scholarly journals Fig 5. Velocity along the drill-string. A. Maximum velocity. B. Root mean square velocity v1 (protocols.io.ke6cthe)

protocols.io ◽  
2017 ◽  
Author(s):  
Peng Wang ◽  
Hongjian Ni ◽  
Ruihe Wang
2019 ◽  
Vol 9 (1) ◽  
pp. 49-60
Author(s):  
Shridhar Digambar Jawak ◽  
Shubhang Kumar ◽  
Alvarinho Joaozinho Luis ◽  
Prashant Hemendra Pandit ◽  
Sagar Filipe Wankhede

Glaciers play a crucial role in the study of the climate change pattern of the Earth. Remote sensing with access to large archives of data has the ability to monitor glaciers frequently throughout the year. Therefore, remote sensing is the most beneficial tool for the study of glacier dynamics. Fed by many tributaries from different sides, the Amery Ice Shelf (AIS) is one of the largest ice shelves that drains ice from the Antarctic ice sheet into the Southern Ocean. This study focuses on the eastern and the western tributaries of the AIS. The primary objective of the study was to derive the velocity of the tributary glaciers and the secondary objective was to compare variations in their velocities between the summer and winter season. This study was carried on using the European Space Agency’s (ESA) Sentinel-1 satellite’s Synthetic Aperture Radar (SAR) data acquired from the Sentinel data portal. Offset tracking method was applied to the Ground Range Detected (GRD) product of the Sentinel-1 interferometric wide (IW) swath acquisition mode. The maximum velocity in summer was observed to be around 610 m/yr in the eastern tributary glacier meeting the ice shelf near the Pickering Nunatak, and around 345 m/yr in the Charybdis Glacier Basin from the western side. The maximum velocity in the winter was observed to be 553 m/yr in the eastern side near the Pickering Nunatak whereas 323 m/yr from the western side in the Charybdis Glacier Basin. The accuracy of the derived glacier velocities was computed using bias and root mean square (RMS) error. For the analysis, the publicly available velocity datasets were used. The accuracy based on RMS error was observed to be 85-90% for both seasons with bias values up to 25 m/yr and root mean square error values up to 30 m/yr.


2020 ◽  
Vol 17 (167) ◽  
pp. 20190892
Author(s):  
Charles M. Greenspon ◽  
Kristine R. McLellan ◽  
Justin D. Lieber ◽  
Sliman J. Bensmaia

To sense the texture of a surface, we run our fingers across it, which leads to the elicitation of skin vibrations that depend both on the surface and on exploratory parameters, particularly scanning speed. The transduction and processing of these vibrations mediate the ability to discern fine surface features. The objective of the present study is to characterize the effect of changes in scanning speed on texture-elicited vibrations to better understand how the exploratory movements shape the neuronal representation of texture. To this end, we scanned a variety of textures across the fingertip of human participants at a variety of speeds (10–160 mm s −1 ) while measuring the resulting vibrations using a laser Doppler vibrometer. First, we found that the intensity of the vibrations—as indexed by root-mean-square velocity—increases with speed but that the skin displacement remains constant. Second, we found that the frequency composition of the vibrations shifts systematically to higher frequencies with increases in scanning speed. Finally, we show that the speed-dependent shift in frequency composition accounts for the speed-dependent change in intensity.


2015 ◽  
Vol 780 ◽  
pp. 649-686 ◽  
Author(s):  
S. S. Srinivas ◽  
V. Kumaran

In comparison to the flow in a rigid channel, there is a multifold reduction in the transition Reynolds number for the flow in a microchannel when one of the walls is made sufficiently soft, due to a dynamical instability induced by the fluid–wall coupling, as shown by Verma & Kumaran (J. Fluid Mech., vol. 727, 2013, pp. 407–455). The flow after transition is characterised using particle image velocimetry in the $x{-}y$ plane, where $x$ is the streamwise direction and $y$ is the cross-stream coordinate along the small dimension of the channel of height 0.2–0.3 mm. The flow after transition is characterised by a mean velocity profile that is flatter at the centre and steeper at the walls in comparison to that for a laminar flow. The root mean square of the streamwise fluctuating velocity shows a characteristic sharp increase away from the wall and a maximum close to the wall, as observed in turbulent flows in rigid-walled channels. However, the profile is asymmetric, with a significantly higher maximum close to the soft wall in comparison to that close to the hard wall, and the Reynolds stress is found to be non-zero at the soft wall, indicating that there is a stress exerted by fluid velocity fluctuations on the wall. The maximum of the root mean square of the velocity fluctuations and the Reynolds stress (divided by the fluid density) in the soft-walled microchannel for Reynolds numbers in the range 250–400, when scaled by suitable powers of the maximum velocity, are comparable to those in a rigid channel at Reynolds numbers in the range 5000–20 000. The near-wall velocity profile shows no evidence of a viscous sublayer for $(yv_{\ast }/{\it\nu})$ as low as two, but there is a logarithmic layer for $(yv_{\ast }/{\it\nu})$ up to approximately 30, where the von Karman constants are very different from those for a rigid-walled channel. Here, $v_{\ast }$ is the friction velocity, ${\it\nu}$ is the kinematic viscosity and $y$ is the distance from the soft surface. The surface of the soft wall in contact with the fluid is marked with dye spots to monitor the deformation and motion along the fluid–wall interface. Low-frequency oscillations in the displacement of the surface are observed after transition in both the streamwise and spanwise directions, indicating that the velocity fluctuations are dynamically coupled to motion in the solid.


