3,928 research outputs found
Astrophysical turbulence modeling
The role of turbulence in various astrophysical settings is reviewed. Among
the differences to laboratory and atmospheric turbulence we highlight the
ubiquitous presence of magnetic fields that are generally produced and
maintained by dynamo action. The extreme temperature and density contrasts and
stratifications are emphasized in connection with turbulence in the
interstellar medium and in stars with outer convection zones, respectively. In
many cases turbulence plays an essential role in facilitating enhanced
transport of mass, momentum, energy, and magnetic fields in terms of the
corresponding coarse-grained mean fields. Those transport properties are
usually strongly modified by anisotropies and often completely new effects
emerge in such a description that have no correspondence in terms of the
original (non coarse-grained) fields.Comment: 88 pages, 26 figures, published in Reports on Progress in Physic
Recommended from our members
Drift waves and transport
Drift waves occur universally in magnetized plasmas producing the dominant mechanism for the transport of particles, energy and momentum across magnetic field lines. A wealth of information obtained from quasistationary laboratory experiments for plasma confinement is reviewed for drift waves driven unstable by density gradients, temperature gradients and trapped particle effects. The modern understanding of Bohm transport and the role of sheared flows and magnetic shear in reducing the transport to the gyro-Bohm rate are explained and illustrated with large scale computer simulations. The types of mixed wave and vortex turbulence spontaneously generated in nonuniform plasmas are derived with reduced magnetized fluid descriptions. The types of theoretical descriptions reviewed include weak turbulence theory, Kolmogorov anisotropic spectral indices, and the mixing length. A number of standard turbulent diffusivity formulas are given for the various space-time Scales of the drift-wave turbulent mixing. [S0034-6861(99)00803-X].Physic
Convective heat transfer control in turbulent boundary layers
Mención Internacional en el título de doctorThe sustainable development of our society opens up concerns in several fields of engineering,
including energy management, production, and the impact of our technology, being thermal
management a common issue to be addressed. The investigation reported in this manuscript
focuses on understanding, controlling and optimizing the physical processes involving
convective heat transfer in turbulent wall-bounded flows. The content is divided into two
main blocks, namely the investigation of classic open-loop active-control techniques to
control heat transfer, and the technological development of machine-learning strategies to
enhance the performance of flow control in the field of convective heat transfer.
The first block focuses on actuator technology, applying dielectric-barrier discharge
(DBD) plasma actuators and a pulsed slot jet in crossflow (JICF), respectively, to control
the convective heat transfer in a turbulent boundary layer (TBL) over a flat plate. In the
former, an array of DBD plasma actuators is employed to induce pairs of counter-rotating,
streamwise-aligned vortices embedded in the TBL to reduce heat transfer downstream of the
actuation. The whole three-dimensional mean flow field downstream of the plasma actuator
is reconstructed from stereoscopic particle image velocimetry (PIV). Infrared thermography
(IR) measurements coupled with a heated thin foil provide ensemble-averaged convective
heat transfer distributions downstream of the actuators. The combination of the flow
field and heat transfer measurements provides a complete picture of the fluid-dynamic
interaction of plasma-induced flow with local turbulent transport effects. The plasmainduced
streamwise vortices are stationary and confined across the spanwise direction due
to the action of the plasma discharge. The opposing plasma discharge causes a mass- and
momentum-flux deficit within the boundary layer, leading to a low-velocity region that
grows in the streamwise direction and which is characterised by an increase in displacement
and momentum thicknesses. This low-velocity ribbon travels downstream, promoting
streak-alike patterns of reduction in the convective heat transfer distribution. Near the wall,
the plasma-induced jets divert the main flow due to the DBD-actuator momentum injection
and the suction on the surrounding fluid by the emerging jets. The stationarity of the
plasma-induced vortices makes them persistent far downstream, reducing the convective
heat transfer.
Conversely, the target of the second paper in this first block is to enhance convective
heat transfer rather than reduce it. A fully modulated, pulsed, slot JICF is used to perturb
the TBL. The slot-jet actuator, flush-mounted and aligned in the spanwise direction, is
controlled based on two design parameters, namely the duty cycle (DC) and the pulsation
frequency (f). Heat transfer and flow-field measurements are performed to characterise the
control performance using IR thermography and planar PIV, respectively. A parametric
study on f and DC is carried out to assess their effect on the heat transfer distribution.
