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Prediction of the remaining time and time interval of pebbles in pebble bed HTGRs aided by CNN via DEM datasets

Prediction of the time-related traits of pebble flow inside pebble-bed HTGRs is of great significance for reactor operation and design. In this work, an image-driven approach with the aid of a convolutional neural network (CNN) is proposed to predict the remaining time of initially loaded pebbles an...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Mengqi Wu, Xu Liu, Nan Gui, Xingtuan Yang, Jiyuan Tu, Shengyao Jiang, Qian Zhao
Format: Artigo
Sprache:Inglês
Veröffentlicht: Elsevier 2023-01-01
Schriftenreihe:Nuclear Engineering and Technology
Schlagworte:
Convolutional neural network (CNN)
Discrete element method (DEM)
Time prediction
Pebble-flow
Pebble bed HTGRs
Online-Zugang:http://www.sciencedirect.com/science/article/pii/S173857332200451X
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