6 papers
A Methodology for Thermal Limit Bias Predictability Through Artificial Intelligence
Anirudh Tunga, Michael J. Mueterthies, Jonathan Nistor
Nuclear power plant operators face significant challenges due to unpredictable deviations between offline and online thermal limits, a phenomenon known as thermal limit bias, which…
Optimization through In-Context Learning and Iterative LLM Prompting for Nuclear Engineering Design Problems
M. Rizki Oktavian, Anirudh Tunga, Amandeep Bakshi +3
The optimization of nuclear engineering designs, such as nuclear fuel assembly configurations, involves managing competing objectives like reactivity control and power distribution…
Predicting BWR Criticality with Data-Driven Machine Learning Model
Muhammad Rizki Oktavian, Anirudh Tunga, Jonathan Nistor +3
One of the challenges in operating nuclear power plants is to decide the amount of fuel needed in a cycle. Large-scale nuclear power plants are designed to operate at base load, me…
AI Enabled Neutron Flux Measurement and Virtual Calibration in Boiling Water Reactors
Anirudh Tunga, Jordan Heim, Michael Mueterthies +2
Accurately capturing the three dimensional power distribution within a reactor core is vital for ensuring the safe and economical operation of the reactor, compliance with Technica…
Multi-Domain Few-Shot Learning and Dataset for Agricultural Applications
Sai Vidyaranya Nuthalapati, Anirudh Tunga
Automatic classification of pests and plants (both healthy and diseased) is of paramount importance in agriculture to improve yield. Conventional deep learning models based on conv…
Pose-based Sign Language Recognition using GCN and BERT
Anirudh Tunga, Sai Vidyaranya Nuthalapati, Juan Wachs
Sign language recognition (SLR) plays a crucial role in bridging the communication gap between the hearing and vocally impaired community and the rest of the society. Word-level si…