Array Of Velocity Sensors Research Articles

Bluff body uses deep-reinforcement-learning trained active flow control to achieve hydrodynamic stealth

We propose a novel active-flow-control strategy for bluff bodies to hide their hydrodynamic traces, i.e., strong shears and periodically shed vortices, from predators. A group of windward-suction-leeward-blowing (WSLB) actuators are adopted to control the wake of a circular cylinder submerged in a uniform flow. An array of velocity sensors is deployed in the near wake to provide feedback signals. Through the data-driven deep reinforcement learning, effective control strategies are trained for the WSLB actuation to mitigate the cylinder's hydrodynamic signatures. Only a 0.29% deficit in streamwise velocity is detected, which is a 99.5% reduction from the uncontrolled value. The same control strategy is found also to be effective when the cylinder undergoes transverse vortex-induced vibration. The findings from this study can shed some light on the design and operation of underwater structures and robotics to achieve hydrodynamic stealth.

Time-domain flexural wave intensity estimation in orthotropic Kirchhoff plates

In this paper, a method for estimating the vibrational energy flow associated with the flexural vibration of an orthotropic Kirchhoff plate, in the time-domain, is presented. The approach is based on the plane propagating wave solution to the equation of motion, and uses a Fourier series approximation of the wave field. The various linear and angular velocities, shear forces and moments that are needed to calculate the energy flow are estimated by digitally filtering and combining the outputs of an array of sensors. A similar approach is used to reconstruct the local wave field to provide an estimate of the wave propagation direction.The theoretical basis of the approach is described, and design considerations for the sensor array and for the filters used for parameter estimation are discussed. Simulations are presented for plane flexural waves and for transient transverse point force excitation of a range of orthotropic plates having different material properties, using a simulated array of velocity sensors. These simulations show that the method can provide accurate estimates of the magnitude and direction of the vibrational energy flow, as well as of the propagation direction of a single wave train or ‘burst’, provided that the sensor array is sufficiently distant from the excitation point. This is consistent with preliminary experimental measurements, also presented in this paper, performed on a composite orthotropic plate.

Spatial Scales of Stress-Carrying Nearshore Turbulence*

Measurements from a horizontal array of velocity sensors indicate that the alongshore scales of turbulence contributing to the near-bottom Reynolds stress just seaward of the surf zone on an ocean beach range from 0 to approximately 4 times the height of the measurements above the seafloor, with shorter scales during stable stratification than during neutral or unstable stratification. The dependence of alongshore turbulence scales on the stratification, Reynolds stress, and height above the bottom is consistent with semiempirical results from the atmospheric surface layer, implying similar dynamics of near-boundary turbulence in the atmosphere and the shallow coastal ocean.

Directivity factors for linear arrays of velocity sensors

Some of the features unique to beamforming a linear array of acoustic velocity sensors, which are not present with scalar-sensing elements (such as conventional pressure sensors), are described in this paper. Four types of sensors are considered here: a uniaxial motion sensor, which measures acoustic particle velocity along a single axis; a biaxial motion sensor measuring velocity in two orthogonal directions; a triaxial motion sensor that measures all three orthogonal components of the velocity vector; and a sensor, denoted as an acoustic vector sensor, that measures acoustic pressure as well as the complete velocity vector. Comparisons are made of the directivity index for each type of sensor and for linear arrays of sensors. It is shown that uniaxial velocity sensors can have a maximum directivity factor three times greater than an omnidirectional pressure sensor, a gain in directivity index of 4.8 dB. Not surprisingly, this directivity gain is highly dependent on signal arrival direction. Indeed, a uniaxial velocity sensor’s directivity can be less than that of an omnidirectional pressure, indicative of a loss in signal level. These comparisons further indicate that a single vector sensor can provide 6 dB of directivity gain, four times the directivity of a pressure sensor. Line arrays of directional sensors can have a directivity index approximately 5 dB greater than that of an identical line array of pressure sensors for approximately all azimuthal array steerings.