2014 ◽  
Vol 556-562 ◽  
pp. 592-596
Author(s):  
Su Zhen Shi ◽  
Juan Li ◽  
Yi Chen Zhao ◽  
Li Biao Yang ◽  
Yao Tang ◽  
...  

In order to improve imaging precision of small structures and small fault blocks of coal seams, the prestack time migration method is used for imaging. Preserved amplitude processing (PAP) is applied to prestack gather firstly after geological data and original seismic data of the exploration area are fully understood. Initial root mean square velocity field is established through the method of picking up root mean square velocity on CRP gather. Then, a precise root mean square velocity model is created after continuous iteration and modification. Meanwhile, appropriate algorithm and migration parameters are selected during the migration process. Finally, the imaging of small fault blocks and small faults in the prestack time migration section is clear and migration is highly coinciding with the case disclosed by boreholes. It’s proved that prestack time migration is especially suitable for processing 3D seismic data of small faults and small fault blocks in coal seams with complicated geological conditions.


2020 ◽  
Vol 495 (4) ◽  
pp. 4820-4827
Author(s):  
Shengdong Lu ◽  
Michele Cappellari ◽  
Shude Mao ◽  
Junqiang Ge ◽  
Ran Li

ABSTRACT Galaxy properties are known to correlate most tightly with the galaxy effective stellar velocity dispersion σe. Here, we look for additional trends at fixed σe using 1339 galaxies (M* ≳ 6 × 109 M⊙) with different morphologies in the MaNGA (DR14) sample with integral-field spectroscopy data. We focus on the gradients (γrms ≡ σ(Re/4)/σe) of the stellar root-mean-square velocity ($V_{\rm rms} \equiv \sqrt{V^2 + \sigma ^2}$), which we show traces the total mass density gradient γtot derived from dynamical models and, more weakly, the bulge fraction. We confirm that γrms increases with σe, age, and metallicity. We additionally find that these correlations still exist at fixed σe, where galaxies with larger γrms are found to be older and more metal-rich. It means that mass density gradients contain information of the stellar population which is not fully accounted for by σe. This result puts an extra constraint on our understanding of galaxy quenching. We compare our results with galaxies in the IllustrisTNG hydrodynamical simulations and find that, at fixed σe, similar trends exist with age, the bulge fraction, and the total mass density slope but, unlike observations, no correlation with metallicity can be detected in the simulations.


Author(s):  
Tuan Norhayati Tuan Chik ◽  
◽  
Cheng Sok Rou ◽  
Ahmad Fahmy Kamarudin ◽  
Seyed Jamalaldin Seyed Hakim ◽  
...  

In the recent years, the level and nature of the ground vibrations has been more concerned in worldwide. Vibration affected on surrounding building is often associated with the vibration from the ground that is mainly caused by internal and external sources. One of the external sources is construction activities. Identify the effects of vibration caused by piling works in construction sites was the purpose of this paper. It is also aiming to determine the vibration criteria due to piling works in Klang Valley construction site. In addition, the objective of this study is to compare the level of vibration with Department of Environment (DOE) guideline between both Kajang MRT and Klang Valley MRT construction sites. The data used for this study is obtained from past researchers and field testing is performed by using Polytec Laser Doppler Vibrometer and Rion VM-55. The data has been analyzed by using ModalV of MATLAB software. Based on the results, it can be concluded that the vibration amplitude for three distance includes 5m, 10m and 20m are located above the ISO level which stated that the area within the distances not suitable for placement of sensitive equipment. The highest value of root mean square velocity is occurred in the distance of 5m and the reading is 80000 µm/s. According to Department of Environment (DOE) guidelines, the vibration at distance of 1m and 3m at Kajang MRT will cause major damage to surrounding buildings while minor damage was produced by the vibration at 5m, 10m and 20m distance from bored piling point which located around the area of Klang Valley MRT.


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