Simulation / Modeling / Design

GTC Digital Demo: Accelerating Scientific and Engineering Simulation Workflows with AI

AI-Generated Summary

  • NVIDIA PhysicsNeMo is an end-to-end AI-driven simulation framework based on a novel physics-informed neural network architecture.
  • The framework solves multiphysics problems to perform automatic design space exploration 1000x faster than traditional simulation while maintaining the accuracy of numerical solvers.
  • Optimized design selection that previously required hours or months can now be completed in seconds or days.

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NVIDIA PhysicsNeMo was previously known as NVIDIA SimNet.

A new demo introduces the recently announced NVIDIA PhysicsNeMo Toolkit, the first multiphysics (CFD and Heat Transfer) analysis using physics-informed neural networks (PINNs).

Simulations form an integral part of product design to reduce significant iterations in physical prototyping and testing to improve quality, cost and time-to-market. However, this process is time-consuming and can take weeks to months. In a typical simulation workflow, several iterations are involved if the results are not satisfactory for a given design. Typically, there is never enough time or compute power to examine all the design variations.

NVIDIA PhysicsNeMo is an end-to-end AI-driven simulation framework based on a novel PINN architecture. This demonstration of PhysicsNeMo is solving a multiphysics problem to perform automatic design space exploration, 1000x faster than traditional simulation, with the accuracy of numerical solvers.

Such unprecedented throughput enables optimized design selection, which we show using PhysicsNeMo. Completing these design tasks take seconds not hours, and complex design optimization can be completed in days instead of months.

Watch the PhysicsNeMo demo with GTC On-Demand.

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