Strength evaluation of eco-friendly concrete using Taguchi method

Umar, Mustafa; Gajalakshmi, P.; Revathy, J.

doi:10.1016/j.matpr.2019.11.136

Cited by 11 publications

(6 citation statements)

References 5 publications

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“…On the basis of some preliminary test results, 12 test data points and the associated limits on space were adopted (Figure 1), and two categorical variables were considered ((w/b)values of 0.25 and 0.40). e analytically fitted response (12 terms) function of this DOE could be formulated for the three process variables (equation ( 1)) and replicated for each test category [20,30,37]. On the other hand, the RSD system required the formulation of a regression formula that would be used to describe the response-dependent surface (y) as a function of the independent variables [1].…”

Section: Discussionmentioning

confidence: 99%

“…e response surface design (RSD) of this technique was also effectively employed to predict and optimize the behavior of a geopolymer composite that contained recycled muck, rice-husk ash, Earth diatomite, MK, and limestone (LS) [28,29]. Furthermore, the Taguchi DOE approach was successfully used to optimize a green-concrete mixture that incorporated recycled aggregate and FA [30]. We need to note that DOE was also used to develop cementitious composites that incorporated various components of micro-and nanosilica and polymeric fibers [31].…”

Section: Introductionmentioning

confidence: 99%

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Optimization of Arabian‐Shield‐Based Natural Pozzolan and Silica Fume for High‐Performance Concrete Using Statistical Design of Experiments

Abbas

Khan

2021

Advances in Civil Engineering

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In this study, the optimum dosages of silica fume (SF) and natural pozzolan (NP) were experimentally and statistically assessed for the best strength and durability properties of high-performance concrete (HPC). SF and NP were used as partial replacement Portland cement (PC) by up to 12 and 25 wt.%, respectively. Additionally, the prediction models based on second-level factorial (SLF) and response surface design (RSD) were formulated to estimate the HPC properties and their validation. The SLF-based model was further employed to investigate the significance and interactions of the PC, SF, and NP blends. The 28-day strength of the blended-cement HPC with a water-to-binder ratio w / b of 0.25 was generally higher than that of the control concrete. The positive synergy of PC–NP–SF was also observed in the HPC permeability. The paired t -test of the mean square error (MSE) of the SLF- and RSD-based models revealed that the MSE of the former was notably less than that of the latter. These results established the superiority of the SLF-based model over the RSD-based model. Therefore, the SLF-based model was further employed to investigate the importance of various binders.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimization of Arabian‐Shield‐Based Natural Pozzolan and Silica Fume for High‐Performance Concrete Using Statistical Design of Experiments

Abbas

Khan

2021

Advances in Civil Engineering

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“…Recently, a research method combining an orthogonal order table and various analysis methods has been widely used. In many cases, it was found that the data obtained from the orthogonal array table and the results obtained from the full factor experiment were not significantly different [37][38][39][40].…”

Section: Data Expansion By Means Of An Orthogonal Array Experiments Dementioning

confidence: 95%

The Experimental Process Design of Artificial Lightweight Aggregates Using an Orthogonal Array Table and Analysis by Machine Learning

Wie

Lee

et al. 2020

Materials

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The purpose of this study is to experimentally design the drying, calcination, and sintering processes of artificial lightweight aggregates through the orthogonal array, to expand the data using the results, and to model the manufacturing process of lightweight aggregates through machine-learning techniques. The experimental design of the process consisted of L18(3661), which means that 36 × 61 data can be obtained in 18 experiments using an orthogonal array design. After the experiment, the data were expanded to 486 instances and trained by several machine-learning techniques such as linear regression, random forest, and support vector regression (SVR). We evaluated the predictive performance of machine-learning models by comparing predicted and actual values. As a result, the SVR showed the best performance for predicting measured values. This model also worked well for predictions of untested cases.

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“…Marine clay has also been employed as a cement alternative to achieve sustainable concrete 23 , 24 . Bio-organic materials were utilized to manufacture PCMs 25 , 26 , while waste-derived fly ash was employed in the production of environmentally-friendly binders for the construction of sustainable buildings 27 , 28 . Moreover, making green bricks through geopolymerization and using slate tailings was also addressed in the literature 29 .…”

Section: Introductionmentioning

confidence: 99%

Multiple objective energy optimization of a trade center building based on genetic algorithm using ecological materials

Kabiri,

Maftouni

2024

Sci Rep

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It is crucial to optimize energy consumption in buildings while considering thermal comfort. The first step here involved an EnergyPlus simulation on a trade center building located in Tehran, Bandar Abbas, and Tabriz, Iran. A multi-objective optimization was then performed based on non-dominated sorting genetic algorithm II (NSGA-II) in jEPlus + EA to establish the building in the selected city where would benefit the most from implementing the radiant ceiling cooling system. Efforts were undertaken to choose environmentally-friendly materials. The final solution by Pareto charts resulted in a 52% reduction in energy consumption, a 37.3% decrease in cooling load, and a 17.4% improvement in comfort hours compared to the original design. Annual emission of greenhouse gas reduced as 167.67 tone of CO2 equivalent emission, 25.77 ton of CH4, and 0.2 ton of NO2. The mentioned algorithm was conducted for the first time on a trade center, including a DOAS system and radiant ceiling cooling system. Simultaneously, the environmental-friendly materials were dealt with. The procedure holds significant relevance for the design and optimization of buildings in Iran, especially wherever the climate is hot and humid. This approach offers advantages to the environment by reducing the impact on energy resources and utilizing environmentally-friendly materials.

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Strength evaluation of eco-friendly concrete using Taguchi method

Cited by 11 publications

References 5 publications

Optimization of Arabian‐Shield‐Based Natural Pozzolan and Silica Fume for High‐Performance Concrete Using Statistical Design of Experiments

Optimization of Arabian‐Shield‐Based Natural Pozzolan and Silica Fume for High‐Performance Concrete Using Statistical Design of Experiments

The Experimental Process Design of Artificial Lightweight Aggregates Using an Orthogonal Array Table and Analysis by Machine Learning

Multiple objective energy optimization of a trade center building based on genetic algorithm using ecological materials

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