Дисертації з теми "Spectral Proper Orthogonal Decomposition"
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Le, Thai Hoa. "UNSTEADY BUFFETING FORCES AND GUST RESPONSE OF BRIDGES WITH PROPER ORTHOGONAL DECOMPOSITION APPLICATIONS." 京都大学 (Kyoto University), 2007. http://hdl.handle.net/2433/49126.
Повний текст джерелаThe unsteady buffeting forces and the gust response prediction of bridges in the atmospheric turbulent flows is recently attracted more attention due to uncertainties in both experiment and analytical theory. The correction functions such as the aerodynamic admittance function and the spatial coherence function have been supplemented to cope with limitations of the quasi-steady theory and strip one so far. Concretely, so-called single-variate quasi-steady aerodynamic admittance functions as the transfer functions between the wind turbulence and induced buffeting forces, as well as coherence of wind turbulence has been widely applied for the gust response prediction. Recent literatures, however, pointed out that the coherence of force exhibits higher than that of turbulence. These correction functions, in the other words, contain their uncertainties which are required to be more understanding. Proper orthogonal decomposition (POD), known as the Karhunen-Loeve decomposition has been applied popularly in many engineering fields. Main advantage of the POD is that the multi-variate correlated random fields/processes can be decomposed and described in such simplified way as a combination of limited number of orthogonally low-order dominant eigenvectors (or turbulent modes) which is convenient and applicable for order-reduced representation, simulation of the random fields/processes such as the turbulent fields, turbulent-induced force fields and stochastic response prediction as well. The POD and its proper transformations based on either zero-time-lag covariance matrix or cross spectral one of random fields/processes have been branched by either the covariance proper transformation (CPT) in the time domain or the spectral proper transformation (SPT) in the frequency domain. So far, the covariance matrix-based POD and its covariance proper transformation in the time domain has been used almost in the wind engineering topics due to its simplification in computation and interpretation. In this research, the unsteady buffeting forces and the gust response prediction of bridges with emphasis on the POD applications have been discussed. Investigations on the admittance function of turbulent-induced buffeting forces and the coherence one of the surface pressure as well as the spatial distribution and correlation of the unsteady pressure fields around some typically rectangular cylinders in the different unsteady flows have been carried out thanks to physical measurements in the wind tunnel. This research indicated effect of the bluff body flow and the wind-structure interaction on the higher coherence of buffeting forces than the coherence of turbulence, thus this effect should be accounted and undated for recent empirical formulae of the coherence function of the unsteady buffeting forces. Especially, the multi-variate nonlinear aerodynamic admittance function has been proposed in this research, as well as the temporo-spectral structure of the coherence functions of the wind turbulence and the buffeting forces has been firstly here using the wavelet transform-based coherence in order to detect intermittent characteristics and temporal correspondence of these coherence functions. In POD applications, three potential topics in the wind engineering field have been discussed in the research: (i) analysis and identification, modeling of unsteady pressure fields around model sections; (ii) representation and simulation of multi-variate correlated turbulent fields and (iii) stochastic response prediction of structures and bridges. Especially, both POD branches and their proper transformations in the time domain and the frequency one have been used in these applications. It found from these studies that only few low-order orthogonal dominant modes are enough accuracy for representing, modeling, simulating the correlated random fields (turbulence and unsteady surface pressure, unsteady buffeting forces), as well as predicting stochastic response of bridges in the time and frequency domains. The gust response prediction of bridges has been formulated in the time domain at the first time in this research using the covariance matrix-based POD and its covariance proper transformation which is very promising to solve the problems of the nonlinear and unsteady aerodynamics. Furthermore, the physical linkage between these low-order modes and physical causes occurring on physical models has been interpreted in some investigated cases.
Kyoto University (京都大学)
0048
新制・課程博士
博士(工学)
甲第13372号
工博第2843号
新制||工||1418(附属図書館)
25528
UT51-2007-Q773
京都大学大学院工学研究科社会基盤工学専攻
(主査)教授 松本 勝, 教授 河井 宏允, 准教授 白土 博通
学位規則第4条第1項該当
Malm, Johan. "Spectral-element simulations of turbulent wall-bounded flows including transition and separation." Doctoral thesis, KTH, Stabilitet, Transition, Kontroll, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-50294.
Повний текст джерелаQC 20111206
Spitz, Nicolas. "Prediction of Trailing Edge Noise from Two-Point Velocity Correlations." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/32637.
Повний текст джерелаMaster of Science
Di, Donfrancesco Fabrizio. "Reduced Order Models for the Navier-Stokes equations for aeroelasticity." Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS603.
