In this dissertation, neural networks are designed to effectively model static non-linear aeroelastic problems in adaptive structures and linear dynamic aeroelastic systems with time varying stiffness. The use of adaptive materials in aircraft wings allows for the change of the contour or the configuration of a wing (morphing) in flight. The use of smart materials, to accomplish these deformations, can imply that the stiffness of the wing with a morphing contour changes as the contour changes. For a rapidly oscillating body in a fluid field, continuously adapting structural parameters may render the wing to behave as a time variant system. Even the internal spars/ribs of the aircraft wing which define the wing stiffness can be made adaptive, that is, their stiffness can be made to vary with time. The immediate effect on the structural dynamics of the wing, is that, the wing motion is governed by a differential equation with time varying coefficients. The study of this concept of a time varying torsional stiffness, made possible by the use of active materials and adaptive spars, in the dynamic aeroelastic behavior of an adaptable airfoil is performed here. A time marching technique is developed for solving linear structural dynamic problems with time-varying parameters. This time-marching technique borrows from the concept of Time-Finite Elements in the sense that for each time interval considered in the time-marching, an analytical solution is obtained. The analytical solution for each time interval is in the form of a matrix exponential and hence this technique is termed as Matrix Exponential time marching. Using this time marching technique, Artificial Neural Networks can be trained to represent the dynamic behavior of any linearly time varying system. In order to extend this methodology to dynamic aeroelasticity, it is also necessary to model the unsteady aerodynamic loads over an airfoil. Accordingly, an unsteady aerodynamic panel method is developed using a distributed set of doublet panels over the surface of the airfoil and along its wake. When the aerodynamic loads predicted by this panel method are made available to the Matrix Exponential time marching scheme for every time interval, a dynamic aeroelastic solver for a time varying aeroelastic system is obtained. This solver is now used to train an array of neural networks to represent the response of this two dimensional aeroelastic system with a time varying torsional stiffness. These neural networks are developed into a control system for flutter suppression. Another type of aeroelastic problem of an adaptive structure that is investigated here is the shape control of an adaptive bump situated on the leading edge of an airfoil. Such a bump is useful in achieving flow separation control for lateral directional maneuverability of the aircraft. Since actuators are being used to create this bump on the wing surface, the energy required to do so needs to be minimized. The adverse pressure drag as a result of this bump needs to be controlled so that the loss in lift over the wing is made minimal. The design of such a "spoiler bump" on the surface of the airfoil is an optimization problem of maximizing pressure drag due to flow separation while minimizing the loss in lift and energy required to deform the bump. One neural network is trained using the CFD code FLUENT to represent the aerodynamic loading over the bump. A second neural network is trained for calculating the actuator loads, bump displacement and lift, drag forces over the airfoil using the finite element solver, ANSYS and the previously trained neural network. This non-linear aeroelastic model of the deforming bump on an airfoil surface using neural networks can serve as a fore-runner for other non-linear aeroelastic problems. This work enhances the traditional aeroelastic modeling by introducing time varying parameters in the differential equations of motion. It investigates the calculation of non-conservative aerodynamic loads on morphing contours and the resulting structural deformation for non-linear aeroelastic problems through the use of neural networks. Geometric modeling of morphing contours is also addressed. / Ph. D.

The nonlinear interactions between aerodynamic forces and wing structures are numerically investigated as integrated dynamic systems, including structural models, aerodynamics, and control systems, in the time domain. An elastic beam model coupled with rigid-body rotation is developed for the wing structure, and the natural frequencies and mode shapes are found by the finite-element method. A general unsteady vortex-lattice method is used to provide aerodynamic forces. This method is verified by comparing the numerical solutions with the experimental results for several cases; and thereafter applied to several applications such as the inboard-wing/twin-fuselage configuration, and formation flights. The original thought that the twin fuselage could achieve two-dimensional flow on the wing by eliminating free wing tips appears to be incorrect. The numerical results show that there can be a lift increase when two or more wings fly together, compared to when they fly alone. Flutter analysis is carried out for a High-Altitude-Long-Endurance aircraft wing cantilevered from the wall of the wind tunnel, a full-span wing mounted on a free-to-roll sting at its mid-span without and with a center mass (fuselage). Numerical solutions show that the rigidity added by the wall results in a higher flutter speed for the wall-mounted semi-model than that for the full-span model. In addition, a predictive control technique based on neural networks is investigated to suppress flutter oscillations. The controller uses a neural network model to predict future plant responses to potential control signals. A search algorithm is used to select the best control input that optimizes future plant performance. The control force is assumed to be given by an actuator that can apply a distributed torque along the spanwise direction of the wing. The solutions with the wing-tip twist or the wing-tip deflection as the plant output show that the flutter oscillations are successfully suppressed with the neural network predictive control scheme. / Ph. D.

