used in regolith-based cement cured under vacuum at temperatures that simulated temperatures that would be expected in construction on the Moon. Workability and other properties were improved by replacing water with concentrated urine solution in the mix. [ABSTRACT FROM AUTHOR]

Purpose: In order to solve the problem of the high cost of backfill and eliminate the use of Gobi aggregate for backfill in the Kalatongke copper-nickel mine. Method; The feasibility of slag for backfill is demonstrated by conducting laboratory and industrial tests. The pumpability and strength characteristics of two types of backfill slurry were studied by slump and uniaxial compressive strength(L/CS) tests respectively. The two types of backfill slurry were using different aggregates. One was only using unclassified tailings backfill as aggregates,and the other was using unclassified tailings and slag as aggregates. Result; The results show that the suitable transporting solid concentrations of unclassified tailings backfill slurry are 66% -- 68%and that the suitable transporting solid concentrations of unclassified tailings and slag filling slurry backfill slurry are 70% -- 72% with 20% -- 30%of slag aggregate. The 28 d UCS of unclassified tailings backfill is lower than 3 MPa,and the addition of slag as coarse aggregate can improve the strength of the backfill. When the amount of slag added is less than 30%, the strength of backfill will increase with the increased addition of slag. Conclusion: The bottom layer backfill of stope should use the composite aggregate of unclassified tailings and slag. When the proportion of slag aggregate is 20% -- 30%,there is no slag segregation inside the backfill test block. Significance; In this paper, high-density slag is innovatively applied to mine backfill. The research results can help guide the backfill process of Kalatongke copper-nickel mine and provide a reference for the bulk utilization of slag in Xinjiang area. [ABSTRACT FROM AUTHOR]

In light of the current situation where excessive amounts of excavated earth from subway tunnel construction are being stacked with low utilization and value, this study used residue as a mineral admixture to investigate the effects of different proportions of residue content (0%, 2.5%, 5.0%, 7.5%, and 10.0%) on the workability and mechanical properties of C50 concrete. The results indicate that: (1) The initial slump and slump loss of C50 concrete decrease gradually as the residue content increases. (2) The compressive strength of C50 concrete with varying residue contents is lower than the control group at early stages (3d, 7d), while it is higher than the control group at 28d. There exists an optimal content of residue for improving C50 concrete compressive strength, and it is found that the highest compressive strength at 28d is achieved when the residue content is 7.5% of the cement content. (3) The microscopic structure of C50 concrete with different residue contents at 28d shows that as the residue content increases, the microscopic structure of C50 concrete gradually becomes more compact and the porosity decreases.

Abstract This study focused on sustainable and novel development of concrete through treated and untreated plastic waste aggregates. In this study, the surface of Elec-waste coarse aggregates was treated with sulfuric acid, marble dust coating, silica fume coating, and alkaline bleach. Elec-waste aggregates were used in concrete by replacing natural coarse aggregates in amounts of 10%, 20%, and 30%. The 10%, 20%, and 30% Elec-waste replacement ratios resulted in the compressive strength reduction of 8.97%, 27.99%, and 42.01%, respectively. The same percentage of Elec-waste aggregates reduced the splitting tensile strength by 21.77%, 35.89%, and 47.89%, respectively. However, the slump was observed to increase by 41.4%, 52.1%, and 68.8%, respectively. All the considered treatments enhanced the performance of Elec-waste aggregate concrete (E-WAC). Overall, the best improvement in the performance of E-WAC was imparted by silica fume coating, irrespective of the quantity of Elec-waste aggregates. The present study proposed an expression to estimate the reduction of the compressive strength of E-WAC. It was demonstrated that the equation by JCI-08 predicted splitting tensile strength of E-WAC close to experimental results.

