Multiscale analysis of nano-composites using surrogate models

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dc.contributor.author Σοϊμοίρης, Γεώργιος el
dc.contributor.author Soimiris, George en
dc.date.accessioned 2021-01-12T07:51:04Z
dc.date.available 2021-01-12T07:51:04Z
dc.date.issued 2021-01-12
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/52764
dc.identifier.uri http://dx.doi.org/10.26240/heal.ntua.20462
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 Νανο-σύνθετα υλικά el
dc.subject Υποκατάστατη μοντελοποίηση el
dc.subject Νανοσωλήνες άνθρακα el
dc.subject Υπολογιστική ομογενοποίηση πολλαπλών κλιμάκων el
dc.subject Στοχαστική ανάλυση el
dc.subject Nano-composite materials en
dc.subject Surrogate modeling en
dc.subject Carbon nanotubes en
dc.subject Computational multiscale homogenization en
dc.subject Stochastic analysis en
dc.title Multiscale analysis of nano-composites using surrogate models en
dc.title.alternative Ανάλυση πολλαπλών κλιμάκων νανο-σύνθετων υλικών με χρήση υποκατάστατων μοντέλων el
dc.contributor.department Τομέας Δομοστατικής, Εργαστήριο Στατικής και Αντισεισμικών Ερευνών el
heal.type doctoralThesis
heal.generalDescription Στοχαστική μη-γραμμική ομογενοποίηση πολλαπλών κλιμάκων σύνθετων υλικών από νανοσωλήνες άνθρακα με χρήση υποκατάστατων μοντέλων el
heal.generalDescription Non-linear stochastic multiscale homogenization of carbon nanotube reinforced composites using surrogate modeling techniques en
heal.classification Υπολογιστική Μηχανική el
heal.classification Computational mechanics en
heal.language en
heal.access free
heal.recordProvider ntua el
heal.publicationDate 2020-12-15
heal.abstract The thesis at hand presents a neural network (NN)-based surrogate modeling approach suitable for the geometrically nonlinear analysis of carbon nanotubes (CNTs). In this work an NN-based Equivalent Beam Element (NN-EBE) is proposed, which is capable of accurately predicting the high-order phenomena caused by size-effects that characterize the behavior of CNTs at the nano-scale and can only be predicted by micro-mechanical models. The basic idea is to approximate the residual forces of the Newton–Raphson incremental-iterative formulation of the classical Euler or Timoshenko beams of the EBE model by an NN prediction, which is based on the response of the detailed MSM model of a CNT portion. Several numerical examples are presented for straight and wavy CNTs under bending and compression, which demonstrate that the proposed methodology is capable of efficiently predicting the nonlinear response of large-scale CNT structures in a fraction computing time compared to the full-scale problem. Moreover, an efficient multiscale analysis method for extracting the nonlinear constitutive law of carbon nanotube-reinforced composites (CNT-RCs) is proposed. This is accomplished via nonlinear computational homogenization on detailed FEM models of statistical volume elements (SVEs) of the composite material that can accurately describe its microstructure in a stochastic context. To this purpose, previous work of the authors on surrogate modeling of carbon nanotubes (CNTs) is extended to include CNT/matrix interface slippage phenomena and generalized to construct realistic RVEs of the composite that contain a large representative number of randomly dispersed, oriented and shaped CNTs. Wavy CNTs are modeled as a series of nonlinear EBEs with random initial imperfections. A statistical volume element (SVE) is developed, featuring the aforementioned modeling properties. The interface between the CNTs and the matrix is simulated using a cohesive zone formulation for the modeling of slippage through a nonlinear constitutive law. Computational homogenization is finally performed via stochastic averaging using a parallel implementation strategy in order to handle the associated extreme computational cost. The proposed analysis setup enables for realistic estimation of constitutive properties of advanced composites in a computationally efficient manner, allowing for sensitivity analysis with respect to various modeling assumptions. en
heal.sponsor European Council Advanced Grant MASTER - Mastering the computational challenges in numerical modeling and optimum design of CNT reinforced composites en
heal.sponsor State Scholarships Foundation Grant Research projects for excellency, IKY/SIEMENS en
heal.sponsor European Regional Development Fund and Greek national funds under the Grant HEAT - Optimal multiscale design of innovative materials for heat exchange applications is greatfully acknowledged en
heal.advisorName Παπαδόπουλος, Βησσαρίων el
heal.advisorName Papadopoulos, Vissarion en
heal.committeeMemberName Παπαδόπουλος, Βησσαρίων el
heal.committeeMemberName Λαγαρός, Νίκος el
heal.committeeMemberName Σπηλιόπουλος, Κωνσταντίνος el
heal.committeeMemberName Σαπουντζάκης, Ευάγγελος el
heal.committeeMemberName Νεραντζάκη, Μαρία el
heal.committeeMemberName Φραγκιαδάκης, Μιχάλης el
heal.committeeMemberName Τριανταφύλλου, Σάββας el
heal.academicPublisher Σχολή Πολιτικών Μηχανικών el
heal.academicPublisherID ntua
heal.numberOfPages 182 p. en
heal.fullTextAvailability false

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Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα Except where otherwise noted, this item's license is described as Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα