June 9th, 2021, 2:15 PM EDT - 3:45 PM EDT
Oil & Gas Applications Track
Deep Dive:
2:15 - 2:45 PM EDT, Paper No. GT2021-58914, “Data Selection and Feature Engineering for the Application of Machine Learning to the Prediction of Gas Turbine Trip”
Deep Dive:
2:45 - 3:15 PM EDT, Paper No. GT2021-58916, “Prediction of Gas Turbine Trip: A Novel Methodology Based on Random Forest Models”
Rapid Talk:
3:15 - 3:25 PM EDT, Paper No. GT2021-59318, “Unit Health Assessment- Oil & Gas Equipment Probabilistic Case Study”
Rapid Talk:
3:25 - 3:35 PM EDT, Paper No. GT2021-58989, “On Small Scale Lng Concepts”
Rapid Talk:
3:35 - 3:45 PM EDT, Paper No. GT2021-59458, “A Stochastics Model for Nanoparticle Deposits Growth”
Presentations
| Participant Role | Details | Action |
|---|---|---|
| Submission | Data Selection and Feature Engineering for the Application of Machine Learning to the Prediction of Gas Turbine Trip | View |
| Submission | Prediction of Gas Turbine Trip: A Novel Methodology Based on Random Forest Models | View |
| Submission | Unit Health Assessment- Oil & Gas Equipment Probabilistic Case Study | View |
| Submission | On Small Scale Lng Concepts | View |
| Submission | A Stochastics Model for Nanoparticle Deposits Growth | View |