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In this chapter, we show how to use optimization to evaluate design studies with many variables. The two numerical optimization methods available in GasTurb (using gradient or random search algorithms) are described, with clear illustrations of the difference between local and global optima. Advice is given on the use of constraints and on the definition of the figure of merit when a study has multiple objectives.

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Optimization

  • 章节

  • 发表日期：

    2025年

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  • Joachim Kurzke,
  • Ian Halliwell,
  • Robert Hill

摘要

In this chapter, we show how to use optimization to evaluate design studies with many variables. The two numerical optimization methods available in GasTurb (using gradient or random search algorithms) are described, with clear illustrations of the difference between local and global optima. Advice is given on the use of constraints and on the definition of the figure of merit when a study has multiple objectives.