Linear stability analysis of a time-divergent slamming flow

When a liquid slams into a solid, the intermediate gas is squeezed out at a speed that diverges when approaching the moment of impact. Although there is mounting experimental evidence that instabilities form on the liquid interface during such an event, understanding of the nature of these instabilities is limited. This study therefore addresses the stability of a liquid–gas interface with surface tension, subject to a diverging flow in the gas phase, where the liquid and the gas phase are both represented as potential fluids. We perform a Kelvin–Helmholtz-type linear modal stability analysis of the surface to obtain an amplitude equation that is subsequently analysed in detail and applied to two cases of interest for impact problems, namely, the parallel impact of a wave onto a vertical wall, and the impact of a horizontal plate onto a liquid surface. In both cases we find that long wavelengths are stabilised considerably in comparison with what may be expected based upon classical knowledge of the stability of interfaces subject to a constant gas flow. In the former case, this leads to the prediction of a marginally stable wavelength that is completely absent in the classical analysis. For the latter we find much resemblance to the classical case, with the connotation that the instability is suppressed for smaller disk sizes. The study ends with a discussion of the influence of gas viscosity and gas compressibility on the respective stability diagrams.

Schemes for Single Electron Transistor Based on Double Quantum Dot Islands Utilizing a Graphene Nanoscroll, Carbon Nanotube and Fullerene

The single electron transistor (SET) is a nanoscale switching device with a simple equivalent circuit. It can work very fast as it is based on the tunneling of single electrons. Its nanostructure contains a quantum dot island whose material impacts on the device operation. Carbon allotropes such as fullerene (C60), carbon nanotubes (CNTs) and graphene nanoscrolls (GNSs) can be utilized as the quantum dot island in SETs. In this study, multiple quantum dot islands such as GNS-CNT and GNS-C60 are utilized in SET devices. The currents of two counterpart devices are modeled and analyzed. The impacts of important parameters such as temperature and applied gate voltage on the current of two SETs are investigated using proposed mathematical models. Moreover, the impacts of CNT length, fullerene diameter, GNS length, and GNS spiral length and number of turns on the SET’s current are explored. Additionally, the Coulomb blockade ranges (CB) of the two SETs are compared. The results reveal that the GNS-CNT SET has a lower Coulomb blockade range and a higher current than the GNS-C60 SET. Their charge stability diagrams indicate that the GNS-CNT SET has smaller Coulomb diamond areas, zero-current regions, and zero-conductance regions than the GNS-C60 SET.

Effects of the Control Parameters on the Stability of a Laminar Boundary Layer on a Porous Flat Plate

This work is devoted to the analysis of the linear temporal stability of a laminar dynamic boundary layer on a horizontal porous plane plate. The basic flow is assumed to be laminar and two-dimensional. The basic flow velocity profiles are obtained by numerically solving the Blasius equation using the Runge-Kutta method. The perturbations of these basic solutions are expressed in the form of three-dimensional Tollmien-Schlichting waves. The formulation of the stability problem leads to the Orr-Sommerfeld equation modified by the permeability parameter (Darcy number) and the small Reynolds number. This equation is given in a general form which can be applied to the Chebyshev domain and the boundary layer domain and solved numerically using the Chebyshev spectral collocation method. The marginal stability diagrams, the critical Reynolds numbers and the eigenvalue spectra are obtained for different values of the parameters which have modified the stability equation. Numerical solutions indicate the importance of the effect of these parameters on the flow stability characteristics.

Detecting Air Pollutant Molecules Using Tube-Shaped Single Electron Transistor

An air pollution detector is proposed based on a tube-shaped single-electron transistor (SET) sensor. By monitoring the flow control component of the detector, each air pollutant molecule can be placed at the center of a SET nanopore and is treated as an island of the SET device in the same framework. Electron transport in the SET was incoherent, and the performances of the SET were sensitive at the single molecule level. Employing first-principles calculations, electronic features of an air pollutant molecule within a tube-shaped SET environment were found to be independent of the molecule rotational orientations with respect to axis of symmetry, unlike the electronic features in a conventional SET environment. Charge stability diagrams of the island molecules were demonstrated to be distinct for each molecule, and thus they can serve as electronic fingerprints for detection. Using the same setup, quantification of the air pollutant can be realized at room temperature as well. The results presented herein may help provide guidance for the identification and quantification of various types of air pollutants at the molecular level by treating the molecule as the island of the SET component in the proposed detector.

