Integrated RANS-LES Computations of Turbomachinery Components: Generic Compressor/Diffuser
Abstract
The goal of the ASCI project at Stanford is the computation of the entire aero-thermal flow in an aircraft gas turbine engine. As part of the project, high performance flow solvers are developed to address the prediction of the flow in components of the turbine. For the turbomachinery parts, a flow solver based on Reynolds-Averaged Navier-Stokes (RANS) approach is used. This flow solver is validated on a variety of turbomachinery applications (Davis et al. 2002; Davis et al. 2003) and is scalable to run on a large number of processors in parallel, a feature necessary in light of the enormous task of the final application. For the prediction of the reacting flow in the combustion chamber, a flow solver based on Large Eddy Simulations (LES) is used. The strongly detached flow in the combustor requires that the numerical approach has to resolve the large scale turbulence in time and space in order to predict the flow features accurately. Furthermore, the temporal resolution of the flow is very beneficial for the modeling of the reactive flow. This makes LES much more suitable for this portion of the flow path. An LES flow solver capable of modeling the variety of physical phenomena, such as turbulence, spray and heat release is currently under development and in the process of validation (Mahesh et al. 2001 Constantinescu et al. 2003). In order to predict multi-component phenomena, such as compressor-combustor instability, combustor-turbine hot-streak migration and combustion instabilities, these RANS and LES flow solvers have to run simultaneously, each computing its part of the gas turbine. At the interfaces of the individual domains, the flow solvers have to communicate the flow parameters required to evaluate appropriately defined boundary conditions.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 2003
- Accession Number
- ADP014817
Entities
People
- H. Pitsch
- J. J. Alonso
- J. U. Schluter
- Seungchan Kim
- Xinghua Wu