The NASA Performance Adaptive Aeroelastic Wing (PAAW) project goals include significant reductions in fuel burn, emissions, and noise via efficient aeroelastic design and improvements in propulsion systems. As modern transport airplane designs become increasingly lightweight and incorporate high aspect-ratio wings, aeroservoelastic effects gain prominence in modeling and design considerations. As a result, the influence of the flight dynamics and controls on the optimal structural and aerodynamic design needs to be captured in the design process. There is an increasing interest in more integrated aircraft multidisciplinary design optimization (MDAO) processes that can bring flight control design into the early stage of an aircraft design cycle. So, in this thesis different flight dynamics modeling methodologies are presented that can be integrated within the MDAO framework. MDAO studies are conducted to maximize the controllability and observability of a UAV type aircraft using curvilinear SpaRibs and straight spars and ribs as the internal structural layout. The impulse residues and controllability Gramians are used as surrogates for the control objectives in the MDAO to maximize the controllability and observability of the aircraft. The optimal control designs are compared with those obtained using weight minimization as the design objective. It is found that using the aforementioned control objectives, the resulting aircraft design is more controllable and can be used to expand the flight envelope by up to 50% as compared to the weight minimized design. / Doctor of Philosophy / Over the last two decades, several attempts have been made towards multidisciplinary design analysis and optimization (MDAO) of flexible wings by integrating flight control laws in the wing design so that the aircraft will have sufficient control authority across different flying conditions. However, most of the studies have been restricted to the wing design only using a predefined control architecture approach, which would be very difficult to implement at the conceptual design stage. There is a need for an approach that would be faster and more practical. Including control surface and control law designs at the conceptual design stage is becoming increasingly important, due to the complexity of both the aircraft control laws and that of the actuation and sensing, and the enhanced wing flexibility of future transport aircraft. A key question that arises is, can one design an aircraft that is more controllable and observable? So, in this thesis, a more fundamental approach, in which the internal structural layout of the aircraft is optimized to design an aircraft that is more controllable, is presented and implemented. The approach uses the fundamentals of linear systems theory for maximizing the controllability and observability of the aircraft using an MDAO framework.

A general aerodynamic model for two-dimensional inviscid flows is developed. This model is used to simulate wakes and blade-vortex interaction. This model is also coupled with dynamics and feedback controls to simulate flutter and flutter suppression. The flow is assumed to be attached and incompressible. The present aerodynamic model is based on a vorticity-panel method coupled with vortex dynamics. The present aerodynamic model is used to simulate some actual experiments: wakes generated by oscillating airfoils and blade-vortex interactions in which one airfoil is placed in or near the wake generated by another oscillating airfoil upstream. The present numerical model predicts wake structures, vorticity strength, and velocity profiles across the wake that compare very favorably with the experiments. The present numerical results of the blade-vortex interaction show good agreement with the experiments when separation does not occur. If separation is involved, the present model fails to accurately simulate blade-vortex interaction because separation is not considered in the present model. Flutter is studied by means of numerical simulations. In an incompressible flow, an airfoil is mounted on an elastic support. The airfoil can pitch (rotate) and plunge (translate vertically). The dynamic equations that describe this two-degree-of-freedom motion are general and nonlinear. To calculate the aerodynamic loads on the airfoil, the aerodynamic model is coupled with this dynamic model. The motions of the airfoil and flowing air are calculated interactively and simultaneously. The coupled aerodynamic/dynamic model accurately predicts the critical flutter speed of the freestream, the speed at which the motion of the airfoil grows spontaneously. The contributions of the phase difference and energy exchange to the flutter motion are discussed. The effect of the static angle of attack on the critical flutter speed is investigated. Also the effect of the nonlinearity of the elastic support (cubic term in the hardening spring) is studied. A feedback control is coupled with aerodynamics/dynamics to suppress the flutter motion of the airfoil. A flap is added at the trailing edge of the airfoil as a control surface, and its deflection (rotation) about the hinge point is commanded by a feedback-control law. The flow, airfoil, elastic support, and control device are considered as one system, and the flow, the motions of the airfoil, and the flap deflections are calculated simultaneously. With carefully designed control laws, oscillations that would be unstable (i.e., growing) without control are suppressed. The numerical results show different control variables can be used. The model of aerodynamics/dynamics/control is also used to successfully suppress the response to a wind gust with the same control laws as used for the suppression of flutter. / Ph. D.

