Empirical eigenfunctions: application in unsteady aerodynamics

Mención Internacional en el título de doctorThe main aim of modal decompositions is to obtain a set of functions which can describe in a compact way the variability contained in a set of observables/data. While this can be easily obtained by means of the eigenfunctions of the operator from which the observables depends, the empirical eigenfunctions allow to obtain a similar result from a set of data, without the knowledge of the problem operator. In Fluid Mechanics and related sciences one of the most prominent techniques to obtain empirical eigenfunctions is referred to as Proper Orthogonal Decomposition (POD). This thesis contains applications of the empirical eigenfunctions to (Experimental) Aerodynamics data. The mathematical framework of the POD is introduced following the bi-orthogonal approach by Aubry (1991). The mathematical derivation of the POD is given, wherever possible, in its most general formulation, without bounding it to the decomposition of a specific quantity. This choice of the author depends on the variety of POD applications which are included in this dissertation, ranging from signal processing problems to applications more strictly related with flow physics. The mathematical framework includes also one of the POD extensions, the Extended POD (EPOD), which allows to extract modes linearly correlated to the empirical eigenfunctions of a second quantity. The first two applications of the empirical eigenfunctions are strictly connected with the signal treatment in experimental techniques for Fluid Mechanics. In Chapter 3, the empirical eigenfunctions are identified as an optimal basis in which perform a "low-pass" spectral filter of experimental fluid data, such as velocity fields measured with Particle Image Velocimetry (PIV). This filtering is extremely beneficial to reduce the random errors contained in the PIV fields and obtain a more accurate estimate of derivative quantities (such as, for instance, vorticity), which are more affected by random errors. In Chapter 4 the POD is exploited for the pre-treatment of a sequence of PIV images. The aim is to remove background and reflections, which are sources of uncertainty in PIV measurements. In this case a "high-pass" spectral filtering is applied to the PIV image ensemble in order to remove the highly-coherent part of the signal corresponding to the background. In the third and fourth applications, the POD is applied to recover the underlying dynamics of a flow. More specifically, in Chapter 5 the POD is applied to the complex wake of a pair of cylinders in tandem arrangement with the additional perturbation of the wall proximity. Through this technique it is possible to track the changes in the oscillatory behaviour of the wake instabilities ascribed to different geometrical configurations of the cylinders. In Chapter 6 the POD and the EPOD are applied respectively to the flow fields around an airfoil in plunging and pitching motion and to the unsteady aerodynamic forces acting on the airfoil. The decomposition allows to extract a reduced set of modes of the flow field which are related to the force generation mechanism. These modes correspond to well-recognizable phenomena of the flow which can be identified for diverse airfoil kinematics. This flow-field driven force decomposition is analysed on the light of existing force models, enabling their reinterpretation and driving towards possible corrections. The final application is devoted to overcome the low temporal resolution of typical flow field measurements, such as PIV, by proposing a robust estimation of turbulent flows dynamics. The method employs a modified version of the EPOD to identify the correlation between a non-time-resolved field measurement and a time-resolved point measurement. The estimation of the time-resolved flow fields is obtained exploiting the correlation of the flow fields with the temporal information contained in the point measurements.El objetivo principal de las descomposiciones modales es obtener un conjunto de funciones que sean capaces de describir de una manera compacta la variabilidad contenida en un conjunto de observables/datos. Si bien este objetivo puede ser fácilmente realizado mediante el uso de las autofunciones del operador del cual los observables dependen, las autofunciones empíricas permiten obtener un resultado similar partiendo de un conjunto de datos sin la necesidad de conocer el operador del problema. En Mecánica de Fluidos y en ciencias relacionadas con esta disciplina, una de las técnicas más relevantes para obtener autofunciones