The use of ferronickel slag powder (FNSP) as a cementitious additional material has been supported by numerous reports. FNSP concrete has the same shortcomings as ordinary concrete, including low hardness. In this study, in order to make FNSP concrete more durable, end-hooked type steel fibers were incorporated. To understand how various elements affect the mechanical properties of steel fibers, an experiment was carried out on the mechanical properties of steel FNSP concrete (SFNSPC). FNSP's principal ingredients, with a particle size distribution ranging from 0.5 to 100 μm and a sheet-like powder shape, are CaO, SiO2, Al2O3, MgO, and others, according to tests conducted on the material's microstructure and composition. Then, eighteen mix proportions were developed, comprising six distinct FNSP replacement rate types and three distinct steel fiber content types. Crucial metrics were evaluated and analyzed, including the relationship among the toughness, tensile strength, and compressive strength as well as slump, splitting tensile strength, compressive strength, and uniaxial compressive stress–strain curve of SFNSPC. The results showed that the slump of SFNSPC under different FNSP replacement rates decreased with increasing steel fiber volume. Steel fibers have a small but positive effect on SFNSPC's compressive strength; nonetheless, as FNSP replacement rates increased, SFNSPC's slump gradually decreased, though not by much. These results show that FNSP is a viable alternative cementitious material in terms of strength. Specifically, the splitting tensile strength of SFNSPC improves with an increase in steel fiber content, and the pace at which SFNSPC strength drops with an increase in the FNSP replacement rate. With varying mix proportions, the stress–strain curve trend of SFNSPC remains mostly constant, and steel fibers improve the compressive toughness of SFNSPC. After adding 0.5% and 1.0% steel fibers, the toughness index of concrete with different FNSP replacement rates increased by 8–30% and 12–43%, respectively. [ABSTRACT FROM AUTHOR]

Due to rising living standards and population growth, saving fresh water will be a significant problem for the next generation. The Government is indirectly impacted by a significant financial burden due to the current usage of treated wastewater, in all of Egypt’s districts. As a case study, Egypt’s new administrative capital was chosen, given that it is today one of the most important cities and that its planning was predicated on making it a smart, sustainable city. The goal of the study was to develop methods for replacing potable water in the manufacture of concrete with tertiary-treated wastewater; however, used for concrete mixing or curing after concrete hardening. Property assessments of the fresh and hardened concrete were conducted, to ascertain the best water quality that can be used without compromising the quality or durability of the concrete. ; The results of this paper will serve as a guide for decision-makers looking to decrease costs and increase sustainability by using treated wastewater in making sustainable concrete for buildings, especially in recent decades, rising construction material usage has generated considerable environmental difficulties, particularly in the production of Ordinary Portland cement (OPC). [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of the Chinese Ceramic Society is the property of Bulletin of the Chinese Ceramic Society Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of New Building Materials / Xinxing Jianzhu Cailiao is the property of New Building Materials Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The process of concrete production involves mixing cement, water, and other materials. The quantity of each of these materials results in a performance that is particularly estimated in terms of compressive or flexural strength. It has been observed that the final performance of concrete has a high variance and that traditional formulation methods do not guarantee consistent results. Consequently, designs tend to be over-designed, generating higher costs than required, to ensure the performance committed to the client. This study proposes the construction of predictive machine learning models to estimate compressive or flexural strength and concrete slump. The study was carried out following the Team Data Science Process (TDSP) methodology, using a dataset generated by the Colombian Ready Mix (RMX) company Cementos Argos S.A. over five years, containing the quantity of materials used for different concrete mixes, as well as performance metrics measured in the laboratory. Predictive models such as XGBoost and neural networks were trained, and hyperparameter tuning was performed using advanced techniques such as genetic algorithms to obtain three models with high performance for estimating compressive strength, flexural strength, and slump. This study concludes that it is possible to use machine learning techniques to design reliable concrete mixes that, when combined with traditional analytical methods, could reduce costs and minimize over-designed concrete mixes. [ABSTRACT FROM AUTHOR]

Abstract Geopolymer concrete (GPC) has achieved a wide popularity since innovating it as an alternative to conventional concrete because of its superior mechanical characteristics and durability, in addition to being a green concrete due to its low negative impact on the environment. However, GPC still suffers from the problem of its poor workability which suppresses its spread in construction applications. This study investigated the most effective parameters on the workability of GPC including GGBFS content, water to binder ratio, and dosage of different types of chemical admixtures, Naphthalene-Based Admixture (NPA) and Polycarboxylate-Based Admixture (PCA), using Taguchi approach and Analysis of Variance (ANOVA) analysis considering the compressive strength at the different concrete ages. It was observed that NPA, in the geopolymer concrete, improved the compressive strength compared to PCA. The NPA-based mixes achieved the highest 28-day compressive strength, 69 MPa, with about 27.8% more than the highest 28-day compressive strength achieved by the PCA-based mixes, 54 MPa. The obtained results revealed that the NPA has achieved the best improvement for both the workability, in terms of initial slump value and slump loss rate, and the compressive strength of GPC mixes compared to PCA.

