J. Nogueira

Data validation, false vectors correction and derived magnitudes calculation on PIV data

Due to the particular features that appear in the vector maps delivered by the PIV method, there are postprocessing steps that can substantially enhance its performance. These steps include: detection of false vectors, correction of these vectors and the calculation of derived flow magnitudes. Many derived magnitudes can be of interest but this work focuses on the calculation of the first spatial derivative, component of flow divergence or vorticity, on a two-dimensional flow configuration. New algorithms, developed for each step, are described, with the aim of jointly applying them in a coherent way. Where applicable, an analytical tool for filter analysis and design is explained. Application to synthetic and real PIV data is presented as well as a performance contrast with other conventional algorithms, in terms of accuracy, frequency response and error propagation, among others.

Local field correction PIV, implemented by means of simple algorithms, and multigrid versions

Local field correction particle image velocimetry (LFCPIV), which was first presented in 1997, is the only correlation PIV method able to resolve flow structures smaller than the interrogation window. It presents advantages over conventional systems and thus offers an alternative in the field of super-resolution methods. Improvements of the initial version are likely to promote its application even further. The issues defining some of these possible improvements were already indicated in the paper that originally introduced LFCPIV, but not developed. This work presents refinements and also simplifications of the technique, so that it can be applied using current algorithms of advanced correlation PIV systems. Furthermore, these refinements reduce the measurement error and enlarge the range of application of LFCPIV. In particular, the application of the system is no longer constrained to images with mean distances between particles larger than 4 pixels. Besides that, the use of interrogation windows smaller than in its previous version is evaluated. This allows multigrid LFCPIV implementations. The results show how multigrid LFCPIV can obtain better measurements than can the usual multigrid PIV, but still the refined version of the LFCPIV technique performs even better, at the expense of a larger computing time. The performance of these methods is evaluated for synthetic and real images. This includes examples in which the ability to cope with gradients in velocity, gradients in seeding density and the presence of boundaries is highlighted.

Analysis and alternatives in two-dimensional multigrid particle image velocimetry methods: application of a dedicated weighting function and symmetric direct correlation

Multigrid particle image velocimetry (PIV) is an open path in the search for high-resolution PIV methods. It is based on an iterative scheme that uses the information of initial processing to adapt the method parameters in order to improve the measurements. This is mainly performed by reducing the size of the interrogation windows and shifting them. In multigrid PIV, two sources of error can significantly affect the final measurement quality: (1) the error coming from the amplitude response of the initial large interrogation windows to spatial frequencies; (2) the error originating from the truncation of particles at the borders of the final small interrogation windows. By applying weighting functions and using symmetric direct correlation both errors can be reduced, respectively. These techniques have been separately tested in the past, but a joint implementation has not yet been analysed. This task is fulfilled and both sources of error are further clarified. For this purpose, a one-dimensional single wavelength displacement field is used. This gives us the opportunity to analyse the non-linear behaviour of PIV, together with the influence of basic parameters on it. In addition to this, the multigrid method, so far described, is enhanced by compensation of the particle pattern deformation. The metrological performance of this advanced method is tested using synthetic images and the results are compared with those delivered by established PIV methods. Coherence between these results and those obtained in a real image is also detailed.

PIV evaluation algorithms for industrial applications

Particle image velocimetry (PIV) is now applied with confidence in industrial facilities such as large wind tunnels, yielding data not possible before. Despite the difficulties that arise in such environments, the conventional PIV methods can provide high quality data, especially when dealing with spatial and temporal slowly varying values of the flow magnitudes. Obtaining highly spatially resolved velocity fields is still challenging due to the inherent difficulties in these industrial facilities, such as large velocity gradients, background light and reflections. This work has focused on: (i) the behaviour of conventional PIV when the conventional limits of the processing algorithm are approached or surpassed and (ii) which kind of advanced methods can reduce the main sources of error that are characterized in this paper. The focus is on the description of vortex flows. Group locking, a major source of error, is introduced, modelled and metrologically characterized. The part of the study devoted to advanced methods deals with one that has already shown to be of profit in images from industrial facilities, local field correction PIV (LFC-PIV). This is a robust and an accurate method, able to obtain a high yield of measurements in these environments, without the need of external adjustment to each particular situation. To illustrate this point, some examples of processing of real images are given. The conclusions of this work suggest guidelines about the error figures when measuring flows with embedded vortex using conventional and advanced methods in industrial facilities.

Multiple Δt strategy for particle image velocimetry (PIV) error correction, applied to a hot propulsive jet

PIV (particle image velocimetry) is a measurement technique with growing application to the study of complex flows with relevance to industry. This work is focused on the assessment of some significant PIV measurement errors. In particular, procedures are proposed for estimating, and sometimes correcting, errors coming from the sensor geometry and performance, namely peak-locking and contemporary CCD camera read-out errors. Although the procedures are of general application to PIV, they are applied to a particular real case, giving an example of the methodology steps and the improvement in results that can be obtained. This real case corresponds to an ensemble of hot high-speed coaxial jets, representative of the civil transport aircraft propulsion system using turbofan engines. Errors of ~0.1 pixels displacements have been assessed. This means 10% of the measured magnitude at many points. These results allow the uncertainty interval associated with the measurement to be provided and, under some circumstances, the correction of some of the bias components of the errors. The detection of conditions where the peak-locking error has a period of 2 pixels instead of the classical 1 pixel has been made possible using these procedures. In addition to the increased worth of the measurement, the uncertainty assessment is of interest for the validation of CFD codes.

