Fuel properties and precipitate formation at low temperature in soy-, cottonseed-, and poultry fat-based biodiesel blends

Tang, Haiying; Salley, Steven O.; Ng, Koon‐Kwan

doi:10.1016/j.fuel.2008.04.030

Cited by 165 publications

(100 citation statements)

References 21 publications

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“…Dunn et al 42 found linear relationships between CP and PP and the blending ratio of methyl esters from soybean oil (SME) and tallow (TME). Tang et al 47 correlated CP and PP with the blend composition of biodiesels based on soybean oil (SBO), cottonseed oil (CSO), and poultry fat (PF) by empirical second-order polynomial equations. However, these equations are applicable to the selected biodiesels and cannot be generalized.…”

Section: 4a Available Methods For Predicting Low-temperature Propementioning

confidence: 99%

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Selection of Prediction Methods for Thermophysical Properties for Process Modeling and Product Design of Biodiesel Manufacturing

Liu

Tovar

et al. 2011

Ind. Eng. Chem. Res.

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To optimize biodiesel manufacturing, many reported studies have built simulation models to quantify the relationship between operating conditions and process performance. For mass and energy balance simulations, it is essential to know the four fundamental thermophysical properties of the feed oil: liquid density (ρ L ), vapor pressure (P vap ), liquid heat capacity (C p L ), and heat of vaporization (ΔH vap ). Additionally, to characterize the fuel qualities, it is critical to develop quantitative correlations to predict three biodiesel properties, namely, viscosity, cetane number, and flash point. Also, to ensure the operability of biodiesel in cold weather, one needs to quantitatively predict three low-temperature flow properties: cloud point (CP), pour point (PP), and cold filter plugging point (CFPP). This article presents the results from a comprehensive evaluation of the methods for predicting these four essential feed oil properties and six key biodiesel fuel properties. We compare the predictions to reported experimental data and recommend the appropriate prediction methods for each property based on accuracy, consistency, and generality. Of particular significance are (1) our presentation of simple and accurate methods for predicting the six key fuel properties based on the number of carbon atoms and the number of double bonds or the composition of total unsaturated fatty acid methyl esters (FAMEs) and (2) our posting of the Excel spreadsheets for implementing all of the evaluated accurate prediction methods on our group website (www.design.che.vt.edu) for the reader to download without charge.ii Acknowledgement

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Section: 4a Available Methods For Predicting Low-temperature Propementioning

confidence: 99%

“…47,84 However, poor low-temperature flow properties limit the application of biodiesel. The formation of precipitates in biodiesels at low temperatures can cause serious effects on diesel fuel delivery systems.…”

Section: Low-temperature Flow Propertiesmentioning

confidence: 99%

Selection of Prediction Methods for Thermophysical Properties for Process Modeling and Product Design of Biodiesel Manufacturing

Liu

Tovar

et al. 2011

Ind. Eng. Chem. Res.

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“…Cold soak filterability is a measurement of how well biodiesel flows when chilled and poured through a filter. Previous studies showed that the formation of precipitates during cold weather conditions depends on the feedstock, blend concentration and storage time [15,16]. Most of the precipitate formed at lower temperatures will be re-dissolved when they are warmed to room temperature [17]; however, minor precipitate components remain as precipitates after warming to room temperature.…”

Section: Cold Soak Filterabilitymentioning

confidence: 99%

“…Sterols are composed of a group of steroid alcohols present in plants. The culprit sterol was found to be sterol glucoside(SG) [15]. Soybean oil may contain up to 0.23 % SG [16].…”

Section: Cold Soak Filterabilitymentioning

confidence: 99%

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Effects of Raw Materials and Production Practices on Biodiesel Quality and Performance

Rodríguez¹

2011

Biodiesel- Quality, Emissions and by-Products

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Biodiesel Properties and Alternative Feedstocks

Moser¹

2013

Bioprocessing Technologies in Biorefinery for Sustainable Production of Fuels, Chemicals, and Polymers

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Fuel properties and precipitate formation at low temperature in soy-, cottonseed-, and poultry fat-based biodiesel blends

Cited by 165 publications

References 21 publications

Selection of Prediction Methods for Thermophysical Properties for Process Modeling and Product Design of Biodiesel Manufacturing

Selection of Prediction Methods for Thermophysical Properties for Process Modeling and Product Design of Biodiesel Manufacturing

Effects of Raw Materials and Production Practices on Biodiesel Quality and Performance

Biodiesel Properties and Alternative Feedstocks

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