A method is presented for calculating the shape sensitivity of a wing aeroelastic response with respect to changes in geometric shape. Yates’ modified strip method is used in conjunction with Giles' equivalent plate analysis to predict the flutter speed, frequency, and reduced frequency of the wing. Three methods are used to calculate the sensitivity of the eigenvalue. The first method is purely a finite difference calculation of the eigenvalue derivative directly from the solution of the flutter problem corresponding to the two different values of the shape parameters. The second method uses an analytic expression for the eigenvalue sensitivities of a general complex matrix, where the derivatives of the aerodynamic, mass, and stiffness matrices are computed using a finite difference approximation. The third method also uses an analytic expression for the eigenvalue sensitivities but the aerodynamic matrix is computed analytically. All three methods are found to be in good agreement with each other. The sensitivities of the eigenvalues were used to predict flutter speed, frequency , and reduced frequency. These approximations were found to be in good agreement with those obtained using a complete reanalysis. However, it is recommended that higher order terms be used in the calculations in order to assure greater accuracy. / Master of Science / incomplete_metadata

Cette thèse apporte des solutions théoriques et pratiques à deux problèmes soulevés par la photographie numérique en présence de mouvement, et par la photographie infrarouge. La photographie d'objets en mouvement semblait ne pouvoir se faire qu'avec des temps d'exposition très courts, jusqu'à ce que deux travaux révolutionnaires proposent deux nouveaux types de caméra permettant un temps d'exposition arbitraire. Le flutter shutter de Agrawal et al. crée en effet un flou inversible, grâce à un obturateur aux séquences d'ouverture-fermeture bie{\it n choisies. Le motion invariant photography de Levin et al. obtient ce même effet avec une accélération constante de la caméra. Les deux méthodes suivent ainsi un nouveau paradigme, la computational photography, selon lequel les caméras sont repensées, car elles incluent un traitement numérique sophistiqué. Cette thèse propose une méthode pour évaluer la qualité image des nouvelles caméras. Le fil conducteur de l'analyse est donc l'évaluation du SNR (signal to noise ratio) de l'image obtenue après déconvolution. La théorie fournit des formules explicites pour le SNR, soulève deux paradoxes de ces caméras, et les résout. Elle permet d'obtenir le modèle de mouvement sous-jacent à chaque flutter shutter, notamment tous ceux qui sont brevetés. Une seconde partie plus brève aborde le problème de qualité principal en imagerie vidéo infrarouge, la non-uniformité. Il s'agit d'un bruit évolutif et structuré en colonnes causé par le capteur. La conclusion des travaux est qu'il est non seulement possible mais également efficace et robuste d'effectuer la correction sur une seule image. Cela permet de contourner le problème récurrent des "ghost artifacts"résultant d'une incohérence du traitement par rapport au modèle d'acquisition. / This thesis provides theoretical and practical solutions to two problems raised by digital photography of moving scenes, and infrared photography. Until recently photographing moving objects could only be done using short exposure times. Yet, two recent groundbreaking works have proposed two new designs of camera allowing arbitrary exposure times. The flutter shutter of Agrawal et al. creates an invertible motion blur by using a clever shutter technique to interrupt the photon flux during the exposure time according to a well chosen binary sequence. The motion-invariant photography of Levin et al. gets the same result by accelerating the camera at a constant rate. Both methods follow computational photography as a new paradigm. The conception of cameras is rethought to include sophisticated digital processing. This thesis proposes a method for evaluating the image quality of these new cameras. The leitmotiv of the analysis is the SNR (signal to noise ratio) of the image after deconvolution. It gives the efficiency of these new camera design in terms of image quality. The theory provides explicit formulas for the SNR. It raises two paradoxes of these cameras, and resolves them. It provides the underlying motion model of each flutter shutter, including patented ones. A shorter second part addresses the the main quality problem in infrared video imaging, the non-uniformity. This perturbation is a time-dependent noise caused by the infrared sensor, structured in columns. The conclusion of this work is that it is not only possible but also efficient and robust to perform the correction on a single image. This permits to ensure the absence of ``ghost artifacts'', a classic of the literature on the subject, coming from inadequate processing relative to the acquisition model.

