The implementation of Sustainable Aviation Fuels (SAFs) in current and future long-haul aircraft to replace fossil-based kerosene represents the main path towards the decarbonization goal of the U.S. aviation industry by 2050. A deep and comprehensive characterization of the behavior of these new synthetic biofuels is a key to fulfill the strict regulations and standards and to ensure compatibility with existing propulsion systems in terms of performance, emissions, and safety. The present work focuses on the development of a Lagrangian-Eulerian thermodynamic framework to simulate SAF surrogates, employing the volume-translated Soave-Redlich-Kwong (VT-SRK) Equation of State (EoS) for accurate and efficient representation of thermodynamic properties. A novel computational fluid dynamics (CFD) solver, realFluidSprayFoam, was implemented within the OpenFOAM platform to account for high-pressure thermodynamics through real-fluid EoS-based departure functions and transport property corrections. This solver extends the application of real-fluid EoS to the Lagrangian phase, enabling precise modeling of multi-component liquid fuel mixtures via mixing rules. A new vapor-liquid equilibrium (VLE) based evaporation model of homogeneous droplets was developed and integrated into the solver to address the limitations of existing evaporation models, such as Raoult's law, under conditions near or beyond the critical point of SAFs. Validation was performed against microgravity experimental data for stationary heptane droplet evaporation at near- and super-critical conditions, demonstrating excellent agreement in evaporation curve slopes and droplet lifetimes. Further testing on multi-component SAF surrogates, showed strong agreement with high-fidelity Eulerian simulation data from the literature across various gas-turbine operating regimes. The preferential evaporation of volatile components and the corresponding impact on droplet lifetimes were effectively captured, highlighting the robustness and accuracy of the developed framework for high-pressure aerospace propulsion applications.@en

Sustainable Aviation Fuels (SAF) are being considered to replace current fuels, such as Jet A, to support the effort of industry and regulatory agencies to target the decarbonization of the aviation sector by 2050. Strict regulations on fuel properties, both in terms of applicability in current engines and in emission improvements (i.e., particulate matter control towards the reduction of contrails), require extensive analysis on the fuel thermophysical and chemical characteristics. The current lack of experimental data at engine-relevant pressure and temperatures for SAF candidates, motivates the exploration of accurate and robust models to capture the behavior of hydrocarbon mixtures at engine relevant conditions to support the development and deployment of net-zero carbon propulsion. This work showcases a data-driven approach based on a novel encoder-Gaussian process, which is designed to guarantee smoothness, comes with uncertainty quantification, and can incorporate physics-guided understanding as required. These capabilities are utilized for the modeling of thermophysical properties of pure species, including transcritical regimes while reducing the need for access to the critical properties. This effort arises from the shortcomings of both input properties availability and overall performance of previously investigated cubic equations of state. This paper introduces MeGS-RFM, a machine-learning based real-fluid modeling approach, and compares its performance with available databases and a volume- translated Soave-Redlich-Kwong equation of state. MeGS-RFM uses a generative modeling approach to generalize across species not available in the training datasets. Finally, we use this to demonstrate improved characterization of iso-paraffins relevant to aviation fuels, showing better agreement with the sparse datasets in open literature.@en

A proven methodology to solve multiphase flows is based on the one-fluid formulation of the governing equations, which treats the phase transition across the interface as a single fluid with varying properties and adds additional source terms to satisfy interface jump conditions, e.g., surface tension and mass transfer. Used interchangeably in the limit of non-evaporative flows, recent literature has formalized the inconsistencies that arise in the momentum balance of the non-conservative one-fluid formulation compared to its conservative counterpart when phase change is involved. This translates into an increased sensitivity of the numerical solution to the choice of formulation. Motivated by the fact that many legacy codes using the non-conservative one-fluid formulation have been extended to phase-change simulations, the inclusion of two corrective forces at the interface and a modification of the pressure-velocity solver with an additional predictor-projection step are shown to recover the exact momentum balance in the evaporative non-conservative one-fluid framework for low-viscosity incompressible flows. This has direct implications for obtaining a physically meaningful pressure jump across the interface and is seen to affect the dynamics of two-phase flows. In the high-viscosity domain, the discretization of the viscous term introduces a momentum imbalance which is highly dependent on the chosen method to model the phase transition. In the context of film boiling, this imbalance affects the time scales for the instability growth. Lastly, the need to develop sub-models for heat and mass transfer and for surface tension becomes evident since typical grid resolutions defined as “resolved” in the literature may not be enough to capture interfacial phenomena.@en

Sustainable Aviation Fuels (SAF) will gradually replace current fossil fuels (e.g., Jet A)over the next few decades to achieve the decarbonization goals of the aviation industry by2050. Despite efforts to design drop-in biofuels which meet specific fuel property requirements, uncertainties remain on the fuel behavior across the engine operating range. Typical chemical pathways to produce SAF result in simpler composition spectrums with potentially few mixture components. Thus, preferential evaporation may become important and affect the evaporation and subsequent combustion characteristics. Currently available experimental data focusing on Category C biofuels (i.e., SAF) from the National Jet Fuels Combustion Program (NJFCP) already shows preferential evaporation effects on the fuel distillation curve at atmospheric pressure. In this study, a computational framework based on a real-fluid thermo physical model is used to analyze the evaporation of Category C fueld roplets at various combustion chamber operating conditions. This includes low pressure –low temperature conditions (e.g., start-up, idle) and high pressure – high temperature environments (e.g., cruise, take-off).

@en