### 186 results for qubit oscillator frequency

Contributors: Shubhi Bansal, Prosenjit Sen

Date: 2016-09-01

The dependence of **oscillation** dynamics of a sessile droplet on the actuation parameters (voltage and **frequency**) in AC electrowetting which leads to the manifestation of non-axisymmetric **oscillation** patterns were investigated through experiments and theoretical modeling. The symmetrical nature of the electrowetting force leads to a circular three phase contact line for low actuation voltages. At higher actuation voltages, despite of symmetrical actuation force the contact line showed a transition from axisymmetric to non-axisymmetric **oscillations**. We found a good match between the experimentally determined region in the actuation parameter space where non-axisymmetric modes are dominant and the theoretically modeled parametric instability region derived from the Mathieu equation. The results showed that these non-axisymmetric modes are degenerate sectoral modes defined by the spherical harmonic functions. In contrast to axisymmetric **oscillations**, for non-axisymmetric **oscillations** the variation of contact angle and base radius remained in-phase between successive resonant modes. Finally, mixing by these parametric **oscillations** was investigated and the best mixing time was approximately 2% of the diffusive mixing time....Non-axisymmetric **oscillations**...Comparison of axisymmetric **oscillations** and non-axisymmetric **oscillations** observed for **frequencies** 40Hz/60Hz and 50Hz respectively, for the same actuation voltage 74Vrms. This figure depicts the existence of a local minimum at 50Hz where non-axisymmetric modes can be observed at lower voltages.
...Number of cycles required for mixing of droplets at different actuation **frequencies** for 115Vrms using non-axisymmetric modes. Below 55Hz, only k=2 mode **oscillations** exist and the number of cycles required for mixing increase with the **frequency**. Beyond 55Hz, other higher **oscillation** modes exist.
...Mixing of droplets of DI water (8μl) and diluted orange food colour droplet (2μl) using non-asymmetric **oscillations** with 115Vrms and **frequencies** (A) 35Hz (mode k=2) and (B) 85Hz (mode k=3). [supplementary videos available]. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
...**Oscillation** patterns (top view) of a 8μl droplet at different voltages and **frequencies** (a) mode k=0 at 35Hz, 74Vrms; (b) mode k=2 at 35Hz, 117Vrms; (c) mode k=3 at 100Hz, 117Vrms. [supplementary videos available].
...Change in base radius of an drop at different **frequencies** for 35Vrms. Axisymmetric **oscillations** at 35Vrms voltage are found to have a resonance peak at 25Hz (having an average contact angle θa∼113°).
... The dependence of **oscillation** dynamics of a sessile droplet on the actuation parameters (voltage and **frequency**) in AC electrowetting which leads to the manifestation of non-axisymmetric **oscillation** patterns were investigated through experiments and theoretical modeling. The symmetrical nature of the electrowetting force leads to a circular three phase contact line for low actuation voltages. At higher actuation voltages, despite of symmetrical actuation force the contact line showed a transition from axisymmetric to non-axisymmetric **oscillations**. We found a good match between the experimentally determined region in the actuation parameter space where non-axisymmetric modes are dominant and the theoretically modeled parametric instability region derived from the Mathieu equation. The results showed that these non-axisymmetric modes are degenerate sectoral modes defined by the spherical harmonic functions. In contrast to axisymmetric **oscillations**, for non-axisymmetric **oscillations** the variation of contact angle and base radius remained in-phase between successive resonant modes. Finally, mixing by these parametric **oscillations** was investigated and the best mixing time was approximately 2% of the diffusive mixing time.

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Contributors: Farzad Rafieian, François Girardin, Zhaoheng Liu, Marc Thomas, Bruce Hazel