Повний текст джерелаThe numerical prediction of aeroelastic systems responses becomes unaffordable when parametric analyses with high-fidelity CFD are required. Reduced order modeling (ROM) methods have therefore been developed in view of reducing the costs of the numerical simulations while preserving a high level of accuracy. The present thesis focuses on the family of projection based methods for the compressible Navier-Stokes equations involving deforming meshes in the case of aeroelastic applications. A vector basis obtained by Proper Orthogonal Decomposition (POD) combined to a Galerkin projection of the system equations is used in order to build a ROM for fluid mechanics. Masked projection approaches are therefore implemented and assessed for different test cases with fixed boundaries in order to provide a fully nonlinear formulation for the projection-based ROMs. Then, the ROM is adapted in the case of deforming boundaries and aeroelastic applications in a parametric context. Finally, a Reduced Order Time Spectral Method (ROTSM) is formulated in order to address the stability issues which involve the projection-based ROMs for fluid mechanics applications
Allison, Timothy Charles. "System Identification via the Proper Orthogonal Decomposition." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/29424.
Повний текст джерелаPh. D.
Omar, Ahmed F. "Calibrating pressure sensitive paints using proper orthogonal decomposition." [Gainesville, Fla.] : University of Florida, 2006. http://purl.fcla.edu/fcla/etd/UFE0013431.
Повний текст джерелаToal, David J. J. "Proper orthogonal decomposition & kriging strategies for design." Thesis, University of Southampton, 2009. https://eprints.soton.ac.uk/72023/.
Повний текст джерелаDOLCI, VALENTINA. "Proper Orthogonal Decomposition for Surrogate Models in Aerodynamics." Doctoral thesis, Politecnico di Torino, 2017. http://hdl.handle.net/11583/2678186.
Повний текст джерелаAkkari, Nissrine. "Etude mathématique de la sensibilité POD (Proper orthogonal decomposition)." Phd thesis, Université de La Rochelle, 2012. http://tel.archives-ouvertes.fr/tel-01066073.
Повний текст джерелаBehzad, Fariduddin. "Proper Orthogonal Decomposition Based Reduced Order Modeling for Fluid Flow." Thesis, Clarkson University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3682451.
Повний текст джерелаProper orthogonal decomposition-based reduced order modeling is a technique that can be used to develop low dimensional models of fluid flow. In this technique, the Navier-Stokes equations are projected onto a finite number of POD basis functions resulting in a system of ODEs that model the system. The overarching goal of this work is to determine the best methods of applying this technique to generate reliable models of fluid flow. The first chapter investigates some basic characteristics of the proper orthogonal decomposition using the Burgers equation as a surrogate model problem. In applying the POD to this problem, we found that the eigenvalue spectrum is affected by machine precision and this leads to non-phsical negative eigenvalues in the POD. To avoid this, we introduced a new method called deflation that gives positive eigenvalues, but has the disadvantage that the orthogonality of the POD modes is more affected by numerical precision errors. To reduce the size of eigenproblem of POD process, the well-known snapshot method was tested. It was found that the number of snapshots required to obtain an accurate eigenvalue spectrum was determined by the smallest time scale of the phenomenon. After resolving this time scale, the errors in the eigenvalues and modes drop rapidly then converge with second-order accuracy. After obtaing POD modes, the ROM error was assessed using two errors, the error of projection of the problem onto the POD modes (the out-plane error) and the error of the ROM in the space spanned by POD modes (the in-plane error). The numerical results showed not only is the in-plane error bounded by the out-plane error (in agreement with theory) but it actually converges faster than the out-of-plane error. The second chapter is dedicated to building a robust POD-ROM for long term simulation of Navier-Stokes equation. The ability of the POD method to decompose the simulation and the capability of POD-ROM to simulate a low and high Reynolds flow over a NACA0015 airfoil was studied. We observed that POD can be applied for low Reynolds flows successfully if a proper stabilization method is used. For the high Reynolds case, the convergence of the eigenvalues spectrum with respect to duration of time window from we observed that the number of modes needed to simulate a certain time window increases almost linearly with the length of the time window. So, generating a POD-ROM for high Reynolds flow that reproduced the correct long-term limit cycle behavior needs many more modes than has been usually used in the literature. In the last chapter, we address the problem that the standard method of generating POD modes may be inaccurate when used "off-design" (at parameter values not used to generate the POD). We tested some of the popular methods developed to remedy that problem. The accuracy of these methods was in direct relation with the amount of data provided for those methods. So, in order to generate appropriate POD modes, very large POD problems must be solved. To avoid this, a new multi-level method, called recursive POD, for enriching the POD modes is introduced that mathematically provides optimal POD modes while reducing the computational size of problem to a manageable degrees. A low Reynolds flow over NACA 0015, actuated with constant suction/blowing of a fluidic jet located on top surface of airfoil is used as benchmark to test the technique. The flow is shifted from one periodic state to another periodic state due to fluidic jet effect. It was found that the modes extracted with the recursive POD method are as accurate as the modes of the best known method, global POD, while the computational effort is lower.
Malla, Bhupatindra. "Study of High-speed Subsonic Jets using Proper Orthogonal Decomposition." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1352397174.
Повний текст джерелаMignee, Juliette L. "Proper Orthogonal Decomposition Applied to a Supersonic Single Flow Jet." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1329935384.
Повний текст джерелаSpencer, Ronald Alex. "Analysis of High Fidelity Turbomachinery CFD Using Proper Orthogonal Decomposition." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/5846.
