An assessment of the two-layer quasi-laminar theory of relaminarization through recent high-Re accelerated TBL experiments

Rajesh Ranjan; Roddam Narasimha

Home/Archive/arXiv

arXiv · 1701.08077

An assessment of the two-layer quasi-laminar theory of relaminarization through recent high-Re accelerated TBL experiments

Rajesh Ranjan·Roddam Narasimha

View original source ↗Read source document ↗Export metadata ↓

Abstract

The phenomenon of relaminarization is observed in many flow situations, including that of an initially turbulent boundary layer subjected to strong favourable pressure gradients. Available turbulence models have hitherto been unsuccessful in correctly predicting boundary layer parameters for such flows. Narasimha and Sreenivasan \cite{narasimha1973relaminarization} proposed a quasi-laminar theory (QLT) based on a two-layer model to explain the later stages of relaminarization. This theory showed good agreement with the experimental data available, which at the time was at relatively low $Re$. QLT, therefore, could not be validated at high $Re$. Some of the more recent experiments report for the first time comprehensive studies of a relaminarizing flow at relatively high Reynolds numbers (of order $5\times 10^3$ in momentum thickness), where all the boundary layer quantities of interest are measured. In the present work, the two-layer model is revisited for these relaminarizing flows with an improved code in which the inner-layer equations for quasi-laminar theory have been solved exactly. It is shown that even for high-$Re$ flows with high acceleration, QLT provides a much superior match with the experimental results than the standard turbulent boundary layer codes. This agreement can be seen as strong support for QLT, which therefore has the potential to be used in RANS simulations along with turbulence models.

Explore related subjects

physics.flu-dyn

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Rajesh Ranjan, Roddam Narasimha. 2017-01-27. An assessment of the two-layer quasi-laminar theory of relaminarization through recent high-Re accelerated TBL experiments. https://arxiv.org/abs/1701.08077

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Bayesian neural network correction of RANS turbulence models with uncertainty quantification in separated flows

Data-driven correction of turbulence models offers a promising route for improving Reynolds-averaged Navier-Stokes (RANS) predictions, but quantifying uncertainty in such corrections and ensuring generalization across flows remain key challenges. This work presents a Bayesian neural network (BNN) framework for uncertainty-aware correction of RANS models. The BNN represents both epistemic and input-dependent aleatoric uncertainty, interpreted here as irreducible scatter in the feature-to-correction relationship, with the latter propagated as spatially correlated fields through the RANS solver. The framework is trained exclusively on a periodic-hill configuration and evaluated without retraining on five unseen separated-flow configurations. The learned corrections improve the training-flow prediction, but the strong momentum-field benefit obtained from the anisotropy correction does not transfer consistently to the unseen flows. Out-of-distribution under-coverage is already present at the correction-field level, indicating that the loss of calibration is already present in transfer of the learned correction rather than being introduced primarily by CFD propagation. Overall, the framework enables joint propagation of epistemic and aleatoric uncertainty while exposing the present limitations of uncertainty calibration under distribution shift.

physics.flu-dyn↗

arXiv2026

Direct numerical simulation of particle-laden flow in a linear compressor cascade: Unsteady boundary-layer effects on particle-blade interactions

We perform point-particle direct numerical simulations (PP-DNS) of particle-laden flow through a linear compressor cascade subjected to synthetic free-stream turbulence. Monodisperse particles are advanced in a one-way coupled Eulerian-Lagrangian framework with drag-only dynamics. We use PP-DNS collision statistics together with empirical deposition and erosion models to estimate particle deposition and blade erosion. Collision hotspots and regions of predicted deposition are identified near the leading edge and over the pressure side. On the pressure side, for the intermediate Stokes number, the onset of frequent collisions and predicted deposition is spatially associated with elevated boundary-layer intermittency during bypass transition. Nevertheless, for the largest particles, impacts occur farther upstream. On the suction side, sparse collisions and predicted deposition events appear only for the smallest particles and are phase-modulated by separation-induced vortex shedding. Joint distributions of impact velocity and angle show that leading-edge impacts are faster and span wider angles than pressure-side impacts. For the two larger particle sizes, the higher normal impact velocities near the leading edge result in a greater likelihood of rebound than on the pressure side. Therefore, appreciable erosion is predicted primarily near the leading edge under the present conditions. The present results highlight the role of unsteady boundary-layer dynamics in affecting particle-blade interactions in compressor cascades.

physics.flu-dyn↗

arXiv2026

Diffusion Enhancement and Directional Suppression Induced by Reciprocal Flows

Reciprocal flows repeatedly return fluid elements to their initial positions, producing no net advective transport on time average. Nevertheless, their interplay with diffusion gives rise to nontrivial transport. To describe this phenomenon, we develop a general theory of effective diffusion under two-dimensional linear flows with arbitrary time dependence. By analyzing the advection-diffusion equation, we derive exact expressions for the mean square displacement and the effective diffusion coefficients for extensional, simple shear, and rotational flows within a single framework. We show that the reciprocal flows universally induce diffusion enhancement. The diffusion tensor exhibits pronounced anisotropy, which can result in directional diffusion suppression in spite of the direction-averaged diffusion enhancement. Our results provide a general framework for diffusion control by time-dependent flows and can provide new strategies for transport manipulation in microfluidic and biological systems.

physics.flu-dyn↗