This experience shows an interactive virtual wind tunnel. Simulating airflow in a virtual wind tunnel with computational fluid dynamics (CFD) requires millions of complex calculations. Without AI, it can take minutes to see the result of a single design change. Developers building the next generation of AI-powered CAE tools are combining simulation AI with immersive virtual environments to enable real-time digital twins where design changes instantly update in the simulation, as you see in this demonstration. NVIDIA is making it easier to create interactive design tools by introducing Omniverse Blueprint for interactive aerodynamics. To enable real-time performance in a virtual wind tunnel, simulation AI models are first trained offline on representative datasets. For this demo, the training dataset was created using Luminary Cloud's GPU-accelerated CFD solver, which models complex airflow over diverse geometries. The simulation AI learns the complex relationships between car geometries (STLs) and airflow. This blueprint is compatible with industry-standard CFD solvers and can connect to third-party tools for meshing and geometry morphing, creating watertight meshes for simulation-ready geometries. The blueprint also integrates NVIDIA Modulus (our framework for simulation AI) with CFD solver data. This enables developers to train surrogate models from scratch or fine-tune NIM foundation models, reducing AI training time and cost. Once trained, the AI runs simulations orders of magnitude faster than traditional CFD, enabling real-time aerodynamic flow simulation. This speed provides designers with creative freedom, allowing designers to innovate and explore changes interactively.
NVIDIA Blueprints are comprehensive reference workflows designed to streamline AI application development across industries and accelerate deployment to production. Built with NVIDIA AI and Omniverse libraries, SDKs, and microservices, they provide a foundation for custom AI solutions. Each blueprint includes reference code for constructing workflows, tools and documentation for deployment and customization, and a reference architecture outlining API definitions and microservice interoperability. By enabling rapid prototyping and speeding time to deployment, these blueprints empower enterprises to operationalize AI-driven solutions like AI agents, digital twins, and synthetic data generation, and more.
The blueprint comes with sample CFD data for training a surrogate model.
This reference solution implements an Omniverse Kit application controller that maintains the application world state and connects the 3D world stage with simulation results produced by the surrogate model
The blueprint comes with pre-built APIs that support continuous model improvement. The feedback loop, or “data flywheel,” allows surrogate models to be fine-tuned over time to enhance both accuracy and cost-effectiveness.
In summary, this NVIDIA Omniverse Blueprint offers a starting point for building real-time digital twins for computer-aided engineering (CAE) workflows combining CUDA-X accelerated solvers, Modulus for simulation AI, and Omniverse for high quality rendering.
The real-time wind tunnel blueprint supports the following hardware:
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Create real-time digital twins by combining accelerated solvers, simulation AI, and virtual environments.