Impact of tamanu oil-diesel blend on combustion, performance and emissions of diesel engine and its prediction methodology

Yarrapragada, K. S. S. Rao

doi:10.1007/s40430-016-0616-5

Cited by 15 publications

(10 citation statements)

References 47 publications

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“…Biodiesel is a renewable fuel that can be used as an alternative or mixture component to conventional oil diesel, consisting of mono-alkyl esters of long-chain fatty acids from algae, vegetable (sunflower, palm, canola, rape, safflower, etc.) and animal oils [3,4].…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation of the cetane improver and bioethanol addition for the use of waste cooking oil biodiesel as an alternative fuel in diesel engines

Örs

2020

J Braz. Soc. Mech. Sci. Eng.

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In this study, bioethanol produced from sugar beet and biodiesel produced from waste cooking oils was blended with each other in the volumetric rates to be 20% and 80%, respectively. Cetane improver (di-tert-butyl peroxide) was added into blend fuel in 1-2-3% as volumetric. The obtained blends were used as a fuel in the diesel engine which is single-cylinder, directinject, four-stroke. The tests were conducted under four different engine loads (25%, 50%, 75% and 100%) and 1400 rpm engine speed. The test results showed that brake-specific fuel consumption was decreased up to 15.5% thanks to the addition of cetane improver, although biodiesel and bioethanol increased brake-specific fuel consumption by 16.1% and 27.54%, respectively. However, brake thermal efficiency values were increased up to 9.44% with both biodiesel and cetane improver added blend fuels, while brake thermal efficiency was decreased by 3.88% with bioethanol addition. The more compatible combustion characteristics with that of diesel fuel have been obtained due to especially the increase in cetane number. The use of biofuels increased both maximum cylinder pressure and heat release rate. While, with the cetane improver addition, a decrease in CO, HC and smoke opacity values was observed up to 22.5%, 17.44% and 24.44%, respectively, CO 2 , NO X and exhaust gas temperature values were increased up to 19.55%, 5% and 15.22%, respectively, according to bioethanol blend fuel. Keywords Waste cooking oil • Biodiesel • Bioethanol • Cetane improver • Diesel engine List of symbols BSFC Brake-specific fuel consumption BTE Brake thermal efficiency CA Crank angle CA50 Crank angle point for 50% accumulated HRR CA90 Crank angle point for 90% accumulated HRR CBD Cotton biodiesel cDF Conventional diesel fuel CI Cetane index CNI Cetane improver CO Carbon monoxide CO 2 Carbon dioxide DI Direct injection DTBP Di-tert-butyl peroxide

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Section: Introductionmentioning

confidence: 99%

Experimental investigation of the cetane improver and bioethanol addition for the use of waste cooking oil biodiesel as an alternative fuel in diesel engines

Örs

2020

J Braz. Soc. Mech. Sci. Eng.

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“…WCO blends also suggest that increase in CR decreases the CO emission due to shortage of oxygen supply at higher CRs 29 . The testing of tamanu oil diesel blend with ND concludes that 10%TO blend produces lesser CO emission compared to 5%TO blend 28 . The test result (Figure 7) of CIB25‐fueled engine depicts that the increase in CR decreases the CO emission of about 50% at CR18 than the CR14.…”

Section: Resultsmentioning

confidence: 92%

“…The diesel and diesel blend with tamanu oil emits lesser HC at higher CRs and at higher loads due to better combustion that takes place at these conditions. Also, it suggests lesser HC emission when the engine fueled with tamanu oil 10% blend than the tamanu oil 5% blend 28 . The investigation of WCO20, WCO40, WCO60, WCO80, and neat diesel for HC emission suggests that at high CRs B40 produces high HC emission than the diesel fuel.…”

Section: Resultsmentioning

confidence: 95%

Developing a smart fuel using artificial neural network for compression ignition engine fueled with Calophyllum inophyllum diesel blend at various compression ratio

Venugopal

Kasimani

Chinnasamy

2020

Env Prog and Sustain Energy

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In machinery, it is evident that the computing system for self‐automated machinery derives nonlinear and complex equations by comparing the machinery's different input parameters with their corresponding performance output parameters. In order to operate the machinery with good performance and better efficiency, the computing system needs a machine‐learning algorithm. Most recent researchers have concentrated more on self‐driving vehicle, which seems to be lack of developing a strong algorithm for compression ignition (CI) engines to predict the performance and emission output parameter. Thus, this article deals with the prediction of performance and emission characteristics of CI engine fueled with 25% Calophyllum inophyllum and 75% diesel blend (CIB25) at various compression ratios using artificial neural network (ANN). Performance and emission tests were conducted in a single‐cylinder four‐stroke variable‐compression‐ratio CI engine fueled with CIB25 with varying loads and at a constant speed of operation. Experimental investigation indicates that 18:1 compression ratio gives better performance results when CIB25 is used as the fuel. Emission test results show better emission characteristics at 17:1 compression ratio. These results show that some input factors affect the output factors under some set of operating conditions, while some input factors improve them. ANN developed for the CI engine learns how the input factors affect and improve the output factors. Also, developed neural network is found to be satisfactory, and it predicts the output at a regression value of 0.998 with an average error of 1.77% in the case of CIB25.

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“…The experimental results related to the mechanical characteristics of combined SFRC with the combination of macro and micro steel fibers is also assumed by the Artificial Neural Network (ANN). 15,16 NN is the mathematical representation of human neural architectures. This method models the reflection pattern of human architecture in terms of knowledge and generalized aptitudes.…”

Section: Nn Predictionmentioning

confidence: 99%

Mechanical properties of mixed steel fiber reinforced concrete with the combination of micro and macro steel fibers

Dhanapal¹,

Jeyaprakash

2019

Structural Concrete

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The paper intends to analyze and study the features of steel fiber reinforced concrete (SFRC) and plain concrete that contains combined fibers of various aspect ratios. Experiments on works are held to examine the features of the new combination of concretes. Simultaneously, the characteristics of the concretes that are hardened are examined by performing tests on compressions, flexural strength tests, and split tensile strength (STS). It further verifies the effects of fibers when they are distributed in the hinged zone of structural components to obtain financial benefits by minimizing the ingredients in steel fiber in the concrete mix. The result shows that the combined reinforced concrete steel fiber can be employed as the better combination to be applied in SFRC for achieving strength in STS, and flexure. Anyhow, enhanced ability for working was achieved as more amounts of microfibers in mixed with concrete. And there is slight variation in the features of concrete between beam of fibers with full length and fibers which are available in hinged zone. Similarly, the categorization of neural network such as Neural Network–Levenberg–Marquardt (NN‐LM) and Neural Network‐Gradient Descent (NN‐GD) is further used to perform the experimentation in an intelligent manner, which comes close to the actual values while calculating the mean absolute error (MAE) and root mean square error (RMSE) values.

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Impact of tamanu oil-diesel blend on combustion, performance and emissions of diesel engine and its prediction methodology

Cited by 15 publications

References 47 publications

Experimental investigation of the cetane improver and bioethanol addition for the use of waste cooking oil biodiesel as an alternative fuel in diesel engines

Experimental investigation of the cetane improver and bioethanol addition for the use of waste cooking oil biodiesel as an alternative fuel in diesel engines

Developing a smart fuel using artificial neural network for compression ignition engine fueled with Calophyllum inophyllum diesel blend at various compression ratio

Mechanical properties of mixed steel fiber reinforced concrete with the combination of micro and macro steel fibers

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