Sand Ratio Research Articles

Optimization of Filling Material Ratio in Yellow Phosphorus Slag Mine

Yellow phosphorus slag has been considered as a potential cement substitute for mine filling material due to its cementing activity; however, its slow setting and low early strength have limited broader use. This study investigates the grading, compactness, and strength of yellow phosphorus slag combined with tailing sand. Using yellow phosphorus slag as an aggregate, cement as a binder, and mixing tailing sand in different ratios, this study evaluates its feasibility as a coarse aggregate in mine backfill. The key findings are as follows. (1) The grading index of tailing sand was 0.5, aligning with Fuller grading, but it required mixing with coarse aggregates to enhance strength and reduce cement consumption. Yellow phosphorus slag, with a grading index of 0.97, does not match Fuller’s curve and thus benefits from mixing with tailing sand. (2) For mixtures of waste rock and tailings, the 5:5 ratio aligned closely with Fuller’s theory, showing optimal packing density and strength. Mixtures of yellow phosphorus slag and tailings at ratios of 3:7, 4:6, and 5:5 had R2 values of 0.73, 0.80, and 0.85, respectively, confirming reliable fit. The 5:5 mixture provided the best packing density and strength. (3) A new strength prediction model, accounting for aggregate, cement, and water effects, suggests that a 5:5 ratio with a 71% mass concentration and 1/7 ash–sand ratio meets industrial strength requirements. FLAC3D simulations indicated that cemented backfill reduces stress concentrations caused by excavation and supports stability during mining while also absorbing energy through compaction, creating favorable conditions for safe mining operations.

Utilization of waste phosphogypsum in high-strength geopolymer concrete: Performance optimization and mechanistic exploration

Phosphogypsum (PG) is an industrial waste produced during the manufacture of phosphoric acid. In this study, dihydrate phosphogypsum (DPG), ground granulated blast furnace slag (GGBFS), fly ash (FA), Portland cement clinker (PCC), sulfate alumina cement clinker (SACC), water reducer, sand, and stone were combined to create a phosphogypsum-based geopolymer (PBG) concrete. Concrete mix design was carried out based on the principle of maximum packing density, and the effects of water reducer type, sand ratio, water-to-binder ratio, and DPG content on PBG concrete properties were investigated. Results indicated that compared to SiKa ViscoCrete 540P (SVC 540P) water reducer, Melflux PLUS 1087L (MP1087L) significantly enhanced the performance of PBG concrete. With a water-to-binder ratio of 0.34, a sand ratio of 32.2 %, and a PG:GGBFS:FA ratio of 5:4:1, the 28-day unconfined compressive strength (UCS) of the concrete exceeded 60 MPa. The concrete primarily consisted of phases such as dihydrate gypsum (CaSO4·2H2O), ettringite (Ca6(Al(OH)6)2(SO4)3(H2O)26), polymer (-Si-O-Al-), quartz (SiO2), albite (Na(AlSi3O8)) and Muscovite ((K,Na)Al2(Si,Al)4O10(OH)2). Using two mild alkalis as activators, PBG concrete can avoid the efflorescence often associated with geopolymer preparation and can cure at 20 °C. PBG concrete offers high strength, ease of preparation, and environmental benefits, providing a new avenue for the reuse of PG.

Study on Crushed-Stone Cementation Properties and Bottom Stope Stability of Goaf by Open Stope Mining in Inclined Ore Bodies

The mining of the part of the inclined ore body below a goaf is crucial for improving resource extraction and safe production. In this study, the cementation properties of crushed stone during the mining of the inclined ore body were investigated by means of laboratory experiments, theoretical analysis, and numerical simulation. Additionally, orthogonal experiments were performed to assess how factors like water–cement ratio, crushed-stone particle size, and cement–sand ratio affect the strength of the grouting concretion body (GCB). Furthermore, the fluidity of the slurry under different ratios was also measured. Considering both the fluidity of the slurry and the strength of the GCB, the optimal ratios of the slurry were determined to be a water–cement ratio of 2.5:1 and a cement–sand ratio of 1:4. This ratio was then used for crushed-stone cementing under the poorest crushed-stone particle size conditions, based on which mechanical parameters were obtained from experiments. Theoretical analysis equated the problem of the grouting range to the width of the plastic zone of surrounding rock, and a conclusion was reached that the width of the GCB should be at least 29 m. The numerical simulation results reveal that among 30 mining rooms formed below the GCB, 24 mining rooms are in a stable state and 6 mining rooms are partially damaged on a small scale. As a whole, the GCB formed by grout filling into the goaf manages to effectively support the stope below, and it is verified that the theoretical calculation method of the width of the GCB is feasible.

