Comparing Scalar and Conjugate Heat Transfer Modelling

We recently announced that Conjugate Heat Transfer (CHT) modelling is now available in bramble. This was a significant enhancement for users modelling thermally coupled systems.
-The CHT announcement post-

To demonstrate the value of this new capability, we conducted a short comparative CFD study evaluating the performance of bramble’s existing Scalar Transport (ST) approach against the more physically coupled CHT model using the AeroSUV geometry at multiple vehicle speeds.

This study highlights the limitations of simplified thermal modelling under certain conditions, and illustrates why CHT is essential when buoyancy effects become non-negligible.

An overview of scalar transport vs. conjugate heat transfer modelling

bramble‘s Scalar Transport (ST) implementation provides a first-order approximation of heat transfer, where energy transport is computed directly from the resolved flowfield. This simplification is valid for conditions dominated by forced external convection, such as high-speed vehicle operation, where temperature gradients have little influence on the external aerodynamics.

However, vehicles often operate in low-speed regimes, including urban traffic, idling at traffic lights, or during hot-soak scenarios, where natural convection becomes significant. Under such conditions, temperature-induced density gradients lead to buoyancy-driven flows, which affect local and global airflow patterns.

These phenomena cannot be captured using the decoupled ST model. CHT, by solving both the energy and momentum equations in a coupled manner, is capable of representing these buoyancy-driven interactions accurately.

Relevance of low-speed conditions

Many important vehicle thermal management scenarios occur at low speeds, where buoyant effects play a dominant role. For example, the EPA FTP city drive cycle, characterised by frequent starts, stops, and low average velocity, is commonly used for thermal validation and regulatory assessments.

Key findings

1. Divergence of results at low speeds

At higher speeds, the flow is dominated by forced convection, and the ST model produces results that are in closer agreement with CHT. However, as speed decreases, buoyancy-induced flow begins to influence thermal behavior, and ST and CHT predictions begin to diverge.

For example:

• At low speed, CHT predicted 13% more heat rejection from the engine bay and 39% more from the exhaust system, compared to ST.
• These differences diminish at higher speeds, where convective forces dominate buoyancy.

2. Flowfield differences due to buoyancy effects

Flow visualisation revealed distinct differences in the flow behaviour within the engine bay and underbody regions:

• At 10 kph and 25 kph, thermal pockets and recirculation zones were more prominent in the CHT model, while the Scalar Transport model showed less signifcant features.
• Buoyant plumes from hot components altered the flowfield, reducing effective convective cooling, especially noticeable in the exhaust region, where CHT predicted less heat rejection to the ambient due to the formation of thermal wakes.

Conclusion

This study reinforces the importance of selecting the appropriate thermal modeling approach based on operating conditions:

Low speed scenarios

•  For low-speed or thermally dominated conditions, such as urban driving, idle cooling, or hot-soak behaviour, CHT is essential to capture the coupled interaction between heat transfer and fluid motion.

With the introduction of CHT capabilities in bramble, users can now model a wider range of real-world vehicle thermal scenarios with greater fidelity. This significantly expands the platform’s applicability in vehicle thermal design.

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