Recent advances in manufacturing and growing concerns on the sustainability of aviation environment have led to a remarkable interest in electrical unmanned aerial systems (UASs) in the past decade. Among various UAS types, the newly designed quadrotor biplane tailsitter class is capable of delivering a wide range of civilian and military tasks, relying on its Vertical Take-Off and Landing (VTOL) capability as well as great maneuverability. Nevertheless, as such UASs employ rotors to generate thrust, and wings to generate lift, and operate at less-understood low to mid-Reynolds flow regime, they experience complicated flight aerodynamics with a noise generation mechanism which is different from common aircrafts. The present work aims at addressing this knowledge gap by studying the aerodynamics and aeroacoustics of a UAS of this type designed by the Army Research Lab. High-fidelity computational fluid dynamics (CFD) simulations are carried out for a wide range of operating conditions to understand the physics involved in the UAS aerodynamics and characterize its performance. Relying on the CFD results, a physics-informed reduced order model (ROM) is developed based on machine learning algorithms, to predict the propellers effects on the wings and calculate the dominant loads. The results of this study indicate that the UAS aerodynamics is significantly influenced by the propeller-wing interaction, which makes it challenging to estimate the loads by classic methods. The proposed physics-informed ROM shows a promising performance based on its computational cost and accuracy. Additionally, it is found that the aeroacoustics of the UAS is ruled by a two-way mechanism through which the propellers and the structure impose unsteadiness on each other.

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In aeromechanical design one of the major rules is to operate under High Cyclic Fatigue (HCF) margins and away from flutter. The level of dynamic excitations and risk of HCF can be estimated by performing forced response analyses from blade row interaction forces or Low Engine Order (LEO) excitation mechanisms. On the other hand, flutter stability prediction can be assessed by calculation of aerodynamic damping forces due to blade motion. In order to include these analyses as regular practices in an industrial aeromechanical design process, interaction between the fields of fluid and structural dynamics must be established in a rather simple yet accurate manner. Effects such as aerodynamic and structural mistuning should also be taken into account where parametric and probabilistic studies take an important role. The present work presents the development and validation of a numerical tool for aeromechanical design. The tool aims to integrate in a standard and simple manner regular aeromechanical analysis such as forced response analysis and aerodynamic damping analysis of bladed disks. Mistuning influence on forced response and aerodynamic damping is assessed by implementing existing model order reduction techniques in order to decrease the computational effort and assess results in an industrially applicable time frame.  The synthesis program solves the interaction of structure and fluid from existing Finite Element Modeling (FEM) and Computational Fluid Dynamics (CFD) solvers inputs by including a mapping program which establishes the fluid and structure mesh compatibility. Blade row interaction harmonic forces and/or blade motion aerodynamic damping forces are inputs from unsteady fluid dynamic solvers whereas the geometry, mass and stiffness matrices of a blade alone or bladed disk sector are inputs from finite element solvers. Structural and aerodynamic damping is also considered. Structural mistuning is assessed by importing different sectors and any combinations of the full disk model can be achieved by using Reduced Order Model (ROM) techniques. Aerodynamic mistuning data can also be imported and its effects on the forced response and stability assessed. The tool is developed in such a way to allow iterative analysis in a simple manner, being possible to realize aerodynamically and structurally coupled analyses of industrial bladed disks. A new method for performing aerodynamic coupled forced response and stability analyses considering the interaction of different mode families has also been implemented. The method is based on the determination of the aerodynamic matrices by means of least square approximations and is here referred as the Multimode Least Square (MLS) method. The present work includes the program description and its applicability is assessed on a high pressure ratio transonic compressor blade and on a simple blisk. / QC 20110324 / Turbopower / AROMA

