文章的目的是对格子玻尔兹曼方法进行系统的介绍,格子玻尔兹曼方法(Lattice BoltzmannMethod)的出现直接来源于20世纪60年代的元胞自动机(Cellular Automata)思想,而这一方法用于解决流动现象时,又可以追溯到19世纪的分子运动论,求解的是Boltzmann提出的玻尔兹曼输运方程,因此将这一方法称为格子玻尔兹曼方法,之前也被称为格子气自动机(Lattice Gas Automa-ton)。该方法多用于研究复杂现象,如材料晶体凝聚时的生长过程、城市土地利用的演化等方面。在20世纪70年代由Hardy、Pomeau和Pazzis建立了第一个用于研究流体运动的格子气自动机,此后,这一方法被广泛用来模拟各种流动问题,诸如二相流、孔隙介质中的渗流等,并根据这一方法开发了相应的商业软件PowerFlow。同时,格子玻尔兹曼方法由于其在微观水平描述运动的特点,成为研究湍流的一个很好的数值计算工具,特别是用其进行直接数值模拟(DNS)计算,成为继传统的差分法、有限体积法和谱方法之后的又一有力的手段。而作为大气运动的一个主要现象的大气湍流,比普通湍流更加复杂,在这里着重介绍了大气湍流的特点和应用格子玻尔兹曼方法模拟湍流的发展过程。
It is found by experiment that under the thermal convection condition, the temperature fluctuation in the urban canopy layer turbulence has the hard state character, and the temperature difference between two points has the exponential probability density function distribution. At the same time, the turbulent energy dissipation rateεfits the log-normal distribution, and is in accord with the hypothesis proposed by Kolmogorov in 1962 and lots of reported experimental results. In this paper, the scaling law of hard state temperature n order structure function is educed by the self-similar multiplicative cascade models. The theory formula isζn = n/3-μ{n(n+6)/72+[2lnn!-nln2]/2ln6}, andμis intermittent exponent. The formula can fit the experimental results up to order 8 exponents, is superior to the predictions by the Kolmogorov theory, the p and log-normal model.
In this study, the Reynolds-averaged Navier-Stokes （RANS） method is employed to simulate the flow within and over an intersection model with three kinds of k-ε turbulence closure schemes, namely, standard model, renormalization group （RNG） model and realizable k-ε model. The comparison between the simulated and observed flow fields shows that the RANS simulation with all the three turbulence models cannot completely and accurately reproduce the observed flow field in all details. A detailed comparison between the predicted profiles of wind velocities and the measured data shows that the realizble k-ε model is the best one among the three turbulence closure models in general. However, the extent to which the improvement is achieved by the realizable k-ε model is still not enough to completely and accurately describe the turbulent flow in a relatively complex environment.
The Regional Atmospheric Modeling System （RAMS） and the computational fluid dynamics （CFD） codes known as FLUENT are combinatorially applied in a multi-scale numerical simulation of the urban surface layer （USL）. RAMS and FLUENT are combined as a multi-scale numerical modeling system, in which the RAMS simulated data are delivered to the computational model for FLUENT simulation in an offline way. Numerical simulations are performed to present and preliminarily validate the capability of the multi-scale modeling system, and the results show that the modeling system can reasonably provide information on the meteorological elements in an urban area from the urban scale to the city-block scale, especially the details of the turbulent flows within the USL.