This is an article in the field of ceramics and composites.To explore the feasibility of using coal waste to replace cement for concrete preparation, the activated coal slag powder and coal gangue powder were used to replace cement at a ratio of 0%, 10%, 20%, 30%, and 40% to prepare concrete samples and prepare concrete samples. The slump, compressive strength, flexural strength and high-temperature performance were tested, and the results show that: as the substitution ratio increases, the slump, compressive strength and flexural strength all increase first and then decrease; The optimal substitution ratio is 20%～30%. The early strength growth rate of the activated coal slag powder sample is large; while the long-term strength growth rate of the activated coal gangue powder sample is large. When the water-cement ratio=0.45, the compressive strength of the sample increases first and then decreases with the increase of temperature, and reaches the maximum at 100 ℃; when the water-cement ratio=0.5, the compressive strength of the concrete sample increases with the temperature; the hydration cement structure in the interface area of the activated coal slag powder sample is the most, followed by the control group, and the activated coal gangue powder sample is the least. With the increase in temperature, the pores and cracks on the surface of the sample increased significantly and the degree of fracture of the damaged surface gradually increased.

Abstract Bentonite plastic concrete (BPC) demonstrated promising potential for remedial cut-off wall construction to mitigate dam seepage, as it fulfills essential criteria for strength, stiffness, and permeability. High workability and consistency are essential attributes for BPC because it is poured into trenches using a tremie pipe, emphasizing the importance of accurately predicting the slump of BPC. In addition, prediction models offer valuable tools to estimate various strength parameters, enabling adjustments to BPC mixing designs to optimize project construction, leading to cost and time savings. Therefore, this study explores the multi-expression programming (MEP) technique to predict the key characteristics of BPC, such as slump, compressive strength (fc), and elastic modulus (Ec). In the present study, 158, 169, and 111 data points were collected from the experimental studies for the slump, fc, and Ec, respectively. The dataset was divided into three sets: 70% for training, 15% for testing, and another 15% for model validation. The MEP models exhibited excellent accuracy with a correlation coefficient (R) of 0.9999 for slump, 0.9831 for fc, and 0.9300 for Ec. Furthermore, the comparative analysis between MEP models and conventional linear and non-linear regression models revealed remarkable precision in the predictions of the proposed MEP models, surpassing the accuracy of traditional regression methods. SHapley Additive exPlanation analysis indicated that water, cement, and bentonite exert significant influence on slump, with water having the greatest impact on compressive strength, while curing time and cement exhibit a higher influence on elastic modulus. In summary, the application of machine learning algorithms offers the capability to deliver prompt and precise early estimates of BPC properties, thus optimizing the efficiency of construction and design processes.

Magnetized water (MW) technology uses a magnetic field to affect the dipole moment of water molecules, changing the hydrogen bonding between them. As a result, the physical and chemical properties of water are altered. MW has the potential to reduce the need for admixtures and cement while preserving the desired strength and workability of concrete. However, the exact mechanisms by which different magnetization conditions improve concrete properties remain unclear. This study explored the effects of magnetic field intensity and water flow velocity on the workability and compressive strength of concrete using a custom-built magnetization device. Twelve distinct MWs were prepared under varying magnetic field intensities (210, 230, 250, and 270 mT) and water flow velocities (0.5, 0.6, and 0.7 m/s), and the performance of the concrete was assessed by slump and compressive strength tests. Additionally, the physicochemical properties of the MW were examined. The research results indicated the presence of significant interactions between the magnetization parameters. When the water was magnetized at a flow velocity of 0.7 m/s, and combined with magnetic field intensities of 210 and 230 mT, both physicochemical properties of MW and the mechanical performance of the MW concrete were optimally enhanced. Under the conditions of a magnetic field intensity of 210 mT and flow velocity of 0.7 m/s, the workability and compressive strength of the concrete prepared with MW improved by 30.4 % and 13.7 %, respectively. These findings highlighted the importance of considering the combined effects of magnetization parameters when optimizing the mechanical properties of MW concrete.

In order to solve the ecological environment pollution caused by a large amount of coal gangue accumulation and the problems of poor conveying performance and low support strength of paste filling materials. Based on the standard slump test and uniaxial compressive strength test, the slump and compressive strength (post-coagulation) of gangue paste under different aggregate size aggregations were obtained through orthogonal experiments in this study. The results show that the slump of the gangue filling paste with four types of aggregate size gradations is negatively correlated with the mass fraction, and the slump of the filling paste with a coarser aggregate content is more obviously affected by the mass fraction The increase of fine aggregate content has a significant impact on the compressive strength of the filling paste, which shows a trend of first increasing and then decreasing. When the mixing ratio of coarse aggregate and fine aggregate is 5:5, the compressive strength of the paste reaches the best. In addition, different proportions of aggregate mixing cause the filling paste to form different skeleton structures, including the skeleton void structure at 7:3 or 6:4, the skeleton dense structure at 5:5, and the skeleton suspension structure at 4:6, which are decisive for the final performance of the paste. By analyzing the experimental results of the compressive strength and slump of the gangue filling paste, it was found that the relationship between the compressive strength and slump of the gangue filling paste is a power index function. Through data fitting, it was found that the regression coefficient of the fitting function is no less than 0.97, and the fitting effect is good for evaluating the strength of the filling paste under the aggregate size grading. [ABSTRACT FROM AUTHOR]