A Otimização Multidisciplinar em Projeto (em inglês, Multidisciplinary Design Optimization - MDO) é uma ferramenta de projeto importante e versátil e seu uso está se expandindo em diversos campos da engenharia. O foco desta metodologia é unir disciplinas envolvidas no projeto para que trabalhem suas variáveis concomitantemente em um ambiente de otimização, para obter soluções melhores. É possível utilizar MDO em qualquer fase do projeto, seja a fase conceitual, preliminar ou detalhada, desde que os modelos numéricos sejam ajustados às necessidades de cada uma delas. Este trabalho descreve o desenvolvimento de um código de MDO para o projeto conceitual de asas flexíveis de aeronaves, com restrição quanto ao fenômeno denominado flutter. Como uma ferramenta para o projetista na fase conceitual, os modelos numéricos devem ser razoavelmente precisos e rápidos. O intuito deste estudo é analisar o uso de metamodelos para a previsão do flutter de asas de aeronaves no código de MDO, ao invés de um modelo convencional, o que pode alterar significativamente o custo computacional da otimização. Para este fim são avaliados três técnicas diferentes de metamodelagem, que foram escolhidas por representarem duas classes básicas de metamodelos, a classe de métodos de interpolação e a de métodos de aproximação. Para representá-las foram escolhidos o método de interpolação por funções de base radial e o método de redes neurais artificiais, respectivamente. O terceiro método, que é considerado um método híbrido dos dois anteriores, é chamado de redes neurais por funções de bases radiais e é uma tentativa de acoplar as características de ambos em um único metamodelo. Os metamodelos são preparados utilizando um código para solução aeroelástica baseado no método dos elementos finitos acoplado com um modelo aerodinâmico linear de faixas. São apresentados resultados de desempenho dos três metamodelos, de onde se pode notar que a rede neural artificial é a mais adequada para previsão de flutter. O processo de MDO é realizado com o uso de um algoritmo genético multi-objetivo baseado em não-dominância, cujos objetivos são a maximização da velocidade crítica de flutter e a minimização da massa estrutural. Dois estudos de caso são apresentados para avaliar o desempenho do código de MDO, revelando que o processo global de otimização realiza de fato a busca pela fronteira de Pareto. / The Multidisciplinary Design Optimization, MDO, is an important and versatile design tool and its use is spreading out in several fields of engineering. The focus of this methodology is to put together disciplines involved with the design to work all their variables concomitantly, at an optimization environment to obtain better solutions. It is possible to use MDO in any stage of the design process, that is in the conceptual, preliminary or detailed design, as long as the numerical models are fitted to the needs of each of these stages. This work describes the development of a MDO code for the conceptual design of flexible aircraft wings, with restrictions regarding the phenomenon called flutter. As a tool for the designer at the conceptual stage, the numerical models must be fairly accurate and fast. The aim of this study is to analyze the use of metamodels for the flutter prediction of aircraft wings in the MDO code, instead of a conventional model itself, what may affect significantly the computational cost of the optimization. For this purpose, three different metamodeling techniques have been evaluated, representing two basic metamodel classes, that are, the interpolation and the approximation class. These classes are represented by the radial basis function interpolation method and the artificial neural networks method, respectively. The third method, which is considered as a hybrid of the other two, is called radial basis function neural networks and is an attempt of coupling the features of both in single code. Metamodels are prepared using an aeroelastic code based on finite element model coupled with linear aerodynamics. Results of the three metamodels performance are presented, from where one can note that the artificial neural network is best suited for flutter prediction. The MDO process is achieved using a non-dominance based multi-objective genetic algorithm, whose objectives are the maximization of critical flutter speed and minimization of structural mass. Two case studies are presented to evaluate the performance of the MDO code, revealing that overall optimization process actually performs the search for the Pareto frontier.

