Response surface methodology-based parameter optimization of single-cylinder diesel engine fueled with graphene oxide dosed sesame oil/diesel fuel blend

Şimşek, Süleyman; Uslu, Samet; Şimşek, Hatice

doi:10.1016/j.egyai.2022.100200

Cited by 30 publications

(3 citation statements)

References 28 publications

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“…When similar studies in the literature are examined, it is seen that the results obtained are close to the literature [47,48,51]. In a study by Şimşek et al [52] using RSM, they stated that the maximum error between the experimental results and the optimum results was 4.96%. In the results obtained, they stated that the RSM model could successfully model a singlecylinder diesel engine.…”

Section: Smoke (%)supporting

confidence: 77%

Combined application of ANN prediction and RSM optimization of performance and emission parameters of a diesel engine using diesel-biodiesel-propanol fuel blends

KARABACAK,

ŞİMŞEK,

ATİK

2023

International Advanced Researches and Engineering Journal

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In this study, the performance and exhaust emission parameters of a diesel engine operating with diesel/biodiesel/propanol fuel mixtures were estimated by Artificial Neural Network (ANN). In addition, the parameters estimated by ANN were tried determining the optimum operating parameter by using Response Surface Methodology (RSM). In the experimental study, propanol was added in 3 different ratios (5%, 10% and 20%) into 100% diesel, 80% diesel and 20% biodiesel fuel blends. In addition, engine tests, were made at 5 different engine speeds with 400 min-1 intervals between 1000 min-1 and 2600 min-1 revolutions at full load. In addition, HC (Hydrocarbon), CO (Carbon Monoxide), NOX (Nitrogen oxides) and Smoke emissions were measured during in the working. ANN model was developed for estimation of engine output parameters depending on fuel mixture ratios and engine speed. In the ANN results, the regression coefficients (R2) of the proposed model were found to be between 0.924 and 0.99. When the obtained ANN results were compared with the experimental results, it was seen that the maximum mean relative error (MRE) was 6.895%. It has been shown that the applied model can predict with a low error rate. The RSM results showed that the optimum operating parameters were 2034-min-1 engine speed, 74.667% diesel, 11.36% biodiesel and 15% propanol fuel mixture. As a result of the study, it was seen that RSM supported ANN is a good method for estimating diesel engine parameters working with diesel/biodiesel/propanol mixtures and determining optimum operating parameters.

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Section: Smoke (%)supporting

confidence: 77%

Combined application of ANN prediction and RSM optimization of performance and emission parameters of a diesel engine using diesel-biodiesel-propanol fuel blends

KARABACAK,

ŞİMŞEK,

ATİK

2023

International Advanced Researches and Engineering Journal

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“…The measured optimal response values for BP (3.54 kW), BTE (28.23%), BSFC (0.38 kg/kWh), CO (0.38 kg/kWh), UHC (28.23%), CO 2 (0.0231% vol), and NO (4.2559 ppm). S Simsek et al (2022) conducted an experiment to examine the effects of varying concentrations of graphene oxide (GO) on CI engine characteristics while using a 30% sesame oil (SO) + 70% diesel fuel combination with RSM to establish optimum operating parameters at various engine loads. Under optimal circumstances, the responses were 1,746.77 W, 968.73 g/kWh, 259.8 °C, 0.0603%, 23.13 ppm, and 185.61 ppm for power, BSFC, EGT, CO, HC, and NOx, respectively.…”

Section: Introductionmentioning

confidence: 99%

Performance characteristics optimization of CRDI engine fuelled with a blend of sesame oil methyl ester and diesel fuel using response surface methodology approach