Coal gangue is a waste product commonly produced during coal mining. Using gangue as a replacement for conventional aggregates in shotcrete applied to underground roadways is a feasible approach to promote the resource utilization of gangue solid waste. The mix proportions of shotcrete materials are crucial to the effectiveness of field applications. The aim of this study was to investigate the effects of mix proportions on the mechanical properties of the gangue-based shotcrete material applied to roadways. To achieve this, we conducted experiments to measure changes in the slump under different gangue sizes, mass concentrations, sand contents, and cement contents. The study analyzed the influences of various mix proportions on the conveying and mechanical properties of the gangue-based shotcrete material applied to roadways. The slump and the compressive strength were analysed. The following was concluded: (1) The gangue size and sand content have a similar effect on the slump. As the gangue size and sand content increase, the slurry slump initially decreases and then increases, which is attributed to the plasticity of the aggregates themselves. The mass concentration has a negative correlation with the slump, which is the least sensitive to changes in cement content. (2) The compressive strength of all specimens increases with prolonged curing, reaching its maximum after 28 d under the compressive experimental conditions. (3) This paper analyzed the reasons for better mechanical properties under the conditions of smaller size gangue, higher mass concentration, and higher cement content. It has also examined the reasons for greater compressive strength at 35% sand content. The experimental results of this paper also offer relevant guidance regarding the specific mix proportions of the material of the field gangue-based shotcrete material applied to roadways. [ABSTRACT FROM AUTHOR]

This comprehensive study analyzes the use of crushed glass as both fine and coarse aggregate in concrete, as well as the prediction accuracy of Artificial Neural Networks (ANN). The primary objectives are to understand the interactions between concrete’s constituents and to assess the accuracy of ANN models in predicting concrete’s mechanical and physical properties. This is achieved using a two-decade experimental results dataset of concrete’s compressive and tensile strengths, slump, density, and the corresponding mix design proportions, including waste glass aggregate. A series of 70 concrete samples were carefully built and tested, with compressive strengths varying from 12 to 71 MPa and glass aggregate percentages ranging from 0-100%. These samples served as the basis for the creation of an input dataset and ANN targets. The ANN model underwent intensive training, validation, testing, and statistical regression analysis. The ANN models are exceptionally accurate, with a continuously low error margin of roughly 2%, highlighting their usefulness in matching experimental and predicted results. Validation techniques highlight the models' dependability, with consistently high coefficients of determination (R-values), including 0.99484, demonstrating their robustness in replicating complicated concrete properties. The data analysis shows a unique pattern, with optimum glass aggregate percentages in the range of 10–20%. Beyond this range, there is a noticeable decline in concrete properties. Finally, the study confirms the efficacy of ANN in predictive modeling while also validating the potential of crushed glass to replace natural aggregates in concrete. [ABSTRACT FROM AUTHOR]

Copyright of Guangdong Architecture Civil Engineering is the property of Guangdong Architecture Civil Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Multipurpose Utilization of Mineral Resources / Kuangchan Zonghe Liyong is the property of Multipurpose Utilization of Mineral Resources Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper aims to exploit fully the heuristic virtues of Keynes' famous 'old bottles' story, deploying a multi-layered argument and drawing out its broadest implications. In essence, we show that through this story Keynes was making a very serious point about anti-crisis policies: the need for authorities to stimulate animal spirits by relying on people's natural impulse to action. Rather than taking the place of entrepreneurs and paying people to dig holes, Keynes seems to be arguing that public authorities should put entrepreneurs in a situation where they are so enthusiastic that they go into debt to dig holes, just like during a gold rush. At the same time, it is a question of restoring the banks' willingness to lend for these overoptimistic projects in a period of total depression. This article explores the conditions that make public intervention as effective as possible through the enthusiasm and individual initiative that can be generated by an artificial gold rush. Such intervention therefore can be as minimal as possible, without having to resort to the opposite authoritarian solution of war. Since the gold rush builds cities and war destroys them, Keynes spent considerable energy convincing his contemporaries that liberal-democratic countries would have to take the former path if they wanted to avoid the latter. [ABSTRACT FROM AUTHOR]

