Statistical second-order two-scale analysis and computation for heat conduction problem with radiation boundary condition in porous materials

This paper discusses a statistical second-order two-scale（SSOTS） analysis and computation for a heat conduction problem with a radiation boundary condition in random porous materials.Firstly,the microscopic configuration for the structure with random distribution is briefly characterized.Secondly,the SSOTS formulae for computing the heat transfer problem are derived successively by means of the construction way for each cell.Then,the statistical prediction algorithm based on the proposed two-scale model is described in detail.Finally,some numerical experiments are proposed,which show that the SSOTS method developed in this paper is effective for predicting the heat transfer performance of porous materials and demonstrating its significant applications in actual engineering computation.

The vertical distribution characteristics of integral turbulence statistics in the atmospheric boundary layer over an urban area in Beijing

Turbulence data(2008–2012) from a 325 m meteorological tower in Beijing, which consisted of three layers(47,140, and 280 m), was used to analyze the vertical distribution characteristics of turbulent transfer over Beijing city according to similarity theory. The conclusions were as follows.(1) Normalized standard deviations of wind speeds/ui * were plotted as a function only of a local stability parameter. The values under near-neutral conditions were 2.15, 1.61, and 1.19 at 47 m, 2.39, 1.75,and 1.21 at 140 m, and 2.51, 1.77, and 1.30 at 280 m, showing a clear increase with height. The normalized standard deviation of wind components fitted the 1/3 law under unstable stratification conditions and decreased with height under both stable and unstable conditions.(2) The normalized standard deviation of temperature fitted the.1/3 law in the free convection limit, but was quite scattered with different characteristics under near-neutral conditions. The normalized standard deviations of humidity and the CO2 concentration fitted the.1/3 law under unstable conditions, and remained constant under near-neutral and stable stratification. The normalized standard deviation of scalars, i.e., temperature, humidity, and CO2 concentration, all increased with height.(3) Compared with momentum, and the water vapor and CO2 concentrations, the turbulence correlation coefficient for heat was smaller under near-neutral conditions, but larger under both stable and unstable conditions. A dissimilarity between heat, and the water vapor and CO2 concentrations was observed in urban areas. The relative correlation coefficients between heat and each of momentum, humidity, and CO2 concentration(|rwT/ruw|, |rwT/rwc| and |rwT/ruq|) in the lower layers were always larger than in higher layers, except for the relative correlation coefficient between heat and humidity in an unstable stratification. Therefore, the ratio between heat and each of momentum, humidity, and CO2 concentration decreased with height.

Boundary Recognition of Light-Pause Marks via Grammar Testing Method

Boundary recognition is an important research of natural language processing, and it provides a basis for the application of Chinese word segmentation, chunk analysis, named entity recognition, etc. Based on ambiguity in boundary recognition of Chinese punctuation marks, this paper proposes grammar testing methods for boundary recognition of slight-pause marks and then calculates the annotation consistency of these methods. The statistical results show that grammar testing methods can greatly improve the annotation consistency of slight-pause marks boundary recognition. The consistency during the second time is 0.030 3 higher than during the first, which will help guarantee the consistency of large-scale corpus annotation and improve the quality of corpus annotation.