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These correlations are usually modelled through the pseudo-reduced fluid properties
: LaTeX Math Inline body --uriencoded--(T_%7Bpr%7D, pP_%7Bpr%7D)
| Pseudo-reduced temperature |
| Pseudo-critical temperature | ||||||||
| Pseudo-reduced pressure |
| Pseudo-critical pressure |
Charts
Implicit Correlations
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These correlations are quite accurate and work in a wide range of pressures and temperatures but computationally expensive and may have problems with convergence when approaching the critical temperature.
Dranchuk, Purvis and Robinson’s Correlation Robinson (Dranchuket al. 1971) | |
| Kassem’s correlation (Abou-kassemand Dranchuk |
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Explicit Correlations
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The explicit correlations do not have convergence issues, generate smooth derivatives for compressibility calculations and provide fast computing.
Explicit Correlations
| Artificial Neural Network correlations |
| Ahmed (2017) |
| Kareem (2016) |
| Brill & Beggs (1973) |
| Standing-Katz (1942) |
| Sanjari and Nemati’s Correlation (2012) |
| Azizi, Behbahani and Isazadeh’s Correlation (2010) |
| Heidaryan, Moghdasi and Rahimi’s Correlation (2010) |
The explicit correlations do not have a convergence issues.
See also
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Natural Science / Physics /Thermodynamics / Equation of State / Z-factor
[ Pseudo-Critical Point Correlations @model ]