The vorticity fields are reconstructed from the Proper Orthogonal Decomposition (POD)
modes, retrieving phase information. The flow topology is considerably altered by the
jet pulsation, even compared to the case of a steady jet. The results show that both the jet penetration in the streamwise direction and the overall Nusselt number increase with
increasing DC. However, the frequency at which the Nusselt number is maximised is
independent of the duty cycle. 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 f and DC 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 among the tested set.
The second block of the thesis splits into a comparative assessment of machine
learning (ML) methods for active feedback flow control and an application of linear genetic
algorithms to an experimental convective heat transfer enhancement problem. First,
the comparative study is carried out numerically based on a well-established benchmark
problem, the drag reduction of a two-dimensional Kármán vortex street past a circular
cylinder at a low Reynolds number (Re = 100). The flow is manipulated with two
blowing/suction actuators on the upper and lower side of a cylinder. The feedback employs
several velocity sensors. Two probe configurations are evaluated: 5 and 11 velocity probes
located at different points around the cylinder and in the wake. The control laws are
optimized with Deep Reinforcement Learning (DRL) and Linear Genetic Programming
Control (LGPC). Both methods successfully stabilize the vortex alley and effectively
reduce drag while using small mass flow rates for the actuation. DRL features higher
robustness with respect to variable initial conditions and noise contamination of the sensor
data; on the other hand, LGPC can identify compact and interpretable control laws, which
only use a subset of sensors, thus allowing reducing the system complexity with reasonably
good results.
The gained experience and knowledge of machine-learning methods motivated the
last study enclosed in this thesis, which utilises linear genetic algorithm control (LGAC)
to identify the best actuation parameters in an experimental application. The actuator
is a set of six slot jets in crossflow aligned with the freestream. An open-loop optimal
periodic forcing is defined by the carrier frequency (f), the duty cycle (DC) and the phase
between actuators (ϕ) as control parameters. The control laws are optimised with respect
to the unperturbed TBL and the steady-jet actuation. The cost function includes wall
convective heat transfer and the cost of the actuation, thus leading to a multi-objective
optimisation problem. Surprisingly, the LGAC algorithm converges to the same frequency
and duty cycle for all the actuators. This frequency is equivalent to the optimal frequency
reported in the second study of the first block of this thesis. The performance of the
controller is characterised by IR thermography and PIV measurements. The action of the
jets considerably alters the flow topology compared to the steady-jet actuation, yielding
a slightly asymmetric flow field. The phase difference between multiple jet actuation
has shown to be very relevant and the main driver of flow asymmetry. A POD analysis
concludes the shedding phenomena characterising the steady-jet actuation, while the
optimised controller exhibits an elongated large-scale structure just downstream of the
actuator.
The investigation carried out in this thesis sheds some light on the application of
different flow control strategies to the field of convective heat transfer. From the utilisation
of plasma actuators and a single jet in cross flow to the development of sophisticated
control logic, the results point to the exceptional potential of machine learning control in unravelling unexplored controllers within the actuation space. Ultimately, this work
demonstrates the viability of employing sophisticated measurement techniques together
with advanced algorithms in an experimental investigation, paving the way towards more
complex applications involving feedback information.El desarrollo sostenible de nuestra sociedad abre preocupaciones en varios campos de
la ingeniería, incluyendo la gestión de la energía, la producción y el impacto de nuestra
tecnología, siendo la gestión térmica un tema común a tratar. La investigación que se
presenta en este manuscrito se centra en la comprensión, el control y la optimización
de los procesos físicos que implican la transferencia de calor por convección en flujos
turbulentos de pared. El contenido se divide en dos bloques principales: la investigación
de las técnicas clásicas de control activo de lazo abierto para controlar la transferencia de
calor, y el desarrollo tecnológico de estrategias de aprendizaje automático para mejorar el
rendimiento del control del flujo en el campo de la transferencia de calor por convección.