Modern turbomachines are designed towards thinner, lighter and highly loaded blades. This gives rise to increased sensitivity to flow induced vibrations such as flutter, which leads to structure failure in a short period of time if not sufficiently damped. Although numerical tools are more and more reliable, flutter prediction still depends on a large degree on simplified models. In addition, the critical nature of flutter, resulting in poor welldocumented real cases in the open literature, and the lack of experimental database typical of engine flows make its apprehension even more challenging. In that context, the present thesis is dedicated to study flutter in recent turbines through aerodynamic analysis of subsonic or supersonic flows in response to a prescribed vibratory mode of the structure. The objective is to highlight some mechanisms potentially responsible for flutter in order to be in better position when designing blades. The strategy consists in leading both experimental and numerical investigations. The experimental part is based on a worldwide unique annular turbine sector cascade employed for measuring the aeroelastic response by means of the aerodynamic influence coefficient technique. The cascade comprises seven low pressure gas turbine blades one of which can oscillate in a controlled way as a rigid body. Aeroelastic responses are measured at various mechanical and aerodynamic parameters: pure and combined modeshapes, reduced frequency, Mach number, incidence angle. In addition to turbulence level measurements, the database aims at assessing the influence of these parameters on the aerodynamic damping, at validating the linear combination principle and at providing input for numerical tools. The numerical part is based on unsteady computations linearized in the frequency domain and performed in the traveling wave mode. The focus is put on two industrial space turbines: 2D computations are performed on an integrally bladed disk, also called blisk; its very low viscous material damping results in complex motions with combined modes and extremely high reduced frequency. The blisk operates at low subsonic conditions without strong non-linearities. Although the blades have been predicted aeroelastically stable, an original methodology based on elementary decompositions of the blade motion is presented to identify the destabilizing movements. The results suggest that the so-called classical flutter is surprisingly prone to occur. Moreover, the aerodynamic damping has been found extremely sensitive to the interblade phase angle and cut-on/cut-off conditions.* 3D computations are then performed on a supersonic turbine, which features shockwaves and boundary layer separation. In contrast, the blade motion is of elementary nature, i.e. purely axial. The blades have been predicted aeroelastically unstable for backward traveling waves and stable for forward traveling waves. The low reduced frequencies allow quasi-steady analysis, which still account for flutter mechanisms: the shock wave motion establishes the boundary between stable and unstable configurations.

A Otimização Multidisciplinar em Projeto (em inglês, Multidisciplinary Design Optimization - MDO) é uma ferramenta de projeto importante e versátil e seu uso está se expandindo em diversos campos da engenharia. O foco desta metodologia é unir disciplinas envolvidas no projeto para que trabalhem suas variáveis concomitantemente em um ambiente de otimização, para obter soluções melhores. É possível utilizar MDO em qualquer fase do projeto, seja a fase conceitual, preliminar ou detalhada, desde que os modelos numéricos sejam ajustados às necessidades de cada uma delas. Este trabalho descreve o desenvolvimento de um código de MDO para o projeto conceitual de asas flexíveis de aeronaves, com restrição quanto ao fenômeno denominado flutter. Como uma ferramenta para o projetista na fase conceitual, os modelos numéricos devem ser razoavelmente precisos e rápidos. O intuito deste estudo é analisar o uso de metamodelos para a previsão do flutter de asas de aeronaves no código de MDO, ao invés de um modelo convencional, o que pode alterar significativamente o custo computacional da otimização. Para este fim são avaliados três técnicas diferentes de metamodelagem, que foram escolhidas por representarem duas classes básicas de metamodelos, a classe de métodos de interpolação e a de métodos de aproximação. Para representá-las foram escolhidos o método de interpolação por funções de base radial e o método de redes neurais artificiais, respectivamente. O terceiro método, que é considerado um método híbrido dos dois anteriores, é chamado de redes neurais por funções de bases radiais e é uma tentativa de acoplar as características de ambos em um único metamodelo. Os metamodelos são preparados utilizando um código para solução aeroelástica baseado no método dos elementos finitos acoplado com um modelo aerodinâmico linear de faixas. São apresentados resultados de desempenho dos três metamodelos, de onde se pode notar que a rede neural artificial é a mais adequada para previsão de flutter. O processo de MDO é realizado com o uso de um algoritmo genético multi-objetivo baseado em não-dominância, cujos objetivos são a maximização da velocidade crítica de flutter e a minimização da massa estrutural. Dois estudos