Thermal convection with generalized friction

A model for thermal convection with generalized friction is investigated. It is shown that the linear instability threshold is the same as the global stability one. In addition, decay of the energy in the $$L^2$$ L 2 norm is shown for the perturbation velocity and temperature fields. However, due to the presence of the generalized friction we establish exponential decay in the $$L^{\beta +1}$$ L β + 1 norm for the perturbation temperature, where $$\beta >1$$ β > 1 .

Effects of Perturbation Velocity, Direction, Background Muscle Activation, and Task Instruction on Long-Latency Responses Measured From Forearm Muscles

The central nervous system uses feedback processes that occur at multiple time scales to control interactions with the environment. The long-latency response (LLR) is the fastest process that directly involves cortical areas, with a motoneuron response measurable 50 ms following an imposed limb displacement. Several behavioral factors concerning perturbation mechanics and the active role of muscles prior or during the perturbation can modulate the long-latency response amplitude (LLRa) in the upper limbs, but the interactions among many of these factors had not been systematically studied before. We conducted a behavioral study on thirteen healthy individuals to determine the effect and interaction of four behavioral factors – background muscle torque, perturbation direction, perturbation velocity, and task instruction – on the LLRa evoked from the flexor carpi radialis (FCR) and extensor carpi ulnaris (ECU) muscles after velocity-controlled wrist displacements. The effects of the four factors were quantified using both a 0D statistical analysis on the average perturbation-evoked EMG signal in the period corresponding to an LLR, and using a timeseries analysis of EMG signals. All factors significantly modulated LLRa, and their combination nonlinearly contributed to modulating the LLRa. Specifically, all the three-way interaction terms that could be computed without including the interaction between instruction and velocity significantly modulated the LLR. Analysis of the three-way interaction terms of the 0D model indicated that for the ECU muscle, the LLRa evoked when subjects are asked to maintain their muscle activation in response to the perturbations was greater than the one observed when subjects yielded to the perturbations (p < 0.001), but this effect was not measured for muscles undergoing shortening or in absence of background muscle activation. Moreover, higher perturbation velocity increased the LLRa evoked from the stretched muscle in presence of a background torque (p < 0.001), but no effects of velocity were measured in absence of background torque. Also, our analysis identified significant modulations of LLRa in muscles shortened by the perturbation, including an interaction between torque and velocity, and an effect of both torque and velocity. The time-series analysis indicated the significance of additional transient effects in the LLR region for muscles undergoing shortening.

Effects of Perturbation Velocity, Direction, Background muscle activation, and Task Instruction on Long-Latency Responses Measured from Forearm Muscles

The centeral nervous system uses feedback processes that occur at multiple time scales to control interactions with the environment. Insight on the neuromechanical mechanisms subserving the faster feedback processes can be gained by applying rapid mechanical perturbations to the limb, and observing the ensuing muscle responses using electromyography (EMG). The long-latency response (LLR) is the fastest process that directly involve cortical areas, with a motorneuron response measurable 50 ms following an imposed limb displacement. Several behavioral factors concerning perturbation mechanics and the active role of muscles prior or during the perturbation can modulate the long-latency response amplitude (LLRa) in the upper limbs, but the interaction between many of these factors had not been systematically studied before.We conducted a behavioral study on thirteen healthy individuals to determine the effect and interaction of four behavioral factors -- background muscle torque, perturbation direction, perturbation velocity, and task instruction -- on the LLRa evoked from the flexor carpi radialis (FCR) and extensor carpi ulnaris (ECU) muscles following the application of wrist displacements. The effects of the four factors listed above were quantified using both a 0D statistical analysis on the average perturbation-evoked EMG signal in the period corresponding to an LLR, and using a timeseries analysis of EMG signals.All factors significantly modulated LLRa, and that their combination nonlinearly contributed to modulating the LLRa. Specifically, all the three-way interaction terms that could be computed without including the interaction between instruction and velocity significantly modulated the LLR. Analysis of the three-way interaction terms of the 0D model indicated that for the ECU muscle, the LLRa evoked when subjects are asked to maintain their muscle activation in response to the perturbations (DNI) was greater than the one observed when subjects yielded (Y) to the perturbations (ΔLLRa — DNI vs. Y: 1.76±0.16 nu, p<0.001), but this effect was not measured for muscles undergoing shortening or in absence of background muscle activation. Moreover, higher perturbation velocity increased the LLRa evoked from the stretched muscle in presence of a background torque (ΔLLRa 200−125 deg/s: 0.94±0.20 nu, p<0.001; ΔLLRa 125−50 deg/s: 1.09 ±0.20 nu, p<0.001), but no effects of velocity were measured in absence of background torque, nor effects of any of those factors was measured on muscles shortened by the perturbations. The time-series analysis indicated the significance of some effects in the LLR region also for muscles undergoing shortening. As an example, the interaction between torque and instruction was significant also for the ECU muscle undergoing shortening, in part due to the composition of a positive and negative modulation of the response due to the interaction between of the two terms. The absence of a nonlinear interaction between task instruction and perturbation velocity suggest that the modulation introduced by these two factors are processed by distinct neural pathways.