El primer bloque se centra en la tecnología de los actuadores, aplicando actuadores de
plasma de descarga de barrera dieléctrica (dielectric barrier dicharge, DBD) y un chorro
con forma de ranura pulsado en flujo cruzado (jet in crossflow, JICF), respectivamente,
para controlar la transferencia de calor por convección en una capa límite turbulenta
(turbulent boundary layer, TBL) sobre una placa plana. En el primero, se emplea un
conjunto de actuadores de plasma DBD para inducir pares de vórtices contra-rotativos,
alineados con la corriente e incrustados en la TBL para reducir la transferencia de calor
aguas abajo de la actuación. El campo de flujo medio tridimensional completo aguas abajo
del actuador de plasma se reconstruye a partir de la velocimetría de imagen de partículas
estereoscópica (particle image velocimetry, PIV). Las mediciones de termografía infrarroja
(IR) junto a una fina lámina calentada proporcionan distribuciones de transferencia de calor
convectiva promediadas aguas abajo de los actuadores. La combinación de las mediciones
del campo de flujo y de la transferencia de calor proporciona una imagen completa de
la interacción fluido-dinámica del flujo inducido por el plasma con los efectos locales de
transporte turbulento. Los vórtices en el sentido de la corriente inducidos por plasma
son estacionarios y están confinados transversalmente debido a la acción de la descarga
de plasma. La descarga de plasma en oposición causa un déficit de flujo de masa y de
momento dentro de la capa límite, lo que conduce a una región de baja velocidad que
crece en la dirección de la corriente y que se caracteriza por un aumento de los espesores
de desplazamiento y de momento. Esta zona de baja velocidad se desplaza corriente abajo,
promoviendo patrones de reducción similares a rayas en los que se reduce la transferencia
de calor por convección. Cerca de la pared, los chorros inducidos por el plasma desvían el
flujo principal debido a la inyección de momento del actuador DBD y a la succión sobre el
fluido circundante por parte de los chorros emergentes. La estacionariedad de los vórtices
inducidos por el plasma los hace persistentes aguas abajo, reduciendo la transferencia de
calor por convección.
Por el contrario, el objetivo del segundo trabajo de este primer bloque es mejorar la
transferencia de calor por convección en lugar de reducirla. Se utiliza un JICF, pulsado
y con forma de ranura, totalmente modulado para perturbar la TBL. El actuador de chorro, montado a ras y alineado en la dirección transversal, se controla en base a dos
parámetros de diseño, a saber, el ciclo de trabajo (DC) y la frecuencia de pulsación (f).
Se realizan mediciones de la transferencia de calor y del campo de flujo para caracterizar
el rendimiento del control mediante termografía IR y PIV planar, respectivamente. Se
lleva a cabo un estudio paramétrico de f y DC para evaluar su efecto en la distribución de
la transferencia de calor. Los campos de vorticidad se reconstruyen a partir de los modos
de descomposición ortogonal adecuada (POD), recuperando la información de fase. La
topología del flujo se ve considerablemente alterada por la pulsación del chorro, incluso
en comparación con el caso de un chorro estacionario. Los resultados muestran que tanto
la penetración del chorro en la dirección de la corriente como el número Nusselt global
aumentan con el incremento de DC. Sin embargo, la frecuencia a la que se maximiza el
número Nusselt es independiente del ciclo de trabajo. Un chorro adherido a la pared sale
de la ranura acompañado de un par de vórtices contrarrotantes que promueven el arrastre
y la mezcla del flujo. Finalmente, se propone un modelo simplificado que desacopla el
efecto de f y DC en la mejora global de la transferencia de calor, con un buen acuerdo
con los datos experimentales. También se cuantifica el coste de la actuación en términos
de la cantidad de fluido inyectado durante la actuación, llegando a la conclusión de que el
ciclo de trabajo más bajo es el más eficiente para la mejora de la transferencia de calor
entre el conjunto probado.