This dissertation contains work that addresses both theoretical and numerical aspects of reduced order models (ROMs). In an under-resolved regime, the classical Galerkin reduced order model (G-ROM) fails to yield accurate approximations. Thus, we propose a new ROM, the data-driven variational multiscale ROM (DD-VMS-ROM) built by adding a closure term to the G-ROM, aiming to increase the numerical accuracy of the ROM approximation without decreasing the computational efficiency. The closure term is constructed based on the variational multiscale framework. To model the closure term, we use data-driven modeling. In other words, by using the available data, we find ROM operators that approximate the closure term. To present the closure term's effect on the ROMs, we numerically compare the DD-VMS-ROM with other standard ROMs. In numerical experiments, we show that the DD-VMS-ROM is significantly more accurate than the standard ROMs. Furthermore, to understand the closure term's physical role, we present a theoretical and numerical investigation of the closure term's role in long-time integration. We theoretically prove and numerically show that there is energy exchange from the most energetic modes to the least energetic modes in closure terms in a long time averaging. One of the promising contributions of this dissertation is providing the numerical analysis of the data-driven closure model, which has not been studied before. At both the theoretical and the numerical levels, we investigate what conditions guarantee that the small difference between the data-driven closure model and the full order model (FOM) closure term implies that the approximated solution is close to the FOM solution. In other words, we perform theoretical and numerical investigations to show that the data-driven model is verifiable. Apart from studying the ROM closure problem, we also investigate the setting in which the G-ROM converges optimality. We explore the ROM error bounds' optimality by considering the difference quotients (DQs). We theoretically prove and numerically illustrate that both the ROM projection error and the ROM error are suboptimal without the DQs, and optimal if the DQs are used. / Doctor of Philosophy / In many realistic applications, obtaining an accurate approximation to a given problem can require a tremendous number of degrees of freedom. Solving these large systems of equations can take days or even weeks on standard computational platforms. Thus, lower-dimensional models, i.e., reduced order models (ROMs), are often used instead. The ROMs are computationally efficient and accurate when the underlying system has dominant and recurrent spatial structures. Our contribution to reduced order modeling is adding a data-driven correction term, which carries important information and yields better ROM approximations. This dissertation's theoretical and numerical results show that the new ROM equipped with a closure term yields more accurate approximations than the standard ROM.

Lithium ion (Li-ion) batteries have been identified as a promising solution to meet the increasing demands for alternative energy in electric vehicles (EVs) and hybrid electric vehicle (HEVs). This work describes experimental and numerical study of thermal management of battery module consisting of cylindrical Li-ion cells, with an emphasis on the use of active control to achieve optimal cooling performance with minimal parasitic power consumption. The major contribution from this work is the first experimental demonstration (based on our review of archival journal and conference literature) and the corresponding analysis of active thermal control of battery modules. The results suggest that the active control strategy, when combined with reciprocating cooling flow, can reduce the parasitic energy consumption and cooling flow amount substantially. Compared with results using passive control with unidirectional cooling flow, the parasitic energy consumption was reduced by about 80%. This contribution was achieved in three steps, which was detailed in this dissertation in chapters 2, 3, and 4, respectively. In the first step, an experimental facility and a corresponding CFD model were developed to capture the thermal behavior of multiple battery cells. Based on the experimental and CFD results, a reduced-order model (ROM) was then developed for active monitoring and control purposes. In the second step, the ROM was parameterized and an observer-based control strategy was developed to control the core temperature of battery cells. Finally, based on the experimental facility and the ROM model, the active control of a battery module was demonstrated. Each of these steps represents an important facet of the thermal management problem, and it is expected that the results and specifics documented in this dissertation lay the groundwork to facilitate further study. / Ph. D.

