In the present study, Gene Expression Programming (GEP) will be used for training a model for subgrid scale (SGS) scalar dissipation rate (SDR) for a large range of filter widths, using a database of statistically planar turbulent premixed flames, featuring different turbulence intensities and heat release parameters. GEP is based on the idea to iteratively improve a population of model candidates using the survival-of-the-fittest concept. The resulting model is a mathematical expression that can be easily implemented, shared with the community and analyzed for physical consistency, as illustrated in this work. Efficient evaluation of the cost function and a smart choice of basis functions have been found to be essential for a successful optimization process. The GEP based model has been found to outperform an existing algebraic model from the literature. However, the optimization process was found to be quite intricate and the SGS SDR closure turned out to be difficult. Some of these problems have been explained using the model-agnostic interpretation method which requires the existence of a trained artificial neural network (ANN). ANNs are known for their ability to represent complex functional relationships and serve as an additional benchmark solution for the GEP based model.
The non-reactive and reactive flows through a model scramjet were investigated using a Improved Delayed Detached Eddy Simulation(IDDES), which is one of the hybrid schemes of Reynold averaged Navier-Stokes equation and large eddy simulation, and flamelet combustion model. Geometries and boundary conditions of scramjet combustor conducted by DLR, German Aerospace Center were considered. The model scramjet combustor consists of 15 holes for hydrogen injection located on the base of a wedge shaped fuel injector providing hydrogen at sonic speed. In this paper, only one of the 15 injection holes was considered, and periodic condition is applied in the spanwise dirction. The parametric studies were conducted with a view to invesitigate better numerical configurations, for example, MUSCL or WENO as convective flux schemes and k-ω SST or IDDES as turbulence models with steady flamelet combustion model. The combination of WENO and IDDES provides best one for reacting case.
NomenclatureD k = turbulent kinetic energy destruction term E = specific total energy f = mixture fraction h = specific enthalpy k = turbulent kinetic energy l = length scale M t = turbulent mach number p = static pressure P k = turbulence kinetic energy production term q j = specific heat flux t = time T = temperature u = velocity x = spatial coordinate Y = species mass concentraion δ ij = Kronecker delta μ = molecular viscosity μ t = turbulent viscosity ρ = density τ ij = viscous stress tensor ω = turbulent frequency Superscripts ‾ = time averaged quantity ~ = Favre averaged quantity 1 Graduate Research Assistant, School of Aerospace and Mechanical Engineering 2 Professor, School of Aerospace and Mechanical Engineering; hgsung@kau.kr. Associate Fellow AIAA Downloaded by UNIVERSITY OF ILLINOIS on October 1, 2015 | http://arc.aiaa.org |
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.