Historically, combustion modeling is important for many transportation- and ground-based applications. More recently, modeling has been offered as an early screening tool in the evaluation of a potential alternative aviation jet fuel. This combustion evaluation path would in theory be conducted by gas turbine Original Equipment Manufacturers (OEMs) on proprietary geometries and conditions. Ideally, OEMs would have access to the latest combustion theory models and would thus have the highest predictive confidence in their model predictions. Unfortunately, the latest combustion theory codes are not written for commercial purposes. This work identifies and develops a conduit for OEM usage of latest flamelet theory for use in the evaluation of alternative jet fuel combustion properties. A so-called “common format routine” (CFR) software with two low-dimensional manifold combustion models that can be used for laminar and turbulent applications is developed, which can be implemented by OEMs on proprietary hardware. The two models are the flamelet prolongation of the intrinsic low-dimensional manifold (FPI), used for premixed combustion, and the flamelet progress variable (FPV), utilized for nonpremixed combustion. The three branches of combustion are computed using a hybrid tool that combines homotopic flamelet calculations with scaling laws and the two- and one-point flamelet continuation methods in order to resolve bifurcations. The mixture fraction and progress variable definitions can be chosen to be any summation of atomic and species composition, respectively. Diffusivity coefficients can be computed using unity Lewis number, mixture-averaged and multicomponent species composition. The turbulence-chemistry interaction is tabulated a priori using Beta probability density function (PDF) for the mixture fraction and Beta or Dirac-delta PDF for the progress variable. Parallel computing is necessary for industrial quality tabulation. The tabulated table can be used for k-ε and k-ω RANS, SAS, DES, and LES simulations. The software can also interact with liquid spray and exchange mass between the liquid and gaseous phase. The software is verified against previous numerical simulations of canonical triple flames, piloted flames and single-cup combustor. The numerical results are validated against experimental measurements of temperature and species mass fractions. The CFR software advances Cantera 2.3. Hence, the software contains an inner layer of C++ code, an intermediate layer of Python wrappers, and an upper layer (GUI) of C# code. The pre-tabulated chemistry is used for CFD simulations. The tables are bi-linearly interpolated for laminar simulations and tri-linearly interpolated for turbulent simulations. The tabulated chemistry can be hooked to commercial software such as Fluent through C and Scheme codes. The simulated flames presented here were computed with this software. The developed software is reliable for modeling and simulation of complex combustion phenomena.

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A numerical optimization study is performed on a small-scale high-swirl cavity-stabilized combustor. A parametric geometry is created in cad software that is coupled with meshing software. The latter automatically transfers meshes and boundary conditions to the solver, which is coupled with a postprocessing tool. Steady, incompressible three-dimensional simulations are performed using a multiphase Realizable k-ε Reynolds-averaged Navier-Stokes (RANS) approach with a nonadiabatic flamelet progress variable (FPV) model. There are nine geometrical input parameters. There are five output parameters, viz., pattern factor (PF), RMS of the profile factor deviation, averaged exit temperature, averaged exit swirl angle, and total pressure loss. An iterative design of experiments (DOE) with a recursive Latin hypercube sampling (LHS) is performed to filter the most important input parameters. The five major input parameters are found with Spearman's order-rank correlation and R2 coefficient of determination. The five input parameters are used for the adaptive multiple objective (AMO) optimization. This provided a candidate design point with the lowest weighted objective function, which was verified through computational fluid dynamic (CFD) simulation. The combined filtering and optimization procedures improve the baseline design point in terms of pattern and profile factor. The former halved from that of the baseline design point, whereas the latter turned from an outer peak to a center peak profile, closely mimicking an ideal profile. The exit swirl angle favorably increased 25%. The averaged exit temperature and the total pressure losses remained nearly unchanged from the baseline design point.

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