Date: 2014-02-20

Detection of high-**frequency** repeating impacts in robotic grinding (detailed views). (For interpretation of the references to color in this figure, the reader is referred to the web version of this article.)
...Impact-cutting map from the speed signal based on the experiment with the bump showing (─) a major regime of 2 impacts/revolution and (…) minor **oscillations**. (For interpretation of the references to color in this figure, the reader is referred to the web version of this article.)
...Vibration and rotational **frequency** in single-pass grinding (overview). (For interpretation of the references to color in this figure, the reader is referred to the web version of this article.)
...Typical values of ω, ωmax and Δω during a cutting impact from measured rotational **frequency** in Test (3) at 4500rpm. (For interpretation of the references to color in this figure, the reader is referred to the web version of this article.)
...In a robotic machining process, a light-weight cutter or grinder is usually held by an articulated robot arm. Material removal is achieved by the rotating cutting tool while the robot end effector ensures that the tool follows a programmed trajectory in order to work on complex curved surfaces or to access hard-to-reach areas. One typical application of such process is maintenance and repair work on hydropower equipment. This paper presents an experimental study of the dynamic characteristics of material removal in robotic grinding, which is unlike conventional grinding due to the lower structural stiffness of the tool-holder robot. The objective of the study is to explore the cyclic nature of this mechanical operation to provide the basis for future development of better process control strategies. Grinding tasks that minimize the number of iterations to converge to the target surface can be better planned based on a good understanding and modeling of the cyclic material removal mechanism. A single degree of freedom dynamic analysis of the process suggests that material removal is performed through high-**frequency** impacts that mainly last for only a small fraction of the grinding disk rotation period. To detect these discrete cutting events in practice, a grinder is equipped with a rotary encoder. The encoder's signal is acquired through the angular sampling technique. A running cyclic synchronous average is applied to the speed signal to remove its non-cyclic events. The measured instantaneous rotational **frequency** clearly indicates the impacting nature of the process and captures the transient response excited by these cyclic impacts. The technique also locates the angular positions of cutting impacts in revolution cycles. It is thus possible to draw conclusions about the cyclic nature of dynamic changes in impact-cutting behavior when grinding with a flexible robot. The dynamics of the impacting regime and transient responses to impact-cutting excitations captured synchronously using the angular sampling technique provide feedback that can be used to regulate the material removal process. The experimental results also make it possible to correlate the energy required to remove a chip of metal through impacting with the measured drop in angular speed during grinding....Instantaneous angular **frequency** ... In a robotic machining process, a light-weight cutter or grinder is usually held by an articulated robot arm. Material removal is achieved by the rotating cutting tool while the robot end effector ensures that the tool follows a programmed trajectory in order to work on complex curved surfaces or to access hard-to-reach areas. One typical application of such process is maintenance and repair work on hydropower equipment. This paper presents an experimental study of the dynamic characteristics of material removal in robotic grinding, which is unlike conventional grinding due to the lower structural stiffness of the tool-holder robot. The objective of the study is to explore the cyclic nature of this mechanical operation to provide the basis for future development of better process control strategies. Grinding tasks that minimize the number of iterations to converge to the target surface can be better planned based on a good understanding and modeling of the cyclic material removal mechanism. A single degree of freedom dynamic analysis of the process suggests that material removal is performed through high-**frequency** impacts that mainly last for only a small fraction of the grinding disk rotation period. To detect these discrete cutting events in practice, a grinder is equipped with a rotary encoder. The encoder's signal is acquired through the angular sampling technique. A running cyclic synchronous average is applied to the speed signal to remove its non-cyclic events. The measured instantaneous rotational **frequency** clearly indicates the impacting nature of the process and captures the transient response excited by these cyclic impacts. The technique also locates the angular positions of cutting impacts in revolution cycles. It is thus possible to draw conclusions about the cyclic nature of dynamic changes in impact-cutting behavior when grinding with a flexible robot. The dynamics of the impacting regime and transient responses to impact-cutting excitations captured synchronously using the angular sampling technique provide feedback that can be used to regulate the material removal process. The experimental results also make it possible to correlate the energy required to remove a chip of metal through impacting with the measured drop in angular speed during grinding.

