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This chapter presents a novel indicator capable of characterizing pressure gradients and sensing turbulent fluctuation intensity at the boundary layer edge, while satisfying Galilean invariance. Leveraging direct numerical simulation (DNS) data, prediction models for both bypass transition and separation-induced transition are developed in RANS framework. The accuracy and universality of these models have been rigorously validated through extensive wind tunnel experiments on benchmark test cases.

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Prediction Model for Bypass Transition and Separation-Induced Transition

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  • 发表日期：

    2025年

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  • Jiakuan Xu,
  • Min Chang,
  • Junqiang Bai

摘要

This chapter presents a novel indicator capable of characterizing pressure gradients and sensing turbulent fluctuation intensity at the boundary layer edge, while satisfying Galilean invariance. Leveraging direct numerical simulation (DNS) data, prediction models for both bypass transition and separation-induced transition are developed in RANS framework. The accuracy and universality of these models have been rigorously validated through extensive wind tunnel experiments on benchmark test cases.