Study on volatility and flash point of the pseudo binary mixtures of sunflower-based biodiesel+methylcyclohexane

Guo, Yihang; Yang, Fengjun; Xing, Yan; Li, Dan; Fang, Wenjun; Lin, Ruisen

doi:10.1016/j.fluid.2008.10.018

Cited by 16 publications

(15 citation statements)

References 24 publications

(24 reference statements)

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“…A literature review reveals that Liaw et al's model is the most frequently used [19,[30][31][32][33][34]. In this paper, we intend to apply it to systematically investigate the flash-point of binary and ternary miscible mixtures either of flammable solvents or of aqueous−organic mixtures, some with new experimental data published here for the first time.…”

Section: Introductionmentioning

confidence: 99%

Prediction of miscible mixtures flash-point from UNIFAC group contribution methods

Liaw¹,

Gerbaud²,

Li³

2011

Fluid Phase Equilibria

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Section: Introductionmentioning

confidence: 99%

Prediction of miscible mixtures flash-point from UNIFAC group contribution methods

Liaw¹,

Gerbaud²,

Li³

2011

Fluid Phase Equilibria

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“…Guo et al used the Liaw model to calculate the flash points of multicomponent mixtures consisting of sunflower-seed-based biodiesel and ethanol 64 and sunflower ethyl esters and methylcyclohexane. 65 In these studies, the sunflower biodiesel/ethyl esters were treated as pseudo-components, i.e., the biodiesel consisting of various fatty acids esters was considered to have a single flash point and temperature−pressure relationship. Both studies showed that the flash points predicted by the Liaw model agreed well with the experimental flash points when a regular solution model 63 was used to calculate the activity coefficients.…”

Section: Flash Point Prediction Model Based On Vapor Pressurementioning

confidence: 99%

“…Overall, the prediction efficiencies of the UNIFAC-type models are comparable to those of the UNIQUAC model 78 for binary aqueous mixtures and those of the NRTL model for binary/ternary miscible mixtures (including aqueous mixtures) 56 and binary/ternary partially miscible aqueous−organic mixtures. 71 Guo et al 65 reported one exception: the regular solution model (for binary mixtures) yields more-accurate predictions than the UNIFAC model for sunflower ethyl esters−methylcyclohexane blends.…”

Section: Liquid-phase Activity Coefficient Modelsmentioning

confidence: 99%

“…Guo et al used the Liaw model to calculate the flash points of multicomponent mixtures consisting of sunflower-seed-based biodiesel and ethanol and sunflower ethyl esters and methylcyclohexane . In these studies, the sunflower biodiesel/ethyl esters were treated as pseudo-components, i.e., the biodiesel consisting of various fatty acids esters was considered to have a single flash point and temperature–pressure relationship.…”

Section: Flash Point Prediction Model Based On Vapor Pressurementioning

confidence: 99%

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A Review of Flash Point Prediction Models for Flammable Liquid Mixtures

Phoon

Mustaffa

Hashim

et al. 2014

Ind. Eng. Chem. Res.

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Flash point has safety implications and is therefore used to ascertain associated explosion hazards and fire of a flammable solution. Technological advances in the synthesis of new blends and chemical waste handlers have created a high demand for the flash point database and the flash point estimation methods of flammable liquid mixtures have become important. The present study reviewed the estimation model of the flammable liquid mixture flash point. These models are based on the following parameters: (1) either a normal boiling point or a composition range, (2) molecular structure (molecular descriptors), and (3) vapor pressure. Models based on boiling points or the composition ranges are empirically obtained using a mathematical regression method or an artificial neural network (ANN) approach. The quantitative structure–property relationship (QSPR) method is used to analyze the relationship between the flash point and the molecular structures that exist in a flammable mixture. Vapor-pressure-based models, which were formulated using Le Chatelier’s rule are more reliable, compared to other prediction models. However, the prediction efficiencies of these vapor-pressure-based models for nonideal mixtures are strongly depend on the accuracy of the activity coefficient models used. Several activity coefficient models are discussed at the end of this paper. In summation, there is no universal flash point prediction model for all flammable mixtures.

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“…Biodiesel and its blend with petroleum-based diesel fuel can be used in diesel engines without any significant modifications to the engines (El-Diwani et al, 2009). The significant advantages of biodiesel are the reduction in gas emissions that cause global warming, reduced tail pipe particulate matter, hydrocarbons, carbon monoxide (CO), and other air toxics (Guo et al, 2009). Biodiesel improves lubricity and reduces premature wearing of fuel pumps (Graboski and Cormick, 1998).…”

Section: Introductionmentioning

confidence: 99%

Performance and emission characteristics of CI engine, fuelled with diesel and oxygenated fuel blends

Pushparaj¹,

Ramabalan

Selvan

2015

IJGW

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Vegetable oils are a potential alternative towards partial or total substitution of diesel fuels. In this study, we used ethanol as the solvent, and a bio fuel enhancer as additive to explore the possible use of higher percentages of biodiesel in an unmodified diesel engine. Biodiesel was produced from cashew nut shell liquid (CNSL) by pyrolysis process. A mixture containing 80% (by volume) of Number 2 diesel fuel and 20% (by volume) of biodiesel is called here as B20. The effect of 10% ethanol, (by volume) blended with B20 was studied in a single cylinder, four strokes direct injection diesel engine after adding a bio fuel enhancer as additive. The impact of test fuels on engine torque, power, brake specific fuel consumption, brake thermal efficiency, and exhaust gas temperature were investigated by the performance tests. The influence of blends on CO, CO 2 , HC, NO and smoke opacity were measured by emission tests. The experimental results showed that when a fuel mixture containing 10% ethanol, B20 and a bio fuel enhancer as additive was used, the exhaust emissions were fairly reduced; especially the NO is reduced remarkably by 30% when compared to using B20 alone. Smoke opacity was reduced by 20% when compared to using diesel alone.Reference to this paper should be made as follows: Pushparaj, T., Ramabalan, S. and Selvan, V.A.M. (2015) 'Performance and emission characteristics of CI engine, fuelled with diesel and oxygenated fuel blends', Int.

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Study on volatility and flash point of the pseudo binary mixtures of sunflower-based biodiesel+methylcyclohexane

Cited by 16 publications

References 24 publications

Prediction of miscible mixtures flash-point from UNIFAC group contribution methods

Prediction of miscible mixtures flash-point from UNIFAC group contribution methods

A Review of Flash Point Prediction Models for Flammable Liquid Mixtures

Performance and emission characteristics of CI engine, fuelled with diesel and oxygenated fuel blends

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