Fly ash and stone powder, which are abundant wastes in Central Vietnam, are viable alternatives to cement and sand in concrete production. However, this replacement may worsen the compressive strength and slump of concrete. This study deals with the prediction of the slump and compressive strength of concrete using fly ash and stone powder in Central Vietnam as cement and sand substitute materials, respectively. First, the Ishikawa diagram was used to analyze the factors affecting the concrete workability and compressive strength, in combination with the method of design of experiment to determine the required number of testing specimens. A total of 72 concrete mixtures with slump of 3 - 12 cm and compressive strengths 10 MPa - 60 MPa were designed. Subsequently, regression and artificial neural network methods were used to predict the concrete slump and compressive strength. The results demonstrated the high accuracy of the artificial neural network model. In addition, the above models allowed us to determine the proportion of concrete ingredients that met the slump and compressive strength requirements.

Structural lightweight concrete (SLWC) is crucial for reducing building weight, reducing structural loads, and enhancing energy efficiency through lower thermal conductivity. This study explores the effects of incorporating silica fume (SF), micro-polypropylene (micro-PP), and macro-PP fibers on the workability, thermal properties, and strength of SLWC. SF was added to all mixtures, substituting 10% of the Portland cement (PC), except for the control mixture. Macro-PP fibers were introduced alone or in combination with micro-PP fibers at volumetric ratios of 0.3% and 0.6%. The study evaluated various parameters, including slump, Vebe time, density, water absorption (WA), ultrasonic pulse velocity (UPV), thermal conductivity coefficients (k), compressive strength (CS), and splitting tensile strength (STS) across six different SLWC formulations. The results indicate that while SF negatively impacted the workability of SLWC mortars, it improved CS and STS due to the formation of calcium silicate hydrate (C-S-H) gels from SF’s high pozzolanic activity. Additionally, using micro-PP fibers in combination with macro-PP fibers rather than solely macro-PP fibers enhanced the workability, CS, and STS of the SLWC samples. Although SF had a minor effect on reducing thermal conductivity, the use of macro-PP fibers alone was more effective for improving thermal properties by creating a more porous structure compared to the hybrid use of micro-PP fibers. Moreover, increasing the ratio of micro- and macro-PP fibers from 0.3% to 0.6% resulted in lower CS values but a significant increase in STS values.

The present paper highlight upon research work is that curing is one of most important aspect of construction. The life of concrete and its serviceability depends heavily on curing. The method of curing applied on concrete will affect its final strength and durability. Owing to this fact this paper contains the research done on concrete under various curing methods. The standard method of curing concrete is done by water and results wastage of a lot of water. With the increase in the deficiency of availability of water, curing becomes a problem. Hence this research aims at providing better methods of curing which will not only improve the strength and durability of concrete but will also save water. The various methods that have been researched upon are plastic covered curing, addition of sodium silicate to curing water, and addition of curing compounds to curing water. The tests are carried on concrete with desirable strengths of M15 and M20. In this research the fine aggregate used in making of M15 and M20 concrete consists of a mixture of sand and crusher dust. Two mixes of ratio 50:50 and 60:40, sand to crusher dust have been taken and the effects of curing on these mixes are considered. Plastic curing is done by covering the concrete with plastic soon after demolding. Hence minimum water is required. The curing done by sodium silicate is done by adding 2% by weight of sodium silicate to curing water. Concrete is submerged in water containing sodium silicate. Once the concrete is cured, this water mix can be reused to cure freshly cast concrete, thereby saving more water. Curing by curing compounds is done in a similar way as that of curing with sodium silicate, only that instead of sodium silicate, curing compounds are used. The effect of these three methods on concrete is studied and discussions are made. [ABSTRACT FROM AUTHOR]