This thesis describes several approaches for stabilizing POD-ROMs (that is, reduced order models based on basis functions derived from the proper orthogonal decomposition) for both the CDR (convection-diffusion-reaction) equation and the NSEs (Navier-Stokes equations). Stabilization is necessary because standard POD-ROMs of convection-dominated problems usually display numerical instabilities. The first stabilized ROM investigated is a streamline-upwind Petrov-Galerkin ROM (SUPG-ROM). I prove error estimates for the SUPG-ROM and derive optimal scalings for the stabilization parameter. I test the SUPG-ROM with the optimal parameter in the numerical simulation of a convection-dominated CDR problem. The SUPG-ROM yields more accurate results than the standard Galerkin ROM (G-ROM) by eliminating the inherent numerical artifacts (noise) in the data and dampening spurious oscillations. I next propose two regularized ROMs (Reg-ROMs) based on ideas from large eddy simulation and turbulence theory: the Leray ROM (L-ROM) and the evolve-then-filter ROM (EF-ROM). Both Reg-ROMs use explicit POD spatial filtering to regularize (smooth) some of the terms in the standard G-ROM. I propose two different POD spatial filters: one based on the POD projection and a novel POD differential filter. These two new Reg-ROMs and the two spatial filters are investigated in the numerical simulation of the three-dimensional flow past a circular cylinder problem at Re = 100. The numerical results show that EF-ROM-DF is the most accurate Reg-ROM and filter combination and the differential filter generally yields better results than the projection filter. The Reg-ROMs perform significantly better than the standard G-ROM and decrease the CPU time (compared against the direct numerical simulation) by orders of magnitude (from about four days to four minutes). / Ph. D.

<p>In aeromechanical design one of the major rules is to operate under High Cyclic Fatigue (HCF) margins and away from flutter. The level of dynamic excitations and risk of HCF can be estimated by performing forced response analyses from blade row interaction forces or Low Engine Order (LEO) excitation mechanisms. On the other hand, flutter stability prediction can be assessed by calculation of aerodynamic damping forces due to blade motion. In order to include these analyses as regular practices in an industrial aeromechanical design process, interaction between the fields of fluid and structural dynamics must be established in a rather simple yet accurate manner. Effects such as aerodynamic and structural mistuning should also be taken into account where parametric and probabilistic studies take an important role.</p><p>The present work presents the development and validation of a numerical tool for aeromechanical design. The tool aims to integrate in a standard and simple manner regular aeromechanical analysis such as forced response analysis and aerodynamic damping analysis of bladed disks.</p><p>Mistuning influence on forced response and aerodynamic damping is assessed by implementing existing model order reduction techniques in order to decrease the computational effort and assess results in an industrially applicable time frame.  The synthesis program solves the interaction of structure and fluid from existing Finite Element Modeling (FEM) and Computational Fluid Dynamics (CFD) solvers inputs by including a mapping program which establishes the fluid and structure mesh compatibility. Blade row interaction harmonic forces and/or blade motion aerodynamic damping forces are inputs from unsteady fluid dynamic solvers whereas the geometry, mass and stiffness matrices of a blade alone or bladed disk sector are inputs from finite element solvers. Structural and aerodynamic damping is also considered.</p><p>Structural mistuning is assessed by importing different sectors and any combinations of the full disk model can be achieved by using Reduced Order Model (ROM) techniques. Aerodynamic mistuning data can also be imported and its effects on the forced response and stability assessed. The tool is developed in such a way to allow iterative analysis in a simple manner, being possible to realize aerodynamically and structurally coupled analyses of industrial bladed disks. A new method for performing aerodynamic coupled forced response and stability analyses considering the interaction of different mode families has also been implemented. The method is based on the determination of the aerodynamic matrices by means of least square approximations and is here referred as the Multimode Least Square (MLS) method.</p><p>The present work includes the program description and its applicability is assessed on a high pressure ratio transonic compressor blade and on a simple blisk.</p> / Turbopower / AROMA

