Thermodynamic properties of biodiesel and petro-diesel blends at high pressures and temperatures. Experimental and modeling

Ivaniš, Gorica R.; Radović, Ivona R.; Veljković, Vlada B.; Kijevčanin, Mirjana Lj.

doi:10.1016/j.fuel.2016.07.023

Cited by 31 publications

(28 citation statements)

References 48 publications

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“…DENSITY CORRELATION The Tait-type equation is widely used for density correlation against pressure and temperature, 23−25 biodiesel, and biodiesel + petrodiesel mixtures, 23,26 by using the following equation (eq 1):…”

Section: High-pressure and High-temperaturementioning

confidence: 99%

Thermodynamic Properties of Biodiesel and Petrodiesel Blends at High Pressure and High Temperature and a New Model for Density Prediction

et al. 2022

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This paper presents a new model to predict the density of biodiesel + petrodiesel mixtures at high pressure and high temperature (HPHT) based on the Murnaghan equation of state, as a function of temperature, pressure, volumetric composition, and petrodiesel and biodiesel densities. This model was validated by using experimental data from the literature, along with a new experimental data set for biodiesel (grape seed, corn, and linseed) + petrodiesel, at high pressure (0.10–100.00 MPa) and high temperature (293.15–413.15 K) in a composition range of 0, 20, 40, 60, 80, and 100%vol. These experimental data were correlated by using the Tammann–Tait equation. From these data, the following derivative properties were determined: isothermal compressibility (κT), isobaric thermal expansibility (αP), internal pressure (p int), and the difference between pressure and volume heat capacities (c p – c v). Deviations obtained from the model proposed in this work (%AARD) were less than 0.50% for biodiesel + petrodiesel density data.

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Section: High-pressure and High-temperaturementioning

confidence: 99%

Thermodynamic Properties of Biodiesel and Petrodiesel Blends at High Pressure and High Temperature and a New Model for Density Prediction

et al. 2022

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“…However, it has been shown that biodiesel has shortcomings that need to be improved before it can be considered for gas turbine application. A study by Ivaniš, Radović [20] reported that biodiesel has higher density and viscosity than conventional diesel which results in poor atomisation of the fuels and may clog fuel nozzles. The properties of a liquid fuel that affect atomisation are viscosity, density, and surface tension.…”

Section: Introductionmentioning

confidence: 99%

Performance and emission characteristics of micro gas turbine engine fuelled with bioethanol-diesel-biodiesel blends

Saifuddin¹,

Refal²,

Palanisamy³

2017

Int. J. Automot. Mech. Eng.

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Biodiesel is receiving increasing attention as an alternative fuel due to the ever-growing demand for energy. However, the inferior physiochemical properties of biodiesel render it incompatible for gas turbine application, which needs to meet the standard requirement of gas turbine fuel accordance to ASTM D2880. In this quest, the biodiesel-dieselbioethanol blends might be a good option. In this paper, the research work was carried out to study experimentally the performance and exhaust emission characteristics of a 25kW micro gas turbine engine (Capstone Model C30) fuelled with biodiesel-dieselbioethanol blends. The assessment on the improved fuel properties of biodiesel by blending with bio-ethanol had shown more superior atomisation characteristics performance compared to unmodified biodiesel. Moreover, the performance test in the micro gas turbine was limited up to 20% blend of biofuel, which showed improved thermal efficiency during the test. Subsequently, the emission test carried out in this work also showed significant enhancement in emissions, except nitrogen oxides (NOx) which contributed to the higher formation in comparison with the distillate diesel. Finally, B80E20 (80:20 of biodiesel-bioethanol) was proposed to be selected as an ideal blended fuel ratio to be applied in micro gas turbine engine due to its adaptability to replace diesel fuel, while showed better performance and emission properties as compared to the pure petroleum diesel.

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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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Thermodynamic properties of biodiesel and petro-diesel blends at high pressures and temperatures. Experimental and modeling

Cited by 31 publications

References 48 publications

Thermodynamic Properties of Biodiesel and Petrodiesel Blends at High Pressure and High Temperature and a New Model for Density Prediction

Thermodynamic Properties of Biodiesel and Petrodiesel Blends at High Pressure and High Temperature and a New Model for Density Prediction

Performance and emission characteristics of micro gas turbine engine fuelled with bioethanol-diesel-biodiesel blends

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

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