Binder Ratio Research Articles

Influence of feature-to-feature interactions on chloride migration in type-I cement concrete: A robust modeling approach using extra random forest

Understanding the chloride transport mechanism is crucial for enhancing the durability of structures exposed to chloride-rich environments. This study assessed various machine learning (ML) algorithms for predicting the chloride migration coefficient in type I Portland cement-based concrete. The fine-tuned extra random forest model demonstrated satisfactory predictive capability, with the majority of tested-predicted data points falling within the ±30 % tolerance margin. This calibrated model was employed to explore feature-to-feature interactions affecting concrete resistance to chloride ingress. Examination of partial dependence plots revealed that an increased sensitivity with decreasing water–binder ratio (WB), reaching saturation beyond 0.40 WB, and the increase in curing age substantially reduced chloride diffusion (DN). Further, an augmented dosage of silica fume (SF) decreased DN, with a more pronounced effect of slag (SL) at higher WB, and the impact of superplasticizer (SP) decreased DN at high WB ratios. Concrete incorporating SF showcased optimal resistance to chloride permeability with the highest SF content (20–30 kg/m3). Similarly, high SL content (>150 kg/m3) enhanced resistance. The interactive influence of SF and SP on DN was marginal at low SF dosages (<20 kg/m3) but became complex at higher levels, with potential minimum values observed in the range of 0.5–1.0 kg/m3 SP. For SL-containing concrete, achieving the lowest DN was possible with PC and SL dosages around 200–400 and exceeding 100 kg/m3, respectively. For concrete incorporating Type I PC, an increase in SP content generally had a negligible impact on DN, with a slight tendency to raise values observed at higher cement amounts (exceeding 380 kg/m3). The optimal combination for achieving the minimum DN involved compositions of PC, fine, and coarse aggregate at 200–300, 100–150, and 250–500 kg/m3, respectively.

Effects of pelletization on biomethane production from wheat straw

ABSTRACT The high lignin content and low bulk density of wheat straw pose challenges for biogas production. To overcome these hurdles, pretreatment and biomass pelletization have emerged as viable options. Thus, this research aims to reduce the recalcitrant nature of WS by employing various thermal pretreatment techniques and identifying the optimum parameters (temperature and time). To prepare pellets, a mixture comprising wheat straw (subjected to the best pretreatment) and cow manure pellets (WCP) at varying substrate and binder (Svs/Bvs) ratios ranging from 0.5 to 2.5 were used. Parameters such as density, water absorption, and drop shattering were evaluated to evaluate the physical characteristics of produced WCP. Additionally, the biomethane yield test of WCP (exhibiting the most favourable physical characteristics) was performed with various total solids (TS) concentrations from 4 to 12%. The WS demonstrated the highest sCOD solubilisation of 9066 mg/L when subjected to a hot air oven pretreatment (90 min at 110°C). The physical qualities of WCP were found to be dependent on the Svs/Bvs ratio (with the optimal ratio being 2.0). It was also observed that a TS content of 6% yielded the highest biomethane production (253.85 mL/g-VSconsumed). In summary, this study’s conclusion waves the path of management of wheat straw and cow dung while simultaneously generating bioenergy.

Study on the Performance Optimization of Plant-Growing Ecological Concrete

The response surface regression model of plant-growing ecological concrete is established based on the factors of the water–binder ratio, fly ash content, and design porosity, with 28-day compressive strength, connectivity porosity, and pH value as response variables. Based on optimizing the mix proportion with the regression model, different dosages of acetic acid are used as excitation agents to increase the compressive strength and reduce the alkalinity of plant-growing ecological concrete to enhance its service life and vegetation performance. The results show that the compressive strength of plant-growing ecological concrete with a water–binder ratio of 0.3, a fly ash content of 26%, and a design porosity of 22% was 10.32 MPa, the connectivity porosity was 20.00%, and the pH value was 11. After the addition of acetic acid at 0.4% of the mass of the cementitious material, the compressive strength increased by 40.29%, and the pH value decreased by 6.33%. This study proposes a cost-effective means and provides data support for the engineering application of plant-growing ecological concrete.

