Cars crossing a bridge in high temperatures

HVAC systems – creating your comfort zone

Summer 2023 was the hottest summer on record, according to the World Meteorological Organization. Find out how to design energy-efficient HVAC systems for improved passenger thermal comfort – also in extreme climes.

Unleashing the power of CFD to design a record-breaking model aircraft – Part 1

Read this guest blog from an ex-intern who is hell-bent on breaking the speed record on a remote controlled model aircraft. Find out how he co-created The Mach Initiative and their achievements to date.

The future of CFD – Your 15 minutes free gaze into the crystal ball

The future of CFD over the next 20, 50, even 100 years… We dare gazing into the crystal ball.

What's new in Simcenter Fluids & Thermal_July 2023

Simcenter Fluids and Thermal solution domain: What’s new?

Look into the most recent release highlights of Simcenter Fluids and Thermal solutions.

How can you get better boundary condition inputs for your whole engine model?

As a whole engine model engineer, you need to ensure that your boundary condition inputs are of the highest fidelity. Read this blog to learn how the Simcenter simulation solutions can help you define an accurate performance of your whole engine model.

Feel the (clean) burn

Combustion systems that burn alternative fuels such as e-fuels, hydrogen, or ammonia are a key to decarbonization. Learn how Simcenter STAR-CCM+ enables you to engineer such systems.

Simcenter STAR-CCM+ 2306 Released! What’s new?

Go faster with GPU-enabled acceleration for an extended set of solvers. Find better designs faster with gradient-based parametric optimization. Tackle…

Fasten your seat belts: the coupled solver is taking off on GPU!

With the coupled solver becoming GPU- native in Simcenter STAR-CCM+ 2306 aerospace aerodynamics CFD and many more applications become faster than ever.

Of white storks, babies, drones and parametric gradient-based optimization for CFD

Parametric Gradient-Based Optimization enables you to leverage adjoint sensitivities of design parameters to find local optima faster.