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Contributors: Nadav Cohen, Izhak Bucher, Michael Feldman

Date: 2012-08-01

A bi-stable vibration-based energy harvester excited by low **frequency** base motions exhibits vibrations characterised by a combination of slow and non-stationary fast components. The conversion of slow into fast **oscillations** by a nonlinear potential barrier can increase the amount of harvested power as has been shown before. In this paper the dynamical behaviour leading to the conversion of low-**frequency** **oscillations** into high **frequency** ones is discussed and explained. A non-parametric response decomposition approach able to separate the slow and fast parts is employed. This decomposition provides deeper insight into the effect of the nonlinear potential barrier by identifying the local evolution of instantaneous amplitude and **frequency** near the potential barrier and far from it. The slow and fast components are utilised to identify the backbone-curves of the two asymmetric potential wells and the nonlinear stiffness of the system. The proposed decomposition and analysis allow one to examine the repetitive transient dynamics near the potential barrier without resorting to averaging or perturbation based methods. The proposed approach and the subsequent analysis are demonstrated and explained via numerical and experiment results....Bi-stable **oscillator**...**Frequency** up-conversion...Velocity decomposition. (Right) Fast component shown in a 3D form: projections show the instantaneous **frequency** (IF) vs. time, the envelope vs. time and IF vs. envelope on the far projection. (Left) Velocity components: instantaneous amplitude vs. instantaneous **frequency**.
...Simulated response of a bi-stable energy harvester under constant **frequency** base excitation ω≈0.1ωn () ωn=7Hz, ζ=0.07. Right: nonlinear (bi-stable) potential (––) and force (–––) functions of the system taken from experimental system.
...Fine resolution spectrum of the bi-stable **oscillator** response to pure sine excitation.
... A bi-stable vibration-based energy harvester excited by low **frequency** base motions exhibits vibrations characterised by a combination of slow and non-stationary fast components. The conversion of slow into fast **oscillations** by a nonlinear potential barrier can increase the amount of harvested power as has been shown before. In this paper the dynamical behaviour leading to the conversion of low-**frequency** **oscillations** into high **frequency** ones is discussed and explained. A non-parametric response decomposition approach able to separate the slow and fast parts is employed. This decomposition provides deeper insight into the effect of the nonlinear potential barrier by identifying the local evolution of instantaneous amplitude and **frequency** near the potential barrier and far from it. The slow and fast components are utilised to identify the backbone-curves of the two asymmetric potential wells and the nonlinear stiffness of the system. The proposed decomposition and analysis allow one to examine the repetitive transient dynamics near the potential barrier without resorting to averaging or perturbation based methods. The proposed approach and the subsequent analysis are demonstrated and explained via numerical and experiment results.

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Contributors: Grace Xiong, George V. Lauder