Повний текст джерелаKrenciszek, Joachim [Verfasser]. "Proper Orthogonal Decomposition for Contact and Free Boundary Problems / Joachim Krenciszek." München : Verlag Dr. Hut, 2014. http://d-nb.info/1055864148/34.
Повний текст джерелаYuan, Tao. "Reduced order modeling for transport phenomena based on proper orthogonal decomposition." Texas A&M University, 2003. http://hdl.handle.net/1969.1/1470.
Повний текст джерелаLau, Tony 1978. "Application of the proper orthogonal decomposition to slat cove noise modeling." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/82776.
Повний текст джерелаJarvis, Christopher Hunter. "Reduced Order Model Study of Burgers' Equation using Proper Orthogonal Decomposition." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/31580.
Повний текст джерелаMaster of Science
Atwell, Jeanne A. "Proper Orthogonal Decomposition for Reduced Order Control of Partial Differential Equations." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/26985.
Повний текст джерелаPh. D.
Beach, Benjamin Josiah. "An Implementation-Based Exploration of HAPOD: Hierarchical Approximate Proper Orthogonal Decomposition." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/81938.
Повний текст джерелаMaster of Science
Sze, Kin Wai. "Structural health monitoring and damage assessment based on proper orthogonal decomposition /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?CIVL%202004%20SZE.
Повний текст джерелаAdnan, Farasatul. "Proper orthogonal decomposition (POD): application to finite element analysis of electromagnetic diffusion." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103769.
Повний текст джерелаLa Décomposition Orthogonale Nécessaire (POD) est une technique qui a été utilisée avec succès pour réduire le temps de compte dans les champs différents d'ingénierie. Ici la POD est appliqué les comptes électromagnétiques de terrain, spécialement à la simulation de la diffusion électromagnétique par le domaine de temps la méthode d'élément finie. La norme la méthode exige à une grande équation matricielle d'être résolue au pas de chaque fois. La POD est appliquée beaucoup réduire la grandeur du matrices. De 1ème que 2ème cas tant d'essai sont considérés. L'application de la POD réduit la dimension matricielle pour un 2ème problème de 2,535 à juste 5, avec la perte négligeable d'exactitude.
Caraballo, Edgar Javier. "An application of the proper orthogonal decomposition to an axisymmetric supersonic jet." The Ohio State University, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=osu1406646741.
Повний текст джерелаRama, Ritesh Rao. "Proper orthogonal decomposition with interpolation-based real-time modelling of the heart." Doctoral thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/26859.
Повний текст джерелаSévénié, Benjamin. "Capsule deformation in a microfluidic channel : experiments, characterization and Proper Orthogonal Decomposition." Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2278/document.
Повний текст джерелаThe motion and deformation of a liquid-filled classic microcapsule flowing in microchannels is investigated bath experimentally and numerically. The flow of capsules into a straight microfluidic channel with a square cross-section is firstly studied. The objective is to develop a method to determine the mechanical properties of the capsule membrane from its hydrodynamic deformation. A method of identification has been devised to compare the particle deformed shape measured experimentally in the microchannels to the ones predicted by a three-dimensional numerical model for the same configuration. The precision and robustness of the inverse analysis algorithm have been tested when the microfluidic channels slightly depart from pure squareness. We have finally applied the method on microcapsules with a membrane made of reticulated albumin and determined their rnechanical properties. A Proper Orthogonal Decomposition (POD) has then been applied to the shapes assumed by the capsules while flowing in either a straight or bi furcated channel. Using numerical data in a straight channel, we have determined the dimension of the capsule shape variety. We have then interpolated the coefficients resulting from the POD analysis to compute the capsule deformed shape at any time for any flow parameter. Capsules have finally been investigated flowing in a bifurcated microchannel. Qualitative results of the motion and deformation of capsules in such channel have been obtained. A semi-automatic contour detection program has been developed to improve the image analysis. The POD method has been applied to the experimental results, thus proving the feasibility of building a reduced-order model of the phenomenon by using a POD reduced basis
Blanc, Trevor Jon. "Analysis and Compression of Large CFD Data Sets Using Proper Orthogonal Decomposition." BYU ScholarsArchive, 2014. https://scholarsarchive.byu.edu/etd/5303.
Повний текст джерелаWise, John Nathaniel. "Inverse modelling and optimisation in numerical groundwater flow models using proper orthogonal decomposition." Thesis, Saint-Etienne, EMSE, 2015. http://www.theses.fr/2015EMSE0773/document.
