Dadun Community:http://hdl.handle.net/10171/1222016-05-29T23:02:48Z2016-05-29T23:02:48ZStochastic dynamics of particles trapped in turbulent flowshttp://hdl.handle.net/10171/401642016-05-11T11:38:08Z2016-01-01T00:00:00ZTitle: Stochastic dynamics of particles trapped in turbulent flows
Abstract: The long-time dynamics of large particles trapped in two nonhomogeneous turbulent shear flows is studied
experimentally. Both flows present a common feature, a shear region that separates two colliding circulations,
but with different spatial symmetries and temporal behaviors. Because large particles are less and less sensitive
to flow fluctuations as their size increases, we observe the emergence of a slow dynamics corresponding to
back-and-forth motions between two attractors, and a super-slow regime synchronized with flow reversals when
they exist. Such dynamics is substantially reproduced by a one-dimensional stochastic model of an overdamped
particle trapped in a two-well potential, forced by a colored noise. An extended model is also proposed that
reproduces observed dynamics and trapping without potential barrier: the key ingredient is the ratio between the
time scales of the noise correlation and the particle dynamics. A total agreement with experiments requires the
introduction of spatially nonhomogeneous fluctuations and a suited confinement strength.2016-01-01T00:00:00ZErgodic-nonergodic transition in tapped granular systems: the role of persistent contactshttp://hdl.handle.net/10171/397702016-03-18T09:44:28Z2016-01-01T00:00:00ZTitle: Ergodic-nonergodic transition in tapped granular systems: the role of persistent contacts
Abstract: Static granular packs have been studied in the last three decades in the frame of a modified equilibrium statistical mechanics that assumes ergodicity as a basic postulate. The canonical example on which this framework is tested consists in the series of static configurations visited by a granular column subjected to taps. By analyzing the response of a realistic model of grains, we demonstrate that volume and stress variables visit different regions of the phase space at low tap intensities in different realizations of the experiment. We show that the tap intensity beyond which sampling by tapping becomes ergodic coincides with the forcing necessary to break all particle-particle contacts during each tap. These results imply that the well-known "reversible" branch of tapped granular columns is only valid at relatively high tap intensities.2016-01-01T00:00:00ZExperimental evidence of the faster is slower effecthttp://hdl.handle.net/10171/396452016-03-22T09:52:32Z2014-01-01T00:00:00ZTitle: Experimental evidence of the faster is slower effect
Abstract: The Faster-Is-Slower effect (Helbing et al (2000)) is an important instance of self-organized phenomenon in pedestrian dynamics.
Despite this, an experimental demonstration is still lacking. We present controlled tests where a group of students are asked to
exit a room through a door. Instead of just measuring the evacuation times, we have analyzed the probability distribution of the
time lapses between consecutive individuals. We show how it displays a power-law tail. This method displays clearly the Faster
Is Slower effect, and also allows to assess the impact of several tactics that can be put in place to alleviate the problem.2014-01-01T00:00:00ZComplexity measures for multi-dimensional and chaotical sources of informationhttp://hdl.handle.net/10171/394612016-03-22T09:38:39Z2015-01-01T00:00:00ZTitle: Complexity measures for multi-dimensional and chaotical sources of information
Abstract: Abstract. We apply a modified LMC complexity measure to an information
source. The source is modeled by two identical Takens-Bogdanov equations
synchronized, bi-directionally coupled and perturbed by a harmonic signal. In this
system, when the frequency of the signal is tuned the complexity of the system
changes. The aim of the work is to show that with a modification on the
interpretation of the LMC measure, we can obtain an extensive measure that can
be applied to measure the complexity of completely unknown systems. As an
example, we apply this procedure to a high-dimensional system with chaotical
behavior.2015-01-01T00:00:00Z