Παρακαλώ χρησιμοποιήστε αυτό το αναγνωριστικό για να παραπέμψετε ή να δημιουργήσετε σύνδεσμο προς αυτό το τεκμήριο: https://hdl.handle.net/10442/19316
Export to:   BibTeX  | EndNote  | RIS
Εξειδίκευση τύπου : Άρθρο σε επιστημονικό περιοδικό
Τίτλος: Structural Diagnosis of Solid Rocket Motors Using Neural Networks and Embedded Optical Strain Sensors
Δημιουργός/Συγγραφέας: Korompili, Georgia
Cholevas, Nicholas
Anyfantis, Konstantinos N.
Mußbach, Günter
[EL] Ριζιώτης, Χρήστος Δ.[EN] Riziotis, Christossemantics logo
Ημερομηνία: 2024
Γλώσσα: Αγγλικά
ISSN: 2304-6732
DOI: 10.3390/photonics11090799
Περίληψη: The main failures that could deteriorate the reliable operation of solid rocket motors (SRMs) and lead to catastrophic events are related to bore cracks and delamination. Current SRMs’ predictive assessment and damage identification practices include time-consuming and cost-demanding destructive inspection techniques. By considering state-of-the-art optical strain sensors based on fiber Bragg gratings, a theoretical study on the use of such sensors embedded in the circumference of the composite propellant grain for damage detection is presented. Deep neural networks were considered for the accurate prediction of the presence and extent of the defects, trained using synthetic datasets derived through finite element analysis method. The evaluation of this combined approach proved highly efficient in discriminating between the healthy and the damaged condition, with an accuracy higher than 98%, and in predicting the extent of the defect with an error of 2.3 mm for the bore crack depth and 1.6° for the delamination angle (for a typical ~406 mm diameter grain) in the worst case of coexistent defects. This work suggests the basis for complete diagnosis of solid rocket motors by overcoming certain integration and performance limitations of currently employed dual bond stress and temperature sensors via the more scalable, safe, sensitive, and robust solution of fiber optic strain sensors.
Τίτλος πηγής δημοσίευσης: Photonics
Τόμος/Κεφάλαιο: 11
Τεύχος: 9
Θεματική Κατηγορία: [EL] Ηλεκτρική μηχανική. Ηλεκτρονική. Πυρινική μηχανικη[EN] Electrical engineering. Electronics. Nuclear engineeringsemantics logo
[EL] Φυσική και θεωρητική χημεία[EN] Physical and theoretical chemistrysemantics logo
Λέξεις-Κλειδιά: solid rocket motors
fiber Bragg gratings
optical strain sensors
finite element analysis
structural health monitoring
strain sensing
neural networks
crack
delamination
EU Grant: RocketSens
First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant
EU Grant identifier: 2018-0720-1
HFRI-FM17-640, InPhoQuC
Κάτοχος πνευματικών δικαιωμάτων: © 2024 by the authors. Licensee MDPI, Basel, Switzerland.
Όροι και προϋποθέσεις δικαιωμάτων: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Ηλεκτρονική διεύθυνση στον εκδότη (link): https://doi.org/10.3390/photonics11090799
Εμφανίζεται στις συλλογές:Ινστιτούτο Θεωρητικής και Φυσικής Χημείας (ΙΘΦΧ) - Επιστημονικό έργο

Αρχεία σε αυτό το τεκμήριο:
Αρχείο Περιγραφή ΣελίδεςΜέγεθοςΜορφότυποςΈκδοσηΆδεια
Korompili et al_2024_photonics11090799.pdfopen access article10.04 MBAdobe PDFΔημοσιευμένη/του ΕκδότηccbyΔείτε/ανοίξτε