Cost Effective Gas Turbine Simulation

Transcription

1 Cost Effective Gas Turbine Simulation Defence Education Conference - Athens GR - 1 June 2017 War Museum Ioannis Templalexis Associate Professor (elected) Hellenic Air Force Academy Department of Aeronautical Sciences Division of Thermodynamics, Propulsion and Power Systems

2 Context Why do we need to model and simulate gas turbine operation? During Design During operation Get the engine built as prescribed the soonest possible spending the minimum of resources Operate the engine safely in a cost effective manner

3 Increasing dimensions Methods Palette Increasing complexity 0-D analysis Zooming methods Mean line analysis 2-D Potential flow methods 3-D Potential flow methods Through-flow methods 3-D Euler methods Genetic Algorithms 3-D RANS 2-D Euler LES methods DNS methods Challenge: Get the optimum combination of resource investment against accuracy needed.

4 Methods Palette Design context Cost effective Cost ineffective Low Fidelity Low Computational Time 0-D or 1-D Analysis Intermediate Fidelity Relatively Low Computational Time 2-D Analysis Viscous free flow High Fidelity High Computational Time Full 3-D Analysis Initial Specifications Engine Testing Final Product Engine Development Road Map

5 User 0D 2D non viscous methods - Cost effective Methods Palette Operation context Mission Analysis OEM 3D viscous methods Cost ineffective Re-design Evaluation of Upgrades Health Monitoring

6 Socrates Synthesis Of Correlations for the Rapid Assessment of Turbomachine Engine Systems Produces two dimensional flow solution based on Streamline Curvature method. Boundary Conditions Inviscid solution core Empirical models Viscous equivalent flow solution Compressor Geometry

7 Socrates Inviscid Solution Full radial equilibrium equation considered along quasi-normal curves. Pseudo force terms included. Incorporation of dynamic convergence schemes with variable tolerance. Empirical Models Profile loss: Bucket shaped curves (incidence vs profile loss) positioned based on flow Mach number level. Shock loss: Advanced loss model based on predicted shock pattern. Deviation angle: Separate individual components considered due to off design operation superimposed on the minimum loss value. Boundary layer: Simplified end wall boundary layer model. Boundary layer shape parameters are defined from an integral approach based on meridional velocity along the boundary layer edge. Biggest Challenges Shock wave pattern handling. Chocked flow handling. Boundary layer handling

8 Validation Performance Maps

9 Validation Velocity Profiles

10 Flexibility in Adaptation Cost effective 2-D Analysis Viscous free flow Initial Specifications Engine Testing Through-Flow coupled with optimizer Through-Flow coupled with 0-D Through-Flow throughout the engine. Design optimization studies Assess the impact of designs on engine performance Design refinements before sending it to CFD.

11 SFC [gr/(kn s)] Socrates - Proosis SFC-0D SFC_2D FN [N]

12 Methods Pallet Operation context Through-Flow coupled with 0-D. Mission analysis with degraded engine and distorted inlet profiles. Mission Analysis Redesign Evaluation of Upgrades Health Monitoring Through-Flow coupled with 0-D. Introduce detailed degradation in order to define more accurate indices

13 Through-Flow methods as educational tool INPUTS EDUCATIONAL TOOL OUTPUTS Geometry Inlet Boundary Conditions SLC Software Performance Characteristic Map Radial Profiles

14 Instead of Conclusions Through-flow methods based computational tools, multiply the value of experimental results. Through-flow methods based computational tools, take advantage of increased computational power to increase accuracy and cover more applications. Through-flow methods based computational tools, exhibit great adaptability characteristics helping you to exploit better the resources according to the needs. Through-flow methods based computational tools, could consist the core of impressive educational tools regarding engine component design.