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Uncertainty Assessment of Equations of State with Application to an Organic Rankine Cycle

Published

Author(s)

Jerome Frutiger, Ian Bell, O'Connell J. P., Kenneth Kroenlein, Jens Abildskov, Gurkan Sin

Abstract

Evaluations of equations of state (EoS) with application to process systems should include uncertainty analysis. A generic method is presented for determining such uncertainties from both the mathematical form and the data for obtaining EoS parameter values. The method is implemented for the Soave-Redlich-Kwong (SRK), the Peng-Robinson (PR) cubic EoS, and the perturbed-chain statistical associating fluid theory (PC-SAFT) EoS, as applied to an organic Rankine cycle (ORC) power system to recover heat from the exhaust gas of a marine diesel engine with cyclopentane as the working fluid. Uncertainties of the EoS input parameters, including their corresponding correlation structure, are quantified from the data using a bootstrap method. A Monte Carlo procedure propagates parameter input uncertainties onto the process output. Regressions have been made of the three cubic EoS parameters from both critical point matching and vapor pressure and density data, as used for the three PC SAFT parameters. ORC power uncertainties of 2-5% are found for all models from the larger data sets. Mean power values for the cubic EoS are similar for both parameter regressions. The mean power from the PC-SAFT EoS is less than for the cubic EoS, with no overlap of the uncertainty distributions.
Proceedings Title
30th INTERNATIONAL CONFERENCE on Efficiency, Cost, Optimisation, Simulation and Environmental
Impact of Energy Systems.
Conference Dates
July 2-6, 2017
Conference Location
San Diego, CA, US

Citation

Frutiger, J. , Bell, I. , P., O. , Kroenlein, K. , Abildskov, J. and Sin, G. (2017), Uncertainty Assessment of Equations of State with Application to an Organic Rankine Cycle, 30th INTERNATIONAL CONFERENCE on Efficiency, Cost, Optimisation, Simulation and Environmental Impact of Energy Systems., San Diego, CA, US (Accessed April 24, 2024)
Created July 1, 2017, Updated October 12, 2021