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Hybrid Digital Twin: The Challenges in Combining Data-Driven and Physics-based Modeling for Digital Twin Creation

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Course Credit: 0.15 CEU, 1.5 PDH

While the aviation, aerospace, and renewable energy industries have experienced enormous benefits over the past decade, the adoption of data-driven and/or physics-based reduced-order models as a digital twin is still in its infancy in the oil and gas (O&G) industry.

Benefits captured across these other industries include: improved quality and speed of decision-making, greater asset utilization, condition-based monitoring and prognostication, enhanced operational-efficiency and improvements in preventive maintenance. However, many challenges exist in our industry with respect to the generation and adoption of data science principles for the creation of a digital twin.

We tend to rely more on physics-based models. Moreover, key gaps exist in the understanding of basic principles concerning how and when to use different data-analytics tools to create a virtual representation from data, and then combining it with trusted physic-based modeling; thereby, allowing the assimilation of data-driven models into physics-based models.

Advances in hardware and software technologies have enabled the development of the information and computational infrastructure, which in turn gives industries the opportunity to explore and take advantage of the exciting possibilities for digital twins to analyze physical assets efficiently and effectively. The challenge of creating these entities, either through physics-based methods, data-driven modelling or combining them to form a “hybrid digital twin,” is of real interest to both academic and industry research and is the main motivation for this webinar.

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 1 chapter

Course Chapters

  • 1Hybrid Digital Twin: The Challenges in Combining Data-Driven and Physics-based Modeling for Digital Twin Creation - Chapter 1
    Media Type: Video

Credits

Earn credits by completing this course0.15 CEU credit1.5 PDH credits

Speakers

Dr. Egidio (Ed) Marotta
Dr. Srinath Madasu