Prediction of bypass transition in hypersonic blunt-plate boundary layers subject to noisy conditions

TL;DR

This paper introduces a hybrid predictive framework combining linear and nonlinear stability analyses to accurately forecast bypass transition in hypersonic blunt-plate boundary layers under noisy conditions, validated against experimental data.

Contribution

It develops an integrated approach using SF-HLNS, NPSE, and BSA to predict transition onset, capturing complex nonlinear and secondary instability effects in hypersonic flows.

Findings

Successfully predicts transition-reversal phenomenon at large nose radii.

Achieves quantitative agreement with experimental transition locations.

Validates the framework's effectiveness in noisy hypersonic boundary-layer conditions.

Abstract

In hypersonic boundary-layer flows over blunt bodies, laminar-turbulent transition exhibits two distinct regimes: for small nose radii, increased bluntness delays transition; beyond a critical radius, further increasing bluntness reverses this trend. The latter regime corresponds to a bypass transition route, whose onset remains challenging to predict. The primary difficulty lies in capturing the excitation of non-modal streaks in the nose region, which is strongly affected by the bow shock and entropy layer effects. Recently, Zhao & Dong (J. Fluid Mech., 2025, 1013: A44) develops a high-efficient, high-accuracy shock-fitting harmonic linearised Navier-Stokes (SF-HLNS) approach to quantify the excitation of linear non-modal perturbations. In this paper, we present a predictive framework for bypass transition by integrating the SF-HLNS approach with the nonlinear parabolised stability equations (NPSE) and the bi-global stability analysis (BSA). The NPSE is employed to track the nonlinear evolution of the streaky perturbations up to nonlinear saturation, while the BSA approach is used to capture the high-growth secondary instabilities. By integrating the growth rates of these secondary instability from their neutral positions, an amplitude amplification factor is obtained, enabling the prediction of transition onset. Under slow-acoustic forcing conditions drawn from wind-tunnel experiments, the present hybrid framework successfully reproduces the transition-reversal phenomenon at large nose radii, and yields quantitative agreement with measured transition locations, thereby validating its predictive capability.