Illustration of laminar to turbulent flow transition over an aircraft wing.

Turbulence Tamed? New Model Offers Hope for Predicting Unruly Airflows

Jordan Keane in Tech & Innovation July 2025 • 4 min read.

"Aerospace engineers are one step closer to mastering the art of flight with a breakthrough in turbulence modeling."

For decades, accurately predicting the transition from smooth, laminar airflow to chaotic turbulence has been a major headache for engineers. While current RANS (Reynolds-Averaged Navier-Stokes) models work well for fully developed turbulence, they often stumble when predicting the crucial transition phase. This inaccuracy can lead to inefficiencies and safety concerns in various industrial applications, especially in aerospace.

Traditionally, researchers have relied on complex methods like eN, intermittency factors, and laminar turbulent kinetic energy approaches to tackle the transition problem. However, a recent study introduces an innovative approach, refining a turbulence model to better capture these elusive transitional flows.

This new model, an improved version of the Kinetic energy Dependent Only turbulence model (KDO), aims to bridge the gap between laminar and turbulent flow predictions. By incorporating "flow-structure-adaptive" parameters, the model dynamically adjusts to changing flow conditions, promising more reliable predictions for a wide range of applications.

How Does This New Model Tame Turbulence?

Illustration of laminar to turbulent flow transition over an aircraft wing.

The improved KDO model builds upon Bradshaw's assumption, extending it from free shear flows to wall-bounded flows. This allows the model to establish a new Reynolds stress constitution, crucial for accurately simulating turbulence. The model hinges on two key empirical coefficients: the Bradshaw function (T12/k) and the coefficient of the dissipation term. These coefficients are calibrated using the turbulent Reynolds number (Rek), which depends on the distance from the wall.

What sets this model apart is its use of "flow-structure-adaptive" parameters, such as the eddy viscosity ratio (r = μτ/μ). By replacing the traditional wall distance parameter with 'r', the model can naturally adapt to various transition phenomena. This adaptation is key to capturing the complex dynamics of airflow as it transitions from laminar to turbulent.

The improved KDO model was put through rigorous testing, including:

Classic bypass transition scenarios (T3A and T3B boundary layers)
Natural transition of the T3A boundary layer
Separation bubble induced transition on an Aero-A airfoil

The results of these assessments are promising. While the improved KDO model may not precisely capture every detail of the laminar-turbulent flow transition, it accurately predicts the onset locations of transition. This is a significant advancement, particularly for high Reynolds numbers and complex flows where different types of transition occur simultaneously. The model achieves this without relying on specific transition mechanisms, making it a robust and reliable tool for engineers.

The Future of Flight: Smoother, Safer, and More Efficient

This improved turbulence model represents a significant step forward in our ability to predict and control airflow. By accurately capturing the transition phase, engineers can design more efficient aircraft, reduce drag, and improve overall performance. While further refinement is always possible, the flow-structure-adaptive KDO RANS model offers a promising path towards taming turbulence and unlocking new possibilities in aerospace engineering.

About this Article -

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This article is based on research published under:

DOI-LINK: 10.1016/j.ast.2018.12.009, Alternate LINK

Title: Capturing Transition With Flow–Structure–Adaptive Kdo Rans Model

Subject: Aerospace Engineering

Journal: Aerospace Science and Technology

Publisher: Elsevier BV

Authors: Jinglei Xu, Ding Xu, Yang Zhang, Junqiang Bai

Published: 2019-02-01

Everything You Need To Know

What is the primary challenge that the new KDO RANS model aims to address?

The primary challenge addressed by the new Kinetic energy Dependent Only (KDO) Reynolds-Averaged Navier-Stokes (RANS) model is accurately predicting the transition from laminar to turbulent airflow. Current RANS models, while effective for fully developed turbulence, often struggle during this crucial transitional phase. This inaccuracy leads to inefficiencies and potential safety issues, especially in aerospace applications. The new model's 'flow-structure-adaptive' parameters are designed to overcome this limitation.

How does the new KDO model improve upon existing turbulence models?

The improved KDO model distinguishes itself by incorporating 'flow-structure-adaptive' parameters. Unlike traditional methods that rely on wall distance parameters, the new model utilizes the eddy viscosity ratio (r = μτ/μ). This allows the model to dynamically adjust to changing flow conditions. Furthermore, it extends Bradshaw's assumption, which was initially for free shear flows, to wall-bounded flows. This extension enables a new Reynolds stress constitution, improving simulation accuracy.

What are the key components and processes that the KDO model uses for turbulence prediction?

The improved KDO model hinges on two key empirical coefficients: the Bradshaw function (T12/k) and the coefficient of the dissipation term. These are calibrated using the turbulent Reynolds number (Rek), which is determined by the distance from the wall. The use of the eddy viscosity ratio, a 'flow-structure-adaptive' parameter, instead of the wall distance parameter, is key for adapting to various transition phenomena, enabling accurate predictions, particularly for high Reynolds numbers and complex flows.

What are the practical implications of more accurate turbulence modeling in aerospace engineering?

More accurate turbulence modeling, as achieved by the KDO model, has several practical implications. Firstly, it enables the design of more efficient aircraft. Secondly, the ability to accurately predict and control airflow during the transition phase can reduce drag, leading to improved fuel efficiency and reduced operational costs. Finally, improved turbulence prediction enhances overall aircraft performance and potentially increases safety by mitigating turbulence-related issues.

What specific transition scenarios were used to test the improved KDO model, and what were the outcomes?

The improved KDO model was rigorously tested on several transition scenarios. These included classic bypass transition scenarios (T3A and T3B boundary layers), the natural transition of the T3A boundary layer, and separation bubble-induced transition on an Aero-A airfoil. The results were promising, as the model accurately predicted the onset locations of transition, even though it might not capture every detail of the laminar-turbulent flow transition. This ability to predict transition onset without relying on specific transition mechanisms makes it a reliable tool for engineers in various applications, especially for complex flows.