Повний текст джерелаThe Richards equation describes the movement of an unsaturated fluid through a porous media, and is characterised as a non-linear partial differential equation. The equation is subject to a number of parameters and is typically computationnaly expensive to solve. To determine the parameters in the Richards equation, inverse modelling studies often need to be undertaken. As a solution to overcome the computational expense incurred in inverse modelling, the use of Proper Orthogonal Decomposition (POD) as a Reduced Order Modelling (ROM) method is proposed in this thesis to speed-up individual simulations. The Petrov-Galerkin POD approach is initially applied to the Richards equation and tested on different case studies. However, due to the non-linear nature of the Richards equation the method does not result in significant speed up times. Subsquently, the Petrov-Galerkin method is adapted by linearising the nonlinear terms in the equation, resulting in speed-up times in the range of [10,100]., The adaptation, notably, does not use any interpolation techniques, favouring an intrusive, but physics-based, approach. While the use of intrusive POD approaches add to the complexity of the ROM, it avoids the problem of finding kernel parameters typically present in interpolative POD approaches. Furthermore, the interpolative and possible extrapolation properties inherent to intrusive PODROM's are explored. The good extrapolation propertie, within predetermined bounds, of intrusive POD's allows for the development of an optimisation approach requiring a very small Design of Experiments (DOE). The optimisation method creates locally accurate models within the parameters space usign Support Vector Classification. The limits of the locally accurate model are called the confidence region. The methods are demonstrated on a hypothetical unsaturated case study requiring the Richards equation, and on true case study in the Table Mountain Group near Cape Town, South Africa
Sen, Mehmet Ali. "Proper Orthogonal Decomposition Methodology to Understand Underlying Physics of Rough-Wall Turbulent Boundary Layer." Fogler Library, University of Maine, 2007. http://www.library.umaine.edu/theses/pdf/SenMA2007.pdf.
Повний текст джерелаGräßle, Carmen [Verfasser], and Michael [Akademischer Betreuer] Hinze. "Adaptivity in Model Order Reduction with Proper Orthogonal Decomposition / Carmen Gräßle ; Betreuer: Michael Hinze." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2019. http://d-nb.info/1190819155/34.
Повний текст джерелаGräßle, Carmen Verfasser], and Michael [Akademischer Betreuer] [Hinze. "Adaptivity in Model Order Reduction with Proper Orthogonal Decomposition / Carmen Gräßle ; Betreuer: Michael Hinze." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2019. http://nbn-resolving.de/urn:nbn:de:gbv:18-98550.
Повний текст джерелаWise, John Nathaniel. "Inverse modelling and optimisation in numerical groundwater flow models using proportional orthogonal decomposition." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/97116.
Повний текст джерелаENGLISH ABSTRACT: Numerical simulations are widely used for predicting and optimising the exploitation of aquifers. They are also used to determine certain physical parameters, for example soil conductivity, by inverse calculations, where the model parameters are changed until the model results correspond optimally to measurements taken on site. The Richards’ equation describes the movement of an unsaturated fluid through porous media, and is characterised as a non-linear partial differential equation. The equation is subject to a number of parameters and is typically computationally expensive to solve. To determine the parameters in the Richards’ equation, inverse modelling studies often need to be undertaken. In these studies, the parameters of a numerical model are varied until the numerical response matches a measured response. Inverse modelling studies typically require 100’s of simulations, which implies that parameter optimisation in unsaturated case studies is common only in small or 1D problems in the literature. As a solution to overcome the computational expense incurred in inverse modelling, the use of Proper Orthogonal Decomposition (POD) as a Reduced Order Modelling (ROM) method is proposed in this thesis to speed-up individual simulations. An explanation of the Finite Element Method (FEM) is given using the Galerkin method, followed by a detailed explanation of the Galerkin POD approach. In the development of the Galerkin POD approach, the method of reducing matrices and vectors is shown, and the treatment of Neumann and Dirichlet boundary values is explained. The Galerkin POD method is applied to two case studies. The first case study is the Kogelberg site in the Table Mountain Group near Cape Town in South Africa. The response of the site is modelled at one well over the period of 2 years, and is assumed to be governed by saturated flow, making it a linear problem. The site is modelled as a 3D transient, homogeneous site, using 15 layers and ≈ 20000 nodes, using the FEM implemented on the open-source software FreeFem++. The model takes the evapotranspiration of the fynbos vegetation at the site into consideration, allowing the calculation of annual recharge into the aquifer. The ROM is created from high-fidelity responses taken over time at different parameter points, and speed-up times of ≈ 500 are achieved, corresponding to speed-up times found in the literature for linear problems. The purpose of the saturated groundwater model is to demonstrate that a POD-based ROM can approximate the full model response over the entire parameter domain, highlighting the excellent interpolation qualities and speed-up times of the Galerkin POD approach, when applied to linear problems. A second case study is undertaken on a synthetic unsaturated case study, using the Richards’ equation to describe the water movement. The model is a 2D transient model consisting of ≈ 5000 nodes, and is also created using FreeFem++. The Galerkin POD method is applied to the case study in order to replicate the high-fidelity response. This did not yield in any speed-up times, since the full matrices of non-linear problems need to be recreated at each time step in the transient simulation. Subsequently, a method is proposed in this thesis that adapts the Galerkin POD method by linearising the non-linear terms in the Richards’ equation, in a method named the Linearised Galerkin POD (LGP) method. This method is applied to the same 2D synthetic problem, and results