NVIDIA PhysicsNeMoNVIDIA
|
Simcenter MAGNETSiemens
|
|||||
Related Products
|
||||||
About
NVIDIA PhysicsNeMo is an open source Python deep-learning framework for building, training, fine-tuning, and inferring physics-AI models that combine physics knowledge with data to accelerate simulations, create high-fidelity surrogate models, and enable near-real-time predictions across domains such as computational fluid dynamics, structural mechanics, electromagnetics, weather and climate, and digital twin applications. It provides scalable, GPU-accelerated tools and Python APIs built on PyTorch and released under the Apache 2.0 license, offering curated model architectures including physics-informed neural networks, neural operators, graph neural networks, and generative AI–based approaches so developers can harness physics-driven causality alongside observed data for engineering-grade modeling. PhysicsNeMo includes end-to-end training pipelines from geometry ingestion to differential equations, reference application recipes to jump-start workflows.
|
About
Simcenter MAGNET is a powerful electromagnetic field simulation solution for performance prediction of motors, generators, sensors, transformers, actuators, solenoids, or any component with permanent magnets or coils. Simcenter MAGNET helps you predict the performance of any component with permanent magnets or coils. Perform low-frequency electromagnetic field simulations. Simcenter MAGNET includes capabilities to accurately model the physics of electromagnetic devices. This includes the ability to model manufacturing processes, temperature-dependent material properties, magnetization and de-magnetization modeling, and vector hysteresis models among others. Simcenter MAGNET also has a built-in motion solver with a six-degree-of-freedom capability. It allows for complex problems like magnetic levitation or complex motion to be accurately modeled and analyzed. This is made possible with a unique smart re-meshing technology.
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
Researchers, engineers, and developers who need an open source Python AI framework to build, train, fine-tune, and deploy physics-informed machine learning models for simulation, digital twins, and real-time prediction
|
Audience
Professionals wanting a tool to perform low-frequency electromagnetic field simulations
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
Free
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationNVIDIA
Founded: 1993
United States
developer.nvidia.com/physicsnemo
|
Company InformationSiemens
United States
plm.sw.siemens.com/en-US/simcenter/electromagnetics-simulation/magnet/
|
|||||
Alternatives |
Alternatives |
|||||
|
|
|
|||||
|
|
|
|||||
|
|
|
|||||
|
|
|
|||||
Categories |
Categories |
|||||
|
|
|