Laminar to turbulent flow transition measurements using an array of SOI-CMOS MEMS wall shear stress sensors

The successful utilization of an array of silicon on insulator complementary metal oxide semiconductor (SOICMOS) micro thermal shear stress sensors for flow measurements at macro-scale is demonstrated. The sensors use CMOS aluminum metallization as the sensing material and are embedded in low thermal conductivity silicon oxide membranes. They have been fabricated using a commercial 1 μm SOI-CMOS process and a post-CMOS DRIE back etch. The sensors with two different sizes were evaluated. The small sensors (18.5 ×18.5 μm2 sensing area on 266 × 266 μm2 oxide membrane) have an ultra low power (100 °C temperature rise at 6mW) and a small time constant of only 5.46 μs which corresponds to a cut-off frequency of 122 kHz. The large sensors (130 × 130 μm2 sensing area on 500 × 500 μm2 membrane) have a time constant of 9.82 μs (cut-off frequency of 67.9 kHz). The sensors' performance has proven to be robust under transonic and supersonic flow conditions. Also, they have successfully identified laminar, separated, transitional and turbulent boundary layers in a low speed flow. © 2008 IEEE.

Characterization of nano-composite M-2411/Y-123 thin films by electron backscatter diffraction and in-field critical current measurements

Thin films of nano-composite Y-Ba-Cu-O (YBCO) superconductors containing nano-sized, non-superconducting particles of Y2Ba 4CuMOx (M-2411 with M = Ag and Nb) have been prepared by the PLD technique. Electron backscatter diffraction (EBSD) has been used to analyze the crystallographic orientation of nano-particles embedded in the film microstructure. The superconducting YBa2Cu3O7 (Y-123) phase matrix is textured with a dominant (001) orientation for all samples, whereas the M-2411 phase exhibits a random orientation. Angular critical current measurements at various temperature (T) and applied magnetic field (B) have been performed on thin films containing different concentration of the M-2411 second phase. An increase in critical current density J c at T < 77 K and B < 6 T is observed for samples with low concentration of the second phase (2 mol % M-2411). Films containing 5 mol % Ag-2411 exhibit lower Jc than pure Y-123 thin films at all fields and temperatures. Samples with 5 mol % Nb-2411 show higher Jc(B) than phase pure Y-123 thin films for T < 77 K. © 2010 IOP Publishing Ltd.

Geometrical properties and turbulent flame speed measurements in stationary premixed V-flames using direct numerical simulation

Three dimensional, fully compressible direct numerical simulations (DNS) of premixed turbulent flames are carried out in a V-flame configuration. The governing equations and the numerical implementation are described in detail, including modifications made to the Navier-Stokes Characteristic Boundary Conditions (NSCBC) to accommodate the steep transverse velocity and composition gradients generated when the flame crosses the boundary. Three cases, at turbulence intensities, u′/sL, of 1, 2, and 6 are considered. The influence of the flame holder on downstream flame properties is assessed through the distributions of the surface-conditioned displacement speed, curvature and tangential strain rates, and compared to data from similarly processed planar flames. The distributions are found to be indistinguishable from planar flames for distances greater than about 17δth downstream of the flame holder, where δth is the laminar flame thermal thickness. Favre mean fields are constructed, and the growth of the mean flame brush is found to be well described by simple Taylor type diffusion. The turbulent flame speed, sT is evaluated from an expression describing the propagation speed of an isosurface of the mean reaction progress variable c̃ in terms of the imbalance between the mean reactive, diffusive, and turbulent fluxes within the flame brush. The results are compared to the consumption speed, sC, calculated from the integral of the mean reaction rate, and to the predictions of a recently developed flame speed model (Kolla et al., Combust Sci Technol 181(3):518-535, 2009). The model predictions are improved in all cases by including the effects of mean molecular diffusion, and the overall agreement is good for the higher turbulence intensity cases once the tangential convective flux of c̃ is taken into account. © 2010 Springer Science+Business Media B.V.

Morphometric measurements as an index for estimating yield of meat in shell fishes, 2. Mussel (Perna viridis) and clam (villorita cyprinoides)

Observations (76 nos) on height-length and whole weight-meat weight relations of mussels (Perna viridis), both wild and cultured were made. From the length of mussel the height can be worked out by the equations (logarithmic scale), 1. y = 0.360+0.988 x for wild; 2. y = 0.334+1.011 x for cultured, where x is the length (cm) and y is the height (cms). So also to any height the corresponding meat weight can be obtained by the regression equation. log w=-0.8178+1.9769 log H for wild variety (1) log w=-1.3049+2.8385 log H for culture-variety (2) where w is the meat weight (g) and H is the height (cm) of the mussel. Fourteen observations on size weight measurements of dams were made. The yield varied from 8.9 to 13%. The length-height relationship worked out for clams (Villorita sp) is y=0.485+1.005 x for length x and height y.

