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Description
NVIDIA Modulus is an advanced neural network framework that integrates the principles of physics, represented through governing partial differential equations (PDEs), with data to create accurate, parameterized surrogate models that operate with near-instantaneous latency. This framework is ideal for those venturing into AI-enhanced physics challenges or for those crafting digital twin models to navigate intricate non-linear, multi-physics systems, offering robust support throughout the process. It provides essential components for constructing physics-based machine learning surrogate models that effectively merge physics principles with data insights. Its versatility ensures applicability across various fields, including engineering simulations and life sciences, while accommodating both forward simulations and inverse/data assimilation tasks. Furthermore, NVIDIA Modulus enables parameterized representations of systems that can tackle multiple scenarios in real time, allowing users to train offline once and subsequently perform real-time inference repeatedly. As such, it empowers researchers and engineers to explore innovative solutions across a spectrum of complex problems with unprecedented efficiency.
Description
Utilizing the distinctive and inherently dynamic Lattice Boltzmann-based physics, the PowerFLOW CFD solution conducts simulations that effectively replicate real-world scenarios. With the PowerFLOW suite, engineers can assess product performance at the early stages of design, before any prototypes are constructed—this is when alterations can have the most substantial effects on both design and budget. The PowerFLOW system seamlessly imports intricate model geometries and conducts aerodynamic, aeroacoustic, and thermal management simulations with high accuracy and efficiency. By automating domain discretization and turbulence modeling along with wall treatment, it removes the need for manual volume meshing and boundary layer meshing. Users can confidently execute PowerFLOW simulations using a large number of compute cores on widely utilized High Performance Computing (HPC) platforms, enhancing productivity and reliability in the simulation process. This capability not only accelerates product development timelines but also ensures that potential issues are identified and addressed early in the design phase.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
developer.nvidia.com/modulus
Vendor Details
Company Name
Dassault Systèmes
Country
United States
Website
www.3ds.com/products-services/simulia/products/powerflow/
Product Features
Product Features
Simulation
1D Simulation
3D Modeling
3D Simulation
Agent-Based Modeling
Continuous Modeling
Design Analysis
Direct Manipulation
Discrete Event Modeling
Dynamic Modeling
Graphical Modeling
Industry Specific Database
Monte Carlo Simulation
Motion Modeling
Presentation Tools
Stochastic Modeling
Turbulence Modeling