Experimental Study and Machine Learning-Based Prediction of the Abrasion Resistance of Manufactured Sand Concrete

To systematically analyze the impact of manufactured sand on the abrasion resistance of concrete, this paper investigates the correlation between sand type, sand ratio, stone powder content, compressive strength, and the abrasion resistance of manufactured sand concrete. Grey correlation analysis was conducted to assess the impact priority of each factor affecting the abrasion resistance, and prediction models for the abrasion resistance were developed using XGBoost, random forest, AdaBoost, and gradient boosting. The results indicate that compared to river sand concrete, C30 and C40 concrete prepared with limestone and diabase manufactured sand has 20% higher abrasion resistance due to the presence of stone powder and higher roughness and solidity. Within the range of 0.40 to 0.44, a lower sand ratio leads to higher abrasion resistance. For concrete prepared with manufactured sand containing 5% to 11% stone powder, the best abrasion resistance can be attained at a stone powder content of 9%, and microscopic analysis suggests the highest concrete density at this level. According to grey system theory, the influence of each affecting factor on the abrasion resistance follows the order: sand ratio > crushing value > roughness > compressive strength > stone powder content > 0.6. Compared to gradient boosting, random forest, and AdaBoost models, the XGBoost model adopted in this study showed relatively higher R2 and lower RMSE in both the training and testing sets, which proved its higher accuracy in predicting the abrasion loss of manufactured sand concrete. The machine learning models offer some guidance for predicting and enhancing the abrasion resistance of manufactured sand concrete in practical engineering.

Multi-Task Learning Network-Based Prediction of Hydraulic Fracturing Effects in Horizontal Wells Within the Ordos Yanchang Formation Tight Reservoir

Accurate prediction of fracture volume and morphology in horizontal wells is essential for optimizing reservoir development. Traditional methods struggle to capture the intricate relationships between fracturing effects, geological variables, and operational factors, leading to reduced prediction accuracy. To address these limitations, this paper introduces a multi-task prediction model designed to forecast fracturing outcomes. The model is based on a comprehensive dataset derived from fracturing simulations within the Long 4 + 5 and Long 6 reservoirs, incorporating both operational and geological factors. Pearson correlation analysis was conducted to assess the relationships between these factors, ranking them according to their influence on fracturing performance. The results reveal that operational variables predominantly affect Stimulated Reservoir Volume (SRV), while geological variables exert a stronger influence on fracture morphology. Key operational parameters impacting fracturing performance include fracturing fluid volume, total fluid volume, pre-fluid volume, construction displacement, fracturing fluid viscosity, and sand ratio. Geological factors affecting fracture morphology include vertical stress, minimum horizontal principal stress, maximum horizontal principal stress, and layer thickness. A multi-task prediction model was developed using random forest (RF) and particle swarm optimization (PSO) methodologies. The model independently predicts SRV and fracture morphology, achieving an R2 value of 0.981 for fracture volume predictions, with an average error reduced to 1.644%. Additionally, the model’s fracture morphology classification accuracy reaches 93.36%, outperforming alternative models and demonstrating strong predictive capabilities. This model offers a valuable tool for improving the precision of fracturing effect predictions, making it a critical asset for reservoir development optimization.

