On 7th August 2024, Johndel OBRA, under the supervision of Dr. Shuichiro Miwa, of the Department of Nuclear Engineering and Management (M1), received the “Best Poster Award” at the 31st International Conference on Nuclear Engineering (ICONE31) held in Prague, Czech Republic.

<Name of the Award and Short Explanation About the Award>

The “Best Poster Award” is given to research works for their outstanding and high-quality posters presented at the Student Paper Competition Track of ICONE31.

<About Awarded Research>
Title: Investigation of Long Short-Term Memory-Based Models for the Forecasting and Diagnosis of PWR LOCA Progression

Abstract:
In the aftermath of the Fukushima – Daiichi accident, there has been a continuous effort to improve the existing LOCA management tools. One of the ways to improve this is to help the operators assess the situation more accurately by providing them with real-time LOCA diagnostic tools. The potential of Long Short-Term Memory (LSTM) models in LOCA forecasting and real-time diagnosis was investigated. The LSTM models were trained and evaluated using simulated LOCA scenarios from RELAP5/SCDAPSIM. LSTM forecasting was first verified through the accurate prediction of the temporal progression of the water level, primary coolant inlet flow rate, and hot leg temperature after the onset of LOCA. Then, the study established the capability of LSTM to diagnose the pipe break location and extent of pipe damage using small portions of data near the onset
of LOCA. Lastly, the study demonstrated the potential of real time LOCA diagnosis by combining the LSTM-based forecasting and predictive models. 

<Your Impression and Future Plan>

I am deeply honored to receive this recognition among a competitive pool of graduate students, especially as an M1 student. I would like to express my utmost gratitude to my adviser, Dr. Shuichiro Miwa, for his invaluable knowledge and insightful comments, continuous guidance, and understanding. I would like to thank Prof. Okamoto for his leadership and support in the lab’s research endeavors. Finally, I would like to thank my colleagues for inspiring me to strive for excellence in my research. I hope to publish the contents of this research work and continue with my research on applying AI in improving nuclear safety and accident diagnosis.