Date: 2014-01-01

Center of mass displacement (green curve) and acceleration (blue curve) relative to tail position (red, shown for reference) in L. macrochirus swimming at 1.5BL/s. Surge acceleration shows a double peak **oscillation** at twice the **frequency** of the tail beat which is absent in the sway data.
...Comparison of COM **oscillation** magnitude for different animals. COM **oscillation** magnitude (peak-to-peak) in each direction was averaged across speeds for terrestrial species to give a single number generally representative of each species. Non-fish data were taken from the literature, and represent COM heave (vertical) motion only since this is the most commonly reported direction of COM **oscillation**, except for the sandfish point which represents sway motion. Fish data (green, red, and blue points) are from the present study and excursions are shown for all three different measured directions: heave, surge, and sway. The linear fit for data on terrestrial animals shown is 1.44x−6.07 (R2=0.88), indicating that COM displacement scales positively with mass, and that larger animals display a larger vertical **oscillation** than would be expected for their size. Fish have significantly lower heave COM **oscillations** than terrestrial animals. The orange point represents lizard sandfish moving in a granular medium and is derived from Ding et al. (2012).
...Two-way ANOVA table to show F-values for speed and species effects on each of the three dimensions of center of mass (COM) **oscillation**.
...Fast Fourier transforms of surge COM acceleration and displacement data for locomotion at 1.5BL/s in (A) L. macrochirus, (B) A. rostrata, and (C) N. chitala. The **frequency** components of the tail beat are shown for comparison in red. At this speed, L. macrochirus uses body and caudal fin undulation and so body undulations are comparable to those of the other species. Grey bars mark the tail beat and double tail beat **frequencies**. Both L. macrochirus and A. rostrata show COM acceleration **frequency** peaks at greater power for double the tail beat **frequency** than for the single beat **frequency**, and significant power for displacement at double the tail beat **frequency**. N. chitala, on the other hand, shows minimal power at double the tail beat **frequency** for acceleration, and negligible power for displacement.
...Speed vs. **frequency** for three species swimming in four swimming modes. **Frequency** had a significant positive relationship (pfrequency was substituted for tail beat **frequency** during labriform propulsion at 0.5BL/s as there was no body undulation at this speed.
...Studies of center of mass (COM) motion are fundamental to understanding the dynamics of animal movement, and have been carried out extensively for terrestrial and aerial locomotion. But despite a large amount of literature describing different body movement patterns in fishes, analyses of how the center of mass moves during undulatory propulsion are not available. These data would be valuable for understanding the dynamics of different body movement patterns and the effect of differing body shapes on locomotor force production. In the present study, we analyzed the magnitude and **frequency** components of COM motion in three dimensions (x: surge, y: sway, z: heave) in three fish species (eel, bluegill sunfish, and clown knifefish) swimming with four locomotor modes at three speeds using high-speed video, and used an image cross-correlation technique to estimate COM motion, thus enabling untethered and unrestrained locomotion. Anguilliform swimming by eels shows reduced COM surge **oscillation** magnitude relative to carangiform swimming, but not compared to knifefish using a gymnotiform locomotor style. Labriform swimming (bluegill at 0.5 body lengths/s) displays reduced COM sway **oscillation** relative to swimming in a carangiform style at higher speeds. **Oscillation** **frequency** of the COM in the surge direction occurs at twice the tail beat **frequency** for carangiform and anguilliform swimming, but at the same **frequency** as the tail beat for gymnotiform locomotion in clown knifefish. Scaling analysis of COM heave **oscillation** for terrestrial locomotion suggests that COM heave motion scales with positive allometry, and that fish have relatively low COM **oscillations** for their body size. ... Studies of center of mass (COM) motion are fundamental to understanding the dynamics of animal movement, and have been carried out extensively for terrestrial and aerial locomotion. But despite a large amount of literature describing different body movement patterns in fishes, analyses of how the center of mass moves during undulatory propulsion are not available. These data would be valuable for understanding the dynamics of different body movement patterns and the effect of differing body shapes on locomotor force production. In the present study, we analyzed the magnitude and **frequency** components of COM motion in three dimensions (x: surge, y: sway, z: heave) in three fish species (eel, bluegill sunfish, and clown knifefish) swimming with four locomotor modes at three speeds using high-speed video, and used an image cross-correlation technique to estimate COM motion, thus enabling untethered and unrestrained locomotion. Anguilliform swimming by eels shows reduced COM surge **oscillation** magnitude relative to carangiform swimming, but not compared to knifefish using a gymnotiform locomotor style. Labriform swimming (bluegill at 0.5 body lengths/s) displays reduced COM sway **oscillation** relative to swimming in a carangiform style at higher speeds. **Oscillation** **frequency** of the COM in the surge direction occurs at twice the tail beat **frequency** for carangiform and anguilliform swimming, but at the same **frequency** as the tail beat for gymnotiform locomotion in clown knifefish. Scaling analysis of COM heave **oscillation** for terrestrial locomotion suggests that COM heave motion scales with positive allometry, and that fish have relatively low COM **oscillations** for their body size.

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Contributors: Nadav Cohen, Izhak Bucher