The utilization of Fiber Reinforced Concrete as a structural material is steadily on the rise. Conventional concrete is characterized by its brittleness, displaying a flexural strength that falls within the range of 10-15% of its compressive strength. Incorporation of fibers into concrete enhances various mechanical properties, including tensile strength, flexural strength, and ductility. In current investigation mix design of 1:4:2:0.8 (cement: sand: aggregate: water) is used for preparing PC. Pine needle fibers hybrid lengths of 37mm, 50 mm and 62.5 mm are used for preparation of pine needle reinforced concrete. Improvement observed in flexural energy absorption by 2.5 times, toughness index 5 times, maximum deflection up to 13 mm and decrease in modulus of rupture observed by 28%. Ductile behavior also observed with respect to the reference specimens. In general, pine needle fibers has the potential to be used in cement concrete composites for different structural applications. The aim of the present research work is to develop an economically efficient concrete keeping its flexural performance. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of the Chinese Ceramic Society is the property of Bulletin of the Chinese Ceramic Society Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The rapid increase in the world's population has resulted in a shortage of water, especially in developing countries. To conserve fresh water, the utilization of seawater in the concrete industry is being considered as a viable alternative due to its abundance. Additionally, seawater is more easily accessible in coastal regions, which can promote their development. In this study, the effect of using Dead Sea Water (DSW) as a mixing water for concrete was investigated. Several concrete mixes were produced using DSW mixed with fresh water at different percentages of 0, 25%, 50%, 75%, and 100%. In addition, the cement content was also changed between 300 to 350 kg/m3 to produce concrete of different strengths ranging from 30 to 44 MPa. Fresh and hardened properties including the slump, air content, density, and compressive and tensile strengths at different ages between 7 to 90 days were investigated. Compared to the reference mix (0% DSW), the concrete produced using DSW provided lower slump values, higher air contents of up to 20%, and lower density of up to 17%. The compressive strength and splitting tensile strength decreased by 30% to 85% and 15% to 75%, respectively, as the percentage of DSW in the mix increased from 25% to 100%. It was found that the use of DSW in concrete can severely impact its fresh and hardened properties. [ABSTRACT FROM AUTHOR]

This study modelled the slump of concrete containing crushed glass and Bida Natural Gravel (BNG) based on deep learning algorithm using the MATLAB neural network toolbox. A total of 240 (150mm x 150mm x 150mm) cubes were cast from 80 mixes generated randomly using Scheffe's simplex lattice approach. Slump was measured for each of the experimental points of fresh concrete before filling in the moulds. The resulting batch for each mix was used as input data while the laboratory results for slump was used as output data for the ANN-model. Hence a shallow multilayer supervised Neural Network was developed to model these data. The developed model would be able to predict concrete slump containing 0% - 25% crushed glass as partial replacement for fine aggregate, water- cement ratio ranging from 0.45 - 0.78 and concrete grade M15 - M25. The architecture of the network contained 6 input parameters: water to cement ratio, water, cement, sand, crushed glass and BNG, 20 neurons in the hidden layer and slump in the outer layer. The adequacy of the developed model was measured using Mean Square Error (MSE) and Correlation Coefficient (R). Results showed that 6:20:1 model architecture for slump model had an MSE values for training, validation and testing as: 1.84e-2, 5.81e-3, 3.64e-3, 1.73e-3 respectively. Regression values for training, validation and testing are: 79%, 94%, 96% and 79%. The study concluded that a shallow multilayer Neural Network architecture with 20 neurons in the hidden layer is sufficient for predicting concrete slump. [ABSTRACT FROM AUTHOR]

Chemical admixtures are widely used for the production of highperformance concrete, but they are responsible for environmental pollution and health issue during construction because of their chemical nature. Also manufactured admixtures are expensive, on this base recently, researches and attempts are focused to find alternatives, and using different natural or bio admixtures for concrete is a good choice. In this study, the impact of Grape Extract (GE), a natural additive, on the properties of concrete was investigated. Various GE percentages were used to investigate the properties of fresh and hardened concrete. The results show that there is a continuous workability enhancement and continuous splitting tensile strength loss with GE increase. Improvement of 28 days compressive strength by 18.5% was observed on using 0.22% GE, while no compressive and flexural strengths loss was observed with GE addition up to 0.55%. Finally, the results of the study showed that GE dosages can strongly impact the fresh properties and mechanical strength of concrete mixtures. So there is a chance to produce self-compacting concrete using GE natural admixture instead of chemical admixture but there is a need for further experimental tests. [ABSTRACT FROM AUTHOR]

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This study investigated the effects of various water types in concrete mixes to minimize freshwater consumption and combat scarcity. River water, sea water, estuary water, domestic wastewater, and fresh water were assessed, analyzing concrete properties such as water absorption, compressive, flexural, and splitting tensile strengths. Results indicated comparable failure modes across different water types in compression, flexure, and splitting. Estuary water decreased compressive strength by 8%, while other water types enhanced it, with domestic wastewater showing the most improvement. Splitting tensile strength saw no significant reductions; domestic wastewater exhibited the highest enhancement (24.39%), followed by estuary and river water, whereas estuary water led in flexural strength improvement. Domestic wastewater reduced absorption and increased slump by up to 60%. To summarize, domestic wastewater positively influenced compressive and splitting tensile strengths, decreased water absorption, and increased slump. River water exhibited properties akin to fresh water, implying its suitability; further exploration into reinforced concrete using these water sources is suggested. [ABSTRACT FROM AUTHOR]