Determination of Settling Velocity for Cohesive Sediments Using a Settling Column Experiment—Case Study: Ca Mau, Vietnam

The settling velocity (Ws) is a fundamental parameter in sediment dynamics, particularly in the coastal zones as estuarine and mangrove ecosystems, where various physical processes interact to influence sediment transport and deposition. Determining settling velocity is essential for understanding and predicting sediment transport, erosion–deposition processes in coastal environments. This study aims to determine the settling velocity and examines how sediment concentration affects settling velocity, using empirical models. The study applies these methods to compute the settling velocity of fine sediments in Ca Mau, Vietnam, which were collected in the Song Doc area (Western) in August 2014 and Rach Goc area (Eastern) in August 2015. The particle size analysis results indicate that the sediment samples from Western Ca Mau are coarser than those from Eastern Ca Mau, with sand ratios of 42.78% and 7.08% at the outer station, and 19.09% and 4.39% at the mangroves, respectively. The results also show that the average settling velocity of the sediment samples from Western Ca Mau is higher than that of the samples from Eastern Ca Mau. Specifically, the settling velocity in Western Ca Mau is 2.80 × 10−4 m s–1 at the outer station and 1.68 × 10−4 m s–1 at the mangroves. Meanwhile, in Eastern Ca Mau, the settling velocity of the sediment samples is 1.99 × 10−4 m s–1 at the outer station and 1.42 × 10−4 m s–1 at the mudflat-mangrove. Hence, it can be seen that the settling velocity of cohesive sediments corresponds well with the sediment’s particle size.

The mechanism of proppant transport dynamic propagation in rough fracture for supercritical CO2 fracturing

Supercritical CO2 fracturing technology has shown great potential for enhancing production in unconventional reservoirs. It is essential to clarify the transport mechanism of proppant under the dynamic propagation conditions within rough fractures. A realistic rough fracture model is reconstructed, and Computational Fluid Dynamics simulations are conducted to track proppant movement during fracture propagation. The typical transport characteristics of proppant within rough fractures are revealed, and the effects of fracture propagation rate, proppant density, mass flow rate, particle size, sand ratio, and temperature on the support effect are discussed. The results show that the flow channels formed by sand carrying fluid in rough fractures are complex, with fracture propagation changing some flow channels. The proppant forms an irregular sand bed interspersed with unfilled areas, and complex flow characteristics are generated. The increase in fractal dimension increases the resistance in the fluid flow process and affects the movement of the proppant, which tends to create unfilled areas. Low density and size of proppant can improve the proppant placement length. In a certain temperature range, high temperature injection of sand carrying fluid can improve the proppant placement effect. In addition, the low sand ratio and high mass flow rate pumping can be used to form the dominant channel, followed by pumping with a high sand ratio and low mass flow rate for effective support.

Investigating the Long-Term Effects of Anthropogenic Practices on Soil Features

Anthropogenic practices have been increasingly conducted on the rise in addressing the escalatingdemands for socioeconomic development, resulting in significant impacts on land ecosystems. This research seeks toevaluate the influence of anthropogenic activities on soil features in mountainous regions of Vietnam by focusing 84samples collected from 12 locations across Lam River Basin at seven soil profiles (0-10, 10-20, 20-30, 30-40, 40-60, 60-80 and 80-100 cm).The findings reveal notable differences in soil texture among land use types (LUTs). Forest cover lands (FCLs),showed the least amount of sand content, varying from 29.7% to 37.6%, while unplanted and bare lands (UBLs) had thehighest sand ratios, up to 53.9%. FCLs exhibited lowest bulk density (BD), soil porosity (SP) and soil electricalconductivity (EC) and C:N ratio with respective ranges of 0.93-1.29 g.cm-3, 32.7-36.5%, 0.526-0.743 mS.m-1 and6.74 -8.52, respectively.In contrast, crop cultivation lands (CCLs) demonstrated higher values for BD (1.17-1.25 g/cm3), SP (39.25-43.19%), EC (0.583-0.792 mS.m-1) and C:N ratio (11.27-15.77). UBLs, on the other hand, exhibited even highest valuesup to 1.23-1.36 g.cm-1, 43.19-49.62%, 0.437-0.619 mS.m-1 and 11.68-16.58% and displayed high levels of exchange ironsand soil organic content compared to FCLs. Other factors such as pH varied little in space between the sampled soillocations and along the soil profiles. Overall, the study indicates that anthropogenic practices have impacts on the soilfeatures across the study area.