Le comportement dynamique de structures complexes, comme les alternateurs, doit être maîtrisé afin d’en garantir un fonctionnement fiable. Cependant, la modélisation comporte de nombreuses incertitudes rendant délicates la prédiction du comportement vibratoire. Ces travaux de recherche ont pour objectif de fournir des outils d’aide à la décision afin de faciliter la prise de décision rapide suite au redémarrage d’alternateurs. Basé sur la théorie info-gap, un premier outil d’aide à la décision est proposé : il a pour objectif d’évaluer la robustesse de réponses dynamiques vis-à-vis d’un modèle modal incertain. Nous avons également étudié comment de l’information nouvelle peut être intégrée au modèle d’incertitude pour améliorer sa représentativité à la réalité.Une expansion par l’erreur en relation de comportement étendue de modes propres identifiés permet ensuite d’enrichir la représentativité du modèle numérique fournissant ainsi un modèle qualifié d’hybride et permettant d’évaluer les niveaux de réponse. Comme la modélisation comporte de nombreuses méconnaissances, nous avons proposé le procédé d’expansion robuste dont l’objectif est d’obtenir des vecteurs étendus robustes. En présence de méconnaissances sévères, nous montrons enfin qu’il est préférable de calibrer un modèle en maximisant la robustesse vis-à-vis des incertitudes plutôt qu’en maximisant uniquement la fidélité vis-à-vis des données. Couplée à des techniques de réduction de modèle et de construction de méta modèles,nous appliquons cette démarche à une structure de complexité industrielle représentative du contexte industriel. / The complex structural dynamic behavior of alternator must be well understood in order to insuretheir reliable and safe operation. The numerical model is however difficult to construct mainlydue to the presence of a high level of uncertainty. The objective of this work is to providedecision support tools in order to assess the vibratory levels in operation before to restart thealternator. Based on info-gap theory, a first decision support tool is proposed: the objective hereis to assess the robustness of the dynamical response to the uncertain modal model. Based on realdata, the calibration of an info-gap model of uncertainty is also proposed in order to enhance itsfidelity to reality. Then, the extended constitutive relation error is used to expand identified modeshapes which are used to assess the vibratory levels. The robust expansion process is proposed inorder to obtain robust expanded mode shapes to parametric uncertainties. In presence of lack-ofknowledge,the trade-off between fidelity-to-data and robustness-to-uncertainties which expressesthat robustness improves as fidelity deteriorates is emphasized on an industrial structure by usingboth reduced order model and surrogate model techniques.

Cette thèse propose trois nouveaux développements de la méthode des bases réduites (RB) et de la méthode d'interpolation empirique (EIM) pour des problèmes non-linéaires. La première contribution est une nouvelle méthodologie, la méthode progressive RB-EIM (PREIM) dont l'objectif est de réduire le coût de la phase de construction du modèle réduit tout en maintenant une bonne approximation RB finale. L'idée est d'enrichir progressivement l'approximation EIM et l'espace RB, contrairement à l'approche standard où leurs constructions sont disjointes. La deuxième contribution concerne la RB pour les inéquations variationnelles avec contraintes non-linéaires. Nous proposons une combinaison RB-EIM pour traiter la contrainte. En outre, nous construisons une base réduite pour les multiplicateurs de Lagrange via un algorithme hiérarchique qui conserve la positivité des vecteurs cette base. Nous appliquons cette stratégie aux problèmes de contact élastique sans frottement pour les maillages non-coïncidents. La troisième contribution concerne la réduction de modèles avec assimilation de données. Une méthode dédiée a été introduite dans la littérature pour combiner un modèle numérique avec des mesures expérimentales. Nous élargissons son cadre d'application aux problèmes instationnaires en exploitant la méthode POD-greedy afin de construire des espaces réduits pour tout le transitoire temporel. Enfin, nous proposons un nouvel algorithme qui produit des espaces réduits plus représentatifs de la solution recherchée tout en minimisant le nombre de mesures nécessaires pour le problème réduit final / This thesis introduces three new developments of the reduced basis method (RB) and the empirical interpolation method (EIM) for nonlinear problems. The first contribution is a new methodology, the Progressive RB-EIM (PREIM) which aims at reducing the cost of the phase during which the reduced model is constructed without compromising the accuracy