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Tesi etd-11192019-110751


Thesis type
Tesi di laurea magistrale
Author
ALUNNO ROSSETTI, BERNARDO
URN
etd-11192019-110751
Title
Numerical investigation of a parametric model for the material characterization of great vessels
Struttura
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA BIOMEDICA
Supervisors
relatore Ing. Positano, Vincenzo
relatore Ing. Fanni, Benigno Marco
controrelatore Prof.ssa Celi, Simona
Parole chiave
  • Young Modulus
  • FSI
  • PPVI
  • Finite element analysis
Data inizio appello
06/12/2019;
Consultabilità
Secretata d'ufficio
Data di rilascio
06/12/2089
Riassunto analitico
Nowadays, computer-based simulations, such as Finite Element Analysis (FEA), represent a powerful tool that can provide predictive information, aimed at outcome improvement. Currently the use of FEA is widely applied also in the medical field to solve basic scientific problems as well as to simulate clinical procedures in an in-silico environment.
The topic of this thesis is the study of the percutaneous pulmonary valve implantation (PPVI). This technique was introduced to handle congenital pulmonary valve pathologies by means of a minimally invasive approach by deploying a crimped valve-equipped stent in the right ventricular outflow tract.
The aim of this thesis is twofold: a preliminary modelling of PPVI procedure and the investigation of the effects of material properties. Regarding the first part, a simplified model of balloon and stent expansion was performed.
Secondly, starting from the solution of a modified inverse problem based on the pulse wave velocity approach, a deep investigation on the material effect on the PPVI is presented. To perform this, a specific in-silico campaign of FSI simulations of vessel models was developed. Different parameters have been analysed simultaneously: the Young modulus, the wall thickness, the vessel diameter and the peak blood flow.
All the simulations were performed by using the LS-DYNA platform.
This work has resulted in a more complete parametrization of the PWV-based equation of the estimation of the Young modulus. A more accurate material description would improve advances in both device design and clinical decisions towards personalised care solutions with new modelling environments for predictive, individualised healthcare to guarantee better patient safety and efficacy.
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