fluet-Nov-2003.ppt

FLUENT CFD Conference 2003 Using FLUENT in Design Optimization Devendra Ghate, Amitay Isaacs, K Sudhakar, A G Marathe, P M Mujumdar Outline CFD in design Problem statement Duct parametrization Flow solution Results Conclusion Using CFD in Design Simulation Time CFD is takes huge amounts of time for real life problems Design requires repetitive runs of disciplinary analyses Integration With optimizer With other disciplinary analyses (e.g. grid generator) Automation No user interaction should be required for simulation Gradient Information No commercial CFD solvers provide gradient information Computationally expensive and problematic ( ) to get gradient information for CFD solvers (finite difference, automatic differentiation) Methodology Methodology 3-D Duct Design Problem Parametrization Parametrization (contd.) Typical 3D-Ducts Grid Generation Turbulence Modeling Relevance: Time per Solution Following aspects of the flow were of interest: Boundary layer development Flow Separation (if any) Turbulence Development Literature Survey Doyle Knight, Smith, Harloff, Loeffer Circular cross-section S-shaped duct Baldwin-Lomax model (Algebraic model) Computationally inexpensive than more sophisticated models Known to give non-accurate results for boundary layer separation etc. k-? realizable turbulence model Two equation model Study by Devaki Ravi Kumar Sujata Bandyopadhyay (FLUENT Inc.) Turbulence Modeling (contd.) Standard k-? model Turbulence Viscosity Ratio exceeding 1,00,000 in 2/3 cells Realizable k-? model Shih et. al. (1994) Cμ is not assumed to be constant A formulation suggested for calculating values of C1 Cμ Computationally little more expensive than the standard k-? model Distortion Analysis DC60 = (PA0 – P60min) /q where, PA0 - average total pressure at the section, P60min - minimum total pressure in a 600 sector, q - dynamic pressure at the cross section. User Defined Functions (UDF) and scheme files were used to generate this