Concrete Mixtures Research Articles

Experimental Performance Study on Axial Compressive Load-Bearing Capacity of Steel Slag Micropowder Ecotype UHPC of Short Columns Steel Pipe

In order to study the axial compression performance of steel pipe concrete short columns filled with steel slag micronized ultra-high-performance concrete (UHPC), this paper designs 27 steel pipe UHPC short columns for axial compression test and compares and analyzes the axial compression performance of the specimens in terms of the damage mode, the deformation curve, and the coefficient of strength enhancement, which is aimed at investigating the differences in the actual load-bearing performance of steel pipe UHPC short columns through changes in the aspect ratio, concrete type, and steel content rate, and so on. The purpose of this paper is to compare and analyze the axial compressive performance of the specimens in terms of damage mode and strength enhancement factor in order to investigate the difference in the actual bearing capacity performance of steel pipe UHPC short columns through the changes in length-to-diameter ratio, concrete type, and steel content. The test results show that the axial compressive performance of steel slag powder steel pipe UHPC short columns is greatly affected by the L/D ratio and steel content; the specimen bearing capacity increases with the increase in the wall thickness of the steel pipe and decreases slightly with the increase in the L/D ratio, and the steel fibers can effectively improve the deformation of the concrete so as to enhance the composite effect with the steel pipe; the contribution of the core UHPC to improve the value of bearing capacity accounts for a higher percentage when UHPC with 1% steel fiber dosage and 20% coarse aggregate dosage gave the best uplift with no change in the type of steel pipe. In this paper, the axial compression test bearing capacity results of steel slag micro powder steel pipe UHPC short column are compared with the calculated bearing capacity results of domestic and international specifications and analyzed from the perspectives of perimeter compression strength, steel fiber mixing of core concrete, and the relevant parameter design suggestions for high-strength steel pipe concrete specimens are put forward.

Flexural performance of UHPC two-way slab reinforced with FRP bars

The flexural behaviors of ultra-high-performance concrete (UHPC) two-way square slabs reinforced with fiber-reinforced polymer (FRP) bars were studied experimentally. Flexural tests were conducted on eight specimens, varying in reinforcement type, reinforcement ratio and confinement condition in compressive zone. Test results showed that the bridging effects of steel fibers in UHPC can mitigate the brittle characteristics of slab experiencing punching shear failure. The failure modes of slabs shifted from tensile failure to compressive failure by increasing the tensile strength of bar, leading to an improvement on the flexural capacity and ductility. The ultimate capacity of the slab with a reinforcement ratio of 1.06 % was 15.8 % greater than that of the slab with a reinforcement ratio of 0.67 %. By incorporating a layer of basalt fiber-reinforced polymer (BFRP) grid in the compressive zone to confine UHPC, the bearing capacity and ductility index of the slab increased by 17.8 % and 56.7 %, respectively. Introducing an enhancement coefficient to account for the confinement effect induced by the BFRP grid, a method was developed for predicting the flexural capacity of FRP reinforced UHPC two-way slab subjected to a local load at the mid-span, and its prediction accuracy was well verified.

Potentiality of Nano Pb2O3–Enhanced Cement as a Nuclear Radiation Shield for Radiation Therapy Facilities

In the present investigation, the gamma and neutron shielding parameters of nano Pb2O3 incorporated into cement in proportions ranging from 0 to 5 wt% were determined using EpiXS and NGCal software. It was observed that the mass attenuation coefficient decreased with increasing photon energy. The introduction of higher concentrations of nano Pb2O3 into the cement resulted in a marked increase in the Pb K-edge. Cement samples enhanced with Pb2O3 content exhibited a pronounced peak in the effective atomic number in the lower energy regions. The exposure buildup factor showed a decrease in its value with increasing Pb2O3 content. Among the compositions used, pure cement with no Pb2O3 addition demonstrated a superior mass attenuation factor for both thermal and fast neutrons. A blend of 95% cement with 5% Pb2O3 emerged as the most effective gamma-ray shielding material within the tested energy range. A comparative analysis of this mix with other concrete types was conducted to evaluate its effectiveness as a shielding material. The findings suggest that this composition could benefit medical imaging and radiation therapy facilities.

