工业化竹材廊屋设计探析——以梅口埠廊桥为例

竹材作为中国本土的生态资源有着巨大的潜力,挖掘竹资源对缓解我国木材长期短缺、发展可持续绿色建筑材料意义重大,但在工业化过程中,由于相关结构体系、建筑技术和理论尚未完全建构,使得工业化竹材产业发展陷入困境。通过松溪梅口埠廊桥项目,运用体系化的设计思维,探索工业化竹材在模数应用、构件预制和规模化建造的可行性,用“廊屋设计”嫁接工业化竹材与建筑应用的桥梁,强调改性竹材的价值,为工业化竹材的研究与廊屋建筑应用提供一定参考。

Establishment of size-dependant constitutive model of micro-sheet metal materials

The inherent mechanism of size effect in micro-sheet material behavior of plastic forming was explained by the surface layer model and theory of metal crystal plasticity. A size-dependant constitutive model based on the surface layer model was established by introducing the scale parameters and modifying the classical Hall-Petch equation. The influence of the geometric dimensions and the grain size on the flow behavior of the material was discussed using the new material constitutive model. The results show that, the flow stress decreases while the sheet metal thickness decreases when the grain size keeps constant, and the micro-sheet metal with a larger grain size is more easily to be influenced by the size effects. The material constitutive model established is validated by the stress-strain curve of the micro-sheet metal with different thicknesses derived from the tensile experiments. The rationality of the material model is verified by the fact that the calculation results are consistent with the experimental results.

Numerical simulation on size effect of copper with nano-scale twins

To understand the tensile deformation of electro-deposited Cu with nano-scale twins, a numerical study was carried out based on a conventional theory of mechanism-based strain gradient plasticity （CMSG）. The concept of twin lamella strengthening zone was used in terms of the cohesive interface model to simulate grain-boundary sliding and separation. The model included a number of material parameters, such as grain size, elastic modulus, plastic strain hardening exponent, initial yield stress, as well as twin lamellar distribution, which may contribute to size effects of twin layers in Cu polycrystalline. The results provide information to understand the mechanical behaviors of Cu with nano-scale growth twins.

Iterative regularization method for image denoising with adaptive scale parameter

In order to decrease the sensitivity of the constant scale parameter, adaptively optimize the scale parameter in the iteration regularization model （IRM） and attain a desirable level of applicability for image denoising, a novel IRM with the adaptive scale parameter is proposed. First, the classic regularization item is modified and the equation of the adaptive scale parameter is deduced. Then, the initial value of the varying scale parameter is obtained by the trend of the number of iterations and the scale parameter sequence vectors. Finally, the novel iterative regularization method is used for image denoising. Numerical experiments show that compared with the IRM with the constant scale parameter, the proposed method with the varying scale parameter can not only reduce the number of iterations when the scale parameter becomes smaller, but also efficiently remove noise when the scale parameter becomes bigger and well preserve the details of images.

Approximation to NLAR(p) with Wavelet Neural Networks

Recently, wavelet neural networks have become a popular tool for non-linear functional approximation. Wavelet neural networks, which basis functions are orthonormal scalling functions, are more suitable in approximating to function. Based on it, approximating to NLAR(p) with wavelet neural networks is studied.

THE FORMATION AND DEVELOPMENT OF A MESOSCALE CONVECTIVE SYSTEM WITH HEAVY RAINFALL ALONG SOUTH CHINA COASTAL AREA

Observational analysis shows that a Mesoscale Convective System (MCS) occurred on May 13-14 2004 along the coastal area in South China. The MCS initiated among the southwesterly flows within a west-east orientation low-level shear line. Associated with the system, in its subsequent development stages, no distinct vortex circulation developed in low-level. Instead, a cyclonic flow disturbance was observed in the mid-troposphere. How the convection starts to develop and evolve into a MCS With observational analysis and numerical simulation, the problem has been studied. The high-resolution MM5 simulation shows that topographic convergence along the coastal line and the nearby mountains in western South China plays an important role to initiate the MCS convection. Once the convection occurs, due to the condensation heating, a cooperative interaction between the preexisting mid-level disturbance and convection is created, which may greatly affect the MCS development during periods when the system continues moving eastward. Compared to some typical MCS that happen in Southern China, which are usually accompanied with upward development of cyclonic vorticity, the development and evolution of the investigated MCS shows distinguishing features. In this article, the physical mechanisms responsible for the intensification of mid-level disturbance are discussed, and a viewpoint to interpret the effects of mid-level disturbance on the MCS organizational development is proposed.

Simulation study on fluctuant flow stress scale effect

Crystal plasticity theory was used to simulate upsetting tests of different dimensions and grain size micro copper cylinders in this study on the fluctuant flow stress scale effect. Results showed that with the decrease of billet grain quantity, flow stress fluctuation is not always increased, but there is a maximum. Through this study, the fluctuant flow stress scale effect can be understood deeper, and relevant necessary information was obtained for further prediction and control of this scale effect and to design the microforming process and die.

Effect of Spatial and Temporal Scales on Habitat Suitability Modeling:A Case Study of Ommastrephes bartramii in the Northwest Pacific Ocean

Temporal and spatial scales play important roles in fishery ecology,and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution.The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling,with the western stock of winter-spring cohort of neon flying squid （Ornmastrephes bartramii） in the northwest Pacific Ocean as an example.In this study,the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature （SST） from remote sensing during August to October of 2003-2008 were used.We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales （0.5°,1 ° and 2°）,four longitude scales （0.5°,1°,2° and 4°）,and three temporal scales （week,fortnight,and month）.The coefficients of variation （CV） of the weekly,biweekly and monthly suitability index （SI） were compared to determine which temporal and spatial scales of SI model are more