Optimization and modeling of synthesis parameters of neodymium(III) bromide by dry method using full factorial design analysis

Bounouri, Yassine; Berkani, Madjid; Zamouche, Abdelmalek; Rycerz, L.

doi:10.1016/j.arabjc.2017.05.003

Cited by 10 publications

(7 citation statements)

References 24 publications

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“…The present study used a 2 4 FFD where two replications at each point were applied to determine the significant factors in the fabrication of an NBC ceramic membrane. The corner point of experiments was replicated to determine the experimental error 24, 25. The factors involved were the particle size of the sawdust ( A ), the percentage of sawdust ( B ), the amount of binder ( C ), and the sintering temperature ( D ), acting as independent variables.…”

Section: Methodsmentioning

confidence: 99%

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Natural Ball Clay Ceramic Membrane Fabrication Using Full Factorial Design for Screening

et al. 2022

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A screening design is used to assess a large number of process or design parameters to identify the most influential factors that affect the process performance. This study investigates factors affecting the fabrication of natural ball clay (NBC) ceramic membranes using the 2 4 full factorial design (FFD) with two replications at each point. The factors studied were: particle size of the sawdust, percentage of sawdust, amount of binder, and sintering temperature. The FFD study results indicated that the sawdust particle size and the percentage of sawdust had a positive impact on the porosity and mechanical strength of the NBC ceramic membrane. This demonstrates the importance of performing a screening experiment prior to an extensive investigation of certain factors such as in the optimization studies.

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Section: Methodsmentioning

confidence: 99%

“…The vertical line in the Pareto charts represents the minimum statistically significant effect at a confidence level of 95 %. The effects are statistically significant at t i > 2.11 [24,39]. Based on the Pareto charts (Fig.…”

Section: Pareto Chartsmentioning

confidence: 99%

Natural Ball Clay Ceramic Membrane Fabrication Using Full Factorial Design for Screening

et al. 2022

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“…A mathematical model that shows the impact of the experimental factors on the reaction yield is found using this analysis method. This model helps to analyze the main and interaction effects of factors [29][30][31]. A full factorial design is a widely used experimental design with each factor at two levels (low and high).…”

Section: Factorial Designmentioning

confidence: 99%

Application of Full Factorial Design Method for Optimization of Heavy Metal Release from Lead Smelting Slag

2021

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Lead-acid batteries are commonly used as power sources for critical operations in the world. They find application in air-traffic control towers, uninterruptible power supplies (UPS), railroad crossings, military installations, hospitals, and weapons systems. Lead-acid batteries are also known as automotive batteries and industrial batteries. Lead-acid batteries consist of large amounts of lead, sulphuric acid, and plastics. The acid is tremendously irritant and a carrier for soluble information. The lead must control because of a range of adverse health effects. Thus, a collectible system that is easily accessible for waste batteries is needed. In this paper, a sustainable model is proposed for the leaching of lead-acid battery slag. The aim is to optimize the leaching of lead-acid batteries slag with natural materials. The leaching characteristic of the lead smelting slag produced using sepiolite and illite. A 23 full factorial design model is used to investigate the combination of the effect of variable factors.

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“…This technique is used to reduce the number of experiments, time and overall process cost with a better response. The importance of this method is shown by different studies using experimental designs …”

Section: Full Factorial Designsmentioning

confidence: 99%

Modeling the effective thermal conductivity of nanofluids using full factorial design analysis

Grine

Benhamza

2019

Heat Trans. Asian Res.

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In this paper, a full factorial design analysis is proposed for predicting nanofluid thermal conductivity ratio (TCR) as well as determining the effects of critical factors and their interactions. A statistical design of experiment approach with three variables (volume fraction, temperature, and nanoparticle diameter) at two levels is carried out. Three types of oxide‐water nanofluids (Al2O3‐water, CuO‐water, and TiO2‐water) are used to evaluate the effectiveness of the proposed mathematical model. The significance and adequacy of the regression model were evaluated by the analysis of variance. The predicted model has a root mean square error equals to 0.0074, R2 = 0.99, and P < .0013, thus showing good results compared to a set of experimental data as well as other mathematical model results. The results illustrate that the TCR of metallic oxide nanoﬂuids increases with temperature and nanoparticles volume fraction but decreases when nanoparticle size intensiﬁes. Furthermore, it is found that the nanoparticles volume fraction has a great impact on the nanoﬂuids thermophysical properties. Finally, the obtained results confirm that the proposed model is considerably accurate and capable of predicting nanoﬂuids thermal conductivity and that it can be used with ease as an alternative to many other models.

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Optimization and modeling of synthesis parameters of neodymium(III) bromide by dry method using full factorial design analysis

Cited by 10 publications

References 24 publications

Natural Ball Clay Ceramic Membrane Fabrication Using Full Factorial Design for Screening

Natural Ball Clay Ceramic Membrane Fabrication Using Full Factorial Design for Screening

Application of Full Factorial Design Method for Optimization of Heavy Metal Release from Lead Smelting Slag

Modeling the effective thermal conductivity of nanofluids using full factorial design analysis

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