Water Turbine Guide Blades Effect of Quartz Sand on Abrasion Rate

Abstract Hydroelectric power plants with the aim of being used to generate electrical energy are mostly operated in areas with sedimentation content which can cause wear and tear on the components of the hydropower plant. This activity is emphasized to determine the effect of quartz sand on the rate of abrasion on the guide vanes of the Francis type water turbine. This activity was carried out using a water turbine guide blade abrasion test tool with a guide blade test object made of SUS 304 stainless steel material. The results are presented quantitatively and qualitatively, the greater the concentration and diameter of the quartz sand particles, the water pressure and the angle given at the same time, the greater the rate of abrasion that occurs in the francis type water turbine guide vane. The highest abrasion rate was 5.10 (g/cm2 x hour) in the angle variation test with a constant Q and a water: sand ratio of 70%: 30%.

Technology and Research on Improving Oil Recovery by Volume Fracturing with Phase Change Permeability in Ultra-low Permeability Reservoirs

Abstract The conventional water injection development production wells in ultra-low permeability reservoirs have low efficiency, low production and low liquid content, and poor economic benefits. Traditional water drive development techniques are difficult to adapt to the requirements of economically effective development in ultra-low permeability reservoirs. Therefore, it is urgent to adjust development ideas and transform water injection development methods. A major development experiment was carried out in the Y284 area of Huaqing Oilfield to transform the water injection development method. Based on the mechanism of reverse osmosis flooding in oil recovery wells, this article uses dynamic monitoring technologies such as downhole microseismic to achieve three-dimensional reservoir transformation, and establishes a large-scale fracturing technology of “collaborative permeability flooding, volume fracturing, and multi-stage temporary plugging” for reverse osmosis wells in ultra-low permeability reservoirs. Research has shown that large-scale fracturing technology for water injection wells can improve single well oil recovery speed by increasing the complexity of fracture networks. The important factors affecting the effectiveness of water injection wells include reservoir properties, fracturing transformation scale, cumulative water injection volume, remaining oil distribution, and heterogeneity of aquifers. At the same time, the construction parameters of large-scale volume fracturing for water injection wells, namely 140-170m, are quantitatively determined based on the actual situation of the mining field ³ The amount of sand added, a sand ratio of 17-22%, and a large displacement of 8-10m3/min, 1400-2000m ³ The amount of liquid entering the ground can most effectively achieve the conditions for reservoir transformation. The conclusion is that large-scale fracturing technology for conversion wells provides technical support for volume fracturing and optimization design of fracturing parameters for low production wells in ultra-low permeability reservoirs, and can provide guidance and reference for the efficient development of other similar ultra-low permeability reservoirs.

Eco-Friendly Shield Muck-Incorporated Grouting Materials: Mix Optimization and Property Evaluation for Silty Clay Tunnel Construction

As shield tunnels increase, managing shield muck strains construction and the environment. To mitigate this problem, shield muck replaced bentonite in silty clay to improve synchronous grouting slurry. Initially, the physical attributes and microstructural composition of shield muck were obtained, alongside an analysis of the effects of the muck content, particle size, and general influencing factors on the slurry properties through standardized tests and regression models. Subsequently, leveraging three-dimensional response surface methodology, admixture interactions and multiple factor impacts on the slurry were explored. Finally, utilizing the SQP optimization technique, an optimal slurry blend ratio tailored for actual project needs was derived for improved muck slurry. The findings reveal with the decreasing bleeding rates as the muck content rises, the particle size diminishes. An inverse relationship exists between the muck content and slurry fluidity. At soil–binder ratios below 0.6, a decrease in the soil–binder ratio intensifies the influence of the water–binder ratio on the slurry density, bleeding rate, and setting time. The fly flash–cement ratio inversely correlates with the slurry bleeding rate, while the ratio greater than 0.6 is positively correlated. For muck particle sizes under 0.2 mm, the fly flash–cement ratio inversely impacts the density, while over 0.2 mm, it correlates positively. The optimal proportion for silty clay stratum synchronous grouting slurry, substituting muck for bentonite, includes a water–binder ratio of 0.559, binder–sand ratio of 0.684, fly flash–cement ratio of 2.080, soil–binder ratio of 0.253, particle size under 0.075 mm, and water-reducing admixture of 0.06.

