nTop acquires CFD software company cloudfluid to accelerate real-time design
February 19, 2025
nTop (formerly known as nTopology), headquartered in New York City, USA, has acquired cloudfluid, a German-based company specialising in computational fluid dynamics (CFD) software.
CFD typically involves complex meshing and long run times, making it impractical to use in rapid design iterations. cloudfluid addresses this challenge with its GPU-native solver technology, which is said to accurately predict fluid flow without the difficulty of creating complex conformal meshes. Coupled with nTop’s implicit geometry kernel, engineers can now iterate on designs in near real-time.
“We are hyper-focused on building software that helps engineers go from requirements to design as fast as the latest computing processors allow – that’s the power of computational design,” said Brad Rothenberg, CEO of nTop. “One of the biggest bottlenecks has always been solving the physics; it takes time to mesh and converge on a solution. cloudfluid solves this by integrating directly with our implicit modelling core, bringing CFD into the iterative computational design loop. With the acquisition of cloudfluid, we’re not only expanding our capabilities in CFD – we’re also strengthening our internal expertise to accelerate future integrations with other best-in-class tools.”
The integration of cloudfluid’s high-speed CFD with nTop’s computational design platform is expected to expand applications in aerospace, defence, and turbomachinery, where fluid dynamics are crucial. Engineers can now explore complex geometries and optimise designs faster, advancing propulsion, aerodynamics, and thermal management systems.
At the same time, these technologies address machine learning’s data challenges, where curated simulation data is often lacking. This integration is hoped to enhance decision-making, accelerate innovation, and improve manufacturing efficiency by enabling the cost-effective generation of high-quality simulation data for training predictive models in digital twins and design optimisation.
