Numerical optimization of a predictive model for the
compressive strength of standard mortar

Κουλογιάννης, Αναστάσιος; Koulogiannis, Anastasios

dc.contributor.author	Κουλογιάννης, Αναστάσιος	el
dc.contributor.author	Koulogiannis, Anastasios	en
dc.date.accessioned	2022-06-16T10:36:08Z
dc.date.available	2022-06-16T10:36:08Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/55290
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.22988
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	Standard mortar	en
dc.subject	Resistance	en
dc.subject	Optimization	en
dc.subject	Hydration	en
dc.subject	Machine learning	en
dc.title	Numerical optimization of a predictive model for the compressive strength of standard mortar	en
dc.title	Αριθμητική βελτιστοποίηση ενός μοντέλου πρόβλεψης της θλιπτικής αντοχής ενός τυπικού κονιάματος	el
heal.type	bachelorThesis
heal.classification	Structural engineering	en
heal.language	en
heal.access	campus
heal.recordProvider	ntua	el
heal.publicationDate	2021-08-31
heal.abstract	In the present work we will deal with the numerical optimization of a predictive model for the compressive strength of standard mortar based on the kinetics of hydration and the assembly of the phases, which was developed by the innovation center of Holcim. The goal of this work will be to optimize the code of the model to solve the memory leak problem and reduce the computation time during the reverse analysis on a large number of data, as well as its further development to include a new database with new thermodynamic data and new types of hydrates. We will also try to develop new models based on machine learning algorithms and compare their results and accuracy with the physical model. The ultimate goal of this work is to find the best descriptor for compressive strength, based on the assembly of the phases. This descriptor allows us an understandable physical modeling and satisfactory predictions of the compressive strength, for different types of compound cements, according to their chemical composition and fineness.	en
heal.advisorName	Γιαννής, Γιώργος	el
heal.committeeMemberName	Φραγκιαδάκης, Μιχαήλ	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Πολιτικών Μηχανικών. Τομέας Μεταφορών και Συγκοινωνιακής Υποδομής	el
heal.academicPublisherID	ntua
heal.numberOfPages	40 σ.	el
heal.fullTextAvailability	false