in speed-up times in the range of 10 to 100. The adaptation, notably, does not use any interpolation techniques, favouring a code intrusive, but physics-based, approach. While the use of an intrusively linearised POD approach adds to the complexity of the ROM, it avoids the problem of finding kernel parameters typically present in interpolative POD approaches. Furthermore, the interpolation and possible extrapolation properties inherent to intrusive POD-based ROM’s are explored. The good extrapolation properties, within predetermined bounds, of intrusive POD’s allows for the development of an optimisation approach requiring a very small Design of Experiments (DOE) sets (e.g. with improved Latin Hypercube sampling). The optimisation method creates locally accurate models within the parameter space using Support Vector Classification (SVC). The region inside of the parameter space in which the optimiser is allowed to move is called the confidence region. This confidence region is chosen as the parameter region in which the ROM meets certain accuracy conditions. With the proposed optimisation technique, advantage is taken of the good extrapolation characteristics of the intrusive POD-based ROM’s. A further advantage of this optimisation approach is that the ROM is built on a set of high-fidelity responses obtained prior to the inverse modelling study, avoiding the need for full simulations during the inverse modelling study. In the methodologies and case studies presented in this thesis, initially infeasible inverse modelling problems are made possible by the use of the POD-based ROM’s. The speed up times and extrapolation properties of POD-based ROM’s are also shown to be favourable. In this research, the use of POD as a groundwater management tool for saturated and unsaturated sites is evident, and allows for the quick evaluation of different scenarios that would otherwise not be possible. It is proposed that a form of POD be implemented in conventional groundwater software to significantly reduce the time required for inverse modelling studies, thereby allowing for more effective groundwater management.
AFRIKAANSE OPSOMMING: Die Richards vergelyking beskryf die beweging van ’n vloeistof deur ’n onversadigde poreuse media, en word gekenmerk as ’n nie-lineêre parsiële differensiaalvergelyking. Die vergelyking is onderhewig aan ’n aantal parameters en is tipies berekeningsintensief om op te los. Om die parameters in die Richards vergelyking te bepaal, moet parameter optimering studies dikwels onderneem word. In hierdie studies, word die parameters van ’n numeriese model verander totdat die numeriese resultate die gemete resultate pas. Parameter optimering studies vereis in die orde van honderde simulasies, wat beteken dat studies wat gebruik maak van die Richards vergelyking net algemeen is in 1D probleme in die literatuur. As ’n oplossing vir die berekingskoste wat vereis word in parameter optimering studies, is die gebruik van Eie Ortogonale Ontbinding (POD) as ’n Verminderde Orde Model (ROM) in hierdie tesis voorgestel om individuele simulasies te versnel in die optimering konteks. Die Galerkin POD benadering is aanvanklik ondersoek en toegepas op die Richards vergelyking, en daarna is die tegniek getoets op verskeie gevallestudies. Die Galerkin POD metode word gedemonstreer op ’n hipotetiese gevallestudie waarin water beweging deur die Richards-vergelyking beskryf word. As gevolg van die nie-lineêre aard van die Richards vergelyking, het die Galerkin POD metode nie gelei tot beduidende vermindering in die berekeningskoste per simulasie nie. ’n Verdere gevallestudie word gedoen op ’n ware grootskaalse terrein in die Tafelberg Groep naby Kaapstad, Suid-Afrika, waar die grondwater beweging as versadig beskou word. Weens die lineêre aard van die vergelyking wat die beweging van versadigde water beskryf, is merkwaardige versnellings van > 500 in die ROM waargeneem in hierdie gevallestudie. Daarna was die die Galerkin POD metode aangepas deur die nie-lineêre terme in die Richards vergelyking te lineariseer. Die tegniek word die geLineariserde Galerkin POD (LGP) tegniek genoem. Die aanpassing het goeie resultate getoon, met versnellings groter as 50 keer wanneer die ROM met die oorspronklike simulasie vergelyk word. Al maak die tegniek gebruik van verder lineariseering, is die metode nogsteeds ’n fisika-gebaseerde benadering, en maak nie gebruik van interpolasie tegnieke nie. Die gebruik van ’n fisika-gebaseerde POD benaderings dra by tot die kompleksiteit van ’n volledige numeriese model, maar die kompleksiteit is geregverdig deur die merkwaardige versnellings in parameter optimerings studies. Verder word die interpolasie eienskappe, en moontlike ekstrapolasie eienskappe, inherent aan fisika-gebaseerde POD ROM tegnieke ondersoek in die navorsing. In die navorsing word ’n tegniek voorgestel waarin hierdie inherente eienskappe gebruik word om plaaslik akkurate modelle binne die parameter ruimte te skep. Die voorgestelde tegniek maak gebruik van ondersteunende vektor klassifikasie. Die grense van die plaaslik akkurate model word ’n vertrouens gebeid genoem. Hierdie vertrouens gebied is gekies as die parameter ruimte waarin die ROM voldoen aan vooraf uitgekiesde akkuraatheidsvereistes. Die optimeeringsbenadering vermy ook die uitvoer van volledige simulasies tydens die parameter optimering, deur gebruik te maak van ’n ROM wat gebaseer is op die resultate van ’n stel volledige simulasies, voordat die parameter optimering studie gedoen word. Die volledige simulasies word tipies uitgevoer op parameter punte wat gekies word deur ’n proses wat genoem word die ontwerp van eksperimente. Verdere hipotetiese grondwater gevallestudies is onderneem om die LGP en die plaaslik akkurate tegnieke te toets. In hierdie gevallestudies is die grondwater beweging weereens beskryf deur die Richards vergelyking. In die gevalle studie word komplekse en tyd-rowende modellerings probleme vervang deur ’n POD gebaseerde ROM, waarin individuele simulasies merkwaardig vinniger is. Die spoed en interpolasie/ekstrapolasie eienskappe blyk baie gunstig te wees. In hierdie navorsing is die gebruik van verminderde orde modelle as ’n grondwaterbestuursinstrument duidelik getoon, waarin voorsiening geskep word vir die vinnige evaluering van verskillende modellering situasies, wat andersins nie moontlik is nie. Daar word voorgestel dat ’n vorm van POD in konvensionele grondwater sagteware geïmplementeer word om aansienlike versnellings in parameter studies moontlik te maak, wat na meer effektiewe bestuur van grondwater sal lei.
