The vapor-liquid equilibrium (VLE) of fuel-N2 mixtures is modeled using the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state, where in this study “fuel” refers to a pure component hydrocarbon. These mixtures are important in evaluating the thermodynamic state of the fuel-air mixture in the combustion chamber, where N2 serves as a surrogate for air. NIST ThermoDataEngine (TDE) was used to catalog fuel-N2 data sets for fuel components expected in sustainable aviation fuels. The goal of this study was to develop a predictive model capable of capturing the structure-property relationships of fuel components in the presence of N2. Therefore, PC-SAFT model parameters were estimated using a group contribution method, which considers the fuel’s molecular structure. Binary interaction parameters (kij) were fit for each fuel-N2 mixture data set and a correlation for kij values for fuel-N2 mixtures was derived. PC-SAFT calculations using fitted parameters reproduced most of the experimental data within average mole fraction residuals of 0.04 and 0.08 for the liquid and vapor phases, respectively. VLE calculations using fitted and correlated kij values yielded a similar performance for most fuel-N2 binary mixtures.
Modeling the Vapor-Liquid Equilibria of Sustainable Aviation Fuel Components with Nitrogen Using the PC-SAFT Equation of State
Menegazzo D.;
2025
Abstract
The vapor-liquid equilibrium (VLE) of fuel-N2 mixtures is modeled using the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state, where in this study “fuel” refers to a pure component hydrocarbon. These mixtures are important in evaluating the thermodynamic state of the fuel-air mixture in the combustion chamber, where N2 serves as a surrogate for air. NIST ThermoDataEngine (TDE) was used to catalog fuel-N2 data sets for fuel components expected in sustainable aviation fuels. The goal of this study was to develop a predictive model capable of capturing the structure-property relationships of fuel components in the presence of N2. Therefore, PC-SAFT model parameters were estimated using a group contribution method, which considers the fuel’s molecular structure. Binary interaction parameters (kij) were fit for each fuel-N2 mixture data set and a correlation for kij values for fuel-N2 mixtures was derived. PC-SAFT calculations using fitted parameters reproduced most of the experimental data within average mole fraction residuals of 0.04 and 0.08 for the liquid and vapor phases, respectively. VLE calculations using fitted and correlated kij values yielded a similar performance for most fuel-N2 binary mixtures.File | Dimensione | Formato | |
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