Multiscale analysis of nano-composites using surrogate models

Σοϊμοίρης, Γεώργιος; Soimiris, George

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