{"id":1733,"date":"2020-11-07T16:59:05","date_gmt":"2020-11-07T15:59:05","guid":{"rendered":"https:\/\/www.netscientificjournals.com\/smart-platform\/?post_type=call_for_papers&#038;p=1733"},"modified":"2021-01-12T16:20:18","modified_gmt":"2021-01-12T15:20:18","slug":"advances-in-modelling-for-nuclear-science-and-engineering","status":"publish","type":"call_for_papers","link":"https:\/\/www.netscientificjournals.com\/smart-platform\/?call_for_papers=advances-in-modelling-for-nuclear-science-and-engineering","title":{"rendered":"Advances in Modelling for Nuclear Science and Engineering"},"content":{"rendered":"<p>Computer models have played a central role in assessing the functioning of nuclear power facilities for decades. They have ensured that nuclear operations are efficient, but also safe to both the public and the environment. The field of nuclear engineering is complex and multi-physics in nature, spanning the fields of neutron transport, thermal hydraulics, structural mechanics, heat transfer, and chemistry. Robust, accurate, and validated models are essential to the areas of rector design, operation and procedure analysis, fuel optimization, and lifetime extension, among others. Nuclear engineering research has been a significant contributor to the field of numerical analysis and modeling by advancing areas in predictive multi-physics modeling, sensitivity and uncertainty quantification, high-fidelity discretizations, reduced-order models, artificial intelligence, and HPC.\u00a0This Special Issue aims to bring together studies describing recent advances in modeling methods for all areas in nuclear engineering applications. We welcome contributions from academia and industry in the aforementioned fields.<br \/>\nKeywords: high-fidelity models; HPC: sensitivity analysis; uncertainty quantification; best estimate plus uncertainty; single and multi-physics modeling; reduced-order modeling; artificial intelligence.<\/p>\n<div>\n<div><\/div>\n<\/div>\n","protected":false},"author":1,"featured_media":0,"parent":0,"template":"","format":"standard","topic":[192,542,563,604],"country":[55],"nsj_language":[57],"class_list":["post-1733","call_for_papers","type-call_for_papers","status-publish","format-standard","hentry","topic-artificial-intelligence","topic-energy-production","topic-modeling","topic-process-modeling-and-simulation","country-switzerland","nsj_language-english"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Advances in Modelling for Nuclear Science and Engineering - NetScientficJournals.com - Science Magazines, Events and More<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.netscientificjournals.com\/smart-platform\/?call_for_papers=advances-in-modelling-for-nuclear-science-and-engineering\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:type\" content=\"article\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:title\" content=\"Advances in Modelling for Nuclear Science and Engineering - NetScientficJournals.com - Science Magazines, Events and More\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:description\" content=\"Computer models have played a central role in assessing the functioning of nuclear power facilities for decades. They have ensured that nuclear operations are efficient, but also safe to both the public and the environment. 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