2023

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The primary aim of this experiment was to use response surface methodology (RSM) to optimize engine operating parameters for optimal performance and emission characteristics of a common rail direct injection (CRDI) diesel engine fuelled with sesame oil methyl ester (SOME)/diesel blends. The experiments were carried out on a water-cooled common rail direct injection engine with a 4-stroke, single-cylinder connected to an eddy current dynamometer. As input variables, the SOME% (0%–20%), fuel injection pressure (FIP) (500–600 bar), EGR rates (0%–14%), and engine load (0–12 kg) were used. The optimization method is utilized to maximize brake thermal efficiency (BTE) while minimizing BSFC, CO, HC, and NOx emissions. Experimental research data were used to create the RSM model through DoE (Design of experiments). The most relevant factors impacting the responses were identified using an ANOVA analysis. According to the optimization findings, the engine’s optimum working parameters were found to be a 20% SOME ratio, 577.5 bar FIP, 5.26% EGR rates, and 5.12 kg engine load. Under these operating circumstances, the optimal responses were determined to be 18.92% BTE, 0.3705 kg/kWh BSFC, 0.03190% vol. CO, 13 ppm HC, and 447.5 ppm NOx emission. At the same time, R2 values were 96.35%, 87.54%, 91.57%, 95.87%, and 93.73% for BTE, BSFC, CO, HC, and NOx respectively.

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“…The recorder results confirmed that the unburned hydrocarbon and carbon dioxide could be reduced by 50% by increasing the fuel Cetane number. A new trend for optimizing the engine response parameters such as BTE and engine emissions with varying operating parameters has been studied by using response surface methodology [15][16][17] . By utilizing these techniques, the number of laboratory trails was dramatically reduced and maximum engine performance was achieved.…”

mentioning

confidence: 99%

Solubility and stability enhancement of ethanol in diesel fuel by using tri-n-butyl phosphate as a new surfactant for CI engine

El-Sheekh,

El-Nagar,

ElKelawy

et al. 2023

Sci Rep

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Nowadays, researchers are very interested in improving the stability and solubility of blending diesel fuel with a high percentage of ethanol. As a result, the goal of this paper was to find a way to use the surfactant of Tri-n-butyl phosphate (TBP) substance to blend ethanol with diesel fuel to a level of 40%. Diesel fuel is mixed with ethanol in volumetric proportions of 10%, 20%, 30%, and 40%, as well as a tiny amount of TBP from 1 to 4%. The prepared blends were the subject of an experiment evaluation by fueling a direct injection diesel engine. This engine is a water-cooled, commercial diesel engine, single cylinder, and four-stroke with 12 kW maximum power. The four blends were evaluated as clean fuel mixtures of 10% ethanol/90% diesel/1% TBP, 20% ethanol/80% diesel/2% TBP, 30% ethanol/70% diesel/3% TBP, and 40% ethanol/60% diesel/4% TBP. As the starting fuel, we used 100% diesel to compare the results. The engine’s output and emissions have been measured at various engine loads and constant speeds of 1500 rpm. According to the data gathered, even when the percentage of ethanol was increased to 40%, neither the base fuel nor the engine BTE changed significantly. The engine exhaust gas temperature was found to decrease slightly when the proportion of ethanol was increased. When bioethanol is increased to 40% of the base volume, it causes an increase in the combustion of unburned hydrocarbons and CO emissions. However, when the percentage of ethanol was increased from 100% diesel to the base fuel to 40%, CO2 emissions decreased, and O2 emissions slightly increased.

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Response surface methodology-based parameter optimization of single-cylinder diesel engine fueled with graphene oxide dosed sesame oil/diesel fuel blend

Cited by 30 publications

References 28 publications

Combined application of ANN prediction and RSM optimization of performance and emission parameters of a diesel engine using diesel-biodiesel-propanol fuel blends

Combined application of ANN prediction and RSM optimization of performance and emission parameters of a diesel engine using diesel-biodiesel-propanol fuel blends

Performance characteristics optimization of CRDI engine fuelled with a blend of sesame oil methyl ester and diesel fuel using response surface methodology approach

Solubility and stability enhancement of ethanol in diesel fuel by using tri-n-butyl phosphate as a new surfactant for CI engine

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