H Χρονικά Μη-Μόνιμη Διακριτή Συζυγής Μέθοδος με Διατύπωση στο Πεδίο του Χρόνου για τη Βελτιστοποίηση Μορφής στις Στροβιλομηχανές

Ντανάκας, Γεώργιος; Ntanakas, Georgios

dc.contributor.author	Ντανάκας, Γεώργιος	el
dc.contributor.author	Ntanakas, Georgios	en
dc.date.accessioned	2019-04-08T09:16:29Z
dc.date.available	2019-04-08T09:16:29Z
dc.date.issued	2019-04-08
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/48580
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.3081
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	Διακριτή Συζυγής Μέθοδος	el
dc.subject	Αεροδυναμική Βελτιστοποίηση Σχήματος	el
dc.subject	Στροβιλομηχανές	el
dc.subject	Υπολογιστική Ρευστοδυναμική	el
dc.subject	Μη-Μόνιμες Ροές	el
dc.subject	Computational Fluid Dynamic	en
dc.subject	Unsteady Discrete Adjoint Method	en
dc.subject	Sensitivity Derivatives	en
dc.subject	Shape Optimization	en
dc.subject	Multi-row Turbomachinery	en
dc.title	H Χρονικά Μη-Μόνιμη Διακριτή Συζυγής Μέθοδος με Διατύπωση στο Πεδίο του Χρόνου για τη Βελτιστοποίηση Μορφής στις Στροβιλομηχανές	el
dc.title	Unsteady Discrete Adjoint Method Formulated in the Time-Domain for Shape Optimization in Turbomachinery	en
dc.contributor.department	Τομέας Στροβιλομηχανών	el
heal.type	doctoralThesis
heal.generalDescription	Αγγλικό Κείμενο + Εκτενής Ελληνική Περίληψη	el
heal.classification	Υπολογιστική Ρευστοδυναμική	el
heal.classification	Computational Fluid Dynamics	en
heal.language	en
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2018-12-21
heal.abstract	This PhD thesis deals with the mathematical formulation, solution, programming and validation of the unsteady discrete adjoint method, formulated in the time-domain, for the computation of first-order sensitivity derivatives for objective functions related to the aerodynamics of turbomachinery and their utilization in optimization algorithms. The cases that are tackled involve the constrained optimization of industrial, 3D, multirow, turbomachinery configurations with transient and periodic flows. The unsteady adjoint equations are formulated for an objective function in the form of a time-integral over a selected time-interval. The dual time-stepping technique is used to solve the unsteady adjoint equations along with an iterative scheme, which is the adjoint to the 5-stage Runge-Kutta scheme used for the flow equations and which is derived "by-hand". The scheme is formulated so as to ensure same convergence rate as the Unsteady Reynolds-Averaged Navier-Stokes (URANS) solver. Algorithmic Differentiation (AD) is employed in the adjoint solver for the computation of selected differential terms. Its usage is restricted to low level operations and combined with hand-differentiation to ensure efficiency. To enable communication between adjacent row-domains in the adjoint solver, the adjoint sliding interface is developed to replace the mixing interface technique used in steady state solvers. Its baseline is the sliding interface of the flow solver where grids of adjacent rows are generated so that there is a one-cell overlap. AD along with hand programming ensure that the implementation is consistent with the reverse flow of information in the adjoint solver. The solver utilizes the SSD disk space instead of RAM to store and read-in, in a parallel manner, the per-time-step flow fields during the adjoint execution. Thus, RAM bottlenecks are avoided while run time is not significantly increased. The temporal coarsening technique is employed in the adjoint solver to decrease the run time and the required storage space when this exceeds the available storage capacity. Adjoint-based derivatives are computed and used within the optimization workflow. If equality constraints are considered, the component of the objective function’s gradient which is normal to the constraints’ gradients is used along with the projected gradient descent method to update the design variables and, thus, the geometry. In unconstrained optimization problems, steepest descent is used. The developed software is applied to the shape optimization of 3D, multi-row, turbomachinery cases for the first time in the literature. The application cases include one single row turbine case (transient operation), one stage turbine case (periodic flow study) and one 3-row compressor case (periodic flow study). The computed derivatives are validated against the derivatives computed via finite differences and, then, used in optimization setups with and without equality constraints.	en
heal.sponsor	AboutFlow ITN, Marie Curie Actions, FP7	en
heal.advisorName	Γιαννάκογλου, Κυριάκος	el
heal.advisorName	Giannakoglou, Kyriakos	en
heal.committeeMemberName	Αρετάκης, Νικόλαος	el
heal.committeeMemberName	Βουτσινάς, Σπυρίδων	el
heal.committeeMemberName	Μαθιουδάκης, Κωνσταντίνος	el
heal.committeeMemberName	Νικολός, Ιωάννης	el
heal.committeeMemberName	Καϊκτσής, Λάμπρος	el
heal.committeeMemberName	Ρουμελιώτης, Ιωάννης	el
heal.academicPublisher	Σχολή Μηχανολόγων Μηχανικών	el
heal.academicPublisherID	ntua
heal.numberOfPages	237
heal.fullTextAvailability	true