Experimental and empirical study of diesel and castor biodiesel blending effect, on kinematic viscosity, density and calorific value

Amin, Ashraf; Gadallah, A. G.; Morsi, A.K. El; El-Ibiari, N.N.; Diwani, G. El

doi:10.1016/j.ejpe.2015.11.002

Cited by 51 publications

(21 citation statements)

References 16 publications

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“…This combo is needed to rustle progressively and H 2 So 4 was enumerated by 1% volume. All the glycerol mediates and bio-diesel waft overhead, when the combo is confessed to mediate for a day [10][11][12][13][14][15].Then, the composites such as B10, B20 and B30 were furnished.…”

Section: Fuel Preparationmentioning

confidence: 99%

Research on Performance And Emission on Compression Ignition Engine Fuelled With Blends of Neem Bio-Diesel

Kumar¹,

Murali²

2019

IJEAT

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In this contemporary era it is mandatory to increasing the usage of non edible biodiesel to replace the fossil fuels. This non edible biodiesels are produced from vegetable oils which is clean burning and renewable. This paper deals with the performance and emission characteristics on diesel engine with blends of Castor oil as biodiesel. Castor oil biodiesel is prepared by the use of adding 1% v/v H2SO4 after the transesterification process. The engine tests were performed with various blends B20, B40, B60 on a single cylinder, 4-stroke, diesel engine. The result shows Higher performance and lower emissions for B20 than the diesel and other blends. The brake thermal efficiency is higher than the diesel and CO, HC and NOX emissions were 22%, 8.4%, and 21% lesser than that of diesel.

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Section: Fuel Preparationmentioning

confidence: 99%

Research on Performance And Emission on Compression Ignition Engine Fuelled With Blends of Neem Bio-Diesel

Kumar¹,

Murali²

2019

IJEAT

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“…Kinematic viscosity and density data of different biodiesel blends samples at different temperatures and volume fraction of biodiesel were gathered from the literature. A total of 900 and 520 experimental points for kinematic viscosity and density, respectively, were obtained from various scientific publications [32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49]. The development of the proposed approaches was performed as follows.…”

Section: Experimental Datamentioning

confidence: 99%

Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) for Predicting the Kinematic Viscosity and Density of Biodiesel-Petroleum Diesel Blends

Kassem¹

2018

AJCST

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Biodiesel is considered as an alternative source of energy obtained from renewable materials. In the present paper, the investigation of the applicability of adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) approaches for modeling the biodiesel blends property including kinematic viscosity and density at various temperatures and the volume fractions of biodiesel. An experimental database of kinematic viscosity and density of biodiesel blends (biodiesel blend with diesel fuel) were used for developing of models, where the input variables in the network were the temperature and volume fractions of biodiesel. The model results were compared with experimental ones for determining the accuracy of the models. The developed models produced idealized results and were found to be useful for predicting the kinematic viscosity and density of biodiesel blends with a limited number of available data. Moreover, the results suggest that the ANFIS approach can be used successfully for predicting the kinematic viscosity and density of biodiesel blends at various volume fractions and temperature compared to another models.

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“…Their predicted values agreed with that of experimental. Also, Amin et al [24] predicted kinematic viscosity (KV), density and calorific value (CV) for castor oil biodiesel (COB)Àfossil diesel blends. They concluded that the models developed were suitable to determine KV, density and CV of COBÀdiesel blends.…”

Section: Introductionmentioning

confidence: 99%

Optimization of coconut oil ethyl esters reaction variables and prediction model of its blends with diesel fuel for density and kinematic viscosity

2016

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This paper presents the synthesis of biodiesel from coconut oil sourced from Nigeria through base-catalyzed transesterification using potassium hydroxide (KOH) as catalyst and ethanol as solvent. Direct transesterification reactions were carried out due to low free fatty acid value (0.65 mg KOH/g oil). The reaction variables optimized were: KOH amount (0.5À2.25 wt.%), reaction temperature (30À80 C), reaction time (30À70 min) and ethanol to oil molar ratio (3À12). Physico-chemical properties of the coconut oil and fuel properties of the coconut oil ethyl esters (CNOEE) were determined using standard test methods, and the properties of the latter were compared with biodiesel standards. Also, the density and viscosity of diesel fuel blends (B5, B10, B20 and B50) with CNOEE were determined and the viscosities compared with that of the Grunberg and Nissan model. In this study, the optimum reaction variables obtained (KOH amount D 1.0 wt.%, ethanol/oil molar ratio D 6:1, reaction temperature D 70 C, reaction time D 60 min) gave a biodiesel yield of 97.20% and the fuel properties of CNOEE at the optimum conditions conformed to both ASTM D6751 and EU 14214 standards. There was agreement between the measured and estimated values for the density and viscosities of CNOEEÀdiesel blends. The results indicate that the density and viscosities of the blends increased with the increased of biodiesel percentage in the blends.

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Experimental and empirical study of diesel and castor biodiesel blending effect, on kinematic viscosity, density and calorific value

Cited by 51 publications

References 16 publications

Research on Performance And Emission on Compression Ignition Engine Fuelled With Blends of Neem Bio-Diesel

Research on Performance And Emission on Compression Ignition Engine Fuelled With Blends of Neem Bio-Diesel

Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) for Predicting the Kinematic Viscosity and Density of Biodiesel-Petroleum Diesel Blends

Optimization of coconut oil ethyl esters reaction variables and prediction model of its blends with diesel fuel for density and kinematic viscosity

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