In-situ observations and acoustic measurements upon fragmentation of free-floating intermetallics under ultrasonic cavitation in water

Grain refinement in alloys is a well-known effect of ultrasonic melt processing. Fragmentation of primary crystals by cavitation-induced action in liquid metals is considered as one of the main driving mechanisms for producing finer and equiaxed grain structures. However, in-situ observations of the fragmentation process are generally complex and difficult to follow in opaque liquid metals, especially for the free-floating crystals. In the present study, we develop a transparent test rig to observe in real time the fragmentation potential of free-floating primary Al₃Zr particles under ultrasonic excitation in water (an established analogue medium to liquid aluminium for cavitation studies). An effective treatment domain was identified and fragmentation time determined using acoustic pressure field mapping. For the first time, real-time high-speed imaging captured the dynamic interaction of shock waves from the collapsing bubbles with floating intermetallic particles that led to their fragmentation. The breakage sequence as well as the cavitation erosion pattern were studied by means of post-treatment microscopic characterisation of the fragments. Fragment size distribution and crack patterns on the fractured surface were then analysed and quantified. Application of ultrasound is shown to rapidly (<10 s) reduce intermetallic size (from 5 mm down to 10 μm), thereby increasing the number of potential nucleation sites for the grain refinement of aluminium alloys during melt treatment.     

Dielectric and electrooptical properties of hockey-stick-shaped liquid crystal with a negative dielectric anisotropy

We investigated dielectric properties of a hockey-stick-shaped liquid crystal (HLC). Two dielectric relaxation modes were observed at 0.91 kHz and 4.51 MHz. The low frequency relaxation modes in isotropic, smectic, and nematic phases are related to the motion of ions, collective tilt fluctuation, and rotation around the long molecular axis, respectively. Meanwhile, the high frequency relaxation modes in nematic and smectic phases was due to the rotation around the short axis of the molecules and hindered by the resistance of the ITO layers. We also examined the electrooptical response of the 5.0 wt% HLC-doped commercial nematic liquid crystal (LC) mixtures. The birefringence of the LC mixture was slightly increased, while the falling time and the rotational viscosity was decreased in the nematic phase.     

Telegraphic Transport Processes and Their Fractional Generalization: A Review and Some Extensions

We address the problem of telegraphic transport in several dimensions. We review the derivation of two and three dimensional telegrapher’s equations—as well as their fractional generalizations—from microscopic random walk models for transport (normal and anomalous). We also present new results on solutions of the higher dimensional fractional equations.     

Modeling and Performance Optimization of an Irreversible Two-Stage Combined Thermal Brownian Heat Engine

Based on finite time thermodynamics, an irreversible combined thermal Brownian heat engine model is established in this paper. The model consists of two thermal Brownian heat engines which are operating in tandem with thermal contact with three heat reservoirs. The rates of heat transfer are finite between the heat engine and the reservoir. Considering the heat leakage and the losses caused by kinetic energy change of particles, the formulas of steady current, power output and efficiency are derived. The power output and efficiency of combined heat engine are smaller than that of single heat engine operating between reservoirs with same temperatures. When the potential filed is free from external load, the effects of asymmetry of the potential, barrier height and heat leakage on the performance of the combined heat engine are analyzed. When the potential field is free from external load, the effects of basic design parameters on the performance of the combined heat engine are analyzed. The optimal power and efficiency are obtained by optimizing the barrier heights of two heat engines. The optimal working regions are obtained. There is optimal temperature ratio which maximize the overall power output or efficiency. When the potential filed is subjected to external load, effect of external load is analyzed. The steady current decreases versus external load; the power output and efficiency are monotonically increasing versus external load.     

Status Set Sequential Pattern Mining Considering Time Windows and Periodic Analysis of Patterns

The traditional sequential pattern mining method is carried out considering the whole time period and often ignores the sequential patterns that only occur in local time windows, as well as possible periodicity. Therefore, in order to overcome the limitations of traditional methods, this paper proposes status set sequential pattern mining with time windows (SSPMTW). In contrast to traditional methods, the item status is considered, and time windows, minimum confidence, minimum coverage, minimum factor set ratios and other constraints are added to mine more valuable rules in local time windows. The periodicity of these rules is also analyzed. According to the proposed method, this paper improves the Apriori algorithm, proposes the TW-Apriori algorithm, and explains the basic idea of the algorithm. Then, the feasibility, validity and efficiency of the proposed method and algorithm are verified by small-scale and large-scale examples. In a large-scale numerical example solution, the influence of various constraints on the mining results is analyzed. Finally, the solution results of SSPM and SSPMTW are compared and analyzed, and it is suggested that SSPMTW can excavate the laws existing in local time windows and analyze the periodicity of the laws, which solves the problem of SSPM ignoring the laws existing in local time windows and overcomes the limitations of traditional sequential pattern mining algorithms. In addition, the rules mined by SSPMTW reduce the entropy of the system.     

