Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Utilizing sophisticated analytics and machine learning techniques is essential for minimizing operational expenses and mitigating risks. A fundamental component of the digital transformation landscape, digital twins provide precise virtual representations of tangible assets, systems, and objects to enhance productivity, optimize processes, and drive profitability. Typically, a digital twin is regarded as a software model of a physical asset or system that is tailored to identify, avert, predict, and refine processes through real-time analytics, ultimately delivering significant business advantages. At GE Digital, our emphasis lies in leveraging digital twin software to assist our clients in three primary domains: Asset, Network, and Process. By effectively monitoring, simulating, and managing an asset, process, or network, organizations can significantly elevate system performance. Furthermore, it is crucial to ensure the well-being and safety of employees and the environment while achieving business goals by minimizing incidents related to assets and processes, as well as preventing unintended downtimes, thereby fostering a more resilient operational framework. The integration of digital twin technology not only enhances efficiency but also paves the way for innovation across various sectors.
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
Yes
API Access
Has API
No
Integrations
APERIO DataWise
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
Yes
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
Yes
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
GE Digital
Founded
2015
Country
United States
Website
www.ge.com/digital/applications/digital-twin
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
developer.nvidia.com/modulus
Product Features
Simulation
1D Simulation
No
3D Modeling
No
3D Simulation
No
Agent-Based Modeling
No
Continuous Modeling
No
Design Analysis
No
Direct Manipulation
No
Discrete Event Modeling
No
Dynamic Modeling
No
Graphical Modeling
No
Industry Specific Database
No
Monte Carlo Simulation
No
Motion Modeling
No
Presentation Tools
No
Stochastic Modeling
No
Turbulence Modeling
No