The Composite Shape and Structure of Braid Patterns in Kelvin–Helmholtz Billows Observed with a Sodar

The structure and dynamic characteristics of the Kelvin–Helmholtz billows (KHB), observed with a sodar in the stable atmospheric boundary layer, are studied by means of composite analysis, which consists in the averaging of samples selected according to certain criteria. Using a specific kind of this method allowed the authors to obtain the fine structure of the perturbation velocity fields from the sodar data. The events of most pronounced KHB were visually selected from echograms of continuous sodar measurements in the Moscow region over 2008–10. The composite patterns of KHB have been constructed for a few cases of clear inclined–stripes echogram patterns to derive a typical finescale structure of billows and a spatial distribution of wind speed and shear within them. The interconnection between echo intensity and wind shear variations within such patterns is shown. The typical distributions of velocity perturbation within various forms of billows are found.

Conditional sampling of transitional boundary layers in pressure gradients

Statistical analysis of transitional boundary layers in pressure gradients is performed using the flow fields from direct numerical simulations of bypass transition. Laminar–turbulent discrimination separates the streaky laminar flow from turbulent regions. Individual streaks are identified and tracked in the flow field in order to obtain statistics of the amplitude of the streak population. An extreme value model is proposed for the distribution of streak amplitudes. It is also possible to differentiate those streaks which break down into turbulent spots from innocuous events. It is shown that turbulence onset is due to high-amplitude streaks, with streamwise perturbation velocity exceeding 20 % of the free stream speed. The resulting turbulent spots are tracked downstream. The current analysis allows for the measurement of the lateral spreading angles of individual spots and their spatial extent and volumes. It is demonstrated that the volumetric growth rate of turbulent spots is insensitive to pressure gradient.

Periodic Disturbance in Turbulent Boundary Layer Method to Study on the Mechanical Properties of the Perturbation Velocity Component

Time-series signals of normal velocity component with different flow direction and normal position of the turbulent boundary layer which were disturbed before and after the different frequency period were made elaborate measurement in the wind tunnel with the sampling frequency higher than the correspondent smallest turbulence structure time scale,IFA300 hot-wire anemometer and TSI-1243 double hot-wire senor probe were used in the experiment. The average waveform of the period phase of the period disturbance velocity signals were extracted in the instantaneous normal velocity component signals of the turbulent boundary layer. The attenuation and distortion along the flow direction and the normal of the disturbance wave with different period in the turbulent boundary layer were made experimental research, the distribution of the disturbance amplitude of the normal velocity component with different disturbance period along the flow direction and the normal in the turbulent boundary layer were measured.

Constraining fault interpretation through tomographic velocity gradients: application to northern Cascadia

Spatial gradients of tomographic velocities are seldom used in interpretation of subsurface fault structures. This study shows that spatial velocity gradients can be used effectively in identifying subsurface discontinuities in the horizontal and vertical directions. Three-dimensional velocity models constructed through tomographic inversion of active source and/or earthquake traveltime data are generally built from an initial 1-D velocity model that varies only with depth. Regularized tomographic inversion algorithms impose constraints on the roughness of the model that help to stabilize the inversion process. Final velocity models obtained from regularized tomographic inversions have smooth three-dimensional structures that are required by the data. Final velocity models are usually analyzed and interpreted either as a perturbation velocity model or as an absolute velocity model. Compared to perturbation velocity model, absolute velocity models have an advantage of providing constraints on lithology. Both velocity models lack the ability to provide sharp constraints on subsurface faults. An interpretational approach utilizing spatial velocity gradients applied to northern Cascadia shows that subsurface faults that are not clearly interpretable from velocity model plots can be identified by sharp contrasts in velocity gradient plots. This interpretation resulted in inferring the locations of the Tacoma, Seattle, Southern Whidbey Island, and Darrington Devil's Mountain faults much more clearly. The Coast Range Boundary fault, previously hypothesized on the basis of sedimentological and tectonic observations, is inferred clearly from the gradient plots. Many of the fault locations imaged from gradient data correlate with earthquake hypocenters, indicating their seismogenic nature.