Mixture designs for quadratic models with constrained experimental regions on ground granulated blast furnace slag concrete

Arina, Faula; Wigena, Aji Hamim; Sumertajaya, I Made; Syafitri, Utami Dyah

doi:10.12988/ams.2018.89128

Cited by 4 publications

(4 citation statements)

References 6 publications

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“…From the plotted FDS result, 0.993, 0.679, and 0.813 were derived for maximum, minimum, and mean standard error, respectively. Furthermore, the condition number of the coefficient matrix of 7.788 was obtained with a G-efficiency of 81.2%, which possesses an inverse relationship with the maximum variance, computed determinant (X'X) −1 of 4.161E + 2, and trace (X'X) −1 of 91.368, and the scaled D-optimality criterion and the I-optimality result of 22.582 and 0.66085 were calculated [46,47].…”

Section: Fraction Of Design Space (Fds)mentioning

confidence: 99%

Optimization and Simulation of Saw Dust Ash Concrete Using Extreme Vertex Design Method

Iro

Alaneme

Milad

et al. 2022

Advances in Materials Science and Engineering

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In this research study, a constrained simplex optimization method was adapted for the evaluation of green concrete’s mechanical property constituting of two-component mixture problem of cement and saw dust ash (SDA), which is a derivative from industrial residue. This experiential research will provide avenue for the recycle and incorporation of waste materials to achieve sustainability and control indiscriminate disposal of waste. The formulated components constrained were realized from the relevant literature studies to obtain the feasible planes in the simplex, and from this computation approach using I-optimality, the design mixture proportions and experimental runs were derived. The experimental results obtained from the laboratory experiments showed a maximum compressive strength of 31.13 N/mm2 with a ratio of 0.875 : 0.125 for cement and SDA, respectively, and a flexural strength of 9.49 N/mm2 with a ratio of 1 : 0 for cement and SDA, respectively; the results were observed to decline linearly with the further addition of SDA. The details generated from laboratory program were utilized for the development of the EVD model through fits statistical evaluation, ANOVA, diagnostic test and influence statistics, numerical optimization, and graphical statistical computations to analyze the datasets and locate the optimal levels of mixture ingredients using desirability function. A desirability score of 0.990 was derived at a mix ratio of 0.89 : 0.110 for the two components, cement and SDA, to produce a maximized compressive strength and a flexural strength of 31.102 N/mm2 and 9.384 N/mm2, respectively. Furthermore, the test of adequacy of the generated EVD model was carried out through simulation and statistical validation exercises using the F-test and student’s t-test, and the outcome signified a good correlation between the EVD model-simulated and actual values with p value >0.05.

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Section: Fraction Of Design Space (Fds)mentioning

confidence: 99%

Optimization and Simulation of Saw Dust Ash Concrete Using Extreme Vertex Design Method

Iro

Alaneme

Milad

et al. 2022

Advances in Materials Science and Engineering

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“…The covariance matrix of split-plot design is not a diagonal matrix. Equation (3) shows the structure of the covariance matrix (𝐕). The matrix 𝐕 consists of 𝜂 = 𝜎 𝛾 2 𝜎 𝜀 2 ⁄ ,which the values cannot define if the response does not exist.…”

Section: Estimation the Covariance Matrix In Spmpvmentioning

confidence: 99%

“…In this case, 𝑛 = 36 runs were specified and the Scheff'e quadratic model was considered. The combination of 𝑏 and 𝑘 be (18, 2), (12,3), and (9,4) in order to have 36 runs in total. The results of ℎ = 1000 times are shown in Table 3.…”

Section: D-optimal Design Of the Steel Slag Concretementioning

confidence: 99%

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D-Optimal Designs for Split-Plot Mixture Process Variable Designs of the Steel Slag Experiment

Arina

Wigena

Fitrianto

et al. 2022

BAREKENG: J. Il. Mat. & Ter.

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The nature of the steel slag concrete experiment followed a mixture process variable (MPV) design. In this study, the concrete is composed of five mixture components, cement, fine aggregate, coarse aggregate, percentage steel slag replaced the fine aggregate and water, and process variable was the size of steel slag. Due to the constraints of the components, the experimental region was not a simplex. The standard MPV of a quadratic model produces large experimental runs. In this paper, D-optimal design with split- plot MPV approach was proposed. The five mixture components were assigned as the subplot factors and the process variable was assigned as the whole plot factors. The main objective of this information is a modified point exchange algorithm was developed to generate the D-optimal design. In addition, the paper investigates related issue namely, the estimation of the covariant matrix in MPV split-plot design. The final design consisted of 18 whole plots each of size 2 and experiment design with 36 observations

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Mechanical strength optimization and simulation of cement kiln dust concrete using extreme vertex design method

Alaneme

Attah

Mbadike

et al. 2021

Nanotechnol. Environ. Eng.

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Mixture designs for quadratic models with constrained experimental regions on ground granulated blast furnace slag concrete

Cited by 4 publications

References 6 publications

Optimization and Simulation of Saw Dust Ash Concrete Using Extreme Vertex Design Method

Optimization and Simulation of Saw Dust Ash Concrete Using Extreme Vertex Design Method

D-Optimal Designs for Split-Plot Mixture Process Variable Designs of the Steel Slag Experiment

Mechanical strength optimization and simulation of cement kiln dust concrete using extreme vertex design method

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