Presentation Open Access

Deep Learning-based Anomaly Detection in Nuclear Reactor Cores

Thanos Tasakos; George Ioannou; Vasudha Verma; Georgios Alexandridis; Abdelhamid Dokhane; Andreas Stafylopatis


JSON-LD (schema.org) Export

{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>&bull;The introduction of a deep learning methodology for the classification of different perturbation types and their position in the reactor core, using convolutional neural networks<br>\n&bull;The performance of a complementary robustness analysis to assess the system&#39;s performance on noisy or missing data<br>\n&bull;The assessment of the system&#39;s functionality on plant measurements obtained from the G&ouml;sgennuclear power plan in Switzerland</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Institute of Communication and Computer Systems National Technical University of Athens", 
      "@type": "Person", 
      "name": "Thanos Tasakos"
    }, 
    {
      "affiliation": "Institute of Communication and Computer Systems National Technical University of Athens", 
      "@type": "Person", 
      "name": "George Ioannou"
    }, 
    {
      "affiliation": "Paul Scherrer Institute", 
      "@type": "Person", 
      "name": "Vasudha Verma"
    }, 
    {
      "affiliation": "Institute of Communication and Computer Systems National Technical University of Athens", 
      "@type": "Person", 
      "name": "Georgios Alexandridis"
    }, 
    {
      "affiliation": "Paul Scherrer Institute", 
      "@type": "Person", 
      "name": "Abdelhamid Dokhane"
    }, 
    {
      "affiliation": "Institute of Communication and Computer Systems National Technical University of Athens", 
      "@type": "Person", 
      "name": "Andreas Stafylopatis"
    }
  ], 
  "url": "https://zenodo.org/record/5575838", 
  "datePublished": "2021-10-03", 
  "@type": "PresentationDigitalDocument", 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.5575838", 
  "@id": "https://doi.org/10.5281/zenodo.5575838", 
  "workFeatured": {
    "@type": "Event", 
    "name": "Int. Conf. Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C2021)"
  }, 
  "name": "Deep Learning-based Anomaly Detection in Nuclear Reactor Cores"
}
7
8
views
downloads
All versions This version
Views 77
Downloads 88
Data volume 5.3 MB5.3 MB
Unique views 77
Unique downloads 66

Share

Cite as