Modeling and dynamics of double Hindmarsh-Rose neuron with memristor-based magnetic coupling and time delay

The firing of a neuron model is mainly affected by the following factors:the magnetic field, external forcing current, time delay, etc. In this paper, a new time-delayed electromagnetic field coupled dual Hindmarsh-Rose neuron network model is constructed. A magnetically controlled threshold memristor is improved to represent the self-connected and the coupled magnetic fields triggered by the dynamic change of neuronal membrane potential for the adjacent neurons. Numerical simulation confirms that the coupled magnetic field can activate resting neurons to generate rich firing patterns, such as spiking firings, bursting firings, and chaotic firings, and enable neurons to generate larger firing amplitudes. The study also found that the strength of magnetic coupling in the neural network also affects the number of peaks in the discharge of bursting firing. Based on the existing medical treatment background of mental illness, the effects of time lag in the coupling process against neuron firing are studied. The results confirm that the neurons can respond well to external stimuli and coupled magnetic field with appropriate time delay, and keep periodic firing under a wide range of external forcing current.     

Transition to chaos in lid-driven square cavity flow

To date, there are very few studies on the transition beyond second Hopf bifurcation in a lid-driven square cavity, due to the difficulties in theoretical analysis and numerical simulations. In this paper, we study the characteristics of the third Hopf bifurcation in a driven square cavity by applying a consistent fourth-order compact finite difference scheme rectently developed by us. We numerically identify the critical Reynolds number of the third Hopf bifurcation located in the interval of (13944.7021,13946.5333) by the method of bisection. Through Fourier analysis, it is discovered that the flow becomes chaotic with a characteristic of period-doubling bifurcation when the Reynolds number is beyond the third bifurcation critical interval. Nonlinear time series analysis further ascertains the flow chaotic behaviors via the phase diagram, Kolmogorov entropy and maximal Lyapunov exponent. The phase diagram changes interestingly from a closed curve with self-intersection to an unclosed curve and the attractor eventually becomes strange when the flow becomes chaotic.     

基于精确时间协议的HL-2M装置定时同步网络研究

基于HL-2M装置对时序精度的要求,参考ITER的设计方案,设计了基于精确时间协议(PTP)的HL-2M分布式时间通讯网络,使HL-2M装置的时钟同步和事件触发的精度从微秒级提高到亚微秒级,最终优于100ns.     

Du Bois–Reymond Type Lemma and Its Application to Dirichlet Problem with the p(t)–Laplacian on a Bounded Time Scale

This paper is devoted to study the existence of solutions and their regularity in the p(t)–Laplacian Dirichlet problem on a bounded time scale. First, we prove a lemma of du Bois–Reymond type in time-scale settings. Then, using direct variational methods and the mountain pass methodology, we present several sufficient conditions for the existence of solutions to the Dirichlet problem.     

Is Bitcoin Still a King? Relationships between Prices,Volatility and Liquidity of Cryptocurrencies during the Pandemic

We try to establish the commonalities and leadership in the cryptocurrency markets by examining the mutual information and lead-lag relationships between Bitcoin and other cryptocurrencies from January 2019 to June 2021. We examine the transfer entropy between volatility and liquidity of seven highly capitalized cryptocurrencies in order to determine the potential direction of information flow. We find that cryptocurrencies are strongly interrelated in returns and volatility but less in liquidity. We show that smaller and younger cryptocurrencies (such as Ripple’s XRP or Litecoin) have started to affect the returns of Bitcoin since the beginning of the pandemic. Regarding liquidity, the results of the dynamic time warping algorithm also suggest that the position of Monero has increased. Those outcomes suggest the gradual increase in the role of privacy-oriented cryptocurrencies.