Attaining a dependable measurement of concrete slump is crucial as it is a valuable indication of concrete workability. On the other hand, complexities associated with costly traditional approaches have driven engineers to use indirect efficient models such as metaheuristic-based machine learning for approximating the slump. While the literature shows promising application of some metaheuristic techniques for this purpose, the large variety of these algorithms calls for evaluating the most capable ones to keep the solution updated. Stochastic fractal search (SFS) is one of the most powerful optimization algorithms in the literature that has not received appropriate attention in analyzing concrete mechanical parameters. In the present research, a multi-layer perceptron neural network (NN-MLP), is enhanced using the SFS. The proposed SFS-NN-MLP model aims to predict the slump based on the amount of ingredients in the mixture, as well as the curing age of specimens. Accuracy assessment revealed that the proposed model can deal with the assigned task with excellent accuracy. It indicates that the SFS could properly tune the parameters required for training the NN-MLP, and consequently, the trained network could reliably calculate the slump of specimens that were not analyzed before. For comparative validation, the SFS was replaced with two similar optimizers, namely elephant herding optimization algorithm (EHO) and slime mould algorithm (SMA). Based on the calculated mean square errors of 5.6526, 6.1129, and 7.3561 along with mean absolute errors of 4.6657, 5.0078, and 6.3066, as well as the percentage-Pearson correlation coefficients of 78.06 %, 73.95 %, and 58.11 %, respectively for the SFS-NN-MLP, EHO–NN–MLP, and SMA–NN–MLP, it was shown that the SFS-NN-MLP is the most accurate predictor. Hereupon, the SFS-NN-MLP model is recommended to be effectively used for obtaining a cost-efficient approximation of concrete slump in real-world projects.

The attempt to reuse plastic waste in concrete is a significant issue because it helps in preserving natural resources and in decreasing environmental contamination. The main aim of this research is to investigate the impact of adding Polyethylene terephthalate (PET) particles on the characteristics of concrete. PET particles were utilized as a partial replacement of fine aggregate by 2.5%, 5%, 7.5%, and 10% of volume. Mechanical characteristics of concrete were evaluated by various tests such as compressive strength, flexural strength, and splitting tensile strength. Absorption rate test, dry unit weight test, and ultrasonic pulse velocity test were conducted to assess the performance of concrete. Fresh concrete properties were determined using a slump test. Different water-to-cement ratios of 0.4 and 0.55 and cement content of 400 kg/m3 and 300 kg/m3, respectively, were used to prepare samples. The compressive strength test was conducted on cubic concrete samples with dimensions of 15×15×15 cm. Beams with dimensions of 10×10×50 cm were utilized to measure the flexural strength of all mixtures. The findings were determined at 28 days of curing. It revealed that PET mixtures had lower workability compared to reference mixture. The mixture with 5% PET achieved maximum compressive strength increase by 7.1%, and 12.39% with respect to that of the reference mixture at w/c=0.4, and 0.55, respectively. Flexural strength takes the same direction as compressive strength. Indirect tensile strength decreased by increasing the ratio of PET. The elastic modulus of PET mixtures decreased with an increase in PET content.

The use of ferronickel slag powder (FNSP) as a cementitious additional material has been supported by numerous reports. FNSP concrete has the same shortcomings as ordinary concrete, including low hardness. In this study, in order to make FNSP concrete more durable, end-hooked type steel fibers were incorporated. To understand how various elements affect the mechanical properties of steel fibers, an experiment was carried out on the mechanical properties of steel FNSP concrete (SFNSPC). FNSP’s principal ingredients, with a particle size distribution ranging from 0.5 to 100 μm and a sheet-like powder shape, are CaO, SiO2, Al2O3, MgO, and others, according to tests conducted on the material’s microstructure and composition. Then, eighteen mix proportions were developed, comprising six distinct FNSP replacement rate types and three distinct steel fiber content types. Crucial metrics were evaluated and analyzed, including the relationship among the toughness, tensile strength, and compressive strength as well as slump, splitting tensile strength, compressive strength, and uniaxial compressive stress–strain curve of SFNSPC. The results showed that the slump of SFNSPC under different FNSP replacement rates decreased with increasing steel fiber volume. Steel fibers have a small but positive effect on SFNSPC’s compressive strength; nonetheless, as FNSP replacement rates increased, SFNSPC’s slump gradually decreased, though not by much. These results show that FNSP is a viable alternative cementitious material in terms of strength. Specifically, the splitting tensile strength of SFNSPC improves with an increase in steel fiber content, and the pace at which SFNSPC strength drops with an increase in the FNSP replacement rate. With varying mix proportions, the stress–strain curve trend of SFNSPC remains mostly constant, and steel fibers improve the compressive toughness of SFNSPC. After adding 0.5% and 1.0% steel fibers, the toughness index of concrete with different FNSP replacement rates increased by 8–30% and 12–43%, respectively.