of the final RB approximation. The idea is to gradually enrich the EIM approximation and the RB space, in contrast to the standard approach where both constructions are separate. The second contribution is related to the RB for variational inequalities with nonlinear constraints. We employ an RB-EIM combination to treat the nonlinear constraint. Also, we build a reduced basis for the Lagrange multipliers via a hierarchical algorithm that preserves the non-negativity of the basis vectors. We apply this strategy to elastic frictionless contact for non-matching meshes. Finally, the third contribution focuses on model reduction with data assimilation. A dedicated method has been introduced in the literature so as to combine numerical models with experimental measurements. We extend the method to a time-dependent framework using a POD-greedy algorithm in order to build accurate reduced spaces for all the time steps. Besides, we devise a new algorithm that produces better reduced spaces while minimizing the number of measurements required for the final reduced problem

Une modélisation d'ordre réduit basée sur le partitionnement des données (cluster-based reduced-order modelling ou CROM) est développée pour identifier de manière non supervisée des mécanismes d'interaction non linéaires. La connaissance de ces mécanismes permet de pronostiquer la formation d’événements souhaitables ou non. L’approche proposée adopteun point de vue probabiliste en mettant à profit la linéarité de l’équation d’évolution de probabilité qui tient cependant compte d'éventuelles actions non linéaires des actionneurs. Le cadre est appliqué à l’attracteur de Lorenz, aux données numériques de la couche de mélange, à la turbulence tridimensionnelle du sillage d’un corps non profilé, d’un train, et aux données expérimentales d’un moteur à combustion.Pour ces exemples, le CROM permettait l'identification des quasi-attracteurs par exemple les deux régimes d’écoulement de la couche de mélange ou les états bimodaux du corps Ahmed . Les transitions principales entre ces quasi-attracteurs sont caractérisées par des regroupements de données appelé « flipper cluster ». L'identification de ces « flipper cluster » peut servir pour le contrôle des écoulements en utilisant le partitionnement des données obtenues par exemple de l'évolution temporelle de la traînée ou de la portance.Un contrôle en boucle fermé basé sur la CROM est appliqué à un écoulement le long d'une rampe courbée en vue de diminuer les extensions de la zone de recirculation par rapport à la meilleure excitation périodique en boucle ouverte. L'actionneur est mis en marche en fonction des regroupements préalablement observés. Le résultat est comparé à l’ensemble des lois de contrôle définies par toutes les combinaisons possibles des « on » et « of » par les regroupements de données. Bien quele contrôle basé sur la CROM ne permet pas de réduire la zone de recirculation par rapport à la réduction maximale en boucle ouverte, 28 % de l'apport d 'énergie nécessaire et 81 % pour une loi de contrôle particulière peuvent être économisé. / A cluster-based reduced-order modeling strategy is developed for the unsupervised identification of nonlinear flow mechanisms and precursors to desirable or undesirable events. The proposed approach assumes a probabilistic viewpoint taking advantage of the linearity of the evolution equation for the probability while including nonlinear actuation dynamics.The framework is applied to the Lorenz attractor, numerical data of the spatially evolving mixing layer, the three-dimensional turbulent wake of a bluf body, of a train, and experimental data of a combustion engine.For these examples, CROM has been shown to identify quasi-attractors such as the two shedding regimes of the mixing layer or the bimodal states of the Ahmed body; main transition processes between those quasiattractors are characterized by branching regions or flipper cluster; desirable phase space regions and possible actuation mechanisms areindicated by analysis of cluster features like drag and lift forces which can be further exploited for control purposes.In particular, a CROM-based feedback control is applied to a separating flow over a smooth ramp to examine whether the recirculation area can be diminished compared to the best open-loop periodic excitation by turning the actuation on or of depending on the applicable cluster. The CROMbased control is compared to the complete set of control laws defined byall possible combinations of 'on' and 'of' for the given set of clusters.While the recirculation area cannot be further decreased compared to the best open-loop forcing, a similar size can be achieved for 28% (CROMbased control) or 81% (one particular control law) savings in the control input energy.