Instability and topology bifurcations on a hemisphere-cylinder at high angle of attack

La configuración de un cilindro acoplado a una semi-esfera, conocida como ’hemispherecylinder’, se considera como un modelo simplificado para numerosas aplicaciones industriales tales como fuselaje de aviones o submarinos. Por tanto, el estudio y entendimiento de los fenómenos fluidos que ocurren alrededor de dicha geometría presenta gran interés. En esta tesis se muestra la investigación del origen y evolución de los, ya conocidos, patrones de flujo (burbuja de separación, vórtices ’horn’ y vórtices ’leeward’) que se dan en esta geometría bajo condiciones de flujo separado. Para ello se han llevado a cabo simulaciones numéricas (DNS) y ensayos experimentales usando la técnica de Particle Image Velocimetry (PIV), para una variedad de números de Reynolds (Re) y ángulos de ataque (AoA). Se ha aplicado sobre los resultados numéricos la teoría de puntos críticos obteniendo, por primera vez para esta geometría, un diagrama de bifurcaciones que clasifica los diferentes regímenes topológicos en función del número de Reynolds y del ángulo de ataque. Se ha llevado a cabo una caracterización completa sobre el origen y la evolución de los patrones estructurales característicos del cuerpo estudiado. Puntos críticos de superficie y líneas de corriente tridimensionales han ayudado a describir el origen y la evolución de las principales estructuras presentes en el flujo hasta alcanzar un estado de estabilidad desde el punto de vista topológico. Este estado se asocia con el patrón de los vórtices ’horn’, definido por una topología característica que se encuentra en un rango de números de Reynolds muy amplio y en regímenes compresibles e incompresibles. Por otro lado, con el objeto de determinar las estructuras presentes en el flujo y sus frecuencias asociadas, se han usado distintas técnicas de análisis: Proper Orthogonal Decomposition (POD), Dynamic Mode Decomposition (DMD) y análisis de Fourier. Dichas técnicas se han aplicado sobre los datos experimentales y numéricos, demostrándose la buena concordancia entre ambos resultados. Finalmente, se ha encontrado en ambos casos, una frecuencia dominante asociada con una inestabilidad de los vórtices ’leeward’. ABSTRACT The hemisphere-cylinder may be considered as a simplified model for several geometries found in industrial applications such as aircrafts’ fuselages or submarines. Understanding the complex flow phenomena that surrounds this particular geometry is therefore of major industrial interest. This thesis presents an investigation of the origin and evolution of the complex flow pattern; i.e. separation bubbles, horn vortices and leeward vortices, around the hemisphere-cylinder under separated flow conditions. To this aim, threedimensional Direct Numerical Simulations (DNS) and experimental tests, using Particle Image Velocimetry (PIV) techniques, have been performed for a variety of Reynolds numbers (Re) and angles of attack (AoA). Critical point theory has been applied to the numerical simulations to provide, for the first time for this geometry, a bifurcation diagram that classifies the different flow topology regimes as a function of the Reynolds number and the angle of attack. A complete characterization about the origin and evolution of the complex structural patterns of this geometry has been put in evidence. Surface critical points and surface and volume streamlines were able to describe the main flow structures and their strong dependence with the flow conditions up to reach the structurally stable state. This state was associated with the pattern of the horn vortices, found on ranges from low to high Reynolds numbers and from incompressible to compressible regimes. In addition, different structural analysis techniques have been employed: Proper Orthogonal Decomposition (POD), Dynamic Mode Decomposition (DMD) and Fourier analysis. These techniques have been applied to the experimental and numerical data to extract flow structure information (i.e. modes and frequencies). Experimental and numerical modes are shown to be in good agreement. A dominant frequency associated with an instability of the leeward vortices has been identified in both, experimental and numerical results

Four Decades of Studying Global Linear Instability: Progress and Challenges

Global linear instability theory is concerned with the temporal or spatial development of small-amplitude perturbations superposed upon laminar steady or time-periodic three-dimensional flows, which are inhomogeneous in two(and periodic in one)or all three spatial directions.After a brief exposition of the theory,some recent advances are reported. First, results are presented on the implementation of a Jacobian-free Newton–Krylov time-stepping method into a standard finite-volume aerodynamic code to obtain global linear instability results in flows of industrial interest. Second, connections are sought between established and more-modern approaches for structure identification in flows, such as proper orthogonal decomposition and Koopman modes analysis (dynamic mode decomposition), and the possibility to connect solutions of the eigenvalue problem obtained by matrix formation or time-stepping with those delivered by dynamic mode decomposition, residual algorithm, and proper orthogonal decomposition analysis is highlighted in the laminar regime; turbulent and three-dimensional flows are identified as open areas for future research. Finally, a new stable very-high-order finite-difference method is implemented for the spatial discretization of the operators describing the spatial biglobal eigenvalue problem, parabolized stability equation three-dimensional analysis, and the triglobal eigenvalue problem; it is shown that, combined with sparse matrix treatment, all these problems may now be solved on standard desktop computer

Causality analysis of large-scale structures in the flow around a wall-mounted square cylinder

