Powering safety and sustainability in energy with industrial and scientific digital twins.
Energy companies can develop physically accurate, AI-enabled digital twins to design, simulate, and optimize products, equipment, and processes in real time before going to production. With virtual assets perfectly synced with their real-world counterparts, this approach maximizes energy production, reduces unplanned downtime, and lowers costs for both enterprises and their customers.
Learn how Honeywell accelerated their UniSim EO industrial process model applications by up to 78X—including models of oil and gas, refining, petrochemical, and chemical process units—using NVIDIA cuDSS.
Learn how Siemens Energy is developing physics-informed machine learning surrogate models, powered by NVIDIA Modulus, that enable more resilient power grids.
Learn how AI is building industrial digital twins for more efficient industrial operations in energy.
Honeywell
Discover how Honeywell Unisim Design integrated the NVIDIA cuDSS 0.2.0 (Preview) to achieve up to a 78X performance increase over traditional sparse linear equation solvers for process simulation.
MPI-M, DKRZ, and NVIDIA
Weather agencies and institutions are using NVIDIA accelerated computing to boost global weather models, resulting in a 24X speedup that saves $225 million and 127 gigawatt hours (GWh) annually.
Siemens Energy
By building industrial digital twins, global energy companies such as Siemens Energy can support predictive maintenance at power plants that could save the energy industry an estimated $1.7 billion a year.
Siemens Gamesa
Siemens Gamesa achieved a 4,000X speedup to simulate wind farms with physics-informed machine learning using Omniverse and Modulus.
The adoption of the metaverse can greatly accelerate the development of new facilities by allowing stakeholders to visualize and collaborate on design in a more immersive and interactive way. This technology enables real-time simulation of various scenarios and provides valuable insights. Additionally, the adoption of the metaverse can reduce the need for physical prototyping or travel due to collaboration across multiple devices and systems with better data availability.
— Maurizio Galardo, CTO 3D Visualization, Schneider Electric/AVEVA
We will continue to collect data, not just on how our wind turbines operate, but also weather forecasting, site planning, and other areas to optimize wind turbine sites. We're exploring augmented reality and extended reality as wind turbines are complicated machines with many types of failure modes. It's imperative to make sure the wind turbines operate safely and service technicians know how to do service repairs in the right way.
— Lasse Lundberg Nowack, Vice President, Engineering Development Power Solutions, Vestas
We started using virtual reality and augmented reality for site visits and visualization of safety studies. We are at the tipping point where to deliver these projects the ecosystem will have to come together.
— Vishal Mehta, Senior Vice President, Digital, Worley
NVIDIA GPUs are faster, higher resolution, and less costly than CPUs for forecasting weather and predicting renewable power. This is important to help reduce carbon-based power generation, enable efficient grid management, and lower energy costs.
— Gene Pache, Founder, President, and CEO, TempoQuest
AceCAST on one NDm A100 (GPU) virtual machine with eight NVIDIA GPUs runs 7 percent faster at 75 percent lower cost than Weather and Research Forecasting (WRF) on 16x HBv3 (CPU) virtual machines.
— Amirreza Rastegari, Senior Program Manager, Azure Specialized Compute, Microsoft
Learn about AI and high-performance computing (HPC) hardware, software, and networking solutions for surface operators.
NVIDIA OVX™ systems are purpose-built to power the creation and operation of real-time, physically accurate, AI-enabled Omniverse applications at data center scale. Digital twins revolutionize how enterprises design, simulate, and optimize complex systems and processes.
NVIDIA Omniverse is an extensible, open platform built for 3D virtual collaboration and real-time physically accurate simulation. Omniverse combined with Modulus, a framework for developing physics-ML models, enables digital twins for wind farms, power plants, electric grids, and someday Earth itself.
With NVIDIA AI Enterprise, energy companies can speed up development of use case applications, such as reservoir simulation, seismic processing, demand forecasting, predictive maintenance, and power grid management. Learn how to get access to the software platform with free curated labs.
NVIDIA Modulus is an open-source framework for building, training, and fine-tuning physics-ML models with a simple Python interface. With Modulus, you can build models for enterprise-scale digital twin applications across multiple physics domains, from computational fluid dynamics to structural analysis to electromagnetics to climate science.
NVIDIA® Jetson™ brings accelerated AI performance to the edge in a power-efficient and compact form factor. Together with the NVIDIA JetPack™ SDK and NVIDIA Isaac™ software for Robotics Operating System, these Jetson modules, including the new NVIDIA Jetson Orin Nano™, support a full range of edge AI and robotics applications.
NVIDIA IGX is an industrial-grade edge AI platform that delivers high performance, advanced functional safety, and security. Purpose-built for industrial and medical environments, IGX enables organizations to confidentially deliver AI safely and securely to support human and machine collaboration.
NVIDIA DGX™ Cloud is a multi-node AI-training-as-a-service solution optimized for the unique demands of enterprise AI. Access NVIDIA DGX Cloud to experience a combined software and infrastructure solution for AI training that includes a full-stack AI developer suite, leadership-class infrastructure, and concierge support, allowing businesses to get started immediately with predictable, all-in-one pricing.
NVIDIA Metropolis features GPU-accelerated SDKs and developer tools that help developers optimally build, deploy, and scale AI-enabled video analytics and IoT applications from the edge to the cloud.
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Webinars
Gain an understanding of the various building blocks of NVIDIA Modulus, the basics of physics-informed deep learning, and how the framework integrates with the overall Omniverse platform.
Get introduced to NVIDIA Isaac Sim™, NVIDIA Omniverse’s solution for simulation and robotics. Learn how to tap into the simulation loop of a 3D engine and initialize experiments with objects, robots, and physics logic.
Learn how to use NVIDIA Base Command™ Platform to accelerate your containerized AI training workloads, discover the tools necessary to build an AI center of excellence, and get the basics of working with, modifying, and running containers from NVIDIA NGC™.
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