Statistics of dissipation and enstrophy induced by localized vortices

The ratios of enstrophy and dissipation moments induced by localized vorticity are inferred to be finite. It follows that the scaling exponents for locally averaged dissipation and enstrophy are equal. However, enstrophy and dissipation exponents measured over finite ranges of scales may be different. The cylindrical vortex profile that yields maximal moment ratios is determined. The moment ratios for cylindrical vortices are used to interpret differences in scale dependence of enstrophy and dissipation previously found in numerical simulations.

Effects Of Subgrid-Scale Modeling On Lagrangian Statistics In Large-Eddy Simulation

The application of large-eddy simulation (LES) to turbulent transport processes requires accurate prediction of the Lagrangian statistics of flow fields. However, in most existing SGS models, no explicit consideration is given to Lagrangian statistics. In this paper, we focus on the effects of SGS modeling on Lagrangian statistics in LES ranging from statistics determining single-particle dispersion to those of pair dispersion and multiparticle dispersion. Lagrangian statistics in homogeneous isotropic turbulence are extracted from direct numerical simulation (DNS) and the LES with a spectral eddy-viscosity model. For the case of longtime single-particle dispersion, it is shown that, compared to DNS, LES overpredicts the time scale of the Lagrangian velocity correlation but underpredicts the Lagrangian velocity fluctuation. These two effects tend to cancel one another leading to an accurate prediction of the longtime turbulent dispersion coefficient. Unlike the single-particle dispersion, LES tends to underestimate significantly the rate of relative dispersion of particle pairs and multiple-particles, when initial separation distances are less than the minimum resolved scale due to the lack of subgrid fluctuations. The overprediction of LES on the time scale of the Lagrangian velocity correlation is further confirmed by a theoretical analysis using a turbulence closure theory.

Fracture statistics of brittle materials: Weibull or normal distribution

The fit of fracture strength data of brittle materials (Si3N4, SiC, and ZnO) to the Weibull and normal distributions is compared in terms of the Akaike information criterion. For Si3N4, the Weibull distribution fits the data better than the normal distribution, but for ZnO the result is just the opposite. In the case of SiC, the difference is not large enough to make a clear distinction between the two distributions. There is not sufficient evidence to show that the Weibull distribution is always preferred to other distributions, and the uncritical use of the Weibull distribution for strength data is questioned.

Influence of threshold stress on the estimation of the Weibull statistics

The influence of threshold stress on the estimation of the Weibull statistics is discussed in terms of the Akaike information criterion. Numerical simulations show that, if sample data are limited in number and threshold stress is not too large, the two-parameter Weibull distribution is still a preferred choice. For example, the fit of strength data of glass and ceramics to the two- and three-parameter Weibull distributions is compared.

Statistics of Turbulence in Benthal Boundary Layers

This paper deals with turbulence behavior inbenthalboundarylayers by means of large eddy simulation (LES). The flow is modeled by moving an infinite plate in an otherwise quiescent water with an oscillatory and a steady velocity components. The oscillatory one aims to simulate wave effect on the flow. A number of large-scale turbulence databases have been established, based on which we have obtained turbulencestatisticsof the boundarylayers, such as Reynolds stress, turbulence intensity, skewness and flatness ofturbulence, and temporal and spatial scales of turbulent bursts, etc. Particular attention is paid to the dependences of those statistics on two nondimensional parameters, namely the Reynolds number and the current-wave velocity ratio defined as the steady current velocity over the oscillatory velocity amplitude. It is found that the Reynolds stress and turbulence intensity profile differently from phase to phase, and exhibit two types of distributions in an oscillatory cycle. One is monotonic occurring during the time when current and wave-induced components are in the same direction, and the other inflectional occurring during the time when current and wave-induced components are in opposite directions. Current component makes an asymmetrical time series of Reynolds stress, as well as turbulence intensity, although the mean velocity series is symmetrical as a sine/cosine function. The skewness and flatness variations suggest that the turbulence distribution is not a normal function but approaches to a normal one with the increasing of Reynolds number and the current-wave velocity ratio as well. As for turbulent bursting, the dimensionless period and the mean area of all bursts per unit bed area tend to increase with Reynolds number and current-wave velocity ratio, rather than being constant as in steady channel flows.

Full counting statistics of transport through two-channel Coulomb blockade systems

A mesoscopic Coulomb blockade system with two transport channels is studied in terms of full counting statistics. It is found that the shot noise and skewness are crucially affected by the quantum mechanical interference. In particular, the super-Poisson behavior can be induced as a consequence of constructive interference, and can be understood by the formation of effective fast-and-slow transport channels. Dephasing and finite temperature effects are carried out together with physical interpretations.

一种任务类型敏感的J2EE事务调度算法

J2EE(Java 2 platform enterprise edition)是构建分布式企业应用的基础中间件平台,当前的J2EE事务对资源的访问调度仍然是简单的先来先服务策略,导致服务器负载很重时,次要任务和关键任务争夺有限的资源,降低了关键任务的性能与成功率.为此,有必要识别任务类型,在资源不足时优先保证关键任务事务的执行.但提交给J2EE的事务基于交互方式执行,且缺乏必要的调度信息,因而不能简单地沿用已有的优先级驱动调度算法.提出一种新的事务调度算法TMPBP(threaded multi-queue priority-based protocol),该算法能够安全、有效地提高系统重负载情况下关键事务的服务质量,防止饥饿和优先级倒置.TMPBP包含了一种新的启发式优先级分派算法HRS(heuristic resource statistics),可以在调度信息缺乏的J2EE环境下动态识别关键事务.结果表明,通过合理地选择参数,TMPBP算法能够显著地提高关键事务的服务质量.