Date: 2014-09-14

Bistable bilinear **oscillator**: (a) bilinear restoring force (solid curve) and (b) numerical solution of (1) for γt=0.118, ζt=0.071, and xs=0.0073 (solid curve).
...NL bistable **oscillator**. (a) Bistable **oscillator** composed of a linear **oscillator** and a NL element. (b) The dimensionless restoring force of a bistable **oscillator** for different values of α (α=0, solid curve; α=0.1, dotted curve; α=0.3, dashed curve; α=1, dot-dashed curve) in the case of k˜NL=1 and β=1. (c) Typical response of bistable **oscillator** to harmonic excitation in a highly pre-resonance regime. The displacement (solid curve), potential (dashed curve) and restoring force (dot-dashed curve) are taken from the experimental setup, see Appendix.
...Bistable nonlinear **oscillators** can transform slow sinusoidal excitations into higher **frequency** periodic or quasi-periodic **oscillations**. This behaviour can be exploited to efficiently convert mechanical **oscillations** into electrical power, but being nonlinear, their dynamical behaviour is relatively complicated. In order to better understand the dynamics of bistable **oscillators**, an approximate bilinear analytical model, which is valid for narrow potential barriers, is developed. This model is expanded to the case of wider potential with experimental verification. Indeed, the model is verified by numerical simulations and a suitable Poincaré section that the analytical model captures most of bifurcations for large amplitude vibrations and can be used to optimize the harvested power of such devices. The method of Shaw and Holmes [1] is enhanced by exploiting symmetry to obtain closed form expressions of the Poincaré section and mapping....Bistable energy harvester prototype. (a) Close-up on coil and MP, (b) the prototype **oscillator**, and (c) excitation base comprised of a motorized lead screw base.
...(a) Power ratio of a bistable **oscillator** vs. linear **oscillator** as a function of (γ,ζ) for xs=±0.0073. Analytical results represented by 2-dimensional surface; numerical results represented by the contour plot at the bottom of the figure. (b) Power ratio numeric simulation of a wide barrier bistable **oscillator**. The restoring force used on the numerical simulation is extracted from the bistable prototype; (c) the extracted force. The excitation amplitude used is Y=50[mm]. For description of the prototype, see Appendix. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
... Bistable nonlinear **oscillators** can transform slow sinusoidal excitations into higher **frequency** periodic or quasi-periodic **oscillations**. This behaviour can be exploited to efficiently convert mechanical **oscillations** into electrical power, but being nonlinear, their dynamical behaviour is relatively complicated. In order to better understand the dynamics of bistable **oscillators**, an approximate bilinear analytical model, which is valid for narrow potential barriers, is developed. This model is expanded to the case of wider potential with experimental verification. Indeed, the model is verified by numerical simulations and a suitable Poincaré section that the analytical model captures most of bifurcations for large amplitude vibrations and can be used to optimize the harvested power of such devices. The method of Shaw and Holmes [1] is enhanced by exploiting symmetry to obtain closed form expressions of the Poincaré section and mapping.

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Contributors: Fanghao Yang, Xianming Dai, Chih-Jung Kuo, Yoav Peles, Jamil Khan, Chen Li

Date: 2013-01-01

High **frequency**...Experimental study of flow boiling heat transfer in a microchannel array consisting of main channels connected to two auxiliary channels (each) was conducted. A microbubble-excited actuation mechanism, powered by high **frequency** vapor bubble growth and collapse, was established to create and sustain strong mixing in the microchannels. It was shown to significantly enhance flow boiling heat transfer in microchannels. Experimental studies were conducted at mass fluxes ranged from 150 to 480kg/m2s with de-ionized (DI) water as the working fluids. Compared with microchannels with inlet restrictors (IRs), the average two-phase heat transfer coefficient was improved by up to 149%. More importantly, a 71–90% reduction in pressure drop at moderate mass fluxes ranged from 400 to 1400kg/m2s was observed. Heat flux up to 552W/cm2 at a mass flux of 480kg/m2s was demonstrated. Flow and heat transfer mechanisms were studied and discussed....High **frequency** two-phase **oscillations** powered by bubble growth/collapse processes at a heat flux of 100W/cm2 for a mass flux of 400kg/m2s.
...Self-sustained two-phase **oscillation** ... Experimental study of flow boiling heat transfer in a microchannel array consisting of main channels connected to two auxiliary channels (each) was conducted. A microbubble-excited actuation mechanism, powered by high **frequency** vapor bubble growth and collapse, was established to create and sustain strong mixing in the microchannels. It was shown to significantly enhance flow boiling heat transfer in microchannels. Experimental studies were conducted at mass fluxes ranged from 150 to 480kg/m2s with de-ionized (DI) water as the working fluids. Compared with microchannels with inlet restrictors (IRs), the average two-phase heat transfer coefficient was improved by up to 149%. More importantly, a 71–90% reduction in pressure drop at moderate mass fluxes ranged from 400 to 1400kg/m2s was observed. Heat flux up to 552W/cm2 at a mass flux of 480kg/m2s was demonstrated. Flow and heat transfer mechanisms were studied and discussed.

