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What is NVIDIA Modulus?

NVIDIA Modulus is a sophisticated neural network framework designed to seamlessly combine the principles of physics, encapsulated through governing partial differential equations (PDEs), with data to develop accurate, parameterized surrogate models that deliver near-instantaneous responses. This framework is particularly suited for individuals tackling AI-driven physics challenges or those creating digital twin models to manage complex non-linear, multi-physics systems, ensuring comprehensive assistance throughout their endeavors. It offers vital elements for developing physics-oriented machine learning surrogate models that adeptly integrate physical laws with empirical data insights. Its adaptability makes it relevant across numerous domains, such as engineering simulations and life sciences, while supporting both forward simulations and inverse/data assimilation tasks. Moreover, NVIDIA Modulus facilitates parameterized representations of systems capable of addressing various scenarios in real time, allowing users to conduct offline training once and then execute real-time inference multiple times. By doing so, it empowers both researchers and engineers to discover innovative solutions across a wide range of intricate problems with remarkable efficiency, ultimately pushing the boundaries of what's achievable in their respective fields. As a result, this framework stands as a transformative tool for advancing the integration of AI in the understanding and simulation of physical phenomena.

What is Fire Dynamics Simulator (FDS)?

The Fire Dynamics Simulator (FDS) is an open-source tool designed for simulating and visualizing fire-influenced flow dynamics. This computational fluid dynamics software adeptly resolves a modified version of the Navier–Stokes equations specifically aimed at low-velocity, thermally-driven airflow, with an emphasis on the movement of smoke and heat generated by fires. By utilizing large-eddy simulation techniques, it effectively captures the complexities of fire-plume behavior and is applicable to a variety of situations, including those involving wind effects, sprinkler systems, ventilation strategies, and different materials that influence fire characteristics. Users can define their scenarios through text-based input files, perform simulations with FDS, and analyze the resulting data afterward. The software provides visual outputs from both FDS and CFAST simulations using sophisticated OpenGL-powered 3D graphics, which include scientific visualization methods like animated smoke patterns, tracer particle animations, and two- and three-dimensional shaded surfaces, along with iso-surfaces, temperature gradients, and flow vector displays indicating both movement direction and strength. Moreover, FDS undergoes regular updates to improve its usability and features, ensuring it remains an essential resource for both researchers and fire safety experts. As a result, its continuous development further solidifies its significance in enhancing fire safety and understanding fire dynamics.

Media

Media

Integrations Supported

Integrations Supported

FireFlow Studio for FDS
OpenGL

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

Linux

Supported Platforms

Windows

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/modulus

Company Facts

Organization Name

NIST

Date Founded

1901

Company Location

United States

Company Website

pages.nist.gov/fds-smv/

Categories and Features

AI Inference

Not specified

Digital Twin

Not specified

HPC

Not specified

Neural Network

Not specified

Categories and Features

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