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Hybrid Analytics for Sim2real Models

This talk will cover methods to create fast and precise predictive models for industrial assets with limited data, useful for control design, XiL models, and digital twins.

Date/Time:
February 17, 2026
11 AM EST

Venue:
Virtual

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Overview

In this talk, we will describe methods to develop predictive and accurate models for industrial assets in the regime of small measurement data. These models are fast, precise, and valuable for plant models for control design, XiL models, and digital twins.
Models are built by using machine learning techniques that augment measurements with simulations to learn system behavior from limited data. We demonstrate that such hybrid models exhibit superior extrapolation and learning efficiency, as illustrated by relevant case studies.

What Attendees Will Learn

  • Efficient ways to build reduced order models from simulations and measurement
  • Combine simulations and measurement to build data efficient models
  • See successful use cases from various industries

Who Should Attend

  • Computational engineers, mathematical modelers, control engineer, and system modelers.

Speakers

  • Srinivasa Mohan - Distinguished Engineer, Ansys
Hybrid Analytics for Sim2real Models

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