Experimental and numerical investigations on phase change thermal storage foam concrete based on CaCl2∙6H2O/silica aerogel composite phase change material

A new type of phase change thermal storage foam concrete was developed by effectively incorporating a composite phase change material (CPCM) into foam concrete. The CPCM was obtained by using 75 wt% CaCl2∙6H2O as PCM and 25 wt% silica aerogel as carrier, with a phase change temperature of 27.0 °C and an enthalpy value of 110.9 J/g. The mechanical and thermal properties of the obtained phase change thermal storage foam concrete blocks were investigated experimentally, along with a numerical analysis of their heat transfer characteristics. The experimental results demonstrated that after adding CPCM, the thermal performances of foam concrete blocks significantly increased, under the condition of their dry densities and compressive strengths met the specification requirements. Adding 20 wt% CPCM, the enthalpy value, specific heat capacity, thermal conductivity and thermal inertia of foam concrete block respectively reached 37.0 J/g, 1782.0 J/(kg∙K), 0.131 W/(m·K) and 770.9, with appropriate phase change temperature (27.2 °C). Numerical analysis for the heat transfer characteristics of the phase change thermal storage foam concrete wall revealed that optimal thermal insulation and thermal storage performances were achieved when the wall contained 20 wt% CPCM and thickness of 80 mm. In this case, the model exhibited a temperature wave attenuation factor of 6.66, the temperature amplitude of 5.84 K and a decline of 9.87 K for the highest temperature of the wall as well as delay time of 198,000 s, effectively regulating indoor temperature and saving energy. Therefore, the as-prepared phase change thermal storage foam concrete had great potential for application in building energy conservation.

Influence of Utilization of Natural Waste Fibers Pyrolysis on Mechanical Properties and Microstructure of Concrete

ABSTRACT The main purpose of this paper is to investigate the impact of the thermal processing of natural fibers on the strength of what is considered fiber-reinforced concrete. Natural fibers extracted from palm trees and bamboo residues were collected and pyrolyzed. The investigation of the morphological alterations that occur during the pyrolysis of natural fibers at a temperature of 200°C showed the impact of the cementitious environment on this process. In addition, the mechanical characteristics of fiber-reinforced concrete were conducted on different dosages (1, 1.5, 2, and 5% wt.) of treated and untreated palm oil, date kernel, and bamboo fibers. The results demonstrated that the inclusion of fibers up to 1.5% wt. enhanced the concrete mixes mechanical properties, which included pyrolyzed fibers. Analyzes of the concrete microstructure revealed that the treated fibers were not damaged. The 1.5% wt. addition of fibers after pyrolysis process can effectively improve their adhesion to the matrix and reduce the width and number of cracks. The analysis of variance results for flexural strength indicated that all sources had no significant impact on the flexural strength of untreated or pyrolysis treated natural fiber reinforced concrete.

A Review on Mechanism and Influencing Factors of Shear Performance of UHPC Beams

Ultra-High-Performance Concrete (UHPC) is increasingly used in various engineering projects due to its exceptional mechanical properties. This work conducts a literature review of research on the shear performance of UHPC beams in recent decades, with a focus on summarizing the formulas for calculating shear capacity and the main factors influencing shear performance. Firstly, this work reviews the calculation methods for the shear capacity of UHPC beams in different countries, along with their respective advantages and limitations. Subsequently, it provides a detailed analysis of various factors influencing the shear performance of UHPC beams, including longitudinal and stirrup reinforcement, steel fiber content, aggregates, admixtures, the shear-span ratio, shear keys, bolts, shear-reinforcement techniques, and environmental impacts. Through horizontal comparisons, the performance of UHPC beams and ordinary concrete beams under similar experimental conditions is examined to reveal the optimal shear working conditions for UHPC beams. Additionally, it is found that UHPC performs exceptionally well in composite beams, being compatible with numerous materials and significantly enhancing the shear strength of these beams. Lastly, the paper proposes suggestions for maximizing the shear performance of UHPC beams within a safe and reliable operating range and outlines future research directions.

Optimization of Laser Cladding Process Parameters and Analysis of Organizational Properties of Mixer Liners

Aiming to address the wear and replacement inconvenience of concrete mixer liners, this study utilizes a laser cladding system to clad Fe60 alloy powder on the liner. It investigates the influence of different process parameters on the forming quality of the Fe60 alloy powder cladding layer. The optimal process parameters were obtained by weighted comprehensive evaluation, and single-layer multi-pass cladding experiments were carried out under the optimal process parameters to investigate the effects of a 30%, 40%, and 50% lap rate on the surface flatness and forming quality of the cladding layer. Using a metallographic microscope, a scanning electron microscope analysis of the macro morphology and microstructure of the cladding layer was conducted, a DPT-5 penetration flaw detector was used to observe the cracks on the surface of the multi-channel cladding, a microhardness tester and friction and wear experimental machine were used for the hardness of the cladding layer, and an abrasive wear resistance test was conducted. The results show that under the process parameters of a laser power of 900 W, powder feeding speed of 7 g/min, scanning speed of 600 mm/min, and 50% lap rate, the average microhardness of the fused cladding layer reaches 742 HV, which is 1.8 times higher than that of the liner plate, and the coefficient of friction is 0.57, which improves the liner plate’s wear resistance performance and service life.

