Environment-friendly novel fuel additives: Investigation of the effects of graphite nanoparticles on performance and regulated gaseous emissions of CI engine

Ahmed, Ammar; Shah, Asad Naeem; Azam, Ali; Uddin, Ghulam Moeen; Ali, Mohammad; Hassan, Saima; Ahmed, Haseeb; Aslam, Touqeer

doi:10.1016/j.enconman.2020.112748

Cited by 52 publications

(13 citation statements)

References 40 publications

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“…Where, x i are the known physical parameters; ∅ y and ∅ x i are errors or uncertainties in y and x i respectively. Putting the error percentages from Table 3 in equation (1), the uncertainty of the experiment was calculated as follow; 51…”

Section: Experimental Workmentioning

confidence: 99%

Application of ANN to predict performance and emissions of SI engine using gasoline-methanol blends

et al. 2021

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The deployment of methanol like alternative fuels in engines is a necessity of the present time to comprehend power requirements and environmental pollution. Furthermore, a comprehensive prediction of the impact of the methanol-gasoline blend on engine characteristics is also required in the era of artificial intelligence. The current study analyzes and compares the experimental and Artificial Neural Network (ANN) aided performance and emissions of four-stroke, single-cylinder SI engine using methanol-gasoline blends of 0%, 3%, 6%, 9%, 12%, 15%, and 18%. The experiments were performed at engine speeds of 1300–3700 rpm with constant loads of 20 and 40 psi for seven different fractions of fuels. Further, an ANN model has developed setting fuel blends, speed and load as inputs, and exhaust emissions and performance parameters as the target. The dataset was randomly divided into three groups of training (70%), validation (15%), and testing (15%) using MATLAB. The feedforward algorithm was used with tangent sigmoid transfer active function (tansig) and gradient descent with an adaptive learning method. It was observed that the continuous addition of methanol up to 12% (M12) increased the performance of the engine. However, a reduction in emissions was observed except for NOx emissions. The regression correlation coefficient (R) and the mean relative error (MRE) were in the range of 0.99100–0.99832 and 1.2%–2.4% respectively, while the values of root mean square error were extremely small. The findings depicted that M12 performed better than other fractions. ANN approach was found suitable for accurately predicting the performance and exhaust emissions of small-scaled SI engines.

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Section: Experimental Workmentioning

confidence: 99%

Application of ANN to predict performance and emissions of SI engine using gasoline-methanol blends

et al. 2021

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“…A small amount of Fe atoms in the reaction zone can enhance the combustion rate of CO. In addition, FFO particles develop condensation sites in reaction zone as a result in oxidation of CO to CO2, hence the decrease in CO formation [33]. B30 blend with FFO nanoparticles gave minimum CO emission corresponding to other nanofuels.…”

Section: Carbon Monoxide (Co) Emissionmentioning

confidence: 99%

An Experimental Investigation on the Effect of Ferrous Ferric Oxide Nano-Additive and Chicken Fat Methyl Ester on Performance and Emission Characteristics of Compression Ignition Engine

et al. 2021

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In recent years, industries have been investing to develop a potential alternative fuel to substitute the depleting fossil fuels which emit noxious emissions. Present work investigated the effect of ferrous ferric oxide nano-additive on performance and emission parameters of compression ignition engine fuelled with chicken fat methyl ester blends. The nano-additive was included with various methyl ester blends at different ppm of 50, 100, and 150 through the ultrasonication process. Probe sonicator was utilized for nano-fuel preparation to inhibit the formation of agglomeration of nanoparticles in base fuel. Experimental results revealed that the addition of 100 ppm dosage of ferrous ferric oxide nanoparticles in blends significantly improves the combustion performance and substantially decrease the pernicious emissions of the engine. It is also found from an experimental results analysis that brake thermal efficiency (BTE) improved by 4.84%, a reduction in brake specific fuel consumption (BSFC) by 10.44%, brake specific energy consumption (BSEC) by 9.44%, exhaust gas temperature (EGT) by 19.47%, carbon monoxides (CO) by 53.22%, unburned hydrocarbon (UHC) by 21.73%, nitrogen oxides (NOx) by 15.39%, and smoke by 14.73% for the nano-fuel B20FFO100 blend. By seeing of analysis, it is concluded that the doping of ferrous ferric oxide nano-additive in chicken fat methyl ester blends shows an overall development in engine characteristics.

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“…According to a survey of the World Commission on Environment and Development [ 4 ], the industrial sectors such as aerospace, automotive, and energy generation are required to develop sustainable production and utilization techniques. This demands a shift towards efficient manufacturing and energy production strategies, resulting in minimum material wastage, greenhouse gas emissions (GHGs), exploitation of natural resources, and disturbances in ecosystems [ 5 , 6 ]. A substantially influential manufacturing technology realizing the motive has emerged as additive manufacturing (AM) or 3-dimensional printing (3DP).…”

Section: Introductionmentioning

confidence: 99%

Applications of additive manufacturing (AM) in sustainable energy generation and battle against COVID-19 pandemic: The knowledge evolution of 3D printing

Wang

Ahmed

Azam

et al. 2021

Journal of Manufacturing Systems

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Environment-friendly novel fuel additives: Investigation of the effects of graphite nanoparticles on performance and regulated gaseous emissions of CI engine

Cited by 52 publications

References 40 publications

Application of ANN to predict performance and emissions of SI engine using gasoline-methanol blends

Application of ANN to predict performance and emissions of SI engine using gasoline-methanol blends

An Experimental Investigation on the Effect of Ferrous Ferric Oxide Nano-Additive and Chicken Fat Methyl Ester on Performance and Emission Characteristics of Compression Ignition Engine

Applications of additive manufacturing (AM) in sustainable energy generation and battle against COVID-19 pandemic: The knowledge evolution of 3D printing

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