El segundo bloque de la tesis se divide en una evaluación comparativa de los métodos
de aprendizaje automático (machine learning, ML) para el control activo del flujo
por retroalimentación y una aplicación de algoritmos genéticos lineales a un problema
experimental de mejora de la transferencia de calor por convección. En primer lugar, el
estudio comparativo se realiza numéricamente a partir de un problema de referencia bien
establecido: la reducción de la resistencia aerodinámica de una calle de vórtices de Kármán
bidimensional tras un cilindro circular a un número de Reynolds bajo (Re = 100). El
flujo se manipula con dos actuadores de soplado/succión en la parte superior e inferior
de un cilindro. La retroalimentación emplea varios sensores de velocidad. Se evalúan
dos configuraciones de sondas: 5 y 11 sondas de velocidad situadas en diferentes puntos
alrededor del cilindro y en la estela. Las leyes de control se optimizan con el aprendizaje
profundo por refuerzo (Deep Reinforcement Learning, DRL) y el control por programación
genética lineal (Linear Genetic Programming Control, LGPC). Ambos métodos estabilizan
con éxito la calle de vórtices y reducen de manera efectiva la resistencia al tiempo que
usan caudales másicos pequeños para la actuación. El DRL se caracteriza por una mayor
robustez con respecto a la variación de la condición inicial y a la contaminación por ruido
de los datos de los sensores; por otro lado, el LGPC puede identificar leyes de control
compactas e interpretables, que sólo utilizan un subconjunto de sensores, lo que permite
reducir la complejidad del sistema con resultados razonablemente buenos.
La experiencia adquirida y el conocimiento de los métodos de aprendizaje automático
motivaron el último estudio incluido en esta tesis, que utiliza el control por algoritmo
genético lineal (Linear Genetic Algorithm Control, LGAC) para identificar los mejores
parámetros de actuación en una aplicación experimental. El actuador es un conjunto de
seis chorros con forma de ranura en flujo cruzado y alineados con la corriente principal.
Se define una ley de forzado periódica en lazo abierto mediante la frecuencia portadora
(f), el ciclo de trabajo (DC) y la fase entre actuadores (ϕ) como parámetros de control.
Las leyes de control se optimizan con respecto a la TBL no perturbada y la actuación
de chorro constante. La función de coste incluye la transferencia de calor por convección de la pared y el coste de la actuación, lo que da lugar a un problema de optimización
multiobjetivo. Sorprendentemente, el algoritmo LGAC converge a la misma frecuencia y
ciclo de trabajo para todos los actuadores. Esta frecuencia es equivalente a la frecuencia
óptima reportada en el segundo estudio del primer bloque de esta tesis. El rendimiento
del controlador se caracteriza mediante termografía IR y mediciones PIV. La acción de los
chorros altera considerablemente la topología del flujo en comparación con la actuación
de los chorros constantes, dando lugar a un campo de flujo ligeramente asimétrico. La
diferencia de fase entre la actuación de múltiples chorros ha demostrado ser muy relevante
y el principal impulsor de la asimetría del flujo. Un análisis POD concluye los fenómenos
de desprendimiento de vórtices que caracterizan la actuación de chorro constante, mientras
que el controlador optimizado muestra una estructura alargada a gran escala justo aguas
abajo del actuador.
La investigación llevada a cabo en esta tesis arroja algo de luz sobre la aplicación
de diferentes estrategias de control de flujo en el campo de la transferencia de calor por
convección. Desde la utilización de actuadores de plasma y un único chorro en flujo cruzado
hasta el desarrollo de una sofisticada lógica de control, los resultados apuntan al excepcional
potencial del control por aprendizaje automático para desentrañar controladores
inexplorados dentro del espacio de actuación. En última instancia, este trabajo demuestra
la viabilidad de emplear sofisticadas técnicas de medición junto con algoritmos avanzados
en una investigación experimental, allanando el camino hacia aplicaciones más complejas
que implican información de retroalimentación.The work enclosed in this thesis has been partially supported by the Universidad Carlos
III de Madrid through a PIPF scholarship awarded on a competitive basis, and by the
following research projects: ARTURO (Active contRol of Turbulence for sUstainable aiRcraft
propulsiOn), ref. PID2019-109717RB-I00/AEI/10.13039/501100011033, funded by
the Spanish State Research Agency (SRA); the 2020 Leonardo Grant for Researchers and
Cultural Creators AEROMATIC (Active flow control of aerodynamic flows with machine
learning), funded by the BBVA Foundation with grant number IN[20]_ING_ING_0163;
and GloWing Starting Grant, funded by the European Research Council (ERC), under
grant agreement ERC-2018.StG-803082.Programa de Doctorado en Mecánica de Fluidos por la Universidad Carlos III de Madrid; la Universidad de Jaén; la Universidad de Zaragoza; la Universidad Nacional de Educación a Distancia; la Universidad Politécnica de Madrid y la Universidad Rovira i VirgiliPresidente: Octavio Armas Vergel.- Secretario: Manuel García-Villalba Navaridas.- Vocal: Gioacchino Cafier
Genetically-inspired convective heat transfer enhancement in a turbulent boundary layer
The convective heat transfer in a turbulent boundary layer (TBL) on a flat
plate is enhanced using an artificial intelligence approach based on linear
genetic algorithms control (LGAC). The actuator is a set of six slot jets in
crossflow aligned with the freestream. An open-loop optimal periodic forcing is
defined by the carrier frequency, the duty cycle and the phase difference
between actuators as control parameters. The control laws are optimised with
respect to the unperturbed TBL and to the actuation with a steady jet. The cost
function includes the wall convective heat transfer rate and the cost of the
actuation. The performance of the controller is assessed by infrared
thermography and characterised also with particle image velocimetry
measurements. The optimal controller yields a slightly asymmetric flow field.