Using Multiple Machine Learning Models to Predict the Strength of UHPC Mixes with Various FA Percentages

Ultra High-Performance Concrete (UHPC) has shown extraordinary performance in terms of strength and durability. However, having a cost-effective and sustainable UHPC mix design is a challenge in the construction sector. This study aims on building a predictable model that can help in determining the compressive strength of UHPC. The research focuses on applying multiple machine learning (ML) models and evaluating their performance in predicting the strength prediction of UHPC. Two reliable metrics are used to evaluate the performance of the model which are the coefficient of determination (R2) and mean squared error (MSE). The parameters that are affecting the compressive strength of UHPC are fly ash percentage levels (FA%), superplasticizer content, water to binder ratio (w/b), and curing period. A total of 54 ML models were used, consisting of Linear Regression, Support Vector Machines (SVM), Neural Networks, and Random forests algorithms. Among these models, Random Forest proved to be the most effective in capturing the relationships in UHPC’s behaviour with an R squared score of 0.8857. The Random Forest ML model is also used in this paper to conduct a parametric study that will help in obtaining the compressive strength of UHPC with higher content of FA%, which is not sufficiently studied in the literature.

The Effect Of The Comparison Of Binders In The Manufacture Of Carp Rolade (Cyprinus Carpio) On The Physical Properties And Consumer Acceptability

This research aims to analyze the effect of binder ratio in the making of carp fish roulade on the physical properties and consumer acceptance. The research was conducted at the Food Processing Laboratory, Department of Culinary Education, Universitas Negeri Jakarta. The research period began in August 2023 and ended in June 2024. The method used in this research was experimental. The research sample used grass carp roulade with a binder ratio between tapioca flour and wheat flour at 1:1, 2:1, and 1:2. The samples were then tested on 30 moderately trained panelists who evaluated overall aspects. Based on the results of statistical hypothesis testing using the Friedman test, it was found that there was no influence of binder ratio on the acceptance of carp fish roulade at ratios of 1:1, 2:1, and 1:2 in terms of skin color before and after frying, filling color before and after frying, fish aroma, spice aroma, taste, and structural compactness. However, one aspect that had an influence was the level of tenderness. Based on the results of statistical hypothesis testing, physical testing using the Kruskal-Wallis test showed that the binder ratio had no significant influence on the physical quality of grass carp roulade in terms of hardness level. The conclusion of this study is that the acceptance of carp fish roulade is recommended at a binder ratio of 1:1 between tapioca flour and wheat flour.

Determination of complex Poisson’s ratio of asphalt binders using torsion-tension tests in a dynamic shear rheometer

A novel test method for measuring the Poisson’s ratio of asphalt binders using a Dynamic Shear Rheometer (DSR) equipped with a linear drive is presented. The paper describes the preparation of homogeneous and isotropic cylindrical binder specimens, their loading into the DSR, and the subsequent measurement of the absolute complex shear modulus |G*|, and the complex elastic modulus |E*|. Both moduli are obtained from the same specimen so the complex Poisson’s ratio, |υ*|, can be measured indirectly as a function of temperature and frequency. This is illustrated for three different samples of plain asphalt binders: hard 30/45 binder, standard 50/70 binder, and soft 70/100 binder.

