The digital twin of the future is a decision making engine that connects optimization with real-world execution through three interconnected phases.

Challenge 1: Better training data for more accurate AI models with simulation. Simulation models can synthesize real-world data that is difficult or expensive to collect into good, clean and ...

Explore how safety professionals are using VR, blended learning, and analytics to transform confined-space rescue training, ...

Sub-model simulation includes all mechanisms for CO 2 sequestering in a saline aquifer. Based on the results, the mechanisms were ranked in importance for application to the full-field scale model.

Porter Novelli has rolled out the simulation model to clients across the financial services, retail and education sectors over the past three months. As a first step, Porter Novelli urges all ...

Due to the structural nature of the concept of nexus suppliers, we use a structural modeling approach in our simulation scenarios. A structural modeling approach differs from the traditional ...

The primary responsibility of the Modelling and Simulation group is the development of aircraft models. To this end, real flight data is analysed using the Quad-M system identification method, which ...

The Large Hadron Collider is one of the biggest experiments in history, but it’s also one of the hardest to interpret. Unlike ...

The authors call for a change of model to apply the FAIR principles—which ensure that data is findable, accessible, interoperable and reusable—to simulation results.

But even if modeling and simulation provides reliable data, researchers are still extrapolating unknown data and one key challenge will be convincing the stakeholders in the program that data is ...

Simulation software or developing charts and models can help you make better decisions. The key is to use existing tools that suppliers have already tested or to test your own methods on past data ...