Impact of Temperature Variation on Performance of Carbon Nanotube Field-Effect Transistor-Based on Chaotic Oscillator:A Quantum Simulation Study

We evaluate the impact of temperature on the output behavior of a carbon nanotube field effect transistor （CNFET） based chaotic generator. The sources cause the variations in both current-voltage characteristics of the CNFET device and an overall chaotic circuit is pointed out. To verify the effect of temperature variation on the output dynamics of the chaotic circuit, a simulation is performed by employing the CNFET compact model of Wong et al. in HSPICE with a temperature range from -100℃ to 100℃. The obtained results with time series, frequency spectra, and bifurcation diagram from the simulation demonstrate that temperature plays a significant role in the output dynamics of the CNFET-based chaotic circuit. Thus, temperature-related issues should be taken into account while designing a high-quality chaotic generator with high stability.

Effect of Nozzle Vane and Rotor Clearance on Performance of Variable Nozzle Turbine

In a variable nozzle turbine(VNT),the nozzle vane and rotor clearance can generate complicated tip leakage flow,which produces a large flow loss and results in a noticeable reduction in the VNT performance.Therefore,it is necessary to study the influence of the nozzle vane and rotor clearance on the VNT performance to reveal the underlying mechanisms.In this study,the variation of VNT performance resulting from the nozzle vane and rotor clearance was studied numerically using the commercial CFD code.The numerical results were in good agreement with the experimental data.VNT performance under three varied clearance conditions under different clearance sizes,rotating speeds,and expansion ratios was analyzed.Clearance conditions included the individual effect of nozzle vane clearance,the individual effect of rotor clearance,and the combined effect of nozzle vane and rotor clearance.The results showed that the rotor clearance(clearance size equal to 0.4 mm)resulted in a certain reduction in thermal efficiency(–3.98%)and torque(–4.48%).Meanwhile,the nozzle vane hub and shroud clearance also affected the thermal efficiency(–3.66%and–13.37%,respectively)and torque(12.54%and–0.05%,respectively).Compared with the rotor clearance,the nozzle vane clearance dominated the variation in the VNT performance,and the values of the mass flow ratio,thermal efficiency,and torque increased by 12.15%,5.43%,and 8.01%,respectively(The clearance on both sides of the vane was equal to 0.2 mm.).Under the combined effect of the nozzle vane and rotor clearance,the deviation of the thermal efficiency and mass flow ratio was smaller than the sum of the values of their individual effects;when the clearance on both sides of the vane was equal to 0.2 mm and the rotor clearance was equal to 0.6 mm,the value was reduced by 2.77%and 1.71%,respectively.This study also explains the influence mechanisms of clearance at both ends of the nozzle vane and the vane/rotor clearance interaction on the VNT performance in detail.

Guaranteeing the response deadline for general aggregation trees

It is essential to provide responses to queries within time deadlines,even if not exact and complete.To reduce the query latency,systems usually partition large-scale data computations as a series of tasks over many processes and aggregate them to reduce the response time by using aggregation trees.An obstacle is that the involved processes of a query usually differ in their speeds,thus not all processes can complete their tasks in time.This would directly degrade the response quality(the number of outputs received by the root of an aggregation tree).In this paper,we propose a general aggregation tree model,Tarot,to maximize the response quality by systematically addressing the following challenging issues:(1)fine-grained partition of the query deadline along the multi-level aggregation tree;(2)learning the distribution of durations at each level in the aggregation tree to optimize the wait durations at aggregators;(3)adaptively reassigning tasks over processes according to their status;(4)performing periodic aggregation of received outputs from the low level to avoid missing the deadline.The prior model does not consider the four aspects simultaneously.Extensive evaluations indicate that Tarot can adapt to multi-level trees and considerably improve the response quality compared to prior work while guaranteeing the query deadline.