scholarly journals Pressure Attenuation Law of Low-Frequency Pulse Pressure Flooding and Its Influence on Oil Recovery

ACS Omega ◽  
2021 ◽  
Author(s):  
Chengting Liu ◽  
Tian Chen ◽  
Zhenguo Yu ◽  
Zhao Yang ◽  
Jingqi Yin
Keyword(s):  
Oil Recovery ◽  
Pulse Pressure ◽  
Low Frequency ◽  
Attenuation Law ◽  
Frequency Pulse

High‐power‐factor dimmable LED driver with low‐frequency pulse‐width modulation

2016 ◽  
Vol 9 (10) ◽  
pp. 2139-2146 ◽  
Author(s):  
Hung‐Liang Cheng ◽  
Yong‐Nong Chang ◽  
Chun‐An Cheng ◽  
Chien‐Hsuan Chang ◽  
Yu‐Hung Lin
Keyword(s):  
Power Factor ◽  
High Power ◽  
Pulse Width ◽  
Pulse Width Modulation ◽  
Low Frequency ◽  
Led Driver ◽  
High Power Factor ◽  
Frequency Pulse

Spike-timing-dependent plasticity model for low-frequency pulse waveform

2019 ◽  
Vol 24 (4) ◽  
pp. 452-459
Author(s):  
Masaya Ohara ◽  
Minami Kaneko ◽  
Fumio Uchikoba ◽  
Ken Saito
Keyword(s):  
Low Frequency ◽  
Spike Timing ◽  
Plasticity Model ◽  
Pulse Waveform ◽  
Spike Timing Dependent Plasticity ◽  
Dependent Plasticity ◽  
Frequency Pulse

The effect of low frequency pulse-shaped substrate bias on the remote plasma deposition of a-Si : H thin films

2009 ◽  
Vol 19 (1) ◽  
pp. 015012 ◽  
Author(s):  
I T Martin ◽  
M A Wank ◽  
M A Blauw ◽  
R A C M M van Swaaij ◽  
W M M Kessels ◽  
...  
Keyword(s):  
Thin Films ◽  
Plasma Deposition ◽  
Low Frequency ◽  
Substrate Bias ◽  
Remote Plasma ◽  
Frequency Pulse

The INFITA low-frequency pulse physiotherapeutic device

1994 ◽  
Vol 28 (5) ◽  
pp. 284-287
Author(s):  
A. Yu. Zaslavskii ◽  
G. S. Markarov
Keyword(s):  
Low Frequency ◽  
Frequency Pulse

The Influence of Salt Concentration in Injected Water on Low-Frequency Electrical-Heating-Assisted Bitumen Recovery

SPE Journal ◽  
2011 ◽  
Vol 16 (03) ◽  
pp. 548-558 ◽  
Author(s):  
I.I.. I. Bogdanov ◽  
J.A.. A. Torres ◽  
H.A.. A. Akhlaghi ◽  
A.M.. M. Kamp
Keyword(s):  
Electric Conductivity ◽  
Oil Recovery ◽  
Salt Concentration ◽  
Salt Water ◽  
Low Frequency ◽  
Water Circulation ◽  
Electrical Heating ◽  
Simple Problem ◽  
Field Scale ◽  
Bitumen Recovery

Summary Steam injection is often not a good alternative for oil recovery from shallow bitumen reservoirs. For instance, the thin caprock creates the danger of steam breakthrough. For deeper reservoirs, the heat losses from injection wells may be prohibitive. A technology that may be better suited is oil recovery aided by low-frequency electrical heating of the reservoir. This technology, well known for environmental remedial applications, has been field tried recently, yielding promising results. The process uses electric conductivity of connate water to propagate an alternating current between electrodes, inducing the Joule heating of the reservoir. An associated problem is the appearance of hot spots around the electrodes that may be relieved by water circulation. However, the water circulation may have a significant effect on the heating process because the electric conductivity of the circulated water depends on its salt content. To find out the influence of salt concentration on process efficiency, we have studied the process of salt-water recirculation around an electrode using numerical simulation. The physical properties and operational data for Athabasca bitumen have been collected from the literature. The model built with Computer Modelling Group's STARS simulator and tested first with available analytical solutions has been validated, and the proper choice of the underlying grid and numerical tuning parameters has been verified. The process was also simulated at field scale for a common pattern of electrodes and production wells. The salt penetrated into the reservoir, far beyond the major water-circulation zone around the electrodes. This process increases the electric conductivity in a large region between electrodes, which improves the heating of the reservoir. The single-electrode simulation studies using different tools yielded similar results for a simple problem. More-complex (and more-realistic) field-scale simulations show that adding salt enhances the oil production. In practice, an upper concentration limit may be given by corrosion problems at the electrodes. The reservoir simulation of bitumen recovery assisted by low-frequency heating is a challenging multiphysics problem. The understanding of the influence of salt concentration on the circulated water provided by this work is an important key in process-design considerations.

