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Description
Energy2D is an interactive multiphysics simulation program grounded in computational physics, designed to model the three primary modes of heat transfer: conduction, convection, and radiation, while also integrating particle dynamics. This software operates efficiently on a wide range of computers, simplifying the process by removing the need for switches between preprocessors, solvers, and postprocessors that are usually necessary for computational fluid dynamics simulations. Users can create "computational experiments" to explore scientific hypotheses or address engineering challenges without the need for intricate mathematical formulations. Additionally, development is ongoing to introduce various energy transformation types and to enhance support for different fluid types. While Energy2D excels in accurately modeling conduction, its representations of convection and radiation are not entirely precise, which means results involving these elements should be regarded as qualitative. Over 40 scientific papers have utilized Energy2D as a valuable research instrument, showcasing its adoption in the academic community. As the program evolves, its capabilities are expected to expand further, potentially offering more comprehensive insights into complex physical interactions.
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.
API Access
Has API
API Access
Has API
Integrations
Raspberry Pi OS
Pricing Details
Free
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
The Concord Consortium
Founded
2010
Country
United States
Website
energy.concord.org/energy2d/
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
developer.nvidia.com/modulus
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
