Design Optimization

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The optimization of an existing design can often be achieved at relatively low costs. In fact, it is a good example where the use of CFD simulations can be very helpful. An in-depth analysis using 3D CFD allows insight into the flow and heat transfer characteristics. For the experienced engineer, these simulation results reveal potential for optimization. Small modifications to the design may, for example, reduce the pressure loss or help to enhance the cooling efficiency.

Where a large number of variables is involved or multiple objectives exist for the optimization (e.g. maximum heat transfer at minimum pressure loss), the use of automated optimization methods may be reasonable. These methods can also be advisable for situations where the impact of a design modification is not straightforward. For such scenarios, we use sophisticated genetic algorithms that mimic natural evolution following the principle Survival of the Fittest. The genetic algorithm is then coupled to CFD computations for a fully automatic optimization with respect to the defined target function.

At Tplus Engineering GmbH, we distinct between the following optimization strategies:

  • Design optimization based on analysis of CFD simulations with respect desired improvement (e.g. flow or cooling efficiency)
  • Automated optimization methods based on genetic algorithms for investigation of large numbers of design variationsand single or multiple target functions