Transport properties of fly ash-slag-based geopolymer concrete with 2M sodium hydroxide combined with variations in slag percentage, Al/Bi ratio, and SS/SH ratio

The aim of this research is to determine the effect of sodium hydroxide molarity 2M combined with variations in slag percentage, ratio of alkali activator to binder (Al/Bi), and ratio of sodium silicate to sodium hydroxide (SS/SH) on the transport properties of fly ash-slag-based GPC cured at ambient temperature. The result is increase in slag percentage and SS/SH ratio lead to a decrease in porosity, water absorption rate and chloride permeability. The alkali activator to binder (Al/Bi) ratio of 0.45 produces the lowest porosity, water absorption rate, and chloride permeability. The porosity, sorptivity, and chloride penetration depths of all GPC are lower than those of OPC. The recommended mix compositions for GPC that exhibit lower transport properties than OPC are GPC4 (slag 40%, SS/SH ratio 1.5, Al/Bi ratio 0.45); GPC5 (slag 50%, SS/SH ratio 1.5, Al/Bi ratio 0.45); and GPC7 (slag 30%, SS/SH ratio 2.0, Al/Bi ratio 0.45).

Improvement of Mechanical And Light Transmittance Properties of Foam Coated Curtain Fabrics

In foam coating, the main factors are the foam density of the coating material and the compatibility among foam structure, the coating material and the fabric surface. In this study, the results of breaking strength, breaking elongation, tear strength and light transmittance testing were compared according to the fabric structure, coating recipes, foam density and the coat layer viscosity statistically. The high yarn density of warp threads per unit length in polyester woven fabric leads to an increase in tensile strength. The best results in tensile strength and elongation at break experiments were obtained at coating recipe 4. As a result, the minimum light transmittance value was 1.0347 and the maximum light transmittance value was 1.12 by using coating recipe 4, respectively. Consequently, the low filler content, soft binder ratio and foam density had a positive effect on the mechanical and light transmittance properties of foam coated fabrics.

A study on composite carbonaceous reducing agent pellets based on low-order unbonded coal

To minimize the cost of carbon-reducing agents and reduce the waste of powder in production, a novel composite carbonaceous reducing agent pellet was prepared through cold pressing, utilizing low-rank unbonded coal (NC) as the primary raw material and incorporating petroleum coke (PC) and high-bonding coal (HVC). This study investigated the influence of different material composition ratios, the addition of organic binder (OBD) and inorganic binder (IBD) (water glass solution), forming moisture ranging from 2 to 12 %, holding temperatures of 60 to 100 ℃, holding times of 2 to 6 h, and material particle sizes ranging from 40 to 250 mesh (0.063–0.420 mm). Additionally, forming pressures of 5 to 30 MPa were analyzed concerning their impact on the cold consolidation strength (CCS) of the resulting pellets. The primary and secondary effects of forming pressure, forming moisture, binder content, and raw material size on pellet strength were examined. According to the actual production situation, the optimum technological conditions were determined. The primary and secondary effects on CCS were ranked as follows: forming pressure > particle size of raw material > binder ratio of 4 % content > forming moisture. External morphology and internal structures of different carbon materials were characterized via FESEM, BET, FTIR, XRD, and XPS. Mechanisms affecting the pellet strength were analyzed. The newly developed composite carbon-reducing agent pellets were suitable for industrial silicon production. This study presented a pathway for the clean and efficient utilization of low-rank unbonded coal and low-viscosity coal, offering substantial economic and social benefits.

Effect of various geopolymerization parameters on poor quality Afşin-Elbistan fly ash-based geopolymer concretes with ground granulated blast furnace slag

The utilization of Afşin-Elbistan fly ash (FA), which cannot be used in cement and concrete industry in production of geopolymers, has been studied with some preliminary trials. In this study, FA of Afşin-Elbistan thermal power plant, which does not fit any of FA classes according to ASTM C 618, was used as a geopolymer binder raw material. The main motivation of the study is to investigate the partial usability of this type of FA, which is not sufficient on its own and creates a large amount of waste, as a geopolymer raw material. FA was replaced with ground granulated blast furnace slag (GGBFS) by the ratios of 25% and 50% (by weights) in order to develop the properties of geopolymer concrete. Sodium silicate (SS) and sodium hydroxide (SH) (10 and 14 M) were used as activators. Three different activator to binder ratios (0.45, 0.55 and 0.65) and three SS/SH ratios (0.75, 1.0 and 1.5) were chosen. Unit weight, compressive strength, splitting tensile strength, and ultrasonic pulse velocity tests were performed for 28 and 60 days. In order to investigate the microstructure, scanning electron microscopy (SEM) analyses were performed. As a result, GGBFS incorporation enhanced the properties of Afşin-Elbistan FA-based geopolymer concrete. With the increase of GGBFS content, the compressive strength values increased. The highest strengths were obtained from 50% GGBFS groups. The results revealed that Afşin-Elbistan FA (AEFA), which has the highest waste reserve among the thermal power plant fly ashes in Turkey, could be evaluated as partial geopolymer raw material.Graphical abstract

