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undergraduate thesis
Primjena umjetne inteligencije u nuklearnom inženjerstvu
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:551118
Habijanec, Marko
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Habijanec, M. (2024). Primjena umjetne inteligencije u nuklearnom inženjerstvu (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:551118

Habijanec, Marko. "Primjena umjetne inteligencije u nuklearnom inženjerstvu." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:551118

Habijanec, Marko. "Primjena umjetne inteligencije u nuklearnom inženjerstvu." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:551118

Habijanec, M. (2024). 'Primjena umjetne inteligencije u nuklearnom inženjerstvu', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 19 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:551118

Habijanec M. Primjena umjetne inteligencije u nuklearnom inženjerstvu [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 December 19] Available at: https://urn.nsk.hr/urn:nbn:hr:168:551118

M. Habijanec, "Primjena umjetne inteligencije u nuklearnom inženjerstvu", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:551118

Metadata
TitlePrimjena umjetne inteligencije u nuklearnom inženjerstvu
Title (english)Application of artificial intelligence in nuclear engineering
AuthorMarko Habijanec
MentorKrešimir Trontl (mentor)
Committee memberSiniša Šadek (član povjerenstva)
Committee memberMario Matijević (član povjerenstva)
Committee memberKrešimir Trontl (predsjednik povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-09-04, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Primjena umjetne inteligencije u nuklearnom inženjerstvu Ovaj rad istražuje primjenu umjetne inteligencije (AI) u nuklearnoj industriji, s posebnim naglaskom na optimizaciju različitih faza životnog ciklusa nuklearnih reaktora, uključujući dizajn, rad, održavanje i zamjenu goriva. AI tehnologije, poput strojnog učenja, koriste se za analizu podataka, nadzor reaktora, predviđanje potreba za održavanjem te optimizaciju potrošnje goriva. Korištenje AI-a omogućava precizniji nadzor i povećava učinkovitost rada nuklearnih elektrana, dok smanjuje troškove i povećava sigurnost. Rad također razmatra postojeće izazove, kao što su problemi s prikupljanjem i kvalitetom podataka te dilema crne kutije koja se odnosi na netransparentnost odluka AI modela. Naglašava se potreba za razvojem standardiziranih skupova podataka i metodologija objašnjive umjetne inteligencije kako bi se povećala pouzdanost i transparentnost AI sustava u nuklearnoj industriji. Cilj rada je pružiti sveobuhvatan pregled trenutnog stanja i budućih smjerova istraživanja AI u nuklearnoj industriji, naglašavajući kako AI može poboljšati učinkovitost, sigurnost i ekonomičnost nuklearnih reaktora. Rad također razmatra potencijalne koristi i izazove u implementaciji AI tehnologija te predlaže rješenja za prevladavanje postojećih prepreka.
Abstract (english)
Application of Artificial Intelligence in Nuclear Engineering This paper explores the application of artificial intelligence (AI) in the nuclear industry, with a particular focus on optimizing various phases of the nuclear reactor lifecycle, including design, operation, maintenance, and fuel replacement. AI technologies, such as machine learning, are utilized for data analysis, reactor monitoring, maintenance prediction, and fuel consumption optimization. The use of AI enables more precise monitoring and enhances the efficiency of nuclear power plants while reducing costs and increasing safety. The paper also addresses existing challenges, such as issues with data collection and quality, and the black box dilemma related to the non-transparency of AI model decisions. It emphasizes the need for the development of standardized datasets and explainable artificial intelligence methodologies to increase the reliability and transparency of AI systems in the nuclear industry. The aim of the paper is to provide a comprehensive overview of the current state and future research directions of AI in the nuclear industry, highlighting how AI can improve the efficiency, safety, and economic viability of nuclear reactors. The paper also examines the potential benefits and challenges in implementing AI technologies and proposes solutions to overcome existing obstacles.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:551118
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2024-10-12 20:45:58