Pradeep Ramuhalli Group Leader, Modern Nuclear I&C Group, Nuclear Energy and Fuel Cycle Division Contact ramuhallip@ornl.gov | 865.341.0035 All Publications An Assessment of Machine Learning Applied to Ultrasonic Nondestructive Evaluation... A Provably Accurate Randomized Sampling Algorithm for Logistic Regression... Ultrasonic Nondestructive Diagnosis of Cylindrical Batteries Under Various Charging Rates Second harmonic generation for estimating state of charge of lithium-ion batteries Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning Data-Driven Modeling of a High Capacity Cryogenic System for Control Optimization... Multi-module-based CVAE to predict HVCM faults in the SNS accelerator... Risk-Informed Decision-Making and Reconfiguration using OPRA... Status Report on Regulatory Criteria Applicable to the Use of Artificial Intelligence (AI) and Machine Learning (ML) Technical Specification Surveillance Interval Extension Using Self-Diagnostics Classification of ultrasonic B-scan images from welding defects using a convolutional neural network... A Risk-Informed Assessment of Operational Options for Successfully Avoiding a Trip Setpoint Technical Challenges and Gaps in Integration of Advanced Sensors, Instrumentation, and Communication Technologies with Digita... Non-Nuclear Advanced Controls Testbed Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems Development of Microreactor Automated Control System (MACS): Surrogate Plant-level Modeling and Control Algorithms Integration Digital Twins for Nuclear Power Plants and Facilities Machine learning for ultrasonic nondestructive examination of welding defects: A systematic review... Uncertainty aware anomaly detection to predict errant beam pulses in the Oak Ridge Spallation Neutron Source accelerator Ultrasonic nondestructive diagnosis of lithium-ion batteries with multiple frequencies... Development of a BWR System Fault Simulator Using TRANSFORM/Modelica... Regulatory Requirements, Guidance, and Review of Digital Twins Laser Doppler vibrometry for piezoelectric coefficient ( d33 ) measurements in irradiated aluminum nitride... How Digital Twins May Be Used in Design and Operations... Application of Convolutional and Feedforward Neural Networks for Fault Detection in Particle Accelerator Power Systems Pagination Current page 1 Page 2 Next page ›› Last page Last » Key Links ORCID Organizations Fusion and Fission Energy and Science Directorate Nuclear Energy and Fuel Cycle Division Advanced Reactor Engineering and Development Section Modern Nuclear I&C Group Energy Science and Technology Directorate Water Power Program Artificial Intelligence (AI) Initiative