旋风分离器内气相流场的相似模化分析(Ⅰ)流动参数

基于数值模拟方法分析了流动参数变化对旋风分离器内气相旋转流流场模化特性的影响。选择直径300mm的旋风分离器为计算模型,在入口气速0.5～30m.s-1、气体温度293～1273K和操作压力0.1～6.5MPa范围内,分析了流动参数变化对流场量纲1速度分布相似性的影响,考察了常规参数模型与高参数原型之间的流场模化关系。模拟结果表明,流动参数变化后,虽然旋风分离器内旋转流流场仍呈现准自由涡与强制涡分布形态,但流场的量纲1速度分布不能保持完全恒定和相似,存在着一定的变化。然而当入口速度高于20m.s-1,或压力高于3.0MPa时,流场量纲1速度可以基本保持恒定,不再随流动参数变化而改变,Euler数与Reynolds数不相关,近似处于流场的自模区;当温度超过1000K后,Euler数基本不受Reynolds数变化的影响,流场也可以保持相似性。最后从能量损失的观点,讨论了Reynolds数和Euler数之间的相互关系,分析了流动参数对旋风分离器气相旋转流流场自模特性作用的机理。

旋风分离器内气相流场的相似模化分析(Ⅱ)尺寸参数

基于数值模拟方法分析了几何相似旋风分离器在直径尺寸变化时的气相流场的模化特性。旋风分离器的直径变化范围为100～2100mm,重点考察流场量纲1速度分布的相似性、尺寸参数的自模特性。模拟结果表明,旋风分离器的直径尺寸变化后,流场的形态结构不变,但量纲1切向速度分布存在一定变化,流场不具有严格的自模性。但随直径尺寸的增大,旋风分离器内流场由弱自模性向强自模性发展,当直径超过2000mm后,流场量纲1速度基本保持相似与恒定,Euler数与Reynolds数不相关,流场处于强自模区。流场的这种自模特性反映了流场的惯性阻力损失和黏性摩擦损失之间的比例关系和大小变化。随着直径尺寸的增大,黏性摩擦损失系数减小,惯性阻力损失系数增大,但Euler数是减小的。当达到很大的直径时,Euler数恒定,Euler数与Reynolds数不相关,流场进入自模区,流场流态保持相似性。

On the method of the automatic modeling in hydraulic pipe networks

In this paper the dynamic characteristics in pipes are analyzed with frequency method, and puts forward a simple and practical describing method. By establishing the model library beforehand, the modeling of the pipe net is completed automatically, and we can accurately calculate the impedance characteristics of the pipe network, achieve the reasonable configuration of the pipe network, so that to decrease the pressure pulsation.

Impeller modeling and analysis based on UG NX/KF and Fluent

Parametric modeling of the impeller which drove a small wind device was built by knowledge fusion technology.NACA2410 airfoil blade was created by KF language.Using technology of UG/KF secondary development for the automatic modeling of wind turbine blade,the program can read in the airfoil data files automatically and the impeller model entity can be generated automatically.In order to modify the model,the aerodynamic characteristics of the impeller were analyzed for getting aerodynamic parameters by Fluent.The maximum force torch and best parameters of impeller were calculated.A physical prototype impeller was manufactured and the correctness of the design was verified,and the error of force torch between simulation and experimental results is about 10%.Parameterization design of the impeller model greatly improves the efficiency of modeling and flexibility of the CAD system.

Optimization of superelevation runoff model for cycling tracks

To improve the possible superelevation runoff models for the cycling track design,at first,two existing representative superelevation runoff models used in China were investigated and fitted. Then,an optimization methodology was proposed,which was focused on the track geometry itself,without the consideration of the physical characteristic of the cyclist,assuming that less vertical curvature values correspond to less riding time. The riding performance formulae were obtained with the variables of riding time,riding velocity and vertical curvature of cycling track. Finally,with the refined adjustment on the vertical curvatures with the help of cycling track design software and considering the effect of horizontal alignments,the optimized models were finalized. It is clearly seen that these optimized models take the form of quartic parabola and are verified to achieve 0.005-0.021 s improvement in the event of 200 m time trial.

Investigation on characteristics of liquid self-diffusion in slit nanopores using simple quasicrystal model of liquid

Dynamical properties of liquid in nano-channels attract much interest because of their applications in engineering and biological systems. The transfer behavior of liquid confined within nanopores differs significantly from that in the bulk. Based on the simple quasicrystal model of liquid, analytical expressions of self-diffusion coefficient both in bulk and in slit nanopore are derived from the Stokes–Einstein equation and the modified Eyring's equation for viscosity. The local self-diffusion coefficient in different layers of liquid and the global self-diffusion coefficient in the slit nanopore are deduced from these expressions. The influences of confinement by pore walls,pore widths, liquid density, and temperature on the self-diffusion coefficient are investigated. The results indicate that the self-diffusion coefficient in nanopore increases with the pore width and approaches the bulk value as the pore width is sufficiently large. Similar to that in bulk state, the self-diffusion coefficient in nanopore decreases with the increase of density and the decrease of temperature, but these dependences are weaker than that in bulk state and become even weaker as the pore width decreases. This work provides a simple method to capture the physical behavior and to investigate the dynamic properties of liquid in nanopores.

Dynamic characteristic analysis of whole machine tools based on Kriging model

In order to study the variation of machine tools’dynamic characteristics in the manufacturing space,a Kriging approximate model is proposed.Finite element method(FEM)is employed on the platform of ANSYS to establish finite element(FE)model with the dynamic characteristic of combined interface for a milling machine,which is newly designed for producing aero engine blades by a certain enterprise group in China.The stiffness and damping of combined interfaces are adjusted by using adaptive simulated annealing algorithm with the optimizing software of iSIGHT in the process of FE model update according to experimental modal analysis(EMA)results.The Kriging approximate model is established according to the finite element analysis results utilizing orthogonal design samples by taking into account of the range of configuration parameters.On the basis of the Kriging approximate model,the response surfaces between key response parameter and configuration parameters are obtained.The results indicate that configuration parameters have great effects on dynamic characteristics of machine tools,and the Kriging approximate model is an effective and rapid method for estimating dynamic characteristics of machine tools in the manufacturing space.

Markov cellular automata models for chronic disease progression

We analyze a Markov cellular automaton that models the spread of viruses that often progress to a chronic condition, such as human immunodeficiency virus （HIV） or hep- atitis C virus （HCV）. We show that the complex dynamical system produces a Markov process at the later stages, whose eigenvectors corresponding to the eigenvalue 1 have physical significance for the long-term prognosis of the virus. Moreover we show that drug treatment leads to chronic conditions that can be modeled by Markov shifts with more optimal eigenveetors.