Morphometric measurements as an index for estimating yield of meat of shell fishes, 1. Crab (Scylla serrata) Forskal

Sixty one observations on length-breadth and whole weight-meat weight relations of India crab (Scylla serrata) were made. From the length of crab (cm) the whole weight (gm) can be computed by the equation: log W=-0.1708+2.3341 log L. Similarly for any given length (cm) the meat weight (gm) can be found by the relation, log w=-1.5745+3.0148 log L.

Adaptation to stable and unstable dynamics achieved by combined impedance control and inverse dynamics model.

This study compared adaptation in novel force fields where trajectories were initially either stable or unstable to elucidate the processes of learning novel skills and adapting to new environments. Subjects learned to move in a null force field (NF), which was unexpectedly changed either to a velocity-dependent force field (VF), which resulted in perturbed but stable hand trajectories, or a position-dependent divergent force field (DF), which resulted in unstable trajectories. With practice, subjects learned to compensate for the perturbations produced by both force fields. Adaptation was characterized by an initial increase in the activation of all muscles followed by a gradual reduction. The time course of the increase in activation was correlated with a reduction in hand-path error for the DF but not for the VF. Adaptation to the VF could have been achieved solely by formation of an inverse dynamics model and adaptation to the DF solely by impedance control. However, indices of learning, such as hand-path error, joint torque, and electromyographic activation and deactivation suggest that the CNS combined these processes during adaptation to both force fields. Our results suggest that during the early phase of learning there is an increase in endpoint stiffness that serves to reduce hand-path error and provides additional stability, regardless of whether the dynamics are stable or unstable. We suggest that the motor control system utilizes an inverse dynamics model to learn the mean dynamics and an impedance controller to assist in the formation of the inverse dynamics model and to generate needed stability.

Impedance control balances stability with metabolically costly muscle activation.

Humans are able to stabilize their movements in environments with unstable dynamics by selectively modifying arm impedance independently of force and torque. We further investigated adaptation to unstable dynamics to determine whether the CNS maintains a constant overall level of stability as the instability of the environmental dynamics is varied. Subjects performed reaching movements in unstable force fields of varying strength, generated by a robotic manipulator. Although the force fields disrupted the initial movements, subjects were able to adapt to the novel dynamics and learned to produce straight trajectories. After adaptation, the endpoint stiffness of the arm was measured at the midpoint of the movement. The stiffness had been selectively modified in the direction of the instability. The stiffness in the stable direction was relatively unchanged from that measured during movements in a null force field prior to exposure to the unstable force field. This impedance modification was achieved without changes in force and torque. The overall stiffness of the arm and environment in the direction of instability was adapted to the force field strength such that it remained equivalent to that of the null force field. This suggests that the CNS attempts both to maintain a minimum level of stability and minimize energy expenditure.

Impedance control and internal model use during the initial stage of adaptation to novel dynamics in humans.

This study investigated the neuromuscular mechanisms underlying the initial stage of adaptation to novel dynamics. A destabilizing velocity-dependent force field (VF) was introduced for sets of three consecutive trials. Between sets a random number of 4-8 null field trials were interposed, where the VF was inactivated. This prevented subjects from learning the novel dynamics, making it possible to repeatedly recreate the initial adaptive response. We were able to investigate detailed changes in neural control between the first, second and third VF trials. We identified two feedforward control mechanisms, which were initiated on the second VF trial and resulted in a 50% reduction in the hand path error. Responses to disturbances encountered on the first VF trial were feedback in nature, i.e. reflexes and voluntary correction of errors. However, on the second VF trial, muscle activation patterns were modified in anticipation of the effects of the force field. Feedforward cocontraction of all muscles was used to increase the viscoelastic impedance of the arm. While stiffening the arm, subjects also exerted a lateral force to counteract the perturbing effect of the force field. These anticipatory actions indicate that the central nervous system responds rapidly to counteract hitherto unfamiliar disturbances by a combination of increased viscoelastic impedance and formation of a crude internal dynamics model.

Impedance control is tuned to multiple directions of movement

Humans are able to learn tool-handling tasks, such as carving, demonstrating their competency to make and vary the direction of movements in unstable environments. It has been shown that when a single reaching movement is repeated in unstable dynamics, the central nervous system (CNS) learns an impedance internal model to compensate for the environment instability. However, there is still no explanation for how humans can learn to move in various directions in such environments. In this study, we investigated whether and how humans compensate for instability while learning two different reaching movements simultaneously. Results show that when performing movements in two different directions, separated by a 35° angle, the CNS was able to compensate for the unstable dynamics. After adaptation, the force was found to be similar to the free movement condition, but stiffness increased in the direction of instability, specifically for each direction of movement. Our findings suggest that the CNS either learned an internal model generalizing over different movements, or alternatively that it was able to switch between specific models acquired simultaneously. © 2008 IEEE.