10,000 LES Simulations in 32 Hours: nTop and CoreWeave Hit NASA's CFD 2030 Target

How nTop Hit NASA’s 2030 CFD Goal Early on CoreWeave | CoreWeave Blog

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Photo credit: Courtesy of nTop

It makes no sense to get on an airplane that hasn’t been physically tested before boarding. But the reality is that while (many) thousands of designs are investigated by engineering teams,  only a handful can actually be physically tested. The role of simulation in engineering is vital and irreplaceable. Whether it’s the flight for your last business trip, the car you drove to pick up your kids, or the appliances in your home, physics-based simulation is essential to how engineering enterprises design their products to be safe and predictable. How physics-based simulation powers modern engineering Engineering simulation is best understood as a set of computational methods that let engineers test physics in software before committing to hardware, materials, prototypes, or field trials. At the highest level, the taxonomy is aligned with the kind of physics being modeled. Many of these simulations are non-linear, which complicates the efforts and methodologies required to get accurate approximations of design performance. “The world is non-linear, it’s true. But fear not, for here is a clue: When signals are small, and stabl’ overall, x˙ = Ax will do.” From fluid dynamics to structural deformation: The many forms of engineering simulation Computational Fluid Dynamics (CFD) predicts fluid flow and heat transfer in applications ranging from aerospace and transportation to energy systems and climate modeling. Since most practical flows are turbulent, turbulence modeling remains a fundamental challenge in CFD. Its importance extends beyond predictive accuracy: turbulence is a major source of viscous drag, and approximately 30% of global energy consumption is spent overcoming drag in transportation systems 1 . Structural simulation, often called Finite Element Analysis (FEA), predicts how parts deform, vibrate, fatigue, crack, or fail under load, which is central to safer buildings, lighter vehicles, stronger machines, and more reliable infrastructure. Electromagnetic simulation models fields, antennas, motors, chips, sensors, and power systems. Molecular and materials simulation looks at behavior at atomic or microscopic scales to help discover better batteries, polymers, semiconductors, drugs, and advanced materials. Multiphysics simulation couples several of these domains together, because real products rarely experience just one kind of physics in isolation. 10,000 drone simulations in 32 hours nTop is a computational design and simulation platform used by leading aerospace, defense, and advanced manufacturing teams to build the kind of complex geometry that traditional CAD can't handle reliably. Its solver, nTop Fluids, runs CFD natively on GPUs. nTop and CoreWeave's physical AI team partnered on a joint proof of concept to test the limits of what a single simulation engineer can accomplish in roughly one day, using nTop Fluids on CoreWeave's GPU cloud infrastructure . The present work is a joint Industrial Test Case which simulates aerodynamics for different drone designs, leveraging nTop Fluids software on CoreWeave Cloud . The goal was to test the boundary of what’s possible for engineers today—how many designs could be evaluated (i.e. simulations ran) in about 1 day as an aerodynamicist/simulation practitioner? What Is Large-Eddy Simulation (LES), and why is it so expensive to run? We chose Large-Eddy Simulation (LES) deliberately, primarily because it’s a higher-fidelity approach than the Reynolds-Averaged Navier-Stokes (RANS) methods most engineering teams rely on. RANS averages turbulence into statistical approximations, which is fast but loses important physical detail. LES directly resolves the large turbulent structures in the flow and only models the smallest scales, which makes it significantly more accurate and orders of magnitude more compute-intensive. That cost is the reason LES has historically been reserved for one-off "capability" calculations rather than large-scale design studies. What it takes to run 10,000 CFD simulations without human intervention Demonstrations like this show what becomes feasible when scalable software and purpose-built infrastructure come together: higher volumes of simulations, shorter time intervals, at higher levels of fidelity. The full study ran headless with no manual intervention required to fix software or infrastructure issues, and scaled reliably end-to-end. The two key ingredients were nTop Fluids' ability to robustly generate and simulate geometries, and CoreWeave Cloud,  purpose-built for AI workloads and accelerated by the latest NVIDIA GPUs. Designing the experiment: 2,400 drone variants across 5 angles of attack A Design of Experiments (DoE) methodology was used to systematically explore the design space and identify high-performing configurations. Each design was represented by a set of parametric variables—such as airfoil thickness—that were varied across predefined ranges. Sampling combinations of these parameters generated a diverse population of drone geometries, as shown in Figure 1, enabling broad coverage of the feasible design space. In total, 2,400 drone planform geometry variants were considered across five angles of attack, for a total of 10,000 simulations. Angle of attack refers to the orientation of the wing relative to the oncoming airflow, which changes as a drone climbs, descends, or maneuvers. Testing across multiple angles captures how each design performs across a range of flight conditions. The base geometry used for this study was a fully parametric Group 3 long-endurance fixed-wing UAS, which was built in nTop.

Hitting NASA's CFD Vision 2030 target four years early By executing a massive ensemble of 10,000 Large-Eddy Simulations (LES) within a 32-hour window, this work marks a paradigm-shifting milestone that directly realizes the ultimate operational goals outlined in NASA's CFD Vision 2030 Study 2 . A foundational pillar of the 2030 vision dictates that engineers must be able to "conceive, create, analyze, and interpret a large ensemble of related simulations in a...