237 research outputs found
Corrigendum: Comparison of three dielectric barrier discharges regarding their physical characteristics and influence on the adhesion properties of maple, high density fiberboard and wood plastic composite (2017 <i>J. Phys. D: Appl. Phys</i>. <b>50</b> 475206)
No full textComparison of three dielectric barrier discharges regarding their physical characteristics and influence on the adhesion properties on maple, high density fiberboards and wood plastic composite
No full text
Determination of view vectors from image warping mapping functions
No full textThe measurands of several reported laser-based measurement techniques are
sensitive to both the propagation direction of the laser and the viewing
direction from the region of interest to the detector. For such imaging
techniques, the view vector must be determined uniquely for each pixel in the
detector array. The bulk view vector is often physically measured and a simple
model used to determine the view vector for each pixel. This, however, has
limitations where access is limited, the distances involved are small, or the
optical system employed introduces errors. We describe a procedure to determine
the unique view vector from a planar region to the detector (CCD camera) for
each element in a 2-D array based on a reference target aligned with the planar
region of interest. Determination of the view vector is based on the spatial
distribution of the mapping function used to dewarp the view. No physical
measurement of the view vector is required. Good agreement is achieved when the
procedure is compared to a simple pin-hole camera model of the view using a
computed test target. (C) 2004 Society of Photo-Optical Instrumentation
Engineers
The flow field at the outlet of a pulsed jet under different periodic signals
No full textAachen, German
Narrow species concepts in the Frullania dilatata–appalachiana–eboracensis complex (Porellales, Jungermanniopsida): evidence from nuclear and chloroplast DNA markers
No full textWe investigated the phylogeny of a Holarctic-Asian group of Frullania species, the Frullania dilatata-F. appalachiana F. eboracensis complex, using multiple accessions of morphologically circumscribed taxa and three molecular markers (nrITS region, cp DNA trnL-F and atpB-rbcL regions). Maximum parsimony and likelihood analyses indicated monophyly of morphologically defined taxa. Our phylogenies support a species rather than a subspecies concept within the complex, with four species in North America (F. appalachiana, F. eboracensis, F. parvistipula and F. virginica), and two species in Europe (F. dilatata and F. parvistipula). Accessions of F. dilatata from Southeast Europe and Asia are separated from other European accessions, indicating a former disjunct range of the species
PIV Uncertainty Quantification and Beyond
No full textThe fundamental properties of computed flow fields using particle imaging velocimetry (PIV) have been investigated, viewing PIV processing as a black box without going in detail into algorithmic details. PIV processing can be analyzed using a linear filter model, i.e. assuming that the computed displacement field is the result of some spatial filtering of the underlying true flow field given a particular shape of the filter function. From such a mathematical framework, relationships are derived between the underlying filter function, wavelength response function (MTF) and response to a step function, power spectral density, and spatial autocorrelation of filter function and noise.A definition of a spatial resolution is provided independent of some arbitrary threshold e.g of the wavelength response function and provides the user with a single number to appropriately set the parameters of the PIV algorithm required for detecting small velocity fluctuations.The most important error sources in PIV are discussed and an uncertainty quantification method based on correlation statistics is derived, which has been compared to other available UQ-methods in two recent publications (Sciacchitano et al. 2015; Boomsma et al. 2016) showing good sensitivity to a variety of error sources. Instantaneous local velocity uncertainties are propagated for derived instantaneous and statistical quantities like vorticity, averages, Reynolds stresses and others. For Stereo-PIV the uncertainties of the 2C-velocity fields of the two cameras are propagated into uncertainties of the computed final 3C-velocity field.A new anisotropic denoising scheme as a post-processing step is presented which uses the uncertainties comparing to the local flow gradients in order to devise an optimal filter kernel for reducing the noise without suppressing true small-scale flow fluctuations.For Stereo-PIV and volumetric PIV/PTV, an accurate perspective calibration is mandatory. A Stereo-PIV self-calibration technique is described to correct misalignment between the actual position of the light sheet and where it is supposed to be according to the initial calibration procedure. For volumetric PIV/PTV, a volumetric self-calibration (VSC) procedure is presented to correct local calibration errors everywhere in the measurement volume.Finally, an iterative method for reconstructing particles (IPR) in a volume is developed, which is the basis for the recently introduced Shake-the-Box (STB) technique (Schanz et al. 2016).Aerodynamic
A super-resolution approach for uncertainty estimation of PIV measurements
No full textA super-resolution approach is proposed for the a posteriori uncertainty estimation of PIV measurements. The measured velocity field is employed to determine the displacement of individual particle images. A disparity set is built from the residual distance between paired particle images of successive recordings. Within each interrogation window, the disparity set is treated with a statistical analysis to infer the measurement uncertainty: the mean disparity is ascribed to bias errors due to poor particle image sampling or spatial modulation effect; the dispersion of the set is related to precision errors, mainly due to random noise in the recordings and to errors in the PIV interrogation. The performance of the estimator is first assessed via Monte Carlo simulation on a uniform flow field with varying out-of-plane displacement. The uncertainty is accurately estimated in optimal imaging condition, while it is underestimated when the imaging conditions are suboptimal. The experimental assessment is conducted on a water jet experiment. For evaluating the performance of the estimator, the actual measurement error is computed as the difference between measured and a reference displacement field; the latter is built with an advanced processing algorithm that exploits the time redundancy of highly oversampled data to reduce the error of one order of magnitude. The capability of the super-resolution technique to quantify the uncertainty within 0.1 px accuracy is proven.Aerodynamics, Wind Energy and PropulsionAerospace Engineerin
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