Effects of aggregates and fibers on the strength and permeability of concrete exposed to low vacuum environment

The performance and regulation of concrete in low vacuum environments are receiving increasing attention. This study investigates the effects of aggregates and fibers on the strength and permeability of concrete in a low vacuum environment, using varying gradients of sand ratios (37.5 %, 40 %, and 42 %) and aggregate-to-binder ratios (3.27, 3.92, and 4.14). Three types of non-metallic fibers are utilized: polyethylene (PE), polyvinyl alcohol (PVA), and glass fibers. Evaluations focus on concrete strength, mass loss, gas permeability, capillary water absorption, and porosity. Results indicate that higher sand and aggregate-to-binder ratios enhance both flexural and compressive strength. Fiber incorporation improves flexural and compressive toughness, with PE fibers showing the most significant toughening effect. The low vacuum environment increases the strength of the concrete but reduces its axial compression toughness ratio and increases brittleness, while fiber incorporation helps improve the compression toughness of the concrete. Higher sand and aggregate-to-binder ratios reduce mass loss and accelerate drying equilibrium, while fibers increase mass loss and prolong drying equilibrium, with PVA fibers causing greater mass loss. The pattern of concrete mass loss can be explained by the tortuosity of the moisture diffusion path. Additionally, low vacuum significantly increases the gas permeability of concrete. Enhancing the sand and aggregate-to-binder ratios reduces permeability both before and after low vacuum treatment. Although fibers increase the gas permeability, they help mitigate this increase under low vacuum condition. Capillary water absorption tests reveal that concrete under low vacuum condition has a significantly higher water absorption rate compared to air-drying condition. Increasing sand and aggregate-to-binder ratios reduces water absorption and capillary water content, whereas fibers have the opposite effect. Porosity tests show that moisture migration in a low vacuum environment is mainly related to permeable porosity, while total porosity is more closely related to compressive strength.

Material Design and Performance Study of a Porous Sound-Absorbing Sound Barrier

A new type of porous sound-absorbing sound barrier was developed with quartz sand and self-developed polysiloxane resin. The forming process of the material was studied. The test specimens of the porous sound-absorbing sound barrier were prepared with different mesh numbers of quartz sand and different proportions of resin, and the void properties, compressive strength, durability, and acoustic performance were investigated. Based on the mix design results, it is suggested that 20-mesh quartz sand and a 10:1 mass ratio of quartz sand are used to prepare the porous sound-absorbing sound barrier. The durability study showed that the porous sound-absorbing sound-barrier material had good salt and alkali resistance, poor acid resistance, good water stability, and freeze–thaw stability. The laboratory acoustic test and practical engineering application results showed that the porous sound-absorbing sound barrier had excellent acoustic performance and good noise-reduction effects.

Soil texture analysis using controlled image processing

Soil texture analysis is crucial for crop selection, fertilizer recommendation, and production. Traditional soil testing in the lab using chemicals is highly time-consuming, expensive, and risky harmful chemicals; proper equipment and trained professionals are required to get the readings and to conduct the analysis. These issues can be resolved using image processing. In this study, we proposed a Blackbox prototype machine to take images in a controlled environment under the fixed intensity of light, distance, and standard dry conditions to analyze soil texture. This innovative machine, with its efficient and precise image processing capabilities, has the potential to revolutionize soil texture analysis. Also, we marked the center points of each type of soil texture as defined in the USDA texture triangle. Hundreds of soil samples were prepared for each type according to the center point's sand, silt, and clay ratio. The image processing-based model is trained for texture analysis. This research aims to reduce the soil texture analysis time and provide a system that can do extensive analyses automatically and with accuracy. The proposed Blackbox prototype machine has proven effective in providing a controlled environment for taking images. Also, the proposed model detects soil texture with a maximum accuracy of 99.5 %. A proposed model trained on the soil samples of different texture classes available in the USDA texture triangle accurately performed texture analysis. The results benefit the recommendation of appropriate crops and fertilizers based on a given soil sample in a very short time and cost-effectively.

