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We present an experimental study of velocity statistics for a partial layer of inelastic colliding beads driven by a vertically oscillating boundary. Over a wide range of parameters (accelerations 3-8 times the gravitational acceleration), the probability distribution P (v) deviates measurably from a Gaussian for the two horizontal velocity components. It can be described by P (v) ∼ exp(−|v/v c | 1.5 ), in agreement with a recent theory. The characteristic velocity v c is proportional to the peak velocity of the boundary. The granular temperature, defined as the mean square particle velocity, varies with particle density and exhibits a maximum at intermediate densities. On the other hand, for free cooling in the absence of excitation, we find an exponential velocity distribution. Finally, we examine the sharing of energy between particles of different mass. The more massive particles are found to have greater kinetic energy. PACS: 83.70.Fn, 05.20.Dd, 83.10.Pp Typeset using REVT E X 1 We determine the statistical properties of particles in a vibrated granular medium experimentally. While many similarities between ordinary gases and excited granular media have been found, a fundamental difference is that collisions between particles in granular matter are inelastic. As a consequence, the velocity distribution deviates measurably from a Gaussian, but can be described by P (v) ∼ exp(−|v/v c | 1.5 ) for a large range of parameters where external excitation is sufficiently frequent, in agreement with a recent theory.

A partial monolayer of approximately 20 000 uniform spherical steel beads, vibrated vertically on a flat plate, shows remarkable ordering transitions and cooperative behavior just below 1g maximum acceleration. We study the stability of a quiescent disordered or "amorphous" state formed when the acceleration is switched off in the excited "gaseous" state. The transition from the amorphous state back to the gaseous state upon increasing the plate's acceleration is generally subcritical: An external perturbation applied to one bead initiates a propagating front that produces a rapid transition. We measure the front velocity as a function of the applied acceleration. This phenomenon is explained by a model based on a single vibrated particle with multiple attractors that is perturbed by collisions. A simulation shows that a sufficiently high rate of interparticle collisions can prevent trapping in the attractor corresponding to the nonmoving ground state.

Axial-flow-induced vibration has been experimentally investigated with clamped-free cantilevered cylindrical rods confined in a tube and subjected to axial water flow directed from the rod free-end towards the clamped end: a simplified configuration relevant for water-cooled nuclear reactor cores. Non-contact optical techniques have been used to simultaneously detect the rods vibration and the flow field around the vibrating rods free-end. The source of excitation is turbulent buffeting at low flow velocity, while a movement induced excitation component is present at large flow velocities. The rods flow-induced vibration consists of a fuzzy period-1 motion: a periodic (period-1) motion with a chaotic component that increases in relative importance as the flow velocity is increased. The experimental data provided here are particularly suited for numerical fluid-structure model development and benchmarking, as they combine a rich fluid-structure multi-physics interaction with a relatively simple configuration and include both the flow field and the mechanical response of the vibrating rods.

Original article can be found at: http://www.pepublishing.com/ Copyright Professional Engineering Publishing [Full text of this article is not available in the UHRA]Online or inline detection of basic debris features, i.e. size, quantity, size distribution, shape, and compositions simultaneously With real time diagnostics is one of the possible ways to perform Wear debris analysis with high reliability. At present many techniques and sensors are available that can perform near real time detection and diagnostics for debris quantitative features. But to perform real time detection and diagnostics for features like shape and composition still requires a reliable technical concept. In this article a new technique for online wear debris shape and composition analysis is described. The developed technique is a combination of hardware and software based oil imaging technology for shape and composition detection. Rule-based algorithms are used to perform near real time debris analysis diagnostics. An experimental study is also presented that shows the possible potential of the developed technique on real applications