Study on Static Mechanical Properties and Numerical Simulation of Coral Aggregate Seawater Shotcrete with Reasonable Mix Proportion

This study aims to explore the static mechanical characteristics of coral aggregate seawater shotcrete (CASS) using an appropriate mix proportion. The orthogonal experiments consisting of four-factor and three-level were conducted to explore an optimal mix proportion of CASS. On a macro-scale, quasi-static compression and splitting tests of CASS with optimal mix proportion at various curing ages employed a combination of acoustic emission (AE) and digital image correlation (DIC) techniques were carried out using an electro-hydraulic servo-controlled test machine. A comparative analysis of static mechanical properties at different curing ages was conducted between the CASS and ordinary aggregate seawater shotcrete (OASS). On a micro-scale, the numerical specimens based on particle flow code (PFC) were subjected to multi-level microcracks division for quantitive analysis of the failure mechanism of specimens. The results show that the optimal mix proportion of CASS consists of 700 kg/m3 of cementitious materials content, a water–binder ratio of 0.45, a sand ratio of 60%, and a dosage of 8% for the accelerator amount. The tensile failure is the primary failure mechanism under uniaxial compression and Brazilian splitting, and the specimens will be closer to the brittle material with increased curing age. The Brazilian splitting failure caused by the arc-shaped main crack initiates from the loading points and propagates along the loading line to the center. Compared with OASS, the CASS has an approximately equal early and low later strength mainly because of the minerals’ filling or unfilling effect on coral pores. The rate of increase in CASS is swifter during the initial strength phase and decelerates during the subsequent stages of strength development. The failure in CASS is experienced primarily within the cement mortar and bonding surface between the cement mortar and aggregate.

Fabrication of Activated Carbon Derived from Glycerin Pitch for Desulfurization of Model Fuel Oil and Electrode Application.

One of the world's challenging energy issues is introducing practical and affordable technology for organosulfur removal in fuel. Adsorptive desulfurization (ADS) can address this issue if highly effective activated carbon (AC) derived from industrial waste with excellent textural properties is used. In this study, the derived ACs from glycerin pitch loaded with P and Fe (AC/P and AC/Fe) were used as adsorbents for the ADS of model fuel oils, such as dibenzothiophene (DBT) at mild operating conditions. Under the optimized experimental conditions, 0.3 g of adsorbent dosage, 60 min reaction time, 30 °C temperature, and pH 4, the maximal DBT removal of 96.28 and 43.64%, respectively, for AC/P and AC/Fe was realized. The results indicated that the phosphorus-doped AC/P increases the selectivity of the ADS mechanism for DBT removal. Kinetic investigations disclosed that the adsorption process follows second-pseudo-order kinetics and the Langmuir adsorption isotherm model. The adsorbents remained active for five successive reuses, indicating their robust real-world applications. The electrochemical properties of the fabricated carbon electrodes were analyzed via cyclic voltammetry by coating the ACs with polytetrafluoroethylene (PTFE) as a binder. The transition-metal-doped AC/Fe, though exhibiting 5 times lower surface area, showed the highest specific capacitance at a scan rate of 5 mVs-1 (0.65 μF cm-2). Similarly, the extended AC:PTFE capacitor at a 10% binder ratio offered the maximum capacitance value (1.13 μF cm-2). The synthesized ACs demonstrated potential application as an electrode material, and hence glycerin pitch could be a low-cost precursor to improve the feasibility of commercial production of AC.