Flexural behaviour of BFRP grid/bar reinforced UHPC beams and slabs

This study investigates the integration of Basalt Fiber Reinforced Polymer (BFRP) and Ultra-High Performance Concrete (UHPC), which exhibit significant potential for a durable and sustainable solution in marine and offshore infrastructure. An experimental program of BFRP grid/bar-reinforced UHPC beams and slabs subjected to four-point bending is presented. A total of nine beams and ten slabs were prepared and tested to investigate the effect of BFRP reinforcement ratio (0 %–3.33 %), type of reinforcement (grid and bar), and steel fiber content of UHPC (0 %, 1 %, 2 % and 3 %). The results revealed that the inclusion of BFRP reinforcement, even at a small reinforcement ratio, is feasible to enhance structural ductility due to the large rupture strain and superior strength characteristics of BFRP material. Moreover, the steel fibers played a crucial role in preventing shear failures of UHPC and creep failures of BFRP reinforcement. Within a range of 0–2 %, the steel fiber content not only benefited the load-resistance and deformation capacity but also effectively improved the cracking load. However, high fiber content (3 %) had a minimal contribution to load-bearing capacity and negatively affected ductility. A theoretical model based on the deflection method was employed to forecast the general behaviour of the flexural members. Comparisons between experimental results and numerical predictions confirm its accuracy.

Sustainable concrete production: Partial aggregate replacement with electric arc furnace slag

Abstract The pursuit of sustainability in the construction industry has stimulated interest in seeking environmentally friendly alternatives to natural aggregates in concrete production. This study evaluates the behavior of concrete when electric arc furnace (EAF) slag is used as aggregates in its production. The primary research gap filled by this study is to deduce the blend of the fine and coarse EAF slag aggregates that would produce concrete of comparative strengths to concrete made with natural aggregates. Concrete mixtures were formulated using varied EAF slag content in the proportions of 0, 10, 15, 25, and 50%, respectively. The compressive strength values increased as the EAF slag content increased. However, this trend was not evident for the density and tensile strength values. The concrete mixture containing 25% EAF slag with 15% fine and 20% coarse EAF slag aggregates had the greatest density value of 2550.00 kg/m3 and the tensile strength value of 4.8 Pa respectively. This could be due to the distribution of the fine and coarse aggregate grains in the mixture. Since the percentage of fine and coarse aggregate grains were 10 and 15%, respectively, it was a close enough range for the fines to fill in the void spaces. This made the mixture more compact which resulted in a higher density and tensile strength values.

Enhancing bond strength prediction at UHPC-NC interface: A data-driven approach with augmentation and explainability

Existing concrete structures often have difficulty reaching their design service life due to aging, increased loads, and natural disasters, and they need to be repaired and strengthened or replaced. Ultra-high-performance concrete (UHPC), known for its ultra-high strength and excellent toughness, offers a promising solution for repairing and strengthening normal concrete (NC) structures. It is expected to be a viable solution when applied to the repair and strengthening of NC structures. A reliable interfacial bonding between the two materials (NC substrate and UHPC) determines the overall performance of this composite structure. In this study, a data-driven approach is proposed to predict the bond performance at the UHPC-NC interface as accurately as possible. To overcome the problem of limited experimental data, a data augmentation model is introduced, combining kernel density estimation (KDE) and tabular generative adversarial networks (TGAN). The optimal model is determined from six decision tree-based ensemble learning models applied to two strategies: "synthetic training - real testing" and "real training - real testing." Finally, a parametric analysis is performed using SHapley Additive exPlanations (SHAP) to elucidate the importance and sensitivity of different features related to bond strength. The findings illustrate that the suggested KDE-TGAN model effectively captures the distribution of the original dataset, enhancing both the accuracy and robustness of the bond strength prediction models. Furthermore, the model's ability to explain the importance and sensitivity of different features provides valuable insights into bond strength prediction. Thus, the proposed data augmentation model provides a reliable approach for modeling experimental data with small samples in structural engineering applications.