empíricas es la conocida como Descomposición Modal Ortogonal (Proper Orthogonal Decomposition, POD). Esta tesis contiene diversas aplicaciones de las autofunciones empíricas en datos de Aerodinámica (Experimental). La base matemática de la POD es introducida siguiendo la aproximación biortogonal realizada por Aubry (1991). La formulación matemática de la POD es expresada siempre que es posible en el marco más general posible, sin condicionarla a la descomposición de una variable en concreto. La elección del autor dependerá de las diferentes aplicaciones de la POD, todas ellas descritas en la presente tesis, las cuales abarcan desde problemas de procesado de señales hasta aplicaciones más estrictamente relacionadas con el análisis de la física del flujo. La formulación matemática incluye también uno de las extensiones de la POD, la POD Extendida (EPOD), la cual permite extraer modos linealmente correlacionados con las autofunciones empíricas de una segunda variable. Las dos primeras aplicaciones de las autofunciones empíricas están estrictamente relacionadas con el tratamiento de señales en técnicas experimentales de Mecánica de Fluidos. En el Capítulo 3, las autofunciones empíricas son identificadas como una base optima, la cual se puede utilizar para realizar un filtro pasa bajos espectral para datos experimentales de flujos, tales como campos de velocidad obtenidos mediante la técnica de Velocimetría por Imágenes de Partículas, (Particle Image Velocimetry, PIV). Este tipo de filtro es muy beneficioso para reducir los errores de carácter aleatorio contenidos en los campos de PIV y por tanto obtener una estimación más precisa en las cantidades que precisan del uso de derivadas (por ejemplo, la vorticidad), ya que están más afectadas por este tipo de errores. En el Capítulo 4, la POD es utilizada para el pretratamiento de una secuencia de imágenes de PIV. El objetivo es reducir el fondo de la imagen y las reflexiones, ambas fuentes de incertidumbre en las medidas de PIV. En este caso, un filtro pasa altos espectral es aplicado al conjunto de imágenes de PIV para poder quitar la parte mayormente correlacionada de la señal, la cual corresponde con el fondo de la imagen. En la tercera y cuarta aplicación de la POD, está técnica es utilizada para reconstruir las dinámicas fundamentales de un flujo. Concretamente, en el Capítulo 5 la POD es utilizada para analizar la estela compleja que se produce en una pareja de cilindros en tándem con la perturbación adicional de una pared próxima a ellos. A través de esta técnica, es posible poder estudiar los cambios en el comportamiento oscilatorio de las inestabilidades de la estela, las cuales están relacionadas con las diferentes configuraciones geométricas de los cilindros. En el capítulo 6, la POD y la EPOD son aplicadas respectivamente a campos fluidos y fuerzas aerodinámicas producidos por un perfil aerodinámico en movimiento (de rotación y desplazamiento vertical) no estacionario. La técnica de descomposición permite extraer un conjunto reducido de modos del campo fluido que están relacionados con el mecanismo que genera las fuerzas aerodinámicas. Estos modos corresponden con fenómenos característicos del flujo que pueden ser identificados para diferentes cinemáticas de perfiles aerodinámicos. Estas dinámicas del flujo que están conectadas con las fuerzas aerodinámicas son analizadas teniendo en cuenta los modelos ya existentes en la literatura que describen las fuerzas aerodinámicas, permitiendo su reinterpretación e incluso pudiendo añadir posibles correcciones. La última aplicación propuesta está destinada a subsanar la baja resolución temporal típica de las medidas de campo fluido, como en aquellas realizadas utilizando PIV, mediante una estimación robusta de las dinámicas del flujo turbulento. El método propuesto emplea una versión modificada de la EPOD para identificar para correlación entre un campo fluido medido que no está resuelto en el tiempo y una medida puntual que sí que está resulta en el tiempo. La estimación del campo fluido resuelto en el tiempo es obtenida mediante la correlación de los campos de flujo con la información temporal contenida en la medida puntual.This work has been partially supported by the Grant TRA2013-41103-P of the Spanish Ministry of Economy and Competitiveness, which includes FEDER funding, and by the Grant DPI2016-79401-R, funded by the Spanish State Research Agency (SRA) and European Regional Development Fund (ERDF).Programa Oficial de Doctorado en Mecánica de FluidosPresidente: Bharathram Ganapathisubramani.- Secretario: Francisco Javier Rodríguez Rodríguez.- Vocal: Francisco J. Huera-Huart

