Measurements and empirical correlations in predicting biodiesel-diesel blends’ viscosity and density
• Density-biodiesel content variation is well correlated by linear model. • Exponential equation is the best model for density-temperature variation. • Rational model is the most proper one to predict viscosities of fuel blends. • Power model is the best one to characterize viscosity vs. temperature...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Gülüm, Mert [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Umfang: |
11 |
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| Übergeordnetes Werk: |
Enthalten in: Achieving highly tunable negative permittivity in titanium nitride/polyimide nanocomposites via controlled DC bias - Yang, Chaoqiang ELSEVIER, 2018, the science and technology of fuel and energy, New York, NY [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:199 ; year:2017 ; day:1 ; month:07 ; pages:567-577 ; extent:11 |
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10.1016/j.fuel.2017.03.001 |
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• Density-biodiesel content variation is well correlated by linear model. • Exponential equation is the best model for density-temperature variation. • Rational model is the most proper one to predict viscosities of fuel blends. • Power model is the best one to characterize viscosity vs. temperature variation. • Two-term power model better correlates density-viscosity variation. |
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