scholarly journals From unspecific to adjusted, how the BOLD response in the rat hippocampus develops during consecutive stimulations

2016 ◽  
Vol 37 (2) ◽  
pp. 590-604 ◽  
Author(s):  
Stephanie Riemann ◽  
Cornelia Helbing ◽  
Frank Angenstein
Keyword(s):  
High Frequency ◽  
Pulse Sequences ◽  
Low Frequency ◽  
Bold Response ◽  
Deconvolution Analysis ◽  
Bold Responses ◽  
Electrical Pulses ◽  
Stimulation Period ◽  
Frequency Pulse ◽  
Spiking Activity

To determine the possibility to deconvolve measured BOLD responses to neuronal signals, the rat perforant pathway was electrically stimulated with 10 related stimulation protocols. All stimulation protocols were composed of low-frequency pulse sequences with superimposed high-frequency pulse bursts. Because high-frequency pulse bursts trigger only one synchronized spiking of granular cells, variations of the stimulation protocol were used: (a) to keep the spiking activity similar during the presentation of different numbers of pulses, (b) to apply identical numbers of pulses to induce different amounts of spiking activity, and (c) to concurrently vary the number of applied electrical pulses and resultant spiking activity. When complex pulse sequences enter the hippocampus, an unspecific default-like BOLD response is first generated, which relates neither to the number of incoming pulses nor to the induced spiking activity. Only during subsequent stimulations does the initial unspecific response adjust to a more adequate response, which in turn either strongly related to spiking activity when low-frequency pulses were applied or depended on the incoming activity when high-frequency pulse bursts were presented. Thus, only the development of BOLD responses during repetitive stimulations can predict the underlying neuronal activity and deconvolution analysis should not be performed during an initial stimulation period.

scholarly journals The Application of Low-Frequency Transition in the Assessment of the Second-Order Zeeman Frequency Shift

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8333
Author(s):  
Yang Bai ◽  
Xinliang Wang ◽  
Junru Shi ◽  
Fan Yang ◽  
Jun Ruan ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Frequency Shift ◽  
Low Frequency ◽  
Pulse Signal ◽  
Second Order ◽  
Magnetic Field Measurement ◽  
Central Frequency ◽  
Zeeman Frequency ◽  
The Magnetic Field ◽  
Frequency Pulse

Second-order Zeeman frequency shift is one of the major systematic factors affecting the frequency uncertainty performance of cesium atomic fountain clock. Second-order Zeeman frequency shift is calculated by experimentally measuring the central frequency of the (1,1) or (−1,−1) magnetically sensitive Ramsey transition. The low-frequency transition method can be used to measure the magnetic field strength and to predict the central fringe of (1,1) or (−1,−1) magnetically sensitive Ramsey transition. In this paper, we deduce the formula for magnetic field measurement using the low-frequency transition method and measured the magnetic field distribution of 4 cm inside the Ramsey cavity and 32 cm along the flight region experimentally. The result shows that the magnetic field fluctuation is less than 1 nT. The influence of low-frequency pulse signal duration on the accuracy of magnetic field measurement is studied and the optimal low-frequency pulse signal duration is determined. The central fringe of (−1,−1) magnetically sensitive Ramsey transition can be predicted by using a numerical integrating of the magnetic field “map”. Comparing the predicted central fringe with that identified by Ramsey method, the frequency difference between these two is, at most, a fringe width of 0.3. We apply the experimentally measured central frequency of the (−1,−1) Ramsey transition to the Breit-Rabi formula, and the second-order Zeeman frequency shift is calculated as 131.03 × 10−15, with the uncertainty of 0.10 × 10−15.

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