Optimising Motorbike Intake: How did the UniBS MotoStudent Team make it ?

The team

We recently had the chance to support the MotoStudent team from the University of Brescia, who are developing a motorcycle prototype for the upcoming final event in Aragón, Spain. Now in their fifth competition cycle, the team is working on the BRX-254 model. AeroCloud was primarily used by their PowerTrain division, which focused on designing a fluid-dynamically optimized intake system made up of three parts: the front ducts, the airbox, and the throttle body interface. They chose AeroCloud because of its ease of use and cloud-based simulation capabilities perfect for avoiding strain on limited local computing resources.

Project Goal and Motivation

The team’s main objective was to design an intake system that could ensure sufficient mass flow to boost power output. With AeroCloud, they focused on optimizing the internal flow, particularly the pressure expansion within the airbox,where velocity drops as pressure builds, and reducing pressure losses at the throttle body interface. In parallel, they used GT-Suite to simulate engine behavior and wave effects from the piston’s motion. This helped define the baseline geometry, while AeroCloud handled the detailed flow optimization. The key performance targets were minimizing pressure loss and reducing turbulence throughout the system.

Simulation and Setup

The team began by creating their CAD models in SolidWorks and converting them to STL format for AeroCloud. Setup was straightforward, only minor adjustments were needed to seal volume gaps between parts, such as adding small extrusions where real-world components like O-rings would normally sit. For the simulations, they set an inlet airspeed of 50 m/s to reflect the bike’s theoretical top speed and excluded ground effects for simplification. Initial tests were run using AeroCloud’s “Basic” quality setting for quick feedback. Once geometries were refined, they switched to “Standard” mode for higher precision. Since the intake system remains static relative to airflow, no rotating components were included in the model.

Results and Workflow

To illustrate the team’s workflow and results, they shared a specific case involving a Y-duct. The focus here was on analyzing the internal fluid dynamics rather than external aerodynamics. The goal was to minimize pressure losses by reducing turbulence and eliminating low-pressure zones inside the ducts. In the results shown, low-pressure regions are visible at the side opening of the Y. To address this, the team refined the geometry by smoothing the transition between the oval inlet and the two circular outlets. Coefficients like CF (friction) and CD (drag) were not considered, as the objective was to study internal flow behavior.

Airflow at the start of the intake

The Design Changes

The geometry changes were directly guided by the turbulence data. Whenever the team observed excessive turbulence in a specific design, they made targeted adjustments to improve flow behavior. To evaluate the impact of these changes, they used two main methods:

• Running follow-up simulations to compare flow performance.
• Analyzing cross-sections in ParaView to track variations in pressure loss, pressure differential, and average velocity.

Flow and pressure inside the intake

The Challenges

One of the main challenges the team faced was integrating the intake system with other motorcycle components like the fairings and frame. Despite this, AeroCloud proved intuitive and easy to use throughout the process, with no major limitations. A key advantage was the ability to run multiple simulations at the same time, enabling team members to collaborate efficiently. In a few cases, the internal geometry of the ducts wasn’t fully visualized within the software, but using ParaView allowed the team to interpret the results effectively.

Testing and Takeaways

The intake system is now being 3D-printed and will soon be mounted on the motorcycle for real-world testing. The team plans to validate its performance on a test bench, comparing results against earlier GT-Suite models. Based on those results, they’ll make refinements and begin developing a second, improved version. AeroCloud played a key role in this process—particularly in visualizing flow lines and identifying turbulence to optimize internal efficiency.

The team also explored simulations on fairing components, evaluating opportunities to trim or reshape certain elements. While AeroCloud excels at external flow simulations—such as on aircraft wings or car spoilers—some limitations were noted in internal applications, like ductwork. A requested improvement was the ability to model the computational domain directly, giving more precise control over inlet and outlet settings.

Still, what stood out most was AeroCloud’s accessibility. Even students without CFD experience were able to visualize flow behavior and understand core principles of fluid dynamics. We’re grateful to the University of Brescia team for their feedback and proud to have supported them throughout their journey.