RSM and Crow Search Algorithm-Based Optimization of Ultrasonicated Transesterification Process Parameters on Synthesis of Polyol Ester-Based Biolubricant

Arumugam, S.; Chengareddy, P.; Tamilarasan, A.; Santhanam, V.

doi:10.1007/s13369-019-03847-1

Cited by 14 publications

(10 citation statements)

References 30 publications

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“…However, studies using an integrated RSM and DF approach for parameters optimization for the heavy metals biosorption process are limited 42 . Recently, Arumugam et al 43 demonstrated an integrated RSM and CSA-based approach to optimizing variables for the synthesis of a biolubricant. The parameters of water jet cutting process have been optimized using hybrid RSM–CSA 44 .…”

Section: Introductionmentioning

confidence: 99%

Experimental study and parameters optimization of microalgae based heavy metals removal process using a hybrid response surface methodology-crow search algorithm

Sultana

Hossain

Mohammed

et al. 2020

Sci Rep

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This study investigates the use of microalgae as a biosorbent to eliminate heavy metals ions from wastewater. The Chlorella kessleri microalgae species was employed to biosorb heavy metals from synthetic wastewater specimens. FTIR, and SEM/XRD analyses were utilized to characterize the microalgal biomass (the adsorbent). The experiments were conducted with several process parameters, including initial solution pH, temperature, and microalgae biomass dose. In order to secure the best experimental conditions, the optimum parameters were estimated using an integrated response surface methodology (RSM), desirability function (DF), and crow search algorithm (CSA) modeling approach. A maximum lead(II) removal efficiency of 99.54% was identified by the RSM–DF platform with the following optimal set of parameters: pH of 6.34, temperature of 27.71 °C, and biomass dosage of 1.5 g L−1. The hybrid RSM–CSA approach provided a globally optimal solution that was similar to the results obtained by the RSM–DF approach. The consistency of the model-predicted optimum conditions was confirmed by conducting experiments under those conditions. It was found that the experimental removal efficiency (97.1%) under optimum conditions was very close (less than a 5% error) to the model-predicted value. The lead(II) biosorption process was better demonstrated by the pseudo-second order kinetic model. Finally, simultaneous removal of metals from wastewater samples containing a mixture of multiple heavy metals was investigated. The removal efficiency of each heavy metal was found to be in the following order: Pb(II) > Co(II) > Cu(II) > Cd(II) > Cr(II).

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Section: Introductionmentioning

confidence: 99%

Experimental study and parameters optimization of microalgae based heavy metals removal process using a hybrid response surface methodology-crow search algorithm

Sultana

Hossain

Mohammed

et al. 2020

Sci Rep

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“…[31] Most of these techniques have certain limitations like complex fitness function, poor search space exploration, premature convergence, and large computing power requirements. [32,33] Also, the precision is dependent on user-dependent parameters. African Buffalo Optimization technique devised by Odili and Kahar in 2015 provides an effective algorithm without all these limitations, still maintaining a real good accuracy level.…”

Section: Figure-11 Ftir Of Wco Biodiesel E Biodiesel Production Yielmentioning

confidence: 99%

Hybrid Response Surface Method African Buffalo Optimization Technique for Ultrasonic Production of Biodiesel from Waste Cooking Oil using Li doped CaO Nan o catalyst

Kumar*,

Gupta

2020

IJITEE

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In the current era, there is an increasing emphasis on green fuels for a clean environment. Authors in this work have tried to devise an innovative method to optimize ultrasonic production of biodiesel from used cooking oil, using composite technique combining Response surface Methodology and African Buffalo optimization. In this research work, heterogeneous catalyst Lithium doped CaO has been obtained from a new natural source by high-temperature thermal decomposition of Musa Balbisiana root ash and tested its Conversion efficiency for conversion of waste cooking oil into methyl esters. It was observed that the catalyst is really effective for the production of biodiesel from even high Free Fatty Acid waste cooking oil. For optimization of production parameters authors have used ABO complemented with RSM to maximize the biodiesel production yield. The maximum biodiesel yield of 96.67% was achieved using ABO which is about 15% higher than provided by RSM which is 81.01%. The highest biodiesel yield of 96.67 % is obtained at 15:1 Molar Ratio with 3.5% catalyst wt. percent, 60 Degree C Temp. in 45 Minutes with an error of 2.5 % in yield prediction by ABO. The work may be utilized by industries and researchers to use ultrasonic reactors optimally to extract better biodiesel volume in very short time instead of presently used slow mechanical stirring tank reactors.

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“…Many standard optimization processes such as simulated annealing (SA), ant colony optimization (ACO), harmony search (HS), and particle swarm optimization (PSO) are available in the published reports. 37,38 Recently, the crow search algorithm (CSA) was developed based on the food hiding capacity of crows (one of the clever birds in nature), which is very attractive for global optimization. 37,39 It is a robust nature-stimulated metaheuristic process for the worldwide optimization of input variables in various research areas.…”

Section: Introductionmentioning

confidence: 99%

“…37,38 Recently, the crow search algorithm (CSA) was developed based on the food hiding capacity of crows (one of the clever birds in nature), which is very attractive for global optimization. 37,39 It is a robust nature-stimulated metaheuristic process for the worldwide optimization of input variables in various research areas.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence‐based super learner approach for prediction and optimization of biodiesel synthesis—A case of waste utilization

Hossain

Sultana

Irfan

et al. 2022

Intl J of Energy Research

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RSM and Crow Search Algorithm-Based Optimization of Ultrasonicated Transesterification Process Parameters on Synthesis of Polyol Ester-Based Biolubricant

Cited by 14 publications

References 30 publications

Experimental study and parameters optimization of microalgae based heavy metals removal process using a hybrid response surface methodology-crow search algorithm

Experimental study and parameters optimization of microalgae based heavy metals removal process using a hybrid response surface methodology-crow search algorithm

Hybrid Response Surface Method African Buffalo Optimization Technique for Ultrasonic Production of Biodiesel from Waste Cooking Oil using Li doped CaO Nan o catalyst

Artificial intelligence‐based super learner approach for prediction and optimization of biodiesel synthesis—A case of waste utilization

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