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Contributors: Alexander Hoover, Laura Miller

Date: 2015-06-07

The trajectories of the diameter **oscillation** during the free vibration study for different viscosities. Notice that the subsequent amplitudes of the free vibration **oscillation** decrease for higher viscosities until the **oscillations** present are negligible, as in μ=64μref.
...The **oscillations** of the diameter during the free vibration study as a function of time. The diameter is measured as the distance between two symmetric points at the widest cross-section of the bell.
...The inverted Strouhal number (St−1) vs. driving **frequency** for several choices of force magnitude. St−1 was calculated using the maximum amplitude and forward velocity information taken from the driving **frequency** simulations. Although the best performing **frequency** is the recorded **frequency** of free vibration for small applied forces, the **frequency** that produces the largest deformations is shifted to lower force magnitudes as the force magnitude is increased. The different values of P show how the swimming speeds change in time as steady state is approached.
...Comparing the maximum amplitude of diameter **oscillation** for each of the driving **frequencies**, f, at different force magnitudes, FMag, during the pulse cycle P=5,10,15,20,25. The recorded **frequency** of free vibration is highlighted with the dotted red line. Notice that the **frequency** with the largest maximum amplitude is found for the largest force magnitude when f=.75s−1, which is slightly below the measured **frequency** of vibration. The different values of P show how the maximum amplitudes change in time as steady state is approached. (For interpretation of the references to color in this figure caption, the reader is referred to the web version of this paper.)
...A current question in swimming and flight is whether or not driving flexible appendages at their resonant **frequency** results in faster or more efficient locomotion. It has been suggested that jellyfish swim faster when the bell is driven at its resonant **frequency**. The goal of this study was to determine whether or not driving a jellyfish bell at its resonant **frequency** results in a significant increase in swimming velocity. To address this question, the immersed boundary method was used to solve the fully coupled fluid structure interaction problem of a flexible bell in a viscous fluid. Free vibration numerical experiments were used to determine the resonant **frequency** of the jellyfish bell. The jellyfish bells were then driven at **frequencies** ranging from above and below the resonant **frequency**. We found that jellyfish do swim fastest for a given amount of applied force when the bells are driven near their resonant **frequency**. Nonlinear effects were observed for larger deformations, shifting the optimal **frequency** to higher than the resonant **frequency**. We also found that the benefit of resonant forcing decreases for lower Reynolds numbers....A comparison of the 5th, 10th, and 15th propulsive cycles of the maximum amplitude of diameter **oscillation** during a driving force study with differing levels of μ. Notice that the peak **frequency** shifts lower **frequencies** as more fluid damping is added. Also note how the maximum amplitudes stay relatively fixed in more damped fluid environments.
... A current question in swimming and flight is whether or not driving flexible appendages at their resonant **frequency** results in faster or more efficient locomotion. It has been suggested that jellyfish swim faster when the bell is driven at its resonant **frequency**. The goal of this study was to determine whether or not driving a jellyfish bell at its resonant **frequency** results in a significant increase in swimming velocity. To address this question, the immersed boundary method was used to solve the fully coupled fluid structure interaction problem of a flexible bell in a viscous fluid. Free vibration numerical experiments were used to determine the resonant **frequency** of the jellyfish bell. The jellyfish bells were then driven at **frequencies** ranging from above and below the resonant **frequency**. We found that jellyfish do swim fastest for a given amount of applied force when the bells are driven near their resonant **frequency**. Nonlinear effects were observed for larger deformations, shifting the optimal **frequency** to higher than the resonant **frequency**. We also found that the benefit of resonant forcing decreases for lower Reynolds numbers.

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Contributors: Miklós Szakáll, Simon Kessler, Karoline Diehl, Subir K. Mitra, Stephan Borrmann