The hardness properties of constructional materials should be investigated as important factors in assessing the performance over the operation period. Two tests are performed to determine the stiffness characteristic, including slump and compressive strength (CS). They must be considered to examine efficiency, durability, and resistance to pressure. Due to the structure's susceptibility and usage in dams, bridges, etc., high-performance concrete must have an appropriate set of these tests. There are two soft-based and laboratory methods for performing these tests. The laboratory method is not economical in terms of cost and time, and artificial intelligence (AI) is used to reduce the aforementioned factors. Models and optimizers use software-based methods to help reduce errors and increase model accuracy. So, The main purpose of this research has been introducing novel ways of coupling an ensemble model with optimizers by adjusting some internal parameters. In this article, two models, the Radial Basis Function Neural network and Support Vector Regression were combined and coupled with General Normal Distribution Optimization (GNDO) and Archimedes optimization algorithm (AOA) into the two frameworks of SVRRBF-AOA and SVRRBF-GNDO. As a result, the hybrid model of SVRRBF-AOA could perform well by obtaining R2 and RMSE of 0.9915 and 2.71 for the slump and 0.9845 and 3.34 for CS, respectively. [ABSTRACT FROM AUTHOR]

This study mainly examines the slump, mass loss (ML), abrasion loss (AL), residual compressive strength (RCS), and residual splitting tensile strength (RSTS) of concrete reinforced with micro- and macro-polypropylene (PP) fibers after the F–T process. In the blends, micro- and macro-PP fibers were added to the blends at 0.3%, 0.6%, and 1% by volume. In total, 25, 50, 100, and 150 F–T cycles were applied to all samples. The study's results show that micro- and macro-PP fibers negatively affect the blends' slump values. Besides, PP fibers did not contribute to reducing the ML values of the samples after the F–T process. Moreover, the contribution of the PP fibers in prohibiting the decrease in RCS capacities of specimens after the F–T process is valid up to 0.3% volumetric fiber content. Additionally, PP fibers were more efficient in hindering reductions in AL and RSTS capacities after the F–T process of the specimens. Furthermore, using macro-PP fibers in hybrid form with micro-PP fibers reduced AL and improved RCS and RSTS capacities more than single macro-PP fibers. After 150 F–T processes, the reduction in AL of C0 control concrete was 9.41%, while the declines in AL of C1-C6 samples ranged from 7.56% to 8.92%. In addition, after 150 F–T processes, the decrease in RCS and RSTS loss of C0 control concrete is 25.09% and 28.30%. In contrast, the decline in RCS and RSTS loss of C1-C6 samples varies between 22.94–32.97% and 20.10–25.75%, respectively. [ABSTRACT FROM AUTHOR]

The influence of the mass concentration and particle size distribution on rheological parameters and slump was investigated by analyzing the mixture of overflow tailings (OT) and classified tailings (CT). The correlation between the rheological parameters, slump and characteristic value of the tailings particle diameter was discussed. Finally, the ratio parameters of a mixed tailings filling slurry were optimized using a lead–zinc mine in Guangdong, China as the engineering background. The results showed a quadratic decrease in the slump of the tailings slurry as the mass concentration increased, while the slump decreased with a decreasing particle size. With the increase in the mass concentration, the yield stress of the tailings slurry follows a quadratic function, while the plastic viscosity exhibits linear growth. The influence of tailings fine particles on the sensitivity of the yield stress and plastic viscosity to the mass concentration is reduced as their content increases. The yield stress and plastic viscosity of the tailings slurry exhibit a quadratic function decrease and linear growth as the slump increases. The slump of the tailings slurry is related to the particle size characteristic value and the mass concentration of the slurry. The correlation coefficient between the yield stress and the aggregate characteristic particle size increases most obviously at d10~d50, and the increase in the characteristic particle size will enhance the correlation between the yield stress and particle gradation. The correlation coefficient between the plastic viscosity and aggregate particle gradation parameters exhibits an initial increase followed by stabilization with an increasing characteristic particle size, with the most significant increase observed at d10~d50. [ABSTRACT FROM AUTHOR]