Computational Fluid Dynamics

Computational fluid dynamics is a focus of many SIMCenter research projects. Using sophisticated software, researchers can accurately predict steady-state and time-dependent external and internal flows.

These techniques are applied in the design processes for many consumer products and are typically used to improve acoustics and aerodynamics.

Featured Projects

Honda Pilot Acoustics
This simulation shows airflow around the vehicle
Vehicle Cabin Wind Noise

Project Sponsor: Honda R&D Americas

Excess wind noise in a vehicle’s cabin can annoy and fatigue the occupants. Researchers conducted a numerical study to establish the coupled simulation between Wave6 and Star CCM+.

Using this data, researchers accurately predicted the cabin noise induced by external flows around side mirrors.

Instantaneous velocity field over a flexible plate (left) and over a rigid panel (right).
Instantaneous static pressure on a flexible plate (left) and on a rigid plate (right).
Fluid-Structure Interaction

Fluid-structure interaction is a complex physical phenomenon that is present in many fields including aerospace, biomedicine and automotive. It is a coupling that occurs between a deformable structure and a surrounding or internal flow. The fluid exerts pressure loads on the structure, causing it to deform. This deformation changes the flow patterns around it, affecting the velocity and pressure fields.

Computational fluid-structure interaction, also defined as computational aeroelasticity, is a predictive capability that allows designers to better understand the design space and optimize structural design. It allows designers to identify potential issues with the structure and reduce manufacturing and prototyping costs.

Aeroacoustics of a small-scale drone
A small-scale drone (left) and the vortex distributions of its twist blade (right). This model shows the airflow interaction between the blade and the airframe.
Aeroacoustics of a Small-Scale Drone

Researchers studied aerodynamics and aeroacoustics at low Reynolds numbers to reduce wind noise from a small-scale drone.

They determined that the dominant noise source was the interaction between the rotor blades and the airframe. Researchers suggested redesigning the twist blade to reduce flow separation on the blades and generate higher lift.

Vertical-axis wind turbine efficiency and airflow
Simulation showing the airflow around a wind turbine.
Wind Turbine Efficiency

A well-designed wind turbine harvests more wind energy. A study was conducted to determine whether adding serrations on the leading edge of a vertical-axis wind turbine was an effective solution.

Flow separation, which increases drag, was more controllable when the serrations were added. When the tip-speed-ratio (TSR) was 2.0, power increased approximately 18 percent, which means more wind energy could be harvested.