Preparation and evaluation of GCD-1 lunar regolith simulant based geopolymer activated by solid sodium silicate

In this study, a new lunar regolith simulant, named "GCD-1", was formulated by combining various minerals, such as anorthite, albite, pyroxene, ilmenite, slag, and fly ash. Through X-ray fluorescence spectroscopy (XRF) and X-ray diffraction (XRD) analysis, it was verified that the main mineral composition of GCD-1 was basically the same as that of the lunar soil at the Apollo 14 landing site, in which the deviation in the main compound (i.e., SiO2 and Al2O3) was within 0.5%. Furthermore, GCD-1 based geopolymer was prepared by the one-part method, which was a mixture of solid GCD-1 precursor, solid sodium silicate (SS) activator, and water. The average daytime temperature at the lunar equator, which was calculated to be 60°C, was set as the curing temperature for the GCD-1 based geopolymer. The strength development of the GCD-1 based geopolymer was then characterized by unconfined compressive strength (UCS) for 3, 7, and 12 curing days to consider the effectiveness of the factors (solid SS to lunar regolith simulant [S/L] and water to binder ratio [W/B]). The micro-analysis tests including scanning electron microscope-energy dispersive spectrometer (SEM-EDS), mercury intrusion porosimetry (MIP), and brunner-emmet-teller (BET), were further conducted to investigate the microstructural development of the GCD-1 based geopolymer. Results showed that the increase of the W/B ratio in the GCD-1 based geopolymer tended to increase the total porosity of the sample, thereby inducing a lower UCS. At the same time, for a fixed W/B ratio, the higher S/L ratio had a certain inhibition effect on the hydration reaction, which caused the reduction in the UCS of the sample. The highest UCS of the GCD-1 based geopolymer reaching 30.54 MPa, was achieved under the simulated lunar equatorial daytime temperature for 12 days with W/B and S/L ratios set at 0.25 and 0.18, respectively. Microstructure and mineralogy analyses indicated that the hydrated sodium aluminosilicate (N-A-S-H) gels contributed to reducing the sample's porosity, thereby enhancing the UCS. The relationship between the UCS and total porosity of GCD-1 based geopolymer was then derived. The results of the current study are crucial for lunar base construction with in-situ resources.

Establishing Strategies to Improve Cracking Resistance of High Recycled Binder Ratio Asphalt Mixtures

This study aims to investigate promising mitigation strategies for improving the cracking performance of high recycled binder ratio (RBR) asphalt mixtures. Moisture-resistant aggregates that do not require anti-stripping agents, reclaimed asphalt pavement (RAP), and recycled asphalt shingles (RAS) were sampled for this study from sources in two climatic zones, south and north. The south-moisture-resistant (SR) mixtures were designed with 0.16 and 0.29 RBRs with RAP, while the north-moisture-resistant (NR) mixtures included 0.21 and 0.37 RBRs with RAP and 0.44 RBR with RAP/RAS. The mitigation strategies evaluated included a softer binder, a different binder source with higher ΔTc, a recycling agent (RA), reduced recycled binder availability (RBA), polymer-modified asphalt (PMA), and hybrid approaches including softer binder + RBA and PMA+RBA. The Indirect Tensile Asphalt Cracking Test (IDEAL-CT) and Disc-Shaped Compact Tension (DCT) test were conducted to capture intermediate-temperature and low-temperature cracking performance, respectively. In addition to the cracking tolerance index (CTindex), an IDEAL-CT interaction diagram analysis was added to further understanding the effect of mixture variables on cracking performance. The findings suggest that while no single strategy works for all RBR mixtures tested, RA, RBA, softer binder, or their combinations yield adequate cracking performance depending on factors including RAP binder stiffness and quantity, RA dose, climatic zone, and RBA.