Pressure from data-driven estimation of velocity fields using snapshot PIV and fast probes

The most explored path to obtain pressure fields from Particle Image Velocimetry (PIV) data roots its basis on accurate measurement of instantaneous velocity fields and their corresponding time derivatives. This requires time-resolved measurements, which are often difficult to achieve due to hardware limitations and expensive to implement. In alternative, snapshot PIV experiments are more affordable but require enforcing physical constraints (e.g. Taylor’s hypothesis) to extract the time derivative of the velocity field. In this work, we propose the use of data-driven techniques to retrieve time resolution from the combination of snapshot PIV and high-repetition-rate sensors measuring flow quantities in a limited set of spatial points. The instantaneous pressure fields can thus be computed by leveraging the Navier–Stokes equations as if the measurement were time-resolved. Extended Proper Orthogonal Decomposition, which can be regarded as one of the simplest algorithm for estimating velocity fields from a finite number of sensors, is used in this paper to prove the feasibility of this concept. The method is fully data-driven and, after training, it requires only probe data to obtain field information of velocity and pressure in the entire flow domain. This is certainly an advantage since model-based methods can retrieve pressure in an observed snapshot, but show increasing error as the field information is propagated over time. The performances of the proposed method are tested on datasets of increasing complexity, including synthetic test cases of the wake of a fluidic pinball and a channel flow, and experimental measurements in the wake of a wing. The results show that the data-driven pressure estimation is effective in flows with compact POD spectrum. In the cases where Taylor’s hypothesis holds well, the in-sample pressure field estimation can be more accurate for model-based methods; nonetheless, the proposed data-driven approach reaches a better accuracy for out-of-sample estimation after less than 0.20 convective times in all tested cases.This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 949085). Funding for APC: Universidad Carlos III de Madrid (Read & Publish Agreement CRUE-CSIC 2022)

Experimental assessment of RANS models for wind load estimation over solar-panel arrays

This article belongs to the Special Issue Application of Computational Fluid Dynamics in Mechanical EngineeringThis paper reports a comparison between wind-tunnel measurements and numerical simulations to assess the capabilities of Reynolds-Averaged Navier-Stokes models to estimate the wind load over solar-panel arrays. The free airstream impinging on solar-panel arrays creates a complex separated flow at large Reynolds number, which is severely challenging for the current Reynolds-Averaged Navier-Stokes models. The Reynolds-Averaged Navier-Stokes models compared in this article are k-ϵ, Shear-Stress Transport k-ω, transition and Reynolds Shear Model. Particle Image Velocimetry measurements are performed to investigate the mean flow-velocity and turbulent-kinetic-energy fields. Pressure taps are located in the surface of the solar panel model in order to obtain static pressure measurements. All the Reynolds-Averaged Navier-Stokes models predict accurate average velocity fields when compared with the experimental ones. One of the challenging factor is to predict correctly the thickness of the turbulent wake. In this aspect, Reynolds Shear provides the best results, reproducing the wake shrink observed on the 3rd panel in the experiment. On the other hand, some other features, most notably the blockage encountered by the flow below the panels, are not correctly reproduced by any of the models. The pressure distributions over the 1st panel obtained from the different Reynolds-Averaged Navier-Stokes models show good agreement with the pressure measurements. However, for the rest of the panels Reynolds-Averaged Navier-Stokes fidelity is severely challenged. Overall, the Reynolds Shear model provides the best pressure estimation in terms of pressure difference between the front and back sides of the panels.The authors wish to thanks Carlos Cobos for contributing the realisation of the experimental setup and J. Rodríguez for providing the PIV system. The authors acknowledge S. Discetti and A. Ianiro for insightful comments and discussions

Adaptive ensemble PTV

Ensemble particle tracking velocimetry (EPTV) is a method to extract high-resolution statistical information on flow fields from particle image velocimetry (PIV) images. The process is based on tracking particles and extracting the velocity probability distribution functions of the image ensemble in averaging-regions deemed to contain a sufficient number of particle pairs/tracks. The size of the averaging regions depends on the particle density and the number of snapshots. An automatic adaptive variation of the ensemble PTV is presented to further push the spatial resolution of the method. The proposed adaptive-EPTV is based on stretching and orienting the averaging regions along the direction of maximum curvature of the velocity fields. The process requires a predictor calculation with isotropic-window EPTV to compute the second derivatives of the mean velocity components. In a second step, the principal directions of the Hessian tensor are calculated to tune the optimal orientation and stretch of the averaging regions. The stretching and orientation are achieved using a Gaussian windowing with different standard deviation along the local principal direction of the Hessian tensor. The algorithm is first validated using three different synthetic datasets: a sinusoidal displacement field, a channel flow and the flow around a NACA 0012 airfoil. An experimental test case of an impinging jet equipped with a fractal grid at the nozzle outlet is also carried out

