This project will apply advanced artificial intelligence and machine learning (AI/ML) tools to automate the analysis of large nondestructive examination (NDE) datasets from in-service inspections for interpretation of measurements made with eddy current (EC) array probes used on pressurized water reactor (PWR) steam generator tubes. The objective is to deploy AI/ML for explainable for interpretation of detection and classification of active damage and degradation in steam generator tubes, and to build comprehensive training datasets by combining existing Argonne data with newly synthesized data generated using in-house software to improve AI/ML performance and reliability.
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Job Type
Part-time
Career Level
Intern
Education Level
No Education Listed
Number of Employees
1,001-5,000 employees