Date: 2014-06-01

3D representation of the **frequencies** of the active **oscillation** modes for all phases of the recorded collisions. Top view represents the dependence of the **frequencies** of the transverse mode, while front view the dependence of the horizontal mode **frequencies** on the **frequency** of the axisymmetric mode.
...Temporal variation of the axis ratio: (a) the virtual canting angle, and (b) the projected drop size (c) of the largest drop during collision. The collision process is divided in four phases: I: pre-collision phase; IIa: transverse **oscillation** and/or rotation phase including also the very short transient phase instantaneously after collision; IIb: damping phase; and IIc: phase with quiescent drop characteristics. (Details about the definitions of the phases are given in Section 4 Results and Discussion.)
...Raindrop **oscillation**...Drop–drop collision experiments were carried out at the Mainz vertical wind tunnel. Water drops of 2.5mm diameter were freely floated at their terminal velocities in a vertical air stream and collided with 0.5mm diameter droplets. The collisions were recorded with a high speed digital video camera at a frame rate of 1000 per second. Altogether 116 collision events were observed, 75 of which ended with coalescence, and the rest with filament type breakup. The coalescence efficiency and its dependence on the Weber number and on the eccentricity of the colliding drops showed good agreement with earlier numerical studies. Thirty-six recorded collisions were further analyzed in order to characterize the **oscillation** behavior of large drops after a collisional excitation. Besides the introduction of the experimental method for studying the raindrop collisions, the study primarily focused on the characterization of the average value and the amplitude of the axis ratio variation, the active **oscillation** modes and their **frequencies**, and the decay of the **oscillations** excited by the collision. In spite of the fact that the amplitude of the axis ratio variation increased up to 4 to 6 times of its value before collision – depending on whether the collision ended with coalescence or breakup –, the average axis ratios increased by less than 1%. Since the sizes of largest drops after collision remained practically unchanged during the collision process, the **frequencies** of the active fundamental (n=2) **oscillation** modes of the drops did not change significantly either. Instantaneously after collision the transverse **oscillation** mode and the whole body rotation dominated, while at a later instant the oblate–prolate mode determined again the drop shape alteration. It was further found that the damping of the **oscillation** after collision can be adequately described by the viscous decay of a liquid spherical drop. ... Drop–drop collision experiments were carried out at the Mainz vertical wind tunnel. Water drops of 2.5mm diameter were freely floated at their terminal velocities in a vertical air stream and collided with 0.5mm diameter droplets. The collisions were recorded with a high speed digital video camera at a frame rate of 1000 per second. Altogether 116 collision events were observed, 75 of which ended with coalescence, and the rest with filament type breakup. The coalescence efficiency and its dependence on the Weber number and on the eccentricity of the colliding drops showed good agreement with earlier numerical studies. Thirty-six recorded collisions were further analyzed in order to characterize the **oscillation** behavior of large drops after a collisional excitation. Besides the introduction of the experimental method for studying the raindrop collisions, the study primarily focused on the characterization of the average value and the amplitude of the axis ratio variation, the active **oscillation** modes and their **frequencies**, and the decay of the **oscillations** excited by the collision. In spite of the fact that the amplitude of the axis ratio variation increased up to 4 to 6 times of its value before collision – depending on whether the collision ended with coalescence or breakup –, the average axis ratios increased by less than 1%. Since the sizes of largest drops after collision remained practically unchanged during the collision process, the **frequencies** of the active fundamental (n=2) **oscillation** modes of the drops did not change significantly either. Instantaneously after collision the transverse **oscillation** mode and the whole body rotation dominated, while at a later instant the oblate–prolate mode determined again the drop shape alteration. It was further found that the damping of the **oscillation** after collision can be adequately described by the viscous decay of a liquid spherical drop.

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Contributors: Seth H. Weinberg, Kelly C. Chang, Renjun Zhu, Harikrishna Tandri, Ronald D. Berger, Natalia A. Trayanova, Leslie Tung

