dc.contributor.author | Λίταινας, Γεώργιος![]() |
el |
dc.contributor.author | Litainas, Georgios![]() |
en |
dc.date.accessioned | 2025-06-12T08:18:51Z | |
dc.date.available | 2025-06-12T08:18:51Z | |
dc.identifier.uri | https://dspace.lib.ntua.gr/xmlui/handle/123456789/62046 | |
dc.identifier.uri | http://dx.doi.org/10.26240/heal.ntua.29742 | |
dc.description | Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Υπολογιστική Μηχανική” | el |
dc.rights | Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/gr/ | * |
dc.subject | Stochastic scaled boundary finite element method | en |
dc.subject | Stochastic finite element method | en |
dc.subject | Monte carlo simulation | en |
dc.subject | Stochastic fields | en |
dc.title | Stochastic analysis via the scaled boundary finite element method | en |
heal.type | masterThesis | |
heal.classification | Computational stochastic mechanics | en |
heal.language | en | |
heal.access | campus | |
heal.recordProvider | ntua | el |
heal.publicationDate | 2024-10-01 | |
heal.abstract | Uncertainty quantification methods used to measure the incertitude of the systems/structures have been upgraded in the last decades and as a result, many more engineers take it into account for the analysis and design. With the view to including all the uncertainty factors that can cause damage to structures, without being considered in deterministic solutions, stochastic methods have been developed over the years. The Monte Carlo simulation is the most well-known technique in the field of stochastic analysis. Nonetheless, this method needs a large number of random samples and as a consequence, the computational cost can be rather high. On the other hand, researchers have developed what is known as the Spectral Stochastic Finite Element Method (SSFEM) to address stochastic challenges in structural analysis. This approach has garnered significant attention over the past decade due to its ability to handle a wide range of stochastic problems effectively. | en |
heal.advisorName | Τριανταφφύλου, Σάββας | el |
heal.committeeMemberName | Τριανταφύλλου, Σάββας | el |
heal.committeeMemberName | Παπαδόπουλος, Βησσαρίων | el |
heal.committeeMemberName | Λαγαρός, Νικόλαος | el |
heal.academicPublisher | Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Χημικών Μηχανικών | el |
heal.academicPublisherID | ntua | |
heal.numberOfPages | 145 σ. | el |
heal.fullTextAvailability | false |
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