de caso são apresentados para avaliar o desempenho do código de MDO, revelando que o processo global de otimização realiza de fato a busca pela fronteira de Pareto. / The Multidisciplinary Design Optimization, MDO, is an important and versatile design tool and its use is spreading out in several fields of engineering. The focus of this methodology is to put together disciplines involved with the design to work all their variables concomitantly, at an optimization environment to obtain better solutions. It is possible to use MDO in any stage of the design process, that is in the conceptual, preliminary or detailed design, as long as the numerical models are fitted to the needs of each of these stages. This work describes the development of a MDO code for the conceptual design of flexible aircraft wings, with restrictions regarding the phenomenon called flutter. As a tool for the designer at the conceptual stage, the numerical models must be fairly accurate and fast. The aim of this study is to analyze the use of metamodels for the flutter prediction of aircraft wings in the MDO code, instead of a conventional model itself, what may affect significantly the computational cost of the optimization. For this purpose, three different metamodeling techniques have been evaluated, representing two basic metamodel classes, that are, the interpolation and the approximation class. These classes are represented by the radial basis function interpolation method and the artificial neural networks method, respectively. The third method, which is considered as a hybrid of the other two, is called radial basis function neural networks and is an attempt of coupling the features of both in single code. Metamodels are prepared using an aeroelastic code based on finite element model coupled with linear aerodynamics. Results of the three metamodels performance are presented, from where one can note that the artificial neural network is best suited for flutter prediction. The MDO process is achieved using a non-dominance based multi-objective genetic algorithm, whose objectives are the maximization of critical flutter speed and minimization of structural mass. Two case studies are presented to evaluate the performance of the MDO code, revealing that overall optimization process actually performs the search for the Pareto frontier.

Le nombre d’adultes porteurs d’une tétralogie de Fallot opérée dans l’enfance est en constante augmentation. Initialement, ces patients étaient considérés comme guéris. A l’âge adulte, ils présentent en fait des complications d’ordre rythmique, responsables de morts subites, et des complications d’ordre mécanique : dilatation du ventricule droit (VD) liée à l’insuffisance pulmonaire chronique, séquellaire de la première chirurgie de réparation de la cardiopathie. Les mécanismes de l’arythmie ainsi qu’une éventuelle interaction entre la dysfonction VD et la survenue de ces arythmies ne restent que partiellement élucidés. Dans ce travail, en couplant les données d’études cliniques et les données expérimentales issues d’un modèle animal (MA) mimant une tétralogie de Fallot réparée, nous avons montré que 1) l’échocardiographie ne pouvait pas se substituer à l’IRM pour la surveillance des patients avec tétralogie de Fallot réparée 2) la valvulation pulmonaire restait une intervention à risque de mortalité 3) une bioprothèse non stentée était une bonne solution pour effectuer cette valvulation 4) en cas de fuite tricuspidienne sévère lors de cette valvulation, une plastie était indispensable 5) plusieurs gènes participaient au remodelage ventriculaire droit (analyse génétique effectuée sur le MA) 6) le remodelage électrophysiologique du VD (MA) s’accompagnait de propriétés pro-arythmogènes. Les mécanismes de décompensation sont intriqués : un lien entre dysfonction VD et arythmie paraît bien établi. D’autres analyses électrophysiologiques sont en cours au niveau du ventricule gauche (MA), pour rechercher d’autres mécanismes pro-arythmogènes. / The number of adults with a repaired tetralogy of Fallot is increasing. In the past, those patients were considered healed. Nonetheless, they present arrhythmogenic issues, with frequent sudden death, and mechanical complications: right ventricular dilation due to long lasting pulmonary valve regurgitation, secondary to surgical repair. The origin of arrhythmia and its interaction with right ventricular dysfunction is only partially understood. In this study, combining clinical with experimental data, we pointed out: 1) concerning the follow-up of this population, echocardiography is not a substitute to MRI 2) operative mortality of pulmonary valve replacement (PVR) still exists 3) a stentless bioprosthesis represents a valid solution for PVR 4) a valve repair is mandatory for severe tricuspid valve regurgitation at PVR 5) the genetic analysis carried out in an animal model of repaired tetralogy of Fallot, demonstrated the involvement of numerous genes in right ventricular remodeling 6) remodeling of the right ventricle in this animal model generates pro-arrhythmic substrate. Heart failure mechanisms in repaired tetralogy of Fallot are complex: a link between right ventricular dysfunction and arrhythmias is demonstrated. Further studies are needed to investigate other pro-arrhythmic mechanisms involving the left ventricle.