Date: 2013-05-01

Conduction block and ventricular fibrillation vulnerability. A: Percentage of trials (a) initiating and (b) terminating ventricular fibrillation (VF) as a function of field **frequency** and strength. (c) Mean defibrillation threshold (DFT; red line) and upper limit of vulnerability (ULV; black line) as functions of **frequency**. Lines at the bottom of the plot indicate pairwise statistical significance. B: (a) Average loss of conduction power (LCP) values and (b) average conduction block (CB) size as a function of field strength and **frequency**. LCP standard errors are given in Table S2. Correlation between (C) average LCP or (D) average CB size and (a) the percentage of trials initiating VF or (b) the percentage of trials terminating VF.
...We recently demonstrated that high **frequency** alternating current (HFAC) electric fields can reversibly block propagation in the heart by inducing an **oscillating**, elevated transmembrane potential (Vm) that maintains myocytes in a refractory state for the field duration and can terminate arrhythmias, including ventricular fibrillation (VF)....Surface and subsurface conduction block and ventricular fibrillation termination. (A) Percentage of simulations terminating ventricular fibrillation (VF), (B) average (a) surface and (b) subsurface loss of conduction power (LCP) values, and (C) average (a) surface and (b) subsurface conduction block (CB) size as a function of field **frequency** and strength. Correlation between (D) average LCP or (E) CB size on the surface (red) or the subsurface (blue) myocardium and the percentage of simulations terminating ventricular fibrillation (VF).
...Conduction block on the surface and subsurface myocardium during high **frequency** alternating current (HFAC) fields. (A) Successful and (B) failed termination of ventricular fibrillation (VF), following 15-V/cm and 10-V/cm HFAC fields, respectively. Spatial maps of loss of conduction power (LCP) on (left) the epicardial surface and (middle) a short-axis slice. (Right) Transmembrane potential (Vm) traces at sites a–e, shown in the spatial maps in image A, with the corresponding LCP values. Gray bar indicates time of the HFAC field. The time windows used for LCP analysis before and during the HFAC field are shown in red and blue, respectively.
...Successful and failed defibrillation following partial conduction block. (A) Successful and (B) failed defibrillation, following 10.7-V/cm and 9.2-V/cm high **frequency** alternating current (HFAC) fields, respectively. Top: Time-space plot, along the dashed line in the first panel of Figure 1B. Red regions in the plots indicate fully depolarized cells; deep blue indicates fully repolarized cells at rest. Propagating activations are denoted by white arrows. Bottom: Spatial map of loss of conduction power (LCP).
...Defibrillation by high **frequency** alternating current (HFAC) field. A: Anterior surface of the heart: left ventricle (LV), right ventricle (RV), and left anterior descending (LAD) artery. The optical mapped field of view is shown in the white box. B: Normalized transmembrane potential (Vm) maps before, during (gray backing), and after 200-Hz 300-ms HFAC field application. Red regions in the maps indicate fully depolarized cells; deep blue indicates fully repolarized cells at rest. C: Vm before, during, and after partial conduction block during the HFAC field. The time windows used for loss of conduction power (LCP) analysis before and during the HFAC field are shown in red and blue, respectively. Gray bar indicates the time of the HFAC field. D: Vm power spectrum before and during partial conduction block during the HFAC field. Sites a and c are close to the left and right field of view edges, respectively; site b is at the center of the field of the view, shown in image A. LCP values for each site are shown.
... We recently demonstrated that high **frequency** alternating current (HFAC) electric fields can reversibly block propagation in the heart by inducing an **oscillating**, elevated transmembrane potential (Vm) that maintains myocytes in a refractory state for the field duration and can terminate arrhythmias, including ventricular fibrillation (VF).

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Contributors: Tomoya Nagira, Noriaki Nakatsuka, Hideyuki Yasuda, Kentaro Uesugi, Akihisa Takeuchi, Yoshio Suzuki

Date: 2015-07-01

The effects of an ultrasonic wave (20kHz) on the dendritic microstructure of Sn–13at%Bi alloys were studied using time-resolved in situ X-ray imaging. Sequential images clearly showed the secondary effects such as the ultrasonic streaming and the **oscillation** with much lower **frequency** comparing to the ultrasonic vibration **frequency**. The ultrasonic wave caused a circulating convection, whose domain size was almost the same as the specimen size, and simultaneously periodic convection (40Hz), which was identified from the longitudinal **oscillation** of the dendrites. The fragmentation of the primary and secondary dendrite arms in the columnar zone was significantly enhanced under the ultrasonic wave. The secondary effects of the ultrasonic wave play a significant role for modifying the solidification structure. ... The effects of an ultrasonic wave (20kHz) on the dendritic microstructure of Sn–13at%Bi alloys were studied using time-resolved in situ X-ray imaging. Sequential images clearly showed the secondary effects such as the ultrasonic streaming and the **oscillation** with much lower **frequency** comparing to the ultrasonic vibration **frequency**. The ultrasonic wave caused a circulating convection, whose domain size was almost the same as the specimen size, and simultaneously periodic convection (40Hz), which was identified from the longitudinal **oscillation** of the dendrites. The fragmentation of the primary and secondary dendrite arms in the columnar zone was significantly enhanced under the ultrasonic wave. The secondary effects of the ultrasonic wave play a significant role for modifying the solidification structure.

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