Geometrical statistics of the vorticity vector and the strain rate tensor in rotating turbulence

We report results on the geometrical statistics of the vorticity vector obtained from experiments in electromagnetically forced rotating turbulence. A range of rotation rates $\Omega$ is considered, from non-rotating to rapidly rotating turbulence with a maximum background rotation rate of $\Omega=5$ rad/s (with Rossby number much smaller than unity). Typically, in our experiments ${\rm{Re}}_{\lambda}\approx 100$. The measurement volume is located in the centre of the fluid container above the bottom boundary layer, where the turbulent flow can be considered locally statistically isotropic and horizontally homogeneous for the non-rotating case, see van Bokhoven et al., Phys. Fluids 21, 096601 (2009). Based on the full set of velocity derivatives, measured in a Lagrangian way by 3D Particle Tracking Velocimetry, we have been able to quantify statistically the effect of system rotation on several flow properties. The experimental results show how the turbulence evolves from almost isotropic 3D turbulence ($\Omega\lesssim 0.2$ rad/s) to quasi-2D turbulence ($\Omega\approx 5.0$ rad/s) and how this is reflected by several statistical quantities. In particular, we have studied the orientation of the vorticity vector with respect to the three eigenvectors of the local strain rate tensor and with respect to the vortex stretching vector. Additionally, we have quantified the role of system rotation on the self-amplification terms of the enstrophy and strain rate equations and the direct contribution of the background rotation on these evolution equations. The main effect is the strong reduction of extreme events and related (strong) reduction of the skewness of PDFs of several quantities such as, for example, the intermediate eigenvalue of the strain rate tensor and the enstrophy self-amplification term.Comment: 17 pages, 6 figures, 3 table

Accessing directly the properties of fundamental scalars in the confinement and Higgs phase

The properties of elementary particles are encoded in their respective propagators and interaction vertices. For a SU(2) gauge theory coupled to a doublet of fundamental complex scalars these propagators are determined in both the Higgs phase and the confinement phase and compared to the Yang-Mills case, using lattice gauge theory. Since the propagators are gauge-dependent, this is done in the Landau limit of 't Hooft gauge, permitting to also determine the ghost propagator. It is found that neither the gauge boson nor the scalar differ qualitatively in the different cases. In particular, the gauge boson acquires a screening mass, and the scalar's screening mass is larger than the renormalized mass. Only the ghost propagator shows a significant change. Furthermore, indications are found that the consequences of the residual non-perturbative gauge freedom due to Gribov copies could be different in the confinement and the Higgs phase.Comment: 11 pages, 6 figures, 1 table; v2: one minor error corrected; v3: one appendix on systematic uncertainties added and some minor changes, version to appear in EPJ

Applications of the PowerGlove

The hand is important in many daily life activities. During aging, quality of fine motor control of hand and fingers is decreasing. Also motor symptoms of the hand are important to define for instance the neurological state of a Parkinson’s disease patient. Although objective and reliable measurement of hand and finger dynamics is of interest, current measurement systems are limited. This paper describes the application of the PowerGlove, a new measurement system based on miniature inertial and magnetic sensors, to study the finger interdependency in healthy elderly and objectively quantify hand motor symptoms in Parkinson’s disease. Results of pilot experiments in young healthy subjects are shown to evaluate the feasibility of the applications

Feasibility studies for the measurement of time-like proton electromagnetic form factors from p¯ p→ μ+μ- at P ¯ ANDA at FAIR

This paper reports on Monte Carlo simulation results for future measurements of the moduli of time-like proton electromagnetic form factors, | GE| and | GM| , using the p¯ p→ μ+μ- reaction at P ¯ ANDA (FAIR). The electromagnetic form factors are fundamental quantities parameterizing the electric and magnetic structure of hadrons. This work estimates the statistical and total accuracy with which the form factors can be measured at P ¯ ANDA , using an analysis of simulated data within the PandaRoot software framework. The most crucial background channel is p¯ p→ π+π-, due to the very similar behavior of muons and pions in the detector. The suppression factors are evaluated for this and all other relevant background channels at different values of antiproton beam momentum. The signal/background separation is based on a multivariate analysis, using the Boosted Decision Trees method. An expected background subtraction is included in this study, based on realistic angular distributions of the background contribution. Systematic uncertainties are considered and the relative total uncertainties of the form factor measurements are presented

Advies voor richtlijnen voor het milieu-effectrapport Herinrichting Hurwenense uiterwaard

Contains fulltext : 57926.pdf (publisher's version ) (Open Access)11 p

An Integrated Spatial and Spectral Approach to the Classification of Mediterranean Land Cover Types: the SSC Method.

Classification of remotely sensed images is often based on assigning classes on a pixel by pixel basis. Such a classification ignores often useful reflectance information in neighbouring pixels. Open types of natural land cover such as maquis and garrigue ecosystems as found in the Mediterranean region may be classified successfully by methods accounting for reflectance patterns in neighbouring pixels. Classification methods capturing neighbouring pixel information are referred to as contextual classifiers. In this paper a new method, the spatial and spectral classifier or SSC is proposed that combines the advantages of two classification methods based on spectral information and on contextual information from neighbouring pixels. The SSC method starts by dividing a hyperspectral image into homogeneous and heterogeneous regions based on spectral variation of pixels within a kernel. Next, the homogeneous image parts are classified using a conventional per-pixel method. The heterogeneous image sections are classified using a combination of spectral and contextual information. The method was tested and the accuracy assessed using airborne DAIS7915 hyperspectral images acquired over an area in southern France covered by semi-natural vegetation, agricultural fields and open mining activities. Classification accuracy is compared with results of purely spectral classifiers. Results were promising and indicate that the accuracy of the SSC classifier was higher than that of the conventional per-pixel classifiers

An Integrated Spatial and Spectral Approach to the Classification of Mediterranean Land Cover Types: the SSC Method.

Classification of remotely sensed images is often based on assigning classes on a pixel by pixel basis. Such a classification ignores often useful reflectance information in neighbouring pixels. Open types of natural land cover such as maquis and garrigue ecosystems as found in the Mediterranean region may be classified successfully by methods accounting for reflectance patterns in neighbouring pixels. Classification methods capturing neighbouring pixel information are referred to as contextual classifiers. In this paper a new method, the spatial and spectral classifier or SSC is proposed that combines the advantages of two classification methods based on spectral information and on contextual information from neighbouring pixels. The SSC method starts by dividing a hyperspectral image into homogeneous and heterogeneous regions based on spectral variation of pixels within a kernel. Next, the homogeneous image parts are classified using a conventional per-pixel method. The heterogeneous image sections are classified using a combination of spectral and contextual information. The method was tested and the accuracy assessed using airborne DAIS7915 hyperspectral images acquired over an area in southern France covered by semi-natural vegetation, agricultural fields and open mining activities. Classification accuracy is compared with results of purely spectral classifiers. Results were promising and indicate that the accuracy of the SSC classifier was higher than that of the conventional per-pixel classifiers