Generative artificial intelligence and optimisation framework for concrete mixture design with low cost and embodied carbon dioxide

This research presents a generative Artificial Intelligence (AI) and design framework that integrates machine learning (ML) and optimisation methodologies to discover new concrete mixture designs. Unlike traditional ML models that predict based on existing data, this framework innovatively generates new concrete mix designs that meet specific requirements such as strength, cost-efficiency, and reduced embodied CO2. To propose a powerful and reliable generative AI model, several advanced ML algorithms were considered, e.g., CatBoost, XGBoost, and LGBM. These models were trained on a unique dataset consisting of 4,936 data points collected from five different batching plants and have not been published yet. Bayesian Optimisation was employed to fine-tune model hyperparameters, resulting in the most effective models attaining R2 values of 0.94 and 0.89 for raw and grouped data, respectively. To verify the trained generative AI model, a case study was conducted, in which the model was requested to provide designs of a mix with pre-determined strength and optimised cost and embodied CO2. The mix designs generated by the framework were successfully validated through experimental tests, corroborating the predictive outcomes. The research culminated in the development of a web application, a tool crafted to streamline the concrete mixture design and optimisation process. This generative AI design framework can be applied to many other aspects of material design and engineering problems.

Evaluation of the Mechanical Behavior of Asphaltic Mixtures Utilizing Waste of the Processing of Iron Ore

Mineral extraction is an important operation for the economy of different countries and generates millions of tons of mining waste. In this context, and in association with the high demand for paving aggregates and the lack of raw materials for this purpose, the feasibility of using iron ore processing waste has emerged as a promising alternative. This study evaluates the physical and mechanical behavior of asphalt mixtures incorporating waste from the company Samarco S.A., collected in Mariana-MG, to replace the fine aggregate in asphalt concrete mixtures, with a view to applications in the bearing layer of local traffic roads. Two mixtures, M2 and M3, containing 20% and 17% waste, respectively, were formulated and analyzed, compared to a reference mixture, M1. Evaluations were carried out using the Marshall method parameters, mechanical tests of resilience modulus, and fatigue life under controlled tension, as well as mechanistic analysis. Brazilian mechanistic–empirical design software (MeDiNa—v 1.5.0) contributed to this analysis. This analysis revealed that, for a traffic level of N = 5 × 106 (average traffic) on a local road, pavements containing the M1 and M3 mixtures had the same layer thicknesses (6.9 cm), as well as the same fatigue class, equal to 1. The pavement with the M2 mixture had the thickest asphalt layer (8.2 cm) and a lower fatigue class equal to 0. But if compared in terms of the percentage of cracked area over 10 years, it still offers ideal performance conditions compared to the M1 and M3 mixes. Thus, it can be considered feasible to replace fine aggregate with iron ore waste in asphalt concrete for use on local roads in the region without altering the bearing capacity of the pavement.

Investigating the factors affecting sustainability of ready mix concrete plants: case study of Pune region

Construction industry plays a significant role in the economic development of the nation. Due to site and other constraints, concreting is preferred by ready mix concrete (RMC) plants. It is very well-known fact that the construction industry immensely contributed for CO2 emission mainly from cement-based materials. One of the way to achieve smart city objective to effectively manage ready mix concrete plants. While opting for RMC over site mixing offers various advantages. In this study, key factors governing the sustainability and energy consumption of RMC plants are identified. This study investigates the efficiency and sustainability of RMC production in Maharashtra, suggesting that its efficiency hinges on various factors. Through a constructivist perspective, the research examines twelve RMC plants in Pune mainly and other parts of Maharashtra, finding that power supply, plant output, and capacity require sustainability. While raw material supply is deemed sustainable, management methods and product control were found lacking. The study identifies challenges affecting demand, such as regulatory issues, management issues and technological limitations. The conclusion emphasizes the need for alternative and sustainable power sources, skilled labor, and improved business processes to enhance RMC production efficiency in Maharashtra, recommending measures like waste reuse and innovative advancements. This study will help the stakeholders in prioritizing the resources and process towards more sustainable way.

