AI and IoT for Flow Modeling

The workshop is organized as part of the Indo-Dutch project, "Digital Twins for pipeline transport networks". The aim of the project is to develop a digital twin that connects sensor data and advanced fluid solvers in order to detect possible leakage of fluid from the pipeline in real-time.
  • What Scientific Computing English Not a Seminar
  • When 20-11-2020 from 10:30 to 17:00 (Europe/Amsterdam / UTC100)
  • Where online
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Organised by Shashi Jain (IISc Bangalore) and Nikolaj T. Mücke (CWI).

The workshop is organized as part of the Indo-Dutch project, "Digital Twins for pipeline transport networks". The aim of the project is to develop a digital twin that connects sensor data and advanced fluid solvers in order to detect possible leakage of fluid from the pipeline in real-time. Of particular interest then is also the development of AI based fluid flow solvers, as traditional fluid flow models are typically much too slow for real-time applications. We thank the NWO (the Netherlands), MeitY (India) and Shell (the Netherlands) for funding the project. As part of the workshop the following talks have been scheduled:

11:00 Jan S. Hesthaven (EPFL): Digital Twins at the interface between modeling, measurements, and machine learning Video
11:45  Yogesh Simhan, (IISc Bangalore): IoT and Analytics for Social Good Video
12:30  Vineet Tyagi (IIT Bombay): Neural Networks for predicting flow parameters in a pipeline network Video
13:00 Amritendu Mukherjee (IISc Bangalore): A comprehensive study to understand the relationship of urbanization and population density with GRACE ΔTWS for selected study regions in India during 2003-2017 Video
13:30 Nikolaj T. Mücke (CWI): Reduced Order Modeling for Fluid Simulations using Deep Learning Video
14:00 Ruud Henkes (Shell): The role of simulation in leak detection for pipeline operations Video

The workshop times are CET, Central European Time.

This workshop will take place, on-line, via Zoom
https://us02web.zoom.us/j/82934190497?pwd=c0U0Nmt5R0dmV0ViWmN0eHJJSXhmUT09
[Meeting ID: 829 3419 0497, Passcode: 635310]

More information about the speakers and their presentation can be found here.