Richardson, Brian Ross. "A reduced-order model based on proper orthogonal decomposition for non-isothermal two-phase flows." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2623.
Повний текст джерелаBlanchard, Ryan P. "Simulating Bluff-body Flameholders: On the Use of Proper Orthogonal Decomposition for Combustion Dynamics Validation." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/48430.
Повний текст джерелаPh. D.
VERFAILLIE, SWANN. "CORRELATIVE STUDIES AND COHERENT STRUCTURES EDUCTION BASED ON PROPER ORTHOGONAL DECOMPOSITION AND LINEAR STOCHASTIC ESTIMATION." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1099519886.
Повний текст джерелаMaddux, Michael Richard. "Using In-Situ Error Tracking For Mode Selection in Proper Orthogonal Decomposition Reduced Order Modelling." Wright State University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=wright1167858889.
Повний текст джерелаMoodley, Kamlin. "A Proper Orthogonal Decomposition-based inverse material parameter optimization method with applications to cardiac mechanics." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/22777.
Повний текст джерелаSteward, Jeff. "The solution of a Burgers' equation inverse problem with reduced-order modeling proper orthogonal decomposition." Tallahassee, Florida : Florida State University, 2009. http://etd.lib.fsu.edu/theses/available/etd-07062009-230217.
Повний текст джерелаAdvisor: Ionel M. Navon, Florida State University, College of Arts and Sciences, Dept. of Scientific Computing. Title and description from dissertation home page (viewed on Nov. 17, 2009). Document formatted into pages; contains ix, 67 pages. Includes bibliographical references.
Wickersham, Andrew Joseph. "Development of Multi-perspective Diagnostics and Analysis Algorithms with Applications to Subsonic and Supersonic Combustors." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/51145.
Повний текст джерелаPh. D.
Durmaz, Oguz. "Dynamical Modeling Of The Flow Over Flapping Wing By Applying Proper Orthogonal Decomposition And System Identification." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613549/index.pdf.
Повний текст джерелаLee, Kyunghoon. "Investigation of probabilistic principal component analysis compared to proper orthogonal decomposition methods for basis extraction and missing data estimation." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34796.
Повний текст джерелаRULLI, FEDERICO. "UN’INDAGINE SULLA VARIABILITA’ CICLICA NEI MOTORI A COMBUSTIONE INTERNA UTILIZZANDO PROPER ORTHOGONAL DECOMPOSITION E LARGE-EDDY SIMULATIONS." Doctoral thesis, Università degli studi di Modena e Reggio Emilia, 2020. http://hdl.handle.net/11380/1200665.