Development of Sustainable Slag-based Geopolymer Concrete Using Different Types of Chemical Admixtures

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.

Optimizing compressive strength of quaternary-blended cement concrete through ensemble-instance-based machine learning

Optimizing the composition of concrete, particularly when incorporating ordinary Portland cement (OPC) along with supplementary materials such as ground granulated blast furnace slag (BF), fly ash (FA), and silica fume (SF), poses challenges due to the intricate nonlinearity inherent in concrete properties. Addressing this challenge has urged growing interest in employing Machine Learning (ML) techniques for precise property assessment. In this investigation, various predictive models, encompassing eXtra Gradient Boosting (XGB), random forests (RF), and K-Nearest Neighbor (KNN) algorithms were formulated to predict the compressive strength (CS) of ternary-blended concrete incorporating OPC, BF, FA, and SF. Through comprehensive analysis of an extensive dataset comprising 810 distinct records, the study identifies optimal concrete blends, providing invaluable insights for practical applications. Evaluation of ML models underscores the superior performance of XGB, with a coefficient of multiple determination (R2) values of 0.923 and 0.997 for training and testing datasets, respectively, indicative of exceptional predictive accuracy. Additionally, SHAP values underscore the importance of input age, water–binder ratio, and OPC content. This research enhances understanding of ternary-blended concrete characteristics, offering practical implications for construction practices and laying a foundation for future research endeavors to refine ML models, explore attribute interactions, and optimize concrete constituent proportions for broader civil engineering applications.

The Design of a Novel Alkali-Activated Binder for Solidifying Silty Soft Clay and the Study of Its Solidification Mechanism.

In order to overcome the problems of the high economic and environmental costs of a traditional ordinary portland cement-based binder, this study used self-combusted coal gangue (SCCG), granulated blast furnace slag (GBFS) and phosphorous slag (PS) to prepare a novel SCCG-GBFS-PS (SGP) ternary alkali-activated binder for solidifying silty soft clay (SC). Firstly, the parameters of the SGP ternary binder were optimized using orthogonal experiments. Then the effects of the SGP ternary binder content (mass ratio of the SGP ternary binder and the SGP-solidified soil), initial water content of SC (mass ratio of SC' water and SC) and types of additives on the unconfined compressive strength (UCS) of the SGP-solidified soil were analyzed. Finally, the hydration products and microstructure of the SGP-solidified soil were analyzed to investigate the solidification mechanism of the SGP ternary binder. The results showed that the optimal mass ratio of GBFS and PS is 2:1, and the optimal alkali activator content (mass ratio of Na2O and the SGP ternary binder) and modulus of alkali activator (molar ratio of SiO2 and Na2O of alkali activator) were 13% and 1.3, respectively. When the SGP ternary binder content was 16% and the initial water content of SC was 35%, the SGP-solidified soil met the requirement of UCS for tertiary cured soil. The incorporation of triethanolamine and polyvinyl alcohol improved the UCS, while the incorporation of Na2SO4 significantly deteriorated the UCS of the SGP-solidified soil. The C-S-H gels and C(N)-A-S-H gels generated by hydration of the SGP-solidified soil were interspersed, interwoven and adhered to each other to form a network-like space structure that played the roles of skeleton, bonding soil particles and filling pores, which improved the macroscopic properties of the SGP-solidified soil. The results of this study provide a reference for the design and development of a solid waste-based binder for solidifying SC.