Heat transfer enhancement in turbulent boundary layers with a pulsed slot jet in crossflow

The convective heat transfer enhancement in a turbulent boundary layer (TBL) employing a pulsed, slot jet in crossflow is investigated experimentally. A parametric study on actuation frequencies and duty cycles is performed. The actuator is a flush-mounted slot jet that injects fluid into a well-behaved zero-pressure-gradient TBL over a flat plate. A heated-thin-foil sensor is employed to measure the time-averaged convective heat transfer coefficient downstream of the actuator location. The results show that both the jet penetration in the streamwise direction and the overall Nusselt number increase with increasing duty cycle. The frequency at which the Nusselt number is maximized is independent of the duty cycle. It is noted that such frequency is strikingly equal to the inverse of the characteristic travel time of large-scale turbulent structures convected within the buffer layer. Eventually, a simplified model is proposed to decouple the effect of pulsation frequency and duty cycle in the overall heat transfer enhancement, with a good agreement with experimental data. The cost of actuation is also quantified in terms of the amount of injected fluid during the actuation, leading to conclude that the lowest duty cycle is the most efficient for heat transfer enhancement

Performance improvement in yo-yo intermittent recovery test Level 2 and during official matches: The role of speed endurance training production in Élite football players

This study aims to examine the performance improvement in yo-yo intermittent recovery test level 2 (IR2) and official matches, during a competitive season in professional football players (Italian 3rd Division Series C, 2019- 2020). Twenty-eight (n=28) élite football players participated in this study (age 21.4±3.3; body weight 79.7±3.4; height 182.4±5.5; fat mass 9.2±1.9), without goalkeepers. In the pre-season (4 weeks, from July to August), the players performed yo-yo intermittent recovery test level 2 (IR2), to evaluate aerobic and anaerobic performance before the start of the season. Every player has been analysed with a K-GPS Live device 50Hz (K-Sport Universal STATS, Italy) and Polar Team System PRO 2 heart-rate sensor (Polar Electro, Finland) to recorder maximal heart rate. After 12 weeks of training (in season), the same players repeat an IR2 test to check performance improvements and verify whether the training programme is correct. The first element was to determine whether the improvement in distance covered during a test is better, the same, or worse with respect to the pre-season. After 12 weeks of training, the difference between the first trial (pre-season) and the second one (in-season) is statistically significant (ES: 0.48; p<0.05; 24%). At the same time, there has been a significant improvement in match physical performance. Regarding the importance of speed endurance training during a season, it is necessary to improve performance in IR2 test after 12 weeks and improve maximal oxygen uptake and glycolytic enzyme activity. Comparing match performance before (T1) the second trial IR2 with match performance after second (T2) trial of this test, there are statistically meaningful changes

Physical Efficiency Index (PEI) and injuries after return to play post Covid-19 in Italian Serie A.