Повний текст джерелаThe main goal of research on reciprocating internal combustion engines (ICEs) consists in increasing the power output while reducing pollutant emission and fuel consumption. Cycle-to-cycle variability (CCV) is closely coupled with the intrinsic turbulent nature of in-cylinder flow and is detrimental in terms of combustion efficiency, fuel consumption, and tailpipe emissions. Due to fluctuations in flame propagation, heat release, and burnt product formation, CCV is now seen as one of the major limiting factors for higher power output and lower fuel consumption in ICEs. Therefore, it is essential to understand and control CCV to improve the overall engine efficiency and performance. Experimental techniques like particle image velocimetry (PIV) provide a powerful technical support for the analysis of the spatial and temporal evolution of the flow field in ICEs. Proper orthogonal decomposition (POD) has been largely used in conjunction with PIV to analyze flow field characteristics. Several methods involving POD have been proposed in the recent years to analyze engine CCV. In this work, phase invariant POD analysis, conditional averaging, and triple and quadruple POD decomposition methods are introduced and applied to a large database of PIV data from the optically accessible TCC-III research engine. Results are discussed with particular emphasis on the capability of the methods to perform both quantitative and qualitative evaluations on CCV. A new quadruple POD decomposition methodology is proposed and compared to those available in the literature. Besides experimental techniques, Computational Fluid Dynamics (CFD) has become a fundamental tool for understanding the complex aero-thermochemical processes that take place in the cylinder and for driving the development of new technological solutions. Large-eddy simulation (LES) is the most practical simulation tool to understand the nature of CCV. This work investigates the CFD capabilities to simulate CCV. Several methods of analysis were assessed on a 50 LES cycles dataset on the TCC-III engine under motored conditions. The accuracy and the reliability of CFD simulations stands in the models used for the discretization of the fluid domain and for the numerical computation of the governing equations. The meshing strategy plays a central role in the computational efficiency, in the management of the moving components of the engine and in the accuracy of results. The overset mesh approach, usually referred to as Chimera grid or Composite grid, was rarely applied to the simulation of ICEs, mainly because of the difficulty in adapting the technique to the specific complexities of ICE flows. This work demonstrates the feasibility and the effectiveness of the overset mesh technique application to ICEs thanks to a purposely designed meshing approach. 50 LES cycles were performed on the TCC-III engine under motored conditions. The proposed POD quadruple decomposition methodology was extensively applied to assess both the accuracy of the simulated results and the potential of the method itself for understanding CCV.
Dinckal, Cigdem. "Decomposition Of Elastic Constant Tensor Into Orthogonal Parts." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612226/index.pdf.
Повний текст джерелаerent symmetries. For these materials,norm and norm ratios are calculated. It is suggested that the norm of a tensor may be used as a criterion for comparing the overall e¤
ect of the properties of anisotropic materials and the norm ratios may be used as a criterion to represent the anisotropy degree of the properties of materials. Finally, comparison of all methods are done in order to determine similarities and differences between them. As a result of this comparison process, it is proposed that the spectral method is a non-linear decomposition method which yields non-linear orthogonal decomposed parts. For symmetric second rank and fourth rank tensors, this case is a significant innovation in decomposition procedures in the literature.
Viggiano, Bianca Fontanin. "Reduced Order Description of Experimental Two-Phase Pipe Flows: Characterization of Flow Structures and Dynamics via Proper Orthogonal Decomposition." PDXScholar, 2017. https://pdxscholar.library.pdx.edu/open_access_etds/3829.
Повний текст джерелаFahlaoui, Tarik. "Réduction de modèles et apprentissage de solutions spatio-temporelles paramétrées à partir de données : application à des couplages EDP-EDO." Thesis, Compiègne, 2020. http://www.theses.fr/2020COMP2535.
Повний текст джерелаIn this thesis, an algorithm for learning an accurate reduced order model from data generated by a high fidelity solver (HF solver) is proposed. To achieve this goal, we use both Dynamic Mode Decomposition (DMD) and Proper Orthogonal Decomposition (POD). Anomaly detection, during the learning process, can be easily done by performing an a posteriori spectral analysis on the reduced order model learnt. Several extensions are presented to make the method as general as possible. Thus, we handle the case of coupled ODE/PDE systems or the case of second order hyperbolic equations. The method is also extended to the case of switched control systems, where the switching rule is learnt by using an Artificial Neural Network (ANN). The reduced order model learnt allows to predict time evolution of the POD coefficients. However, the POD coefficients have no interpretable meaning. To tackle this issue, we propose an interpretable reduction method using the Empirical Interpolation Method (EIM). This reduction method is then adapted to the case of third-order tensors, and combining with the Kernel Ridge Regression (KRR) we can learn the solution manifold in the case of parametrized PDEs. In this way, we can learn a parametrized reduced order model. The case of non-linear PDEs or disturbed data is finally presented in the opening
Ceccato, Chiara. "THE LATTICE DISCRETE PARTICLE MODEL (LDPM) FOR FRP CONFINED CONCRETE COLUMNS, EXPLORING THE PROPER ORTHOGONAL DECOMPOSITION (POD) TECHNIQUE." Doctoral thesis, Università degli studi di Padova, 2016. http://hdl.handle.net/11577/3424817.