Predicting compressive strength of fiber-reinforced coral aggregate concrete: Interpretable optimized XGBoost model and experimental validation

The addition of macro and micro fibers can enhance the compressive strength of fiber-reinforced coral aggregate concrete (FRCAC-CS). Traditional explicit models for FRCAC-CS suffer from shortcomings related to accuracy and generalization capabilities. To address this issue, a comprehensive database for FRCAC-CS was established by collecting 834 sets of experimental data from 15 literature sources. The hunger games search algorithm (HGS), sooty tern optimization algorithm, and whales optimization algorithm were used to optimize the hyperparameters of the XGBoost algorithm, resulting in optimized XGBoost models for FRCAC-CS. The performance of the prediction models was assessed through comparisons between predicted and actual values, model residual distribution, and performance evaluation metrics. Sensitivity analysis was conducted using the Shapley additive explanations method. Subsequently, 9 different mix proportions were formulated to validate the performance of the optimal model. The results suggest that the HGS–XGBoost model yields predictions that are closer to the actual values, exhibiting smaller mean and standard deviation in model residuals. The five major performance evaluation metrics, including RMSE, MSE, MAPE, MAE, and R2, for the HGS–XGBoost model are 0.91, 0.83, 2.35, 0.77, and 0.99, respectively, surpassing those of other models. Sensitivity analysis highlights the water–to–binder ratio and total aggregate content as the two most crucial factors among the mix components. Decreasing the water–to–binder ratio and the total aggregate content improves the FRCAC-CS. The experimental results from the 9 mix proportions demonstrate that the error between predicted and experimental values is below 7%, affirming the HGS–XGBoost model’s adequate accuracy and generalization capabilities for new datasets. This study introduces a novel AI-based prediction method for FRCAC-CS, establishing the groundwork for its potential application in reef construction.

Predicting corrosion behaviour of steel reinforcement in eco-friendly coral aggregate concrete based on hybrid machine learning methods

ABSTRACT This study proposes a machine learning-assisted method for assessing steel reinforcement corrosion, utilising data on chloride ion concentration (CIC) and chloride ion concentration threshold (CCT) from eco-friendly coral aggregate concrete (EFCAC). A total of 2185 data points were collected to establish the EFCAC-CIC database. A multi-objective slime mould optimised support vector regression (MOSMA-SVR) model for EFCAC-CIC was developed. The significance of each feature to EFCAC-CIC was analysed. Subsequently, a graphical user interface (GUI) was developed based on the MOSMA-SVR model. Finally, the GUI and EFCAC-CCT were used to assess the corrosion behaviour of reinforcement. Results indicate that the MOSMA-SVR model provides predictions that are closer to the actual values, with smaller mean errors and standard deviations. The performance indicators, including coefficient of determination, mean absolute error, mean absolute percentage error, mean square error, root mean square error, and a20-index, of the MOSMA-SVR model are 0.987, 0.0124, 0.0332, 2.91e − 4, 0.0171 and 0.9991, respectively, and they are superior to those of the other tested models. The water type and the water–binder ratio are identified as the two most critical factors. Furthermore, by integrating the GUI and feature importance analysis results, chloride salt-resistant EFCAC can be designed. When this is combined with the GUI and EFCAC-CCT, the corrosion of rebar in EFCAC can be assessed in real time.

Development and characterization study of bagasse with stubble reinforced polyester hybrid composite

In the present day, recycling and reducing environmental pollution are the primary objectives of sustainable development. A lot of experts are considering the possibility of creating a new composite technology with waste materials. This work aims to investigate the effects of waste material on mechanical and hydrophobic properties, with a particular focus on bagasse fiber with stubble. The tensile, flexural, impact, and hardness properties of bagasse with stubble polyester composite were investigated to see if it may be used as a novel material in various engineering applications for a longer life. To improve the impact resistance of the composite, bagasse fibers is mixed in different ratios with polyester and stubble as infill. Additionally, a very tiny amount of TiO2 was added to every sample. Tensile, flexural, and impact mechanical properties were assessed using the Universal Testing Machine, the Rockwell Hardness Testing Machine, and the Izod Impact Test. Samples were hand-set out using varying weight ratios of binder, filler, and fiber. The study's findings demonstrated that the sample with a higher percentage of bagasse fiber demonstrated better mechanical and hydrophobic qualities as compared to the neat and other samples. It is an economical, long-lasting, and environmentally responsible option for a variety of applications.