Hybrid AI Analytics

HYB

Hybrid AI Analytics

Man looking at screen in officeThe purpose of this work package is to:

  • Develop robust, stable and explainable data-driven models for physical systems
  • Constrain models to enforce meaningful predictions
  • Transfer data-driven models from simulations to reality
  • Characterise and quantify uncertainty of data-driven models

This work package will develop methods to predict and reduce the uncertainty of data-driven models. The models will be constrained by existing knowledge, allowing to interpret the model (explainable AI) and reducing the amount of required training data. Applying this methods on real world applications will allow the industry partners to better predict the behavior of their facilities and improve their simulations, e.g. for condition monitoring, predictive maintenance, optimal utilization. 


Projects

Projects

Projects

Short description: The aim of this project is to develop methodology for transfer learning for quantifying uncertainty from non-representative training data , i.e. how we can learn from simulated data and utilize this to quantify uncertainty in physical systems. Developed methodology will be tested in two usecases. 

Time perspective: 2020-2022 

Usecase 1:Virtual flow meter  

Involved partners:

Usecase 2: Predictive maintenance for wind turbines

Involved partners:

SINTEF logo

DNV Logo

Trønderenergi logo

 

Stories

Stories

Can competitors cooperate? Yes!

Can competitors cooperate? Yes!

NorwAi partners Kongsberg and Cognite fight in the same market, both companies with unique strengths. Under the guidance of SINTEF Digital the competitors has joined hands to overcome challenges they else would have struggled with. Also other NorwAI partners are looking at the unique cooperation taking place in the work package Hybrid AI Analytics. 

Signe Riemer-Sørensen
Signe Riemer-Sørensen, Research Manager at SINTEF Digital and work package leader for Hybrid AI Analytics at NorwAI.
Foto: Kai T. Dragland

2024-02-27 


Research stay at Brown university

Research stay at Brown university

Katarzyna Michalowska, one of the NorwAI PhD students and researcher at SINTEF Digital is halfway into a one-year research stay at Brown University in the United States as a part of the NorwAI project. Katarzyna shares her experiences so far from working with the CRUNCH group at Brown.

Katarzyna in front of gates at Brown University
Katarzyna Michalowska at Brown University

2023-02-09