- GE researchers developing an artificial intelligence (AI) and machine learning (ML)- enabled inverse design framework that allows performance metrics to create more optimized designs for industrial gas turbine (IGT) aerodynamic components
- Project aims to achieve a 30-50% reduction in design cycle times, or from 1 year to a few months
- Partnered with University of Notre Dame and GE Gas Power on the project
- Emerging digital toolset will help push combined cycle
business unit
tags
Fixing Cells On-Site
Editing Out Cancer