Mock-up pragmatic study on the impact performance of self-compacting concrete incorporating sea sand

Self-Compacting Concrete (SCC) allows for the use of non-desalted sea sand as a fine aggregate, but the durability of triple mix SCC with partial sea sand replacement remains unclear. To optimize binder and fine aggregate replacements, tests for consistency, setting times, soundness, compressive strength, and Ultrasonic Pulse Velocity were performed. Six SCC variations, incorporating 30%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} Class F Fly Ash (FA), 5%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} Ground Granulated Blast Furnace Slag (GGBS), and various fine aggregate combinations, were evaluated for their fresh, mechanical, microstructural, and durability properties. Results demonstrated that SCC with 50%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} sea sand and 50%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} manufactured sand achieved superior 90th\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{th}$$\\end{document} day compressive strength. This improvement was attributed to accelerated cement setting and enhanced FA reactivity, leading to better hydration products. Microstructural analysis revealed more hydration products and fewer pores in specimens with 50%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} sea sand, due to the disconnected pore structure from Friedel’s salt formation. Chloride binding in concrete involves both chemical and physical mechanisms. Chemical binding is related to Friedel’s salt, while physical binding depends on Calcium-Silicate-Hydrate (C-S-H) content. Dense C-S-H formation from sea sand, confirmed by Scanning Electron Microscope (SEM) images, results in greater chloride binding. Additionally, aluminum oxide in FA and GGBS enhances chemical binding by forming Friedel’s salt.

Harnessing machine learning for accurate estimation of compressive strength of high-performance self-compacting concrete from non-destructive tests: A comparative study

This study investigates the compressive strength (CS-28d) of high-performance self-compacting concrete. To accurately estimate the CS-28d, the study employed regression techniques (linear regression (LR) and stepwise polynomial regression (SPR)) as well as machine learning techniques (M5Prime, Random Forest, Random Tree and REP Tree). The study was based on 600 experimental results were collected from literature, with the rebound number (R), and ultrasonic pulse velocity (Vp) used to predict the CS-28d. The results indicate that the M5Prime model performed the best, with the highest coefficient of determination (Pearson R of 95.06 %) and the lowest root mean square error (RMSE of 4.84516 %). Among the tested regression models, the SPR model demonstrated the best performance and an empirical equation was introduced to estimate the CS-28d of a high-performance self-compacting concrete with high accuracy. An in-depth exploration of the model's sensitivity to its input parameters was conducted to quantify their effect on the CS-28d outcome. The results showed that the rebound number (R) had the most significant impact, with a sensitivity analysis parameter of 95 %. This was followed by the ultrasonic pulse velocity (Vp) had a relatively insignificant effect of only 5 % on the CS-28d values.

ბეტონში წყლის შემამცირებელი და შეკავშირების მარეგულირებელი ქიმიური დანამატების შესახებ

The article states that in order to prolong the safe service life of concrete under the influence of various artificial and natural factors, an appropriate chemical admixtures is used. Using water-reducing and bonding control chemical admixtures mainly reduces the frictional force between the cement particles. This simplifies the transportation of the concrete mixture, its placement in the construction formwork, and its reinforcement. It is possible to control the setting time of concrete according to climatic conditions. Laboratory and field tests are required to select this supplement. It is necessary to carry out proper scientific-research work on the establishment and application of the mechanism of influence of the water-reducing and bonding control chemical additive on the properties of concrete.

Comparative LCA-MCDA of high-strength eco-pervious concrete by using recycled waste glass materials

Sustainable management of construction and demolition (C&D) waste and waste glass (WG) presents a significant challenge in densely populated regions like Hong Kong. While the potential for using WG in concrete is acknowledged, there is limited research on how to optimally use these materials to achieve sustainability, cost-effectiveness, and mechanical integrity. This study addresses these challenges by employing an integrated life cycle assessment and multi-criteria decision analysis (LCA-MCDA) within a cradle-to-gate scope, utilizing site-specific data. The VIKOR method, known for its robust decision-making capabilities in complex environmental assessments, was used to identify optimal concrete mixtures based on environmental, economic, and mechanical performance. The results indicate that replacing 25% of natural aggregate with recycled WG materials provides the best balance across the evaluated criteria. Furthermore, additional environmental benefits can be achieved by substituting natural aggregates with recycled waste concrete aggregates. This research underscores the importance of life cycle thinking in construction materials decision-making, demonstrating that significant use of recycled WG reduces energy consumption and greenhouse gas emissions, offering a sustainable alternative to conventional concrete.

