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2019 AIAA SciTech

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CRAFT Tech will be presenting at the 2019 AIAA Science and Technology Forum and Exposition in San Diego, California. Tim Weathers will be discussing his recent work in molecular dynamics.

Date: Wednesday January 9, 2019 at 11:30 am
Title: Characterizing Thermodynamic Properties of Pure Components and Binary Mixtures at Rocket Conditions Using Molecular Dynamics
Session: Transport and Thermophysical Properties

Conventional descriptions of mixing and combustion processes are inadequate for conditions seen in rocket engines. Mixtures at these conditions can exhibit complicated non-linear critical locus behavior that is strongly dependent on composition, temperature, and pressure. As a step towards better understanding the mixing process, thermodynamic properties for pure component and binary mixture systems have been computed using molecular modeling techniques at both subcritical and supercritical conditions. Molecular models were first validated by analyzing pure component systems and comparing against available experimental data. After the capabilities and limitations of the models were understood, simulations were performed to compute and predict properties of binary systems. Properties of interest include density, heat capacity, enthalpy of vaporization, and vapor-liquid equilibrium. The pure components analyzed are those found in rocket engines including nitrogen, carbon dioxide, water, and dodecane. The binary systems analyzed include alkane-nitrogen, alkane-carbon dioxide, and alkane-water. The single component simulations showed that simple models available for N2, CO2, and H2O reliably reproduce experimental densities of coexisting vapor and liquid, saturation pressures, and heats of evaporation. For dodecane the simple united atom models give good agreement with experimental data for the VLE data but not for predicting heat capacity. The binary mixtures simulations showed that the simple models using the Lorentz-Berthelot mixing rule (kij =1) are not able to accurately predict the VLE data. Adjusting the kij value to 0.935, 0.95, and 1.3 proved to increase prediction accuracy for alkane-nitrogen, alkane-carbon dioxide, and alkane-water respectively.

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