Silicon on Nothing Mems Electromechanical Resonator

The very significant growth of the wireless communication industry has spawned tremendous interest in the development of high performances radio frequencies (RF) components. Micro Electro Mechanical Systems (MEMS) are good candidates to allow reconfigurable RF functions such as filters, oscillators or antennas. This paper will focus on the MEMS electromechanical resonators which show interesting performances to replace SAW filters or quartz reference oscillators, allowing smaller integrated functions with lower power consumption. The resonant frequency depends on the material properties, such as Young's modulus and density, and on the movable mechanical structure dimensions (beam length defined by photolithography). Thus, it is possible to obtain multi frequencies resonators on a wafer. The resonator performance (frequency, quality factor) strongly depends on the environment, like moisture or pressure, which imply the need for a vacuum package. This paper will present first resonator mechanisms and mechanical behaviors followed by state of the art descriptions with applications and specifications overview. Then MEMS resonator developments at STMicroelectronics including FEM analysis, technological developments and characterization are detailed.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/EDA-Publishing

Estimating Mean Bedload Transport Rates and Their Uncertainty

Measuring bedload transport rates usually involves measuring the flux of sediment or collecting sediment during a certain interval of time Δt. Because bedload transport rates exhibit significant non‐Gaussian fluctuations, their time‐averaged rates depend a great deal on Δt. We begin by exploring this issue theoretically within the framework of Markov processes. We define the bedload transport rate either as the particle flux through a control surface or as a quantity related to the number of moving particles and their velocities in a control volume. These quantities are double averaged; that is, we calculate their ensemble and time averages. Both definitions lead to the same expression for the double‐averaged mean rate and to the same scaling for the variance's dependence on the length of the sampling duration Δt. These findings lead us to propose a protocol for measuring double‐averaged transport rates. We apply this protocol to an experiment we ran in a narrow flume using steady‐state conditions (constant water discharge and sediment feed rates), in which the time variations in the particle flux, the number of moving particles, and their velocities were measured using high‐speed cameras. The data agree well with the previously defined theoretical relationships. Lastly, we apply our experimental protocol to other flow conditions (a long laboratory flume and a gravel‐bed river) to show its potential across various contexts

Measuring bedload transport rates in a laboratory flume: fluctuations and uncertainties

&amp;lt;p&amp;gt;Measuring sediment fluxes in rivers and laboratory flumes has long been a challenge. Different definitions of sediment transport rates have been proposed over the past decades. Most measurement techniques involve collecting a volume of sediment in a sampler or counting the number of particles crossing a reference section within a given time interval. In laboratory experiments, scientists routinely use high-speed cameras and particle tracking techniques for monitoring bedload transport, but measuring the relevant transport parameters (i.e. the number of moving particles, their velocities and size, etc.) remains a demanding task. Moreover, no clear consensus has emerged on how to define mean bedload transport rates. To address this controversy, we ran an experiment in which we measured the particle flux in different places along a flume using high-speed cameras. Furthermore, we also determined the number of particles moving in a fixed control volume, their trajectories, and their velocities. Even under steady-state conditions, particle transport rates exhibited significant non-Gaussian fluctuations, which caused the time-averaged transport rate to fluctuate widely. In such a situation, determining the mean transport rate becomes a non-trivial operation. To solve this issue, we developed a procedure for estimating the uncertainties associated with the time-averaged transport rates. The theoretical underpinnings are provided by a Markovian model of bedload transport. We demonstrated its versatility by applying it to other laboratory and field cases with different monitoring systems.&amp;lt;/p&amp;gt; </jats:p

Shallow flows of generalised Newtonian fluids on an inclined plane

We derive a general evolution equation for a shallow layer of a generalised Newtonian fluid undergoing two-dimensional gravity-driven flow on an inclined plane. The flux term appearing in this equation is expressed in terms of an integral involving the prescribed constitutive relation and, crucially, does not require explicit knowledge of the velocity profile of the flow; this allows the equation to be formulated for any generalised Newtonian fluid. In particular, we develop general solutions for travelling waves on a mild slope and for kinematic waves on a moderately steep slope; these results provide simple and accessible models of, for example, the propagation of non-Newtonian mud and debris flows

How bar generate sediment transport pulses in gravel-bed channels

We ran flume experiments with constant water dis- charge and sediment feed rate at the inlet. Experi- ments were conducted over long times (typically 600 h). The bars migrated downstream intermittently, producing the most important pulses. When the bar position was stable for a few hours, additional pulses resulted from sediment transfer from pool to pool, in the form of sediment waves (bedload sheets)