The aim of this work is to analyse the formation mechanisms of large-scale coherent structures in the flow around a wall-mounted square cylinder, due to their impact on pollutant transport within cities. To this end, we assess causal relations between the modes of a reduced-order model obtained by applying proper-orthogonal decomposition to high-fidelity-simulation data of the flow case under study. The causal relations are identified using conditional transfer entropy, which is an information-theoretical quantity that estimates the amount of information contained in the past of one variable about another. This allows for an understanding of the origins and evolution of different phenomena in the flow, with the aim of identifying the modes responsible for the formation of the main vortical structures. Our approach unveils that vortex-breaker modes are the most causal modes, in particular, over higher-order modes, and no significant causal relationships were found for vortex-generator modes. We validate this technique by determining the causal relations present in the nine-equation model of near-wall turbulence developed by Moehlis et al. (New J. Phys, vol. 6, 2004, p. 56), which are in good agreement with literature results for turbulent channel flows.Comment: 19 pages, 10 figure

POD on the fly: an adaptive combination of CFD and POD to simulate complex dynamics

Reduced order models is a fashionable field that aims at dramatically reducing the computational cost of standard numerical solvers. Such reduction is possible when the number of physically relevant degrees of freedom is much smaller than the number of `numerical degrees of freedom'. POD on the fly combines  short runs of a standard numerical solver with a low-dimensional system, which is used for the majority of the simulation. The basic ideas of this strategy will be outlined and applications to various fields (including the complex Ginzburg?Landau equation, the unsteady lid?driven cavity, an aero?elastic system, and a subsurface oil?reservoir simulation) briefly reporte

Aplicaciones de descomposición dinámica de modos de alto orden

We present a method, higher order dynamic mode decomposition (HODMD) that is suitable to analyze flow structures of complex flows. These types of flows are found in nature or in several industrial applications, such as aerospace engineering, food processing or even physiological fluids. For this reason, studying and understanding complex flow behavior is a research topic of high interest. HODMD has been successfully applied to study several types of complex flows that cover from non-linear dynamical systems, to complex fluid dynamic problems. The method combines singular value decomposition (SVD) with DMD and Takens' delay embedding theorem to approximate flow dynamics. In this seminar, we will present the good performance of HODMD applied to study noisy experimental data (transitional or thermal flow), and its extrapolation properties, which make this method a suitable tool that can be used to reduce the computational cost in numerical simulations. Finally, we will briefly introduce the spatio-temporal HODMD analysis, to calculate flow structures, defined as traveling waves. Some examples such as the analysis of a rotating spherical shell with thermal convection or the analysis of the wake of a wind turbine, will be presented at the time of the conference.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Application of Principal Component Analysis to the Investigation of the Conjugate Heat transfer in Ribbed Ducts

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Temporal extrapolation of quasi-periodic solutions via DMD-like methods

The main goal of this paper is to study the performance of a DMD-based extrapolation technique for reduced order modeling. The DMD-based model is tested in a quasi-periodic solution of an external flow around a multi-body configuration, which is made up of three bodies: two square cylinder and a circular cylinder. The results show the suitable performance of this type of models to accelerate numerical simulations

Model-free short-term fluid dynamics estimator with a deep 3D-convolutional neural network

Producción CientíficaDeep learning models are not yet fully applied to fluid dynamics predictions, while they are the state-of-the-art solution in many other areas i.e. video and language processing, finance, robotics . Prediction problems on high-dimensional, complex dynamical systems require deep learning models devised to avoid overfitting while maintaining the required model complexity. In this work we present a deep learning prediction model based on a combination of 3D convolutional layers and a low-dimensional intermediate representation that is specifically designed to forecast the future states of this type of dynamical systems. The model predicts p future velocity-field time-slices (samples) based on k past samples from a training dataset consisting of a synthetic jet in transitional regime. The complexity of this flow is characterized by two topology patterns that are periodically changing, making this flow as a suitable example to test the performance of deep learning models to predict time states in complex flows. Moreover, the wide number of applications of synthetic jets (i.e.: fluid mixing, heat transfer enhancement, flow control), points out this example as a reference for future applications, where modeling synthetic jet flows with a reduced computational effort is needed. This work additionally opens up research opportunities for other areas that also operate with complex and high-dimensional time-series data: future frame video prediction, network traffic forecasting, network intrusion detection . The proposed model is presented in detail. A comprehensive analysis of the results is provided. The results are based on a strict validation strategy to ensure its generalization. The model offers an average symmetric mean absolute error (sMAPE) and a relative root mean square error (RRMSE) of 1.068 and 0.026 respectively (one order of magnitude improvement over low-rank approximation tools), using 10 past samples and predicting 6 future samples of a two-dimensional velocity field on a 70x50 point matrix associated to a synthetic jet dataset.Ministerio de Ciencia, Innovación y Universidades Proyectos de I+D+i ‘‘Retos investigación’’, (grant RTI2018-098958- B-I00

An alternative method to calculate cross-flow instabilities

This work presents a new method to compute instabilities associated to cross-flow transition scenarios. The method analyses base flows issued from CFD simulations (RANS model) using higher order dynamic mode decomposition (HODMD). The flow field is then approximated as an expansion of modes and it is possible to identify the primary and secondary flow instabilities, in cross-flows. The good performance of this novel method is first validated by locating the transition point related to the first instability in a low-speed 2D NLF0416 airfoil. Then, 3D cross-flow instabilities over a wing with 40◦ back-sweep angle (shaped from a NACA642A015 airfoil) are presented

Normas y procedimientos de auditoria y las normas para atestiguar emitidas en México

The main goal of this study is to obtain the dominant frequencies and wavenumbers related to the main flow structures of a zero-net-mass-flux (ZNMF) jet. For this purpose, numerical simulations have been carried out at Reynolds Number 1000. The influence of including a cavity for the ZNMF piston is also studied. With this aim, the data obtained from the numerical simulations are analysed using higher order dynamic mode decomposition. The method has been applied in both directions, time and space. The results show that the effect of including a cavity increases the flow complexity