Simulation of Particle Trajectories in a Vortex-Induced Flow: Application to Seed-Dependent Flow Measurement Techniques

The trajectories of heavy particles (ρparticle/ρfluid>>1) are simulated in a two-dimensional free vortex flow. The results show that heavy particles, even with small diameters, cannot properly trace the fluid and develop a centrifugal motion. This behaviour leads to a rapid depletion of particles in the vortex core, which, in seed-dependent measurements such as particle image velocimetry (PIV) or laser Doppler velocimetry, produces a marked increase in measurement errors. Some examples are given and the evolution of the local concentration of particles is simulated. Synthetic images have been generated using the information about its motion in a two-dimensional free vortex flow. A wing-tip vortex is simulated, showing good agreement with experimental results present in the literature. Standard PIV measurements have been performed over the synthetic images, showing the effect of core depletion of particles on the incidence of erroneous measurements.

Analysis of the Vortex Street Generatedat the Core-Bypass Lip of a Jet-Engine Nozzle

The reduction of the noise generated by jet-engine aircrafts is of growing concern in the present society. A better understanding of the aircraft noise production and the development of predictive tools is of great interest. Within this framework, the CoJeN (Coaxial Jet Noise) European Project includes the measurement of the flow field and the noise generated by typical turbofan jet-engine nozzles. One of the many aspects of interest is the occasional presence of acoustic tones of a defined frequency, symptomatic of the presence of quasiperiodic coherent structures within the flow. This chapter analyzes the characteristics of a vortex street in the core-bypass lip of one of the nozzles under study. The measurements were made by means of advanced PIV techniques within the above-mentioned project.

Flowfield Vorticity Calculation using PIV Data

The simultaneous velocity measurement at different flowfield locations is one of the key advantages of a PIV system. This allows a straightforward calculation of derived flow magnitudes including spatial correlations. Thus, postprocessing techniques need further attention in order to assure maximum feature extraction with minimum error, among other issues. This paper is devoted to expand the capability of calculating vorticity in a PIV sampled flow field. The methodology proposed is based on linear algorithms (FIR filters) able to obtain the first spatial derivative of a grid sampled magnitude containing random noise. Generalization to other flow magnitudes based on spatial derivatives is immediate. Been this a widely used method, the main objective of the study is to develop new filters from families already documented. The relevant performance parameters of these filters are evaluated and commented. Synthetic data fields are used to test the basic metrological attributes in a controlled way. As a result of the study, algorithms with better performances than the usual ones are proposed and strong points are highlighted. Finally, results of the application to real PIV data are exhibited and commented.

PIV measurements in co—flowing jets subjected to axial forcing. Vorticity and strain field structure

A study of the evolving shear layer in the near field of ReD=7000, co-flowing water jets is presented. The inner jet is subjected to a strong axial forcing and to a small, controlled azimuthal perturbation. This flow configuration is characterised by a strong lateral expansion of the inner jet in the near field, controlled by the forcing parameters. Instantaneous, whole-field, 2D velocity measurements were obtained, using the Digital Particle Image Velocimetry (DPIV) technique. The two-component velocity measurements allows for the computation of fields of azimuthal vorticity and strain in a plane. These parameters control the inviscid dynamics of the structures of azimuthal vorticity that dominates the near field evolution of the flow. The combined information of these flow parameters provides a deep insight in the flow nature and evolution.

CCD image sensor induced error in PIV applications

The readout procedure of charge-coupled device (CCD) cameras is known to generate some image degradation in different scientific imaging fields, especially in astrophysics. In the particular field of particle image velocimetry (PIV), widely extended in the scientific community, the readout procedure of the interline CCD sensor induces a bias in the registered position of particle images. This work proposes simple procedures to predict the magnitude of the associated measurement error. Generally, there are differences in the position bias for the different images of a certain particle at each PIV frame. This leads to a substantial bias error in the PIV velocity measurement (~0.1 pixels). This is the order of magnitude that other typical PIV errors such as peak-locking may reach. Based on modern CCD technology and architecture, this work offers a description of the readout phenomenon and proposes a modeling for the CCD readout bias error magnitude. This bias, in turn, generates a velocity measurement bias error when there is an illumination difference between two successive PIV exposures. The model predictions match the experiments performed with two 12-bit-depth interline CCD cameras (MegaPlus ES 4.0/E incorporating the Kodak KAI-4000M CCD sensor with 4 megapixels). For different cameras, only two constant values are needed to fit the proposed calibration model and predict the error from the readout procedure. Tests by different researchers using different cameras would allow verification of the model, that can be used to optimize acquisition setups. Simple procedures to obtain these two calibration values are also described.