The structural performance of fiber-reinforced concrete beams with nanosilica

Matéria (Rio de Janeiro), Год журнала: 2024, Номер 29(3)

Опубликована: Янв. 1, 2024

This study explores the enhanced performance of nano-silica-enriched concrete beams, with a focus on effects including steel fibers. A thorough examination was conducted eighteen finely constructed each three thousand millimeters long and 150 × 250 millimeter cross-section. study's main goal to evaluate how fibers affected these beams' mechanical characteristics. number static loading tests were used carefully examine specimens' structural strength. The overall effectiveness beams assessed by using key parameters as indicators, such first crack load, yield load deflection, ultimate deflection ductility, ductility ratio, energy ratio. findings extensive testing clearly show that adding contain nano silica improves their significantly. enhancement regularly seen in important areas behavior, proving without shadow doubt beneficial effect fiber incorporation

Язык: Английский

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Enhancing the sustainability, mechanical and durability properties of recycled aggregate concrete using calcium-rich waste glass powder as a supplementary cementitious material: An experimental study and environmental assessment

Sustainable Chemistry and Pharmacy, Год журнала: 2025, Номер 44, С. 101985 - 101985

Опубликована: Март 8, 2025

Язык: Английский

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Investigations on physical, mechanical and metallurgical characteristics of ZK60/ZrB2 composites produced by stir casting route

Matéria (Rio de Janeiro), Год журнала: 2024, Номер 29(3)

Опубликована: Янв. 1, 2024

Язык: Английский

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An SPSS and CNN modelling based quality assessment using ceramic materials and membrane filtration techniques

Matéria (Rio de Janeiro), Год журнала: 2025, Номер 30

Опубликована: Янв. 1, 2025

ABSTRACT This study investigates the treatment of Sago Wastewater (SW) using natural materials and α-Al2O3 ceramic membranes for filtration. SW samples were collected from influent effluent sago industries in Salem Namakkal districts, Tamil Nadu, as well nearby open wells bore wells. The physico-chemical parameters, including pH, color, turbidity, TSS, TDS, TS, DO, COD, BOD, analyzed. High levels BOD (1800–1550 mg/L) COD (3400–4150 observed, reflecting high organic content effluents. Post-filtration, pH values ranged 6.9 to 7.3, with within permissible limits set by TNPCB. Toxic substances reduced 52% 96%. Statistical analysis multiple linear regression showed an R2 0.98 predicted phase 0.9 phase, while CNN yielded 0.99 MSE 5.9 after 2000 epochs. filtration process significantly reduces toxins, making treated water suitable irrigation purposes.

Язык: Английский

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Estimating punching performance in fiber-reinforced polymer concrete slabs utilizing machine learning and gradient-boosted regression techniques

Matéria (Rio de Janeiro), Год журнала: 2025, Номер 30

Опубликована: Янв. 1, 2025

ABSTRACT The study explores the perforating shear performance of Fiber-Reinforced Polymer (FRP) concrete blocks using machine learning techniques like Gradient-Boosted Regression Trees (GBRT), k-nearest Neighbours (KNN), and Lasso Regression. It aims to predict structural integrity FRP under conditions based on experimental data. models were assessed Coefficient Determination (R2), Root Mean Square Error (RMSE), Absolute (MAE). GBRT demonstrated superior during training with an R2 0.9786, RMSE 52.75, MAE 34.12, indicating strong predictive accuracy minimal error. outperformed KNN (R2 = 0.92, 83.91, 45.71) 0.71, 162.45, 115.83). In validation, again excelled 0.93, 76.23, 58.46, confirming its robustness in generalizing unseen showed lower validation 0.86), increased error values, while lagged further behind 0.681, 185.23, 138.34). consistently traditional regression methods, highlighting potential for more accurate reliable analysis slabs.

Язык: Английский

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Revolutionizing iron texture analysis: the role of cold reduction and rolling directions through machine learning insights

Matéria (Rio de Janeiro), Год журнала: 2025, Номер 30

Опубликована: Янв. 1, 2025

ABSTRACT This study employs machine learning (ML) to analyze the melting and reconsolidation behaviors of iron, emphasizing influence cold reduction ratios rolling sequences. Five samples with varied patterns were examined. Findings indicate that when ratio exceeds 65%, coordinated minimally impacts crystallographic consistency. Texture formation remains largely unaffected during short-duration annealing. However, extended annealing prompts irregular grain growth, altering crystal orientation. Sheets rolled in alignment their initial condition exhibit consistency similar conventionally cold-melted pure iron after prolonged Key parameters influencing material performance evaluated, revealing temperature as most significant factor (5.94), followed by direction order (1.46), while hanging period had minimal impact (1.02). ML models employed predict Goss angle expansion using cold-rolling parameters. approach demonstrates potential texture evolution offering valuable insights for optimizing industrial practices.

