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Ανάλυση κόστους κύκλου ζωής και βελτιστοποίηση για κατασκευές από χάλυβα και οπλισμένο σκυρόδεμα

Bekas Georgios

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/DA2CC5F3-8011-4CDC-88E6-7A85E600C6FB
Έτος 2017
Τύπος Διδακτορική Διατριβή
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά Γεώργιος Μπέκας, "Ανάλυση κόστους κύκλου ζωής και βελτιστοποίηση για κατασκευές από χάλυβα και οπλισμένο σκυρόδεμα", Διδακτορική Διατριβή, Σχολή Μηχανικών Παραγωγής και Διοίκησης, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2017 https://doi.org/10.26233/heallink.tuc.71491
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Περίληψη

The present study seeks to investigate the factors that play a key role in the whole life cost of a new building construction, aiming to its minimization with the use of the optimization theory. An analysis on the notion of the whole life cost, as well as of the subsystems that primarily influence the whole life cost of a typical building, leads to the conclusion that the subsystems related to its massing, its structural components and its energy performance, are the ones whose optimization -at an early stage- has significant importance.The models that will be presented are based on the calculation and optimization of the most critical parameters related to the energy and the structural design of buildings with steel, timber or reinforced concrete frames. The examined variables of the optimization therefore concern all the characteristic structural, envelope, mechanical and energy subsystems throughout their life cycle (building envelope U-values in every possible orientation, area of windows in every possible orientation of the building, window glazing solar gain coefficient, power and performance of the heating and the cooling HVAC systems, cross sections of all the beam and column elements of the building, optimal number of frame bays, optimal lengths of frame bays, spacing among frames). Various life cycle periods with different durations and building plans, are examined. Other parameters that are analyzed, is the effect of the fuzziness of the design temperature inside a building on its life cycle cost, maintenance and potential replacement of the examined subsystems and methods to predict an optimal scenario for the management of the structural frame components at the end of a building's life cycle. The modeling is based on KENAK, the Eurocodes, evolutionary algorithms, statistical, stochastic and machine learning systems. A literature review regarding modern specifications and scientific approaches has also included in the study, about the following topics: life cycle analysis, whole life cost analysis, multivariate statistics and machine learning, stochastic processes and optimization, energy simulation of buildings, sizing of thermal and cooling systems, structural design of steel, RC or timber buildings.

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