Experimental Study on the Transport Behavior of Micron-Sized Sand Particles in a Wellbore

In the process of natural gas hydrate extraction, especially in offshore hydrate extraction, the multiphase flow inside the wellbore is complex and prone to flow difficulties caused by reservoir sand production, leading to pipeline blockage accidents, posing a threat to the safety of hydrate extraction. This paper presents experimental research on the migration characteristics of micrometer-sized sand particles entering the wellbore, detailing the influence of key parameters such as sand particle size, sand ratio, wellbore deviation angle, fluid velocity, and fluid viscosity on the sand bed height. It establishes a predictive model for the deposition height of micrometer-sized sand particles. The model’s predicted results align well with experimental findings, and under the experimental conditions of this study, the model’s average prediction error for the sand bed height is 12.47%, indicating that the proposed model demonstrates a high level of accuracy in predicting the bed height. The research results can serve as a practical basis and engineering guidance for reducing the risk of natural gas hydrate and sand blockages, determining reasonable extraction procedures, and ensuring the safety of wellbore flow.

Multi-angle research on the performance of self-foaming filling materials and analysis of engineering applications

Utilizing self-foaming filling material to fill the hollow area is an effective way to settle the issues of low rate and poor effect of filling and roofing in the large stope. There are fewer studies related to the expansion rate, hydration exotherm and strength properties of self-foaming fillers in mines. Based on this, this paper investigates the expansion characteristics, hydration exothermic characteristics and compressive strength characteristics of the self-foaming filler under different cement-tailings ratios (1:4, 1:6, 1:8), reveals the hydration reaction mechanism of the material and its microscopic characteristics through XRD, TG and SEM tests, and evaluates the application effect and economy of the self-foaming filler in practical engineering with the background of Mashong Iron Ore Mine. The main findings are as follows: (1) The volumetric expansion of self-foaming filling material can be divided into the initial stage Ⅰ (0–1.5 h), the rapid reaction stage Ⅱ (1.5–8 h) and the stabilization stage, and as the cement-tailings ratio grows, the expansion rate of the filling body increases, and the expansion rate of the filling material with 1:4 ratio is as high as 20.4 %. (2) The hydration process of a self-foaming filled body does not contain induction and acceleration stages; under the same conditions, the self-foaming filled body has more exothermic heat of hydration than that of a self-foaming filled body by about 50 J/g, and the bigger the cement-tailings ratio, the bigger the hydration exothermic rate and exothermic quantity. (3) The compressive strength of self-foaming filler is inferior to the strength of conventional filler, the higher the cement-tailings ratio, the greater the degree of hydration, the more hydration products are produced, and the greater the compressive strength. (4) The bigger the ratio of gray sand, the greater the proportion of macropores and the actual engineering of self-foaming filling materials to catch the top rate of up to 98 %, directly saving the total cost of 11.6 %. The above research results can offer theoretical support and scientific guidance for the utilization of spontaneous foam materials to fill the goaf and control the roof rate, temperature, and strength of the stope.

Investigation on compressive strength and splitting tensile strength of manufactured sand concrete: Machine learning prediction and experimental verification

Due to experimental constraints, traditional strength prediction models for manufactured sand concrete (MSC) exhibit significant limitations and have a narrow range of applicability. To overcome these limitations and enhance prediction accuracy, this paper, based on the widespread application of machine learning in concrete performance research, employed four algorithms: Support Vector Regression (SVR), Random Forest Regression (RFR), Gradient Boosting (GB), and Extreme Gradient Boosting (XGB) to develop highly accurate and strongly generalizable models for predicting the compressive strength (CS) and splitting tensile strength (STS) ofMSC. The predictive performance of each model was evaluated, the influence laws of various factors were analyzed, and finally, macroscopic experiments were conducted to validate the models' prediction accuracy and generalization ability. The development of these models and the analysis of the influence laws of various factors on the strength of MSC provide a valuable reference for the mix design. The conclusions are as follows: (1) The XGB model demonstrates the highest prediction accuracy and strongest generalization ability for both the CS and STS of MSC, achieving R2 values of 0.98 and 0.94 on the testing set, respectively. (2) The CS and STS of MSC are primarily influenced by four factors: water-binder ratio (W/B), curing age (AGE), cement (C), and coarse aggregate (RI≥0.08869, RI: relative importance), showing a positive correlation with AGE and C, and a negative correlation with W/B. As the fly ash content, stone powder content, maximum particle size of coarse aggregate, and sand ratio increase, the CS and STS initially increase and then decrease. Appropriately increasing the fineness modulus of manufactured sand is beneficial to both CS and STS, while the addition of slag is beneficial to CS and harmful to STS. (3) The prediction accuracy and generalization ability of the XGB model are verified through three sets of macroscopic experiments: C30, C35, and C40. The relative errors of each set's predictions are less than 8 %. (4) A graphical user interface is constructed based on the XGB model, enhancing its practicality.