The LGAC algorithm converges to the same frequency and duty cycle for all the
actuators. It is noted that such frequency is strikingly equal to the inverse
of the characteristic travel time of large-scale turbulent structures advected
within the near-wall region. The phase difference between multiple jet
actuation has shown to be very relevant and the main driver of flow asymmetry.
The results pinpoint the potential of machine learning control in unravelling
unexplored controllers within the actuation space. Our study furthermore
demonstrates the viability of employing sophisticated measurement techniques
together with advanced algorithms in an experimental investigation.Comment: 20 pages, 13 figure
Towards a solution of the closure problem for convective atmospheric boundary-layer turbulence
We consider the closure problem for turbulence in the dry convective atmospheric boundary
layer (CBL). Transport in the CBL is carried by small scale eddies near the surface and large
plumes in the well mixed middle part up to the inversion that separates the CBL from the
stably stratified air above. An analytically tractable model based on a multivariate Delta-PDF
approach is developed. It is an extension of the model of Gryanik and Hartmann [1] (GH02)
that additionally includes a term for background turbulence. Thus an exact solution is derived
and all higher order moments (HOMs) are explained by second order moments, correlation
coefficients and the skewness. The solution provides a proof of the extended universality
hypothesis of GH02 which is the refinement of the Millionshchikov hypothesis (quasi-
normality of FOM). This refined hypothesis states that CBL turbulence can be considered as
result of a linear interpolation between the Gaussian and the very skewed turbulence regimes.
Although the extended universality hypothesis was confirmed by results of field
measurements, LES and DNS simulations (see e.g. [2-4]), several questions remained
unexplained. These are now answered by the new model including the reasons of the
universality of the functional form of the HOMs, the significant scatter of the values of the
coefficients and the source of the magic of the linear interpolation. Finally, the closures
61
predicted by the model are tested against measurements and LES data. Some of the other
issues of CBL turbulence, e.g. familiar kurtosis-skewness relationships and relation of area
coverage parameters of plumes (so called filling factors) with HOM will be discussed also
The Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric and oceanic flows: model formulation, recent developments, and future perspectives
In this paper we present the current version of the Parallelized Large-Eddy Simulation Model (PALM) whose core has been developed at the Institute of Meteorology and Climatology at Leibniz Universität Hannover (Germany). PALM is a Fortran 95-based 5 code with some Fortran 2003 extensions and has been applied for the simulation of a variety of atmospheric and oceanic boundary layers for more than 15 years. PALM is optimized for use on massively parallel computer architectures and was recently ported to general-purpose graphics processing units. In the present paper we give a detailed description of the current version of the model and its features, such as an embedded 10 Lagrangian cloud model and the possibility to use Cartesian topography. Moreover, we discuss recent model developments and future perspectives for LES applications.DFG/RA/617/3DFG/RA/617/6DFG/RA/617/16DFG/RA/617/27-
Multi-scale transport and exchange processes in the atmosphere over mountains. Programme and experiment
TEAMx is an international research programme that aims at improving the understanding of exchange processes in the atmosphere over mountains at multiple scales and at advancing the parameterizations of these processes in numerical models for weather and climate prediction–hence its acronyms stands for Multi-scale transport and exchange processes in the atmosphere over mountains – Programme and experiment. TEAMx is a bottom-up initiative promoted by a number of universities, research institutions and operational centres, internationally integrated through a Memorandum of Understanding between inter- ested parties. It is carried out by means of coordinated national, bi-national and multi-national research projects and supported by a Programme Coordination Office at the Department of Atmospheric and Cryospheric Sciences of the University of Innsbruck, Austria. The present document, compiled by the TEAMx Programme Coordination Office, provides a concise overview of the scientific scope of TEAMx. In the interest of accessibility and readability, the document aims at being self-contained and uses only a minimum of references to scientific literature. Greyboxes at the beginning of chapters list the literature sources that provide the scientific basis of the document. This largely builds on review articles published by the journal Atmosphere between 2018 and 2019, in a special issue on Atmospheric Processes over Complex Terrain. A few other important literature pieces have been referenced where appropriate. Interested readers are encouraged to examine the large body of literature summarized and referenced in these articles. Blue boxes have been added to most sub-chapters. Their purpose is to highlight key ideas and proposals for future collaborative research