Miniaturizing neural networks for charge state autotuning in quantum dots

A key challenge in scaling quantum computers is the calibration and control of multiple qubits. In solid-state quantum dots (QDs), the gate voltages required to stabilize quantized charges are unique for each individual qubit, resulting in a high-dimensional control parameter space that must be tuned automatically. Machine learning techniques are capable of processing high-dimensional data—provided that an appropriate training set is available—and have been successfully used for autotuning in the past. In this paper, we develop extremely small feed-forward neural networks that can be used to detect charge-state transitions in QD stability diagrams. We demonstrate that these neural networks can be trained on synthetic data produced by computer simulations, and robustly transferred to the task of tuning an experimental device into a desired charge state. The neural networks required for this task are sufficiently small as to enable an implementation in existing memristor crossbar arrays in the near future. This opens up the possibility of miniaturizing powerful control elements on low-power hardware, a significant step towards on-chip autotuning in future QD computers.

Chirality detected in Hartley’s electronic oscillator

Chirality is an elusive asymmetry important in science and technology and confined mainly to the quantum realm. This paper reports the observation of chirality in a classical (that is, not quantum) scenario, namely in stability diagrams of an autonomous electronic oscillator with a junction-gate field-effect transistor (JFET) and a tapped coil. As the number of spikes (local maxima) of stable oscillations changes along closed parameter paths, they generate two types of intricate structures. Surprisingly, such pair of structures are artful images of each other when reflected on a mirror. They are dual chiral pairs interconnecting families of stable oscillations in closed loops. Chiral pairs should not be difficult to detect experimentally. This chirality is conjectured to be a generic property of nonlinear oscillators governed by classical (that is, not quantum) equations.

Chatter Stability of Serrated Milling Tools in Frequency Domain

Serrated milling tools are widely used for chatter suppression in roughing difficult-to-cut Titanium and Nickel alloys in the aerospace industry. Due to the complexity of chip generation and serration wave geometries ground on the flutes, the chatter stability diagrams are predicted with time marching numerical simulation or semi-discrete time-domain methods, which are computationally too costly to use in practice. This paper presents a frequency domain model of milling dynamics with variable delays caused by the flute serrations. The endmill is divided into discrete cylindrical elements, each having a different radius from the cutter axis. As the cutter rotates and cuts metal, the angular distance between the subsequent tooth varies as a function of serration amplitudes and feedrate; hence the regenerative delays vary. The angular delays and effective directional factors are averaged for each tooth to form a time-independent but serration-dependent characteristics equation for all discrete cutter elements. The stability of the resulting characteristic equation of the system is solved using Nyquist theory and compared against the experimental results and existing time marching and semi-discrete time-domain solutions. The proposed analytical model predicts the stability charts about thirty times faster than the time-domain models while providing acceptable accuracy.

Evaluation of an Experimental Modal Analysis Device for Micromilling Tools

Stable machining conditions in the micromilling process are critical to increase the production of small components. Precise frequency response measurements are essential to generate the stability diagrams. Therefore, impact hammer application which mostly relies on operator's skill and experience is very time-consuming and can produce imprecise results. This study aims to analyze a device developed to perform the experimental modal analysis of micromilling tools. The device facilitates the positioning of a fixed point Laser Doppler Vibrometer ( LDV ) as well as providing automatic and reproductive impact tests. Two mirrors supported by kinematic mounts are used to position the laser beam on the micro milling tool surface. The impact hammer is composed of a force sensor attached to a custom designed flexure-based body, in which an automated electromagnetic releases the mechanism. A set of experiments were conducted to perform the precision positioning of the laser beam and the impact hits. The impact force repeatability in terms of the magnitude and impulse duration were also investigated. The application of the device was demonstrated through modal testing of two micromilling tools with two different diameters.

Coding and robustness of signal processing in streaming recurrent neural networks

Introduction: When substantiating promising architectures of streaming recurrent neural networks, it becomes necessary to assess their stability in processing various input signals. For this, stability diagrams are constructed containing the results of simulation for each of the nodes of these diagrams. Such an estimation can be time-consuming and computationally intensive, especially when analyzing large neural networks. Purpose: Search for methods of quick construction of such diagrams and assessing the stability of streaming recurrent neural networks. Results: Analysis of the features of the stability diagrams under study showed that the nodes of the diagrams are grouped into continuous zones with the same ratio characteristics of the input signal processing defects. With this in mind, the article proposes a method for constructing these diagrams based on bypassing the boundaries of their zones. With this approach, you do not have to perform simulation for the interior nodes of each zone. The simulation should be performed only for the nodes adjacent to zone boundaries. Due to this, the number of nodes for which you need to perform simulation sessions is reduced by an order of magnitude. The influence of the input signal coding types on the streaming recurrent neural network stability has been investigated. It is shown that the representation of input signals in the form of sequences of single pulses with intersecting elements can provide greater stability as compared to pulses without any intersection.