Повний текст джерелаI materiali fibrorinforzati a matrice polimerica (FRP) sono utilizzati in svariate applicazioni nel campo dell'ingegneria civile, per migliorare le prestazioni delle strutture in calcestruzzo, dal punto di vista della resistenza a flessione, a taglio, a compressione. Uno degli utilizzi più comuni e apprezzati di questi materiali è legato al confinamento di membrature verticali esistenti, che necessitano di recupero o di un'aumentata resistenza e/o duttilità. La progettazione efficace del rinforzo con FRP richiede piena comprensione del comportamento del calcestruzzo soggetto ai complessi stati tensionali dovuti al confinamento passivo e, per questa ragione, lo sviluppo di un modello numerico realistico è stato ed è tutt'ora uno degli obiettivi principali dei ricercatori. In questa sede, il cosiddetto Lattice Discrete Particle Model (LDPM), recentemente sviluppato per simulare il calcestruzzo attraverso l'interazione degli aggregati a livello di mesoscala, è stato applicato al problema della modellazione di colonne confinate con FRP e sottoposte a compressione, utilizzando come riferimento dati sperimentali di letteratura. LDPM era stato estesamente calibrato e validato sulla base di una larga varietà di condizioni di carico, sia quasi statiche che dinamiche, ma non in relazione a stati tensionali dovuti a compressione con bassi livelli di confinamento, che sono quelli rilevanti nella presente applicazione. Con il miglioramento proposto delle equazioni constitutive in compressione, LDPM è in grado di predire la risposta del calcestruzzo confinato con FRP e il modello sviluppato può simulare realisticamente il comportamento di colonne confinate con differenti sezioni. La presente ricerca affronta, parallelamente, gli aspetti più computazionali delle simulazioni con LDPM: questo modello è implementato in un software chiamato MARS, che si basa su un algoritmo esplicito, vantaggioso in termini di convergenza. Tuttavia, per ragioni di stabilità il costo computazionale richiesto per simulare eventi quasi statici, come i test di compressione di questo studio, può risultare molto sconveniente. Per ridurre i tempi di analisi, la tecnica della Proper Orthogonal Decomposition (POD) è stata esplorata in relazione all'applicazione di LDPM al caso delle colonne confinate con FRP sottoposte a compressione, valutando il rapporto tra guadagno computazionale e accuratezza dei risultati.
Ghoman, Satyajit Sudhir. "A Hybrid Optimization Framework with POD-based Order Reduction and Design-Space Evolution Scheme." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/23113.
Повний текст джерелаThe first part of this dissertation describes the development of a conceptual Multi-Fidelity Multi-Strategy and Multi-Disciplinary Design Optimization Environment (M3 DOE), in context of aircraft wing optimization. M3 DOE provides the user a capability to optimize configurations with a choice of (i) the level of fidelity desired, (ii) the use of a single-step or multi-step optimization strategy, and (iii) combination of a series of structural and aerodynamic analyses. The modularity of M3 DOE allows it to be a part of other inclusive optimization frameworks. The M3 DOE is demonstrated within the context of shape and sizing optimization of the wing of a Generic Business Jet aircraft. Two different optimization objectives, viz. dry weight minimization, and cruise range maximization are studied by conducting one low-fidelity and two high-fidelity optimization runs to demonstrate the application scope of M3 DOE.
The second part of this dissertation describes the development of an innovative hybrid optimization framework that extends the robustness of M3 DOE by employing a proper orthogonal decomposition-based design-space order reduction scheme combined with the evolutionary algorithm technique. The POD method of extracting dominant modes from an ensemble of candidate configurations is used for the design-space order reduction. The snapshot of candidate population is updated iteratively using evolutionary algorithm technique of fitness-driven retention. This strategy capitalizes on the advantages of evolutionary algorithm as well as POD-based reduced order modeling, while overcoming the shortcomings inherent with these techniques. When linked with M3 DOE, this strategy offers a computationally efficient methodology for problems with high level of complexity and a challenging design-space. This newly developed framework is demonstrated for its robustness on a non-conventional supersonic tailless air vehicle wing shape optimization problem.
Ph. D.
Sutton, Daniel. "Improved Reduced Order Modeling Strategies for Coupled and Parametric Systems." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/34639.
Повний текст джерелаMaster of Science
Christ, Paul [Verfasser], Thomas [Akademischer Betreuer] Sattelmayer, Jürgen [Gutachter] Köhler, and Thomas [Gutachter] Sattelmayer. "Modeling of Automotive HVAC Units Using Proper Orthogonal Decomposition / Paul Christ ; Gutachter: Jürgen Köhler, Thomas Sattelmayer ; Betreuer: Thomas Sattelmayer." München : Universitätsbibliothek der TU München, 2019. http://d-nb.info/118840878X/34.
Повний текст джерелаLee, Jaehyung. "Study on aerodynamic interference and unsteady pressure field around B/D=4 rectangular cylinder based on proper orthogonal decomposition." 京都大学 (Kyoto University), 2006. http://hdl.handle.net/2433/136143.
Повний текст джерела0048
新制・課程博士
博士(工学)
甲第12587号
工博第2700号
新制||工||1388(附属図書館)
UT51-2006-S595
京都大学大学院工学研究科社会基盤工学専攻
(主査)教授 松本 勝, 教授 河井 宏允, 助教授 白土 博通, 教授 田村 武
学位規則第4条第1項該当
Flores, Vera Rafael. "The Use of the Proper Orthogonal Decomposition for the Characterization of the Dynamic Response of Structures Due to Wind Loading." Thesis, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/19762.
Повний текст джерелаDanby, Sean James. "Optimization of Proper Orthogonal Decomposition using Various Preconditioning Techniques to Analyze Autoignition Simulation Data of Non-Homogeneous Hydrogen-Air Mixtures." NCSU, 2004. http://www.lib.ncsu.edu/theses/available/etd-11042004-203408/.
Повний текст джерела