Response Surface Grey Relational Analysis On The Manufacturing of High Grade Biomedical Ti-13Zr-13Nb

Abifarin, Johnson Kehinde; Fidelis, Fredah Batale; Abdulrahim, Moshood Yemi; Oyedeji, Elijah Oyewusi; Nkwuo, Tochukwu; Prakash, Chander

doi:10.21203/rs.3.rs-1225030/v1

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…GRA technique is employed to assist the Taguchi design technique because the engine performance conditions were complex to optimize due to incomplete and uncertain information present in this study. GRA has been proven to mitigate this very challenge (Javed 2019;Javed et al, 2019;Abifarin, 2021;Abifarin et al, 2022a).…”

Section: Introductionmentioning

confidence: 99%

Modeling and Grey Relational Multi-response Optimization of Chemical Additives and Engine Parameters on Performance Efficiency of Diesel Engine

Abifarin

Ofodu

2022

IJGS

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Singular optimization of engine conditions for better engine performance have been studied extensively. However, in the practical sense, more than one performance characteristics are essential in the optimization of engine conditions. The current study investigates the effect, optimization, and modeling of engine conditions on multi-characteristics of a single cylinder-dual direct injection-water cooled diesel engine with the help of Taguchi-grey relational and regression analyses. The engine conditions employed are engine load, hydrogen, multi-walled carbon nanotubes (MWCNTs), ignition pressure, and ignition timing, at four different levels. The engine performance characteristics analyzed were brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), hydrocarbons (HC), nitrogen oxide (NOx), carbon monoxide (CO), and carbon dioxide (CO2). The results showed that there was a similar behavioral pattern of the effect of engine conditions on engine performance, except for ignition timing. The optimal settings for better engine performance were obtained at 25% engine load, 20% hydrogen, 50 ppm MWCNTs, 220 bar ignition pressure, and 21 obTDC ignition timing. Interestingly, the discovered optimal did not fall within the considered experimental runs, however, the predicted optimal engine performance was within 95% confidence bounds. It is recommended that the experimental work based on the obtained optimal settings should be conducted to elucidate the efficacy of the confirmation analysis. The analysis of variance showed that the engine load was the most significant factor on the overall engine performance, having a contribution of 71.47%, followed by hydrogen and MWCNTs. Also, the ignition pressure and timing were not significant on the overall engine performance, which showed a need to place more attention on the significant factors for better engine performance. The mathematical and graphical modeling showed the efficacy of the design analysis, while the interaction plots showed broader detailed factor settings for better engine performance.

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Section: Introductionmentioning

confidence: 99%

Modeling and Grey Relational Multi-response Optimization of Chemical Additives and Engine Parameters on Performance Efficiency of Diesel Engine

Abifarin

Ofodu

2022

IJGS

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“…It is not blurred that several optimization techniques only solve a problem of optimization of a singular performance characteristic, such as Taguchi design technique, response surface methodology (RSM), etc. However, Grey relational analysis (GRA) has been proven to be effective in singularizing as many performance characteristics as possible for multi-objective optimization [17][18][19][20][21][22][23]. Hence, in this study, RSM is assisted by GRA to conduct multi-objective optimization analysis on consistency index (K), flow behavior index (n), yield point (YP), and plastic viscosity (PV) of water-based drilling muds.…”

Section: Introductionmentioning

confidence: 99%

Computational Analysis on the Selection of High Efficient Biodegradable-PolymerBased Nanofluids for Drilling Mud

2022

JBTS

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Proper and optimal selection of processing conditions in the production of nanofluids for drilling muds is critical. In this study, grey relational analysis (GRA) was employed as the computation analysis assisted by mathematical and graphical modeling to determine some optimal processing parameters to produce highly efficient biodegradable-polymer-based nanofluids for drilling muds. The multiple performance characteristics analyzed are consistency index (K), flow behavior index (n), yield point (YP), and plastic viscosity (YP). The obtained results revealed that 0.6 wt% starch, 1 wt% nanoparticles and 45 min. ultrasonic time are the optimal settings to be considered in the production of highly efficient nanofluids for drilling muds. The graphical modeling and ANOVA results also revealed that the experimental setups were influenced by some significant and unconsidered external factors in drilling fluids formulation. It is recommended that deeper study should be conducted to identify and employ some other unconsidered factors that may be responsible on the performance of drilling muds.

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Employment of probability-based multi-response optimization in high voltage thermofluids

Ofodu¹,

Abifarin²

2022

Vojnotehnički glasnik

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Introduction/purpose: Researchers of fluids for high voltage engineering application always experience problems when selecting and recommending specific fluids suitable for high voltage application. This is due to the dual functionality of fluids required for high voltage equipment. Methods: This study introduced and employed a probability-based multi-objective optimization technique in the selection of high voltage thermofluids. Beneficial and unbeneficial preferable probability utility indexes were employed based on the desired properties of oils. Results: It was shown that the nanofluid with 0.6 wt% Al2O3 is the most promising candidate for high voltage equipment compared to other produced fluids considered. It is also noteworthy to state that coconut oil exhibited better performance efficiency compared to standard oil. This study also identifies that the produced Jatropha oil was inadequate for high voltage equipment. Conclusion: In conclusion, a preliminary study essential for final usage of 0.6 wt% Al2O3 nanofluids and coconut oil for high voltage equipment is recommended as well as the improvement of the performance characteristics of Jatropha oil for usage in high voltage equipment.

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Response Surface Grey Relational Analysis On The Manufacturing of High Grade Biomedical Ti-13Zr-13Nb

Cited by 4 publications

References 18 publications

Modeling and Grey Relational Multi-response Optimization of Chemical Additives and Engine Parameters on Performance Efficiency of Diesel Engine

Modeling and Grey Relational Multi-response Optimization of Chemical Additives and Engine Parameters on Performance Efficiency of Diesel Engine

Computational Analysis on the Selection of High Efficient Biodegradable-PolymerBased Nanofluids for Drilling Mud

Employment of probability-based multi-response optimization in high voltage thermofluids

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