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Tesi etd-09152016-153922


Tipo di tesi
Tesi di laurea magistrale
Autore
IZZI, MICHELE IACOPO
URN
etd-09152016-153922
Titolo
Multi-scale analysis, design and optimisation of multilayer plates: application and experimental validation of the two-level multi-scale design strategy.
Dipartimento
INGEGNERIA CIVILE E INDUSTRIALE
Corso di studi
INGEGNERIA AEROSPAZIALE
Relatori
relatore Prof. Fanteria, Daniele
relatore Prof. Montemurro, Marco
correlatore Prof. Perry, Nicolas
correlatore Prof. El-yagoubi, Jalal
Parole chiave
  • buckling
  • composite plate
  • genetic algorithm
  • laminate
  • optimization
  • Polar parameters
Data inizio appello
04/10/2016
Consultabilità
Completa
Riassunto
In this text is presented an application and experimental validation of a two-level multi-scale design strategy for composite laminates. The case study-case is the least weight design of a flat laminated plate that could reach an assigned buckling load under compressive loading. The applied design strategy, known as “Polar-Genetic”, consists of two steps: in the first step the least weight problem is solved searching the polar parameters that define the optimal plate as an equivalent single layer, in the second step the stacking sequence that better corresponds to this optimal plate is found. Both steps are solved by mean of a genetic algorithm. The choice of the studied case, deliberately simple, allowed the setup of an experimental activity aimed at validating the FEM simulation model used in the first optimization process and at laying the foundations for a first validation of the design strategy. At the same time the studied case is enough complex to be non-trivial and highlight much of the potential of the design strategy. To compare the experimental work with the numerical one, the mechanical properties of the used material were needed, so an experimental activity of mechanical characterization has also been performed and is described in this report. The presence of a coupled experimental activity is the real adding to the work already done by Montemurro in applying the Polar-Genetic strategy to various engineering optimal design problems.
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