Impact parameter prediction of a simulated metallic loose part using convolutional neural network-Reference-Cited by-同舟云学术

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Impact parameter prediction of a simulated metallic loose part using convolutional neural network

Published:2021-04 Issue:4 Volume:53 Page:1199-1209
ISSN:1738-5733
Container-title:Nuclear Engineering and Technology
language:en
Short-container-title:Nuclear Engineering and Technology

Author:

Moon Seongin,Han Seongjin,Kang To,Han Soonwoo,Kim Kyungmo,Yu Yongkyun,Eom Joseph

Funder

R&D Program of Korea Atomic Energy Research Institute

Publisher

Elsevier BV

Subject

Nuclear Energy and Engineering

Reference24 articles.

1. Export Control Guide: Loose Parts Monitoring Systems for Nuclear Power Plants;Rhodes,2012

2. Loose-Parts Monitoring System Improvements;Mayo,1988

3. Detection method of loose parts in nuclear reactor based on eigenvector algorithm;Yang;Prog. Nucl. Energy,2016

4. Mass estimation of impacting objects against a structure using an artificial neural network without consideration of background noise;Shin;Nuclear Engineering and Technology,2011

5. Development of automatic algorithm for localizing loose parts with a steam generator;Kim;Nucl. Eng. Des.,2002

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3. Compression after multiple impact strength of composite laminates prediction method based on machine learning approach;Aerospace Science and Technology;2023-05

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