Effects of recycled sand and shell sand as sand replacement on the dynamic properties of seawater sea-sand recycled aggregate concrete

This study utilizes recycled sand and shell sand to replace sea-sand in seawater sea-sand recycled aggregate concrete (SSRAC) and explores their dynamic compressive properties. A total of 28 sets of specimens were designed, and their stress-strain curves under different strain rates were analyzed. The findings indicated that the dynamic increasing factor (DIF) of peak stress in SSRAC reached its peak at a 50% replacement ratio of recycled sand, exhibiting a 3.9% to 7.7% increase compared to a 0% replacement ratio. Conversely, there was an overall decreasing trend in the DIF when the replacement ratio of shell sand increased. Using recycled sand resulted in an average reduction of approximately 45% in the elastic modulus of the interfacial transition zone (ITZ), while the introduction of shell sand slightly increased that of it. Finally, considering strain rate effects, a dynamic compressive prediction model for SSRAC with different types of fine aggregates was established.

Study on Freeze–Thaw Resistance of Cement Concrete with Manufactured Sand Based on BP Neural Network

In this study, experiments were conducted on the freeze–thaw performance of manufactured sand cement concrete with different sand ratios and fly ash contents. The research found that during 200 freeze–thaw cycles, as the fly ash content increased, the concrete exhibited a higher mass loss rate and a decline in the relative dynamic modulus of elasticity. This was due to the lower activity of SiO2 and Al2O3 in the fly ash, which reduced the hydration products. Incorporating an optimal amount of manufactured sand can increase the density of concrete, thereby improving its resistance to freeze–thaw cycles. However, when the content of manufactured sand was high, its large surface area could interfere with the hydration process and reduce strength, thereby diminishing the freeze–thaw resistance of the concrete. Given that studying the freeze–thaw resistance of manufactured sand concrete is time-consuming and influenced by many factors, a prediction model based on a BP (back propagation) neural network was developed to estimate the mass loss rate and the relative dynamic modulus of elasticity following freeze–thaw cycles. After validation, the model was found to be highly reliable and could serve as a foundation for mix design decisions and freeze–thaw performance prediction of manufactured sand cement concrete.

Harnessing hazardous wastes: the production, characterization, and performance of controlled low strength materials using common effluent treatment plant sludge

India's rapid industrialization has led to an increase in waste generation, necessitating efficient disposal methods. This research addresses this challenge by exploring the use of Common Effluent Treatment Plant (CETP) sludge, a hazardous waste, in the production of Controlled Low-Strength Materials (CLSM). The study aims to mitigate the environmental impacts associated with CETP sludge disposal while providing a sustainable solution. To assess the feasibility of this approach, an experimental program was conducted with variations in the mix ratio of CETP sludge and slag sand, a byproduct of steel production. The properties of the produced CLSM, such as flowability and unconfined compressive strength (UCS), were thoroughly examined using Scanning Electron Microscopy, X-ray Diffraction, and X-ray Fluorescence analyses. The results reveal that the CLSM produced with CETP sludge and slag sand exhibits promising performance, with excellent flowability and UCS values ranging from 1.8 to 5.5 MPa. This research underscores the potential of waste materials in creating sustainable and environmentally friendly construction materials, contributing to effective waste management practices and sustainable industrial growth.