Relevance of Modern Optimization Methods in Turbo Machinery Applications



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Relevance of Modern Optimization Methods in Turbo Machinery Applications - From Analytical Models via Three Dimensional Multidisciplinary Approaches to the Optimization of a Wind Turbine - Prof. Dr. Ing. M. Geller Dipl. Ing. C. Schemmann Dipl. Ing. N. Kluck

Relevance of Modern Optimization Methods in Turbo Machinery Applications Presented by the Research Center Computer Simulation in Mechanical Engineering Partner of the

Relevance of Modern Optimization Methods in Turbo Machinery Applications In nearly every case turbomachinery is an essential component for energy conversion.

Relevance of Modern Optimization Methods in Turbo Machinery Applications Motivation Important component for energy conversion Energy efficiency is a global problem Complex physical phenomena High computational expense Efficient optimization strategies are essential!

Relevance of Modern Optimization Methods in Turbo Machinery Applications CONTENTS ONE DIMENSIONAL RADIAL IMPELLER OPTIMIZATION THREE DIMENSIONAL RADIAL IMPELLER OPTIMIZATION THREE DIMENSIONAL TURBINE OPTIMIZATION OPTIMIZATION OF A VERTICAL AXIS WINDTURBINE

One Dimensional Radial Impeller Optimization One Dimensional Radial Impeller Optimization Goal: Prediction of the operation characteristic of a single stage radial compressor with loss modells for every machine component. Results: Operation Characteristic Pressure ratio Mass flow rate

Loss Models One Dimensional Radial Impeller Optimization Volute Losses: Skin Friction Loss Meridional velocity head dissipation Loss Tangential velocity head dissipation Loss Impeller Losses: Blade Loading Loss Hub to Shroud Loss Blockage Loss Supercritical Mach Number Loss Skin Friction Loss Slip Trailing Edge Losses: Wake Mixing Loss Recirculation Loss Impeller Throat Loss: Choking Loss Inlet Passage Loss: Choking Loss Inflow Vaned Diffuser Losses: Skin Friction Loss Blockage Loss Blade Loading Loss Leading Edge Incidence Loss Throat Choking Loss Trailing Edge Wake Mixing Loss Leading Edge Losses: Incidence Loss Diffusion Loss P mech,p E,T E, Outflow p A, T A, Vaneless Diffuser / Passage Losses: Skin Friction Loss Diffusion Loss Blockage Loss Curvature Loss

One Dimensional Radial Impeller Optimization Optimization 14 input parameters Fast calculation: less then one minute per design point A direct optimization with an evolutionary algorithm can be used!

One Dimensional Radial Impeller Optimization Results Optimization Design of an optimal stage with N = 21120 rev/min Impeller diameter = 340 mm Pressure ratio > 2 Due to numerical instabilities at stall and choke operation a single point optimization at operation condition is preformed. Start Design Optimal Design Pressure Ratio 2.40 2.47 Efficiency 79% 85% A rise of 6 points in efficiency can be obtained by a fast method!

One Dimensional Radial Impeller Optimization Results CFD Validation (Complete Stage, ~25 Mill. Elements, High Fidelity CFD)

One Dimensional Radial Impeller Optimization Results Comparison of one dimensional and CFD compressor characteristic The one dimensional and the CFD model show good correlation.

Relevance of Modern Optimization Methods in Turbo Machinery Applications CONTENTS ONE DIMENSIONAL RADIAL IMPELLER OPTIMIZATION THREE DIMENSIONAL RADIAL IMPELLER OPTIMIZATION THREE DIMENSIONAL TURBINE OPTIMIZATION OPTIMIZATION OF A VERTICAL AXIS WINDTURBINE

Three Dimensional Radial Impeller Optimization Three Dimensional Radial Impeller Optimization Challenges: Impeller design with critical operation point single stage design, pressure ratio ~2,4 0,9 < Mach-Number < 1 Complex flow field High mechanical loads Machanical strength Errors in design have disastrous consquences

Three Dimensional Radial Impeller Optimization Examples for Impeller Damage

Three Dimensional Radial Impeller Optimization Startdesign with N = 20.000 rev/min Startdesign generated with 1D design tool (pure fluid mechanic design) Output Pressure Ratio Value Π 2.4 Optimization goal: Lower the stress while retaining the good aerodynamic behaviour! Polytrophic Efficiency 87% Maximum Equivalent Stress >

Three Dimensional Radial Impeller Optimization Model Robust geometry definition Solid geometry based on fluid geometry 29 geometric parameters Arbitrary impeller designs can be modeled!

Three Dimensional Radial Impeller Optimization Process Generation and Export of Samples Geometry generation and meshing (no calculations) FEA calcualtions parallelized on several workstations CFD calculations parallelized on LiDOng Cluster (1778 Cores) Re-import and evaluation of the results

Three Dimensional Radial Impeller Optimization Sensitivity Reduction of input parameters from 29 to 14!