The aim of this study is analyze physical performance in Italian Serie A 2019-2020, after return to play post Covid-19, in the 20 club participants in the championship (n=567 players, age 27.2±1.1, value: 8.12 mln), to understand the causes of injuries that occurred during the last 12 match for the conclusion of the Serie A and variation in high intensity production. The analysis of physical performance is analyzed with SPORTVU OPTICAL TRACKING (STATS PERFORM, CHICAGO, USA) during each football match, from 27 match day (June 2020, after lockdown) to 38 match day (August 2020). Using a semiautomatic video analysis system that has incorporated new parameters able to measure physical efficiency (“Method for game analysis”, patented in 2010, PCT/IB2010/002593, K-SPORT UNIVERSAL, MONTELABBATE, ITALY). At the same time we analyzed players absence from each match day for all teams (n=20), to better understand how many injuries the lockdown (3 and a half months) caused over time. Our research relates with a professional Top Level Championship, physical efficiency index and injuries occured during a post Covid-19 period. The championship was suspended due to the Covid-19 emergency on matchday 26 and restart from matchday 27a in June 2020. The percentage of absences due to injury by comparing matchday 27 (post lockdown) and matchday 38 (last season) has showed a statistically significant increase 26% (n=20; p<0.05). Negative correlations was found between PEI (Physical Efficiency Index) and number of injuries occured post lockdown respectively, (n=20, r = -0.25, p > 0.05). For the 2019-20 season there is a total number of absences equal to 2213; compared with the data of the last thirteen seasons , an increase of 6%, statistical meaningfulness, (n=20; p<0.05) is observed compared to the previous season (2018-19). Key performance indicators in this research not predict injuries and they have a low correlation with them. Future studies it’s necessary to have more information on absence of injuires and their relation with performance and techinical/tactical game intelligence. Of course, PEI (Physical Efficiency Index), it’s a good indicator of physical team condition

Heat transfer enhancement in turbulent boundary layers with a pulsed slot jet in crossflow

The convective heat transfer enhancement in a turbulent boundary layer (TBL) employing a pulsed, slot jet in crossflow is investigated experimentally. A parametric study on actuation frequencies and duty cycles is performed. The actuator is a flush-mounted slot jet that injects fluid into a well-behaved zero-pressure-gradient TBL over a flat plate. A heated-thin-foil sensor measures the time-averaged convective heat transfer coefficient downstream of the actuator location and the flow field is characterised by means of Particle Image Velocimetry. The results show that both the jet penetration in the streamwise direction and the overall Nusselt number increase with increasing duty cycle. The frequency at which the Nusselt number is maximised is independent of the duty cycle. The flow topology is considerably altered by the jet pulsation. A wall-attached jet rises from the slot accompanied by a pair of counter-rotating vortices that promote flow entrainment and mixing. Eventually, a simplified model is proposed which decouples the effect of pulsation frequency and duty cycle in the overall heat transfer enhancement, with a good agreement with experimental data. The cost of actuation is also quantified in terms of the amount of injected fluid during the actuation, leading to conclude that the lowest duty cycle is the most efficient for heat transfer enhancement.The work has been supported by the project ARTURO, ref. PID2019-109717RB-I00/AEI/10.13039/501100011033, funded by the Spanish State Research Agency. Funding for APC: Universidad Carlos III de Madrid (Read & Publish Agreement CRUE-CSIC 2022). Paul Murphy is kindly acknowledged for his support during the experimental campaign

Post-transplant cerebral toxoplasmosis diagnosed by magnetic resonance imaging.

Cerebral toxoplasmosis is a rare late complication in allogeneic bone marrow transplanted patients. Neuroradiological findings may suggest the correct diagnosis. We report a patient in whom cerebral magnetic resonance imaging (MRI) showed a lesion characteristic of toxoplasmosis. Anti- toxoplasma treatment led to clinical and radiological improvement. MRI seems to be a valid tool for detection and follow-up of cerebral toxoplasmosis

CD34+ enriched donor lymphocyte infusions in a case of pure red cell aplasia and late graft failure after major ABO-incompatible bone marrow transplantation

A variety of immunohematological complications may occur after ABO-incompatible BMT. We report a CML patient (blood group O) who received a BMT from an HLA-identical sibling (blood group AB). The transplant was followed by normal myeloid and megakaryocytic engraftment, but erythroblastopenia persisted for more than 200 days after BMT. By bone marrow culture studies, a complement-dependent serum inhibitor of hemopoiesis was detected, suggesting immunological inhibition of erythropoiesis. The patient was resistant to a number of treatments such as intravenous gamma-globulins, prednisolone and high-dose erythropoietin. Full engraftment with normal blood counts and marrow cellularity was achieved after two dose-escalating CD34+-enriched donor lymphocyte infusions (DLI). This experience suggests that CD34+-enriched DLI may be an effective treatment for patients with delayed engraftment or late graft failure due to major ABO-incompatibility