LES Working Group
Traditional scientific and engineering approaches have taken us far – efficiencies have been increased and pollutant release has been decreased. However, it is known that, in principle, combustion can be even more efficient and cleaner. We are now at a point where we must utilize simulation-based optimization strategies to find the best possible combustion strategies; combustion strategies that we cannot find without the targeted use of predictive simulation tools. And such tools are, unfortunately, not quite yet ready.
A concerted experimental and numerical effort is undertaken to understand and describe the nature of stochastic processes in internal combustion engines. The overall goal is to develop physics-based computational tools for a more effective design of combustion engines of the future.
The nature and cause of cyclic variability in engines is not yet fully understood but their importance in developing advanced engine concepts keeps increasing. Giving automotive engineers design tools to predict cyclic variability, and more generally unsteady engine phenomena like warm-up or engine transients, can be viewed as a major challenge for a more effective design of combustion engines of the future. Experimental efforts alone are not sufficient to fully explore the many facets of cycle-to-cycle fluctuations, and therefore Computational Fluid Dynamics (CFD) simulations appear as the best candidate for providing such a design tool. A suitable candidate is the Large Eddy Simulation (LES) technique. Identifying and solving the underlying fundamental flow physics will be the key to success in understanding the stochastic nature of in-cylinder flow – this, in turn, is required to develop practical first-principles-based predictive computational LES design tools for robust and reliable industrial use.In this study, low-, medium-, and high-resolution LES approaches are being pursued in parallel to address these needs. High-resolution LES (minimal subgrid-scale modeling, approaching DNS; >108 cells per cylinder) is being used for physics discovery and model development/validation. Low-resolution LES (RANS-like resolution; currently 105-106 cells per cylinder) is being used for engineering development and applications. Medium-resolution LES (currently 106-107 cells per cylinder) bridges these two extremes. Mesh sizes and the number of cycles that are simulated will increase with time.Optical single-cylinder engines were specifically designed, built, and characterized for LES model development and validation. Optical, including laser-based, imaging tools are available to measure flow and scalar quantities with high spatial and temporal resolution. In particular, the use of high-speed imaging tools enables recording of the evolution of flow structures through a cycle and from cycle to cycle.The intent of this program is to create an interactive collaboration between the modeling and experimental efforts that will identify and execute the experiments and models needed to produce physically based LES models with sufficient fidelity for research and engineering applications.
A concerted experimental and numerical effort is undertaken to understand and describe the nature of stochastic flows in internal combustion engines. The overall goal is to develop physics-based computational tools for a more effective design of combustion engines of the future. An optical engine was developed for the specific purpose of supporting the development and validation of a range of LES approaches. The engine features a two-valve head with simple intake and exhaust port/runner geometries and a pancake-shape combustion chamber. The overall optical access is maximized to allow acquisition of three-dimensional in-cylinder flow fields and the investigation of near-wall, boundary layer flows. Experimental data are acquired with optical multi-dimensional high-speed diagnostics techniques. In addition, the engine is fully instrumented with pressure and temperature sensors for high-fidelity measurements of boundary conditions.
Tang-Wei Kuo (GM), David Reuss (UM), Volker Sick (UM), Chris Rutland (UW-Madison), Dan Haworth (Penn State), Joe Oefelein (Sandia).
The "TCC Engine Details" page provides details about engine geometry, stl files, GT Power model, etc. for free download. Some of that information is mirrored at the Engine Combustion Network
Those interested in utilizing more experimental data for model development and/or validation please contact Volker Sick.