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Direkt zum Inhalt

4. Metamodeling

For CFD, FEM, and Look-up Tables.

 

Benefits of Local Model Network Architecture

 

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  • Distinction between rule premises (if…) and rule consequents (then…)
  • Easy to interpret
  • Well suited for high-dimensional input spaces
  • Gained knowledge about premises and consequents can be used for DoE designs


Artificial Example
 

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AiF Project in cooperation with the Institute of Fluid- and Thermodynamics

(AiF: Arbeitsgemeinschaft industrieller Forschungsvereinigungen)

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  • Problem: New EU regulation requires higher degree of efficiency for ventilators
    • Most existing ventilators will be prohibited
    • New efficient dimensioning and optimization strategies required
  • Computational Fluid Dynamic (CFD) models fulfill accuracy requirements, but:
    • Many evaluations necessary for optimization
    • Computationally very expensive
    • Economically unviable!
  • Approach to solving the problem:
    • Metamodel: Model of the CFD model
    • CFD model generates data set
    • Local model network (LMN) is used


Local Model Network Advantages for the AiF Project Tasks
 

System Identification

  • Automatic model complexity determination saves data for the training
    • Akaike’s corrected information criterion (AICc) instead of validation data
  • Deterministic training procedure (no initialization required)
     

Design of Experiments

  • Active learning strategy
    • Structure of LMN is utilized to determine future CFD simulations
  • Exploitation of separation between linear and nonlinear effects
     

Optimization

  • Local quadratic models can be used
  • Very likely to find global optimum of the LMN
    • M local models => M reasonable initialization points

 

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Construction of Centrifugal Fan

Computational fluid dynamics (CFD) simulations utilized (~4 hours per simulation)

  • Target values
    • Pressure curve and efficiency curve
  • Design parameters
    • Number of blades, inner and outer diameter, several angles, etc.
       
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Two Metamodeling Approaches
 

1. Direct Metamodeling

 

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  • 10 inputs: Geometric parameters and volume flow.
  • 2 outputs: Efficiency and pressure.


2. Indirect Metamodeling via Characteristic Curves

 

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  • 9 inputs: Geometric parameters.
  • 3 or 4 outputs: Characteristic parameters of efficiency and pressure curves.


Characteristic Curve Model 

  • 3 or 4 inputs: Characteristic parameters (metamodel outputs).
  • 2 outputs: Efficiency and pressure.

 

CFD (black line), Indirect (MIMO, blue line), Indirect (multiple MISO, green line), Direct (red line)
 

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