Fracture toughness of alkali-activated concrete subjected to aggressive environment

This study investigates the fracture toughness of alkali-activated granulated blast-furnace slag (GBFS)-based geopolymer concrete (GPC), non-activated slag cement concrete, and ordinary Portland cement (OPC) concrete in acidic, alkaline, and chloride solutions over six months. A total of 580 centrally straight-notched Brazilian disc (CSNBD) specimens were cast to assess pure mode-I (0°), pure mode-II (28.7°), and mixed-mode (15° and 45°) fractures under these conditions. Microstructural analyses (SEM) were performed to evaluate microstructural changes after six months of exposure. Results showed that GPC exhibited the lowest initial fracture toughness but the smallest reduction (7 %-11 % depending on the mode) across all environments, with slag cement concrete and OPC experiencing reductions of 11 %-14 % and 14 %-21 %, respectively, in acidic conditions. In alkaline environments, GPC showed a 3 %-6 % decrease in fracture toughness, while OPC and slag cement concrete showed reductions of 6 %-13 %. The gradient boosting regressor accurately predicted the failure load of CSNBD specimens, achieving an R² score of 0.948. Finally, SHAP sensitivity analysis identified concrete type, exposure time, and environment as critical input features, consistent with experimental results.

Analysis of waste glass as a partial substitute for coarse aggregate in self-compacting concrete: An experimental and machine learning study

With the growing environmental burden to minimize debris and recycle, the concrete industry has replaced wasted glass with concrete composition elements in multiple ways. This study provides a comprehensive analysis of integrating waste glass aggregate (WGA) at various proportions (0 %, 5 %, 10 %, 15 %, and 20 %) as substitutes for coarse aggregates along with a consistent 20 % silica fume (SF) as cement replacement in self-compacting concrete (SCC). In addition to determining the mechanical, durability and microstructural properties of SCC, this research also uses advanced machine learning (ML) techniques to predict the mechanical properties accurately. By employing slump flow, j-ring flow and v-funnel time the rheology of fresh SCC was evaluated. Mechanical properties were assessed through the evaluation of compressive, splitting tensile, and flexural strength, whereas electrical resistivity, water permeability, rapid chloride permeability (RCPT), and accelerated mortar bar test (AMBT) were employed to evaluate durability. The microstructure was further examined using scanning electron microscopic (SEM) and energy-dispersive X-ray spectroscopy (EDS) analysis. The replacement of WGA with a constant SF in SCC improved flowability while lessening its passing ability. Furthermore, the study indicated that adding 5 % WGA along with 20 % SF to SCC resulted in a slight decrease of 4.53 % in compressive strength and 3.61 % in flexural strength compared to the reference mix containing 0 % WGA and 20 % SF after 28 days, which yields a favorable outcome. Findings from further assessments revealed that SCC's durability characteristics were enhanced by adding WGA and SF. Expansion of the Ca/Si ratio observed in EDS analysis significantly impacts the strength, while voids and cracks patterns detected in SEM analysis, result in an inferior microstructural performance with the incorporation of WGA. Notwithstanding both the ML models exhibiting excellent regression coefficients (R2), the random forest model showed superior accuracy and reliability in its results.

Experimental investigation on bond properties of nano-Al2O3 and hydroxypropyl methyl cellulose (HPMC) modified coated steel bar embedded in concrete

In this work, cementitious coatings incorporate nano-Al2O3 (NA) and HPMC were developed applying to the surface of steel bars to enhance bond behavior. A total of 81 pull-out specimens were prepared to evaluated bond properties of different coated steel bars embedded in ordinary performance concrete (OPC), high performance concrete (HPC) and ultra-high-performance concrete (UHPC). The mechanical properties of the cement-based coatings have also been examined. Test results show that flexural and compressive strengths of coating paste exhibited initially increasing and followed by decreasing as NA content increase. Synergistic effect of NA and HPMC results in cement-based coating exhibiting superior mechanical properties. Besides, coating microscopic morphology characterized by scanning electron microscope (SEM) technique revealed that fewer coating defects with NA and HPMC compounding. More importantly, the highest bond strength between coated steel bar and different types concretes was found at 1.0 % NA content in the coatings. Synergistic effect of 1.0 % NA and 0.12 % HPMC improved bond strength of coated steel bar embedded in OPC, HPC and UHPC. It can be obtained from bond-slip curve that, regardless of the HPMC addition to coatings, coated steel bar with 1.0 % NA content shows higher bond stiffness. With both NA and HPMC added, bond stiffness, bond toughness and bond ductility of coated steel bar are superior to those of the coating with NA alone. Moreover, as concrete strength increases, the bond strength, bond stiffness and bond toughness of coated steel bar also increase, respectively.