Three Dimensional Radial Impeller Optimization Results Optimum

Three Dimensional Radial Impeller Optimization Summary Optimization with 560 Samples Optimal impeller: 0,95 416 Π 2,4 84 %

Relevance of Modern Optimization Methods in Turbo Machinery Applications CONTENTS ONE DIMENSIONAL RADIAL IMPELLER OPTIMIZATION THREE DIMENSIONAL RADIAL IMPELLER OPTIMIZATION THREE DIMENSIONAL TURBINE OPTIMIZATION OPTIMIZATION OF A VERTICAL AXIS WINDTURBINE

Three Dimensional Turbine Optimization Three Dimensional Turbine Optimization 3d CFD optimization of a Turbine stage

Three Dimensional Turbine Optimization Modelling Fully parameterized aerofoils for impeller and guide vanes Twisted blades 7 parameters per aerofoil Interaction of impeller and guide vanes taken into account

Three Dimensional Turbine Optimization Results Strong wake in the whole stage Polytrophic efficiency of 73% Pressure ratio of 0.87 Shroud Middle Hub Baseline Geometry

Three Dimensional Turbine Optimization Results Nearly no wake Polytrophic efficiency of 89% Pressure ratio if 0.81 Shroud Middle Hub Optimized Geometry

Three Dimensional Turbine Optimization Results Comparison of the optimal design with existing machines Good correlation of the blade design Helicopter engine Small plane engine

Relevance of Modern Optimization Methods in Turbo Machinery Applications CONTENTS ONE DIMENSIONAL RADIAL IMPELLER OPTIMIZATION THREE DIMENSIONAL RADIAL IMPELLER OPTIMIZATION THREE DIMENSIONAL TURBINE OPTIMIZATION OPTIMIZATION OF A VERTICAL AXIS WINDTURBINE

Optimization of a Vertical Axis Windturbine Introduction Advantages of Vertical Axis Wind Turbines (VAWT): Lower cost compared to horizontal axis wind turbines Independent of wind direction Good efficiency for lower wind speeds

Optimization of a Vertical Axis Windturbine Theory Mechanical Power: 1 2 1 2 1 1 with deceleration ratio Power coefficient: 1 2 1 1 Theoretical maximum for, 0,593 (Betz Law)

Optimization of a Vertical Axis Windturbine Theory Theoretical and actual power coefficients for different wind turbines

Optimization of a Vertical Axis Windturbine Motivation Prediction with analytical methods is very vague CFD approach needed Unsteady flow Transient simulations are required Large scale machinery High grid size High computational expense Solution: A high-quality metamodel admits efficient optimizations!

Optimization of a Vertical Axis Windturbine Modelling camber line Parameterization according to Aerofoil Theory: chord line Relative thickness Relative camber Relative distance of maximum thickness from the leading edge Relative distance of maximum camber from the leading edge Relative leading edge radius Relative trailing edge radius

Optimization of a Vertical Axis Windturbine Modelling Variation of the aerofoil geometry Further parameters: Wind turbine diameter Aerofoil size ratio Wind speed

Optimization of a Vertical Axis Windturbine Modelling up to 120m up to 80m up to 10m 100 to 700mm Different geometric scales have to be represented by the grid High grid size

Optimization of a Vertical Axis Windturbine Process Design Parameters 2D Aerofoil Generation Results Geometry and Grid Generation, CFD Computation 2D Aerofoil

Optimization of a Vertical Axis Windturbine Results Flow field for one rotor revolution (As seen in video, video can be provided on request)

Optimization of a Vertical Axis Windturbine Results MLS Approximation of the Efficiency / Power Output based on the Meta Model of optimal Prognosis (MoP) High CoP for both Efficiency and Power Output (CoP = 91%) (CoP = 84%)

Optimization of a Vertical Axis Windturbine Results Validation of the metamodel against CFD calculations

Optimization of a Vertical Axis Windturbine Results Validation of the metamodel against an existing Machine Aerofoil type NACA 0021 Aerofoil length 250 mm Number of wings 3 Rotor radius Rotor height 3 m 5 m Tip speed ratio 4 Nominal wind speed Nominal Power Output 12 m/s 12 kw Marsta-VAWT Uppsala

Optimization of a Vertical Axis Windturbine Results Validation of the metamodel against an existing Machine 14 12 10 Operation characteristic predicted by MoP Power Output [kw] 8 6 4 2 Measured point 0 0 2 4 6 8 10 12 14 Wind Speed [m/s] Marsta-VAWT Uppsala

Optimization of a Vertical Axis Windturbine Results FEA Frequency Anlysis First critical frequency occurs at 132rpm Nominal operation range: 50 100rpm Safe Operation can be guaranteed!

Optimization of a Vertical Axis Windturbine Summary 200 CFD Designs calculated Metamodel with high CoP Metamodel validated with additional CFD caluclations Metamodel validated against existing machines Operation characteristics of arbitrary machines can be predicted natively in optislang without further CFD Simulations!