Optimization of mixture proportions by statistical experimental design using response surface method - A review

Journal of Building Engineering, Journal Year: 2020, Volume and Issue: 36, P. 102101 - 102101

Published: Dec. 18, 2020

Language: Английский

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Multi-objective optimization of the mix proportion for dune sand concrete based on response surface methodology

Construction and Building Materials, Journal Year: 2023, Volume and Issue: 366, P. 129928 - 129928

Published: Jan. 5, 2023

Language: Английский

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Effects of aggregate sizes on the performance of laterized concrete

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 3, 2024

Abstract Due to the high costs of traditional concrete materials in Nigeria, such as river sand, there is an increasing demand explore alternative like laterite for fine aggregates. Although abundant its full potential construction industry remains untapped. Previous studies have shown that partially replacing sand with produces competitive strength properties. This research aims validate and extend these findings, evaluating impact different aggregate sizes (12 mm, 20 40 mm) on 10% 25% replacements aggregate. Results revealed percentage increased, compressive, flexural, split tensile strengths decreased. While 0% met required strength, mix fell short. Increasing maximum coarse size led higher strengths, mm exhibiting highest, 12 lowest. Compressive ranged from 22.1 37.6 N/mm 2 , flexural 4.07 5.99 split-tensile 2.93 4.30 . highlights need meticulous design adjustments when using laterite, balancing workability objectives. The developed regression models offer a valuable tool predicting properties based parameters, providing insights optimizing laterized designs across diverse applications supporting sustainable building practices.

Language: Английский

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A comprehensive study on the impact of nano-silica and ground granulated blast furnace slag on high strength concrete characteristics: RSM modeling and optimization

Structures, Journal Year: 2024, Volume and Issue: 62, P. 106160 - 106160

Published: March 11, 2024

In light of the global climate change crisis, imperative to mitigate carbon emission sources is growing in significance. Cement a notable contributor greenhouse gas emissions (GHG) due its industrial manufacturing process, which results release 0.9 kg GHG per kilogram produced. Therefore, reduce by using Ground granulated blast furnace slag (GGBFS) as substitution for cement high strength concrete (HSC). However, use nano silica (NS) nanomaterial HSC improve mechanical and durability characteristics HSC. Besides, Response Surface Methodology (RSM) was adopted assess workability test (slump), compressive (CS), splitting tensile (STS), flexural (FS), modulus elasticity water absorption (WA) blended with 5–20% GGBFS an 5% increment 1–4% NS 1% nanomaterial. CS outcomes were obtained at 7 days, 28 90 days while STS, FS, MOE, WA assessments observed days. From experimental outcomes, Slump found be reduced addition rises Moreover, highest CS, MOE 91.78 MPa, 5.25 5.05 46.06 GPa 10% 3% together respectively. Additionally, embodied decreasing increases Furthermore, response prediction models developed verified ANOVA significance level 95%. The R-Square values ranged from 93 99.50%. It has been concluded that replacement providing optimum therefore, it recommended construction industry.

Language: Английский

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Durability performance of pervious concrete containing rice husk ash and calcium carbide: A response surface methodology approach

Case Studies in Construction Materials, Journal Year: 2021, Volume and Issue: 14, P. e00547 - e00547

Published: April 15, 2021

Pervious concrete is a special type of used for stormwater management due to its high porosity and permeability. However, the large pores in pervious resulted low mechanical strength. Moreover, emissions greenhouse gases from Portland cement (PC) production are contribute climate changes leading change. Calcium carbide waste (CCW) rice husk ash (RHA) were as supplementary cementitious material partially replace by 5%, 10 %, 15 20 %. Response Surface Methodology was design experiments develop models predicting water absorption permeability PC. The properties developed like investigated. most vital property water-permeability. result findings showed that both RHA CCW have negative effect on durability PC, with having worst effect. RSM degree correlation between variables responses. optimized which give best performance combination 0% 5% following properties, 0.96 cm/s 4.338 can be capacity concrete.

Language: Английский

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Compressive Behavior and Durability Performance of High-Volume Fly-Ash Concrete with Plastic Waste and Graphene Nanoplatelets by Using Response-Surface Methodology

Journal of Materials in Civil Engineering, Journal Year: 2022, Volume and Issue: 34(9)

Published: June 28, 2022

Plastic waste (PW) generation continuously increases every year due to the growing population and demand for plastic materials. This situation poses a challenge many countries, including developed ones, on how dispose of PW. Accordingly, PW was utilized in this study replace coarse aggregates partially high-volume fly-ash (HVFA) concrete. However, decreased strength durability To address issue, graphene nanoplatelets (GNPs) were added mitigate negative consequences HVFA concrete's properties. The objective is investigate influences GNP contents deformation Response-surface methodology (RSM) used design optimize series cement mixes achieve most desirable Independent variables included content as partial replacement (0%, 15%, 30%, 45%, 60% by volume), fly ash substitute 20%, 40%, 60%, 80% GNPs additives 0.075%, 0.15%, 0.225%, 0.3%). considered responses concrete unit weight, modulus elasticity (MoE), Cantabro abrasion loss at 300 revolutions. Results showed that weight MoE but increased loss. By contrast, also compressive toughness porosity concrete, while its stiffness porosity. mathematical models predict MoE, resistance significant, with errors less than 6%. An optimized mix achieved replacing 12.44% 24.57% adding 0.279% desirability 100%.

Language: Английский

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Reuse of clay brick and ceramic waste in concrete: A study on compressive strength and durability using the Taguchi and Box–Behnken design method

Construction and Building Materials, Journal Year: 2023, Volume and Issue: 373, P. 130801 - 130801

Published: March 2, 2023

Language: Английский

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Modeling and optimization of photo-fermentation biohydrogen production from co-substrates basing on response surface methodology and artificial neural network integrated genetic algorithm

Bioresource Technology, Journal Year: 2023, Volume and Issue: 374, P. 128789 - 128789

Published: Feb. 24, 2023

Language: Английский

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Multi-scale synergistic modification and mechanical properties of cement-based composites based on in-situ polymerization

Cement and Concrete Composites, Journal Year: 2023, Volume and Issue: 137, P. 104945 - 104945

Published: Jan. 15, 2023

Language: Английский

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Optimizing pervious concrete with machine learning: Predicting permeability and compressive strength using artificial neural networks

Construction and Building Materials, Journal Year: 2024, Volume and Issue: 443, P. 137619 - 137619

Published: Aug. 7, 2024

This study makes a significant contribution to the field of pervious concrete by using machine learning innovatively predict both mechanical and hydraulic performance. Unlike existing methods that rely on labor-intensive trial-and-error experiments, our proposed approach leverages multilayer perceptron network. To develop this approach, we compiled comprehensive dataset comprising 271 sets 3,252 experimental data points. Our methodology involved evaluating 22,246 network configurations, employing Monte Carlo cross-validation over 20 iterations, 4 training algorithms, resulting in total 1,779,680 iterations. results an optimized model integrates diverse mix design parameters, enabling accurate predictions permeability compressive strength even absence data, achieving R² values 0.97 0.98, respectively. Sensitivity analyses validate model's alignment with established principles behavior. By demonstrating efficacy as complementary tool for optimizing designs, research not only addresses current methodological limitations but also lays groundwork more efficient effective approaches field.

Language: Английский

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