Язык: Английский

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Pioneering the next frontier in construction with high-strength concrete infused by nano materials

Matéria (Rio de Janeiro), Год журнала: 2025, Номер 30

Опубликована: Янв. 1, 2025

ABSTRACT The advancement of nano engineering technology plays a major role in the cementitious materials especially graphene oxide which got high attention. In this research addition oxide, silica fume and flyash with various mix proposition partial replacement cement have be investigated for mechanical properties concrete is macro level (workability, strength behavior, flexural water absorption, porosity, durability) micro structural analysis (SEM analysis). Polycarboxylate ethers are used as super plasticizers to offset decrease, substantially improves concrete’s workability. Silica fly ash utilized fixed 10% ash, by weight, enhance concrete. After conducting tests, it has been determined that optimal combination involves both ordinary Portland cement, particularly grade 53, resulting superior outcomes. Addition its varying percentages from 0, 0.01, 0.02, 0.03, 0.04 0.05% Graphene find optimum percentage GO weight obtain strength. grapheme replaced 0.04%.

Язык: Английский

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Effective utilization of green synthesized zinc oxide nanoparticles for sequestering methylene blue dye from pharmaceutical industry

Matéria (Rio de Janeiro), Год журнала: 2025, Номер 30

Опубликована: Янв. 1, 2025

ABSTRACT In order to improve the removal of methylene blue dye from water, zinc oxide nanoparticles (ZnO NPs) were synthesized utilizing Annona squamosa leaf extract as a green reducing agent. Particle size analysis (PSA), FT-IR, XRD, FE-SEM, and EDX) among methods used characterize ZnO NPs. Following batch adsorption tests, effectiveness these in removing was evaluated. Many factors carefully examined, including pH, temperature, initial focus, adsorbent dosage. The outcomes demonstrated strong agreement between second-order kinetics process Langmuir isotherm model. is exothermic, according thermodynamic study, which also estimated important parameters like ΔH°, ΔS°, ΔG°. reached up 99% under ideal conditions, included contact period 60 minutes, an dosage 0.1 g, concentration 80 ppm, pH 8.0. Consequently, produced NPs show great promise efficient for dye, especially when it comes treating pharmaceutical wastewater.

Язык: Английский

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Evaluation of self compacting concrete performance incorporated with presoaked lightweight aggregates

Matéria (Rio de Janeiro), Год журнала: 2025, Номер 30

Опубликована: Янв. 1, 2025

Abstract The study aims the performance of presoaked light expanded clay aggregate (LECA) and fly ash (FAA) as partial replacement river sand in self compacting concrete (SCC). On a volume basis, LECA FAA partially replace sand. are for 24 hours before casting SCC. water retained lightweight aggregates (LWAs) pores acts an internal curing reservoir. SCC workability characteristics, including flowability, filling passing capabilities, resistance to segregation, bleeding, were evaluated using slump cones, U-boxes, L-boxes, V-Funnels, J-ring tests. Addition reduces also attain good strength durability characteristics such sulphate attack, acid attack conducted various durations like 7, 28, 56, 90, 180 days. Further, bond accelerated corrosion tests conducted. From all mechanical on with by 15% fine shows more beneficial effect strength, microstructural properties than those demonstrated control mix concrete.

Язык: Английский

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Improving forecasting of concrete strength using advanced machine learning methods

Matéria (Rio de Janeiro), Год журнала: 2025, Номер 30

Опубликована: Янв. 1, 2025

Abstract This study presents an improved technique that uses many machine-learning models to estimate the compressive strength of concrete. The goal project is increase precision predictions based on age and composition concrete mixes. Cement, fly ash, water, superplasticizer, coarse fine aggregate, sample are among materials. Megapascals (MPa) used quantify strength. To determine connections between mix proportions, age, strength, a variety blends were examined. Machine learning techniques including Random Forest, XGBoost, AdaBoost, Bagging, Support Vector Regression, Linear Regression used. efficiency model was assessed using performance indicators such as accuracy, R-squared (R2), Mean Absolute Error (MAE), Squared (MSE). With MAE 2.2, MSE 10.5, R2 0.94, MAPE 8.5, RMSE 3.25, accuracy 0.92, XGBoost (optimized) performed best. noticeably better than others, highlighting how machine may improve optimize concrete, thus promoting fields materials science civil engineering.

Язык: Английский

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