Confronting Grand Challenges in environmental fluid mechanics
Environmental fluid mechanics underlies a wealth of natural, industrial and,
by extension, societal challenges. In the coming decades, as we strive towards
a more sustainable planet, there are a wide range of grand challenge problems
that need to be tackled, ranging from fundamental advances in understanding and
modeling of stratified turbulence and consequent mixing, to applied studies of
pollution transport in the ocean, atmosphere and urban environments. A workshop
was organized in the Les Houches School of Physics in France in January 2019
with the objective of gathering leading figures in the field to produce a road
map for the scientific community. Five subject areas were addressed: multiphase
flow, stratified flow, ocean transport, atmospheric and urban transport, and
weather and climate prediction. This article summarizes the discussions and
outcomes of the meeting, with the intent of providing a resource for the
community going forward
Center for Modeling of Turbulence and Transition (CMOTT). Research briefs: 1990
Brief progress reports of the Center for Modeling of Turbulence and Transition (CMOTT) research staff from May 1990 to May 1991 are given. The objectives of the CMOTT are to develop, validate, and implement the models for turbulence and boundary layer transition in the practical engineering flows. The flows of interest are three dimensional, incompressible, and compressible flows with chemistry. The schemes being studied include the two-equation and algebraic Reynolds stress models, the full Reynolds stress (or second moment closure) models, the probability density function models, the Renormalization Group Theory (RNG) and Interaction Approximation (DIA), the Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS)
Numerical methods for the unsteady incompressible Navier-Stokes equations and their application to the Direct Numerical Simulation of turbulent flows
Two new methods for the efficient parallel computation of the unsteady incompressible Navier-Stokes equations are presented. Such efficient methods are desired for large scale parallel computations of unsteady turbulent flows such as Direct Numerical Simulations (DNS). The performance of the new methods has a distinct advantage over the artificial compressibility method, in that the methods exhibit robust convergence for a variety of flow problems without extensive need for tuning computational parameters. These methods and others have been implemented in a computer program designed for massively parallel computer architectures, written by the author and used to obtain all results in this work. A DNS of a film-cooling jet is performed in order to evaluate the accuracy of the modeled expressions in the k-e turbulence model. Using the results of the DNS, the terms in the exact and modeled k-e equations are computed. These terms are examined to see where the models fail for these flows. DNS budgets for k and dissipation in a film cooling jet flow are presented to provide turbulence modelers with information as to where the models used to replace the exact k-e equations need improvement for this particular type of flow. A DNS of a pulsed jet is performed to analyze the effect of external pulsing on the flow structures and the resulting mixing of the jet with the crossflow. As the problem is inherently unsteady, the key to the successful prediction of such flows is the ability to resolve the dynamics of all important flow structures resulting from the interaction of the unsteady pulsed jet with the crossflow. In the present work massless particles are released into the flow at various locations. These particles are colored by their seed locations and residence time, greatly aiding the understanding of the dynamics of the flow. A new origin for the formation of the wake vortices has been discovered for both pulsed and unpulsed jets. Pulsing is shown to drastically change the jet spreading and penetration and to increase the mixing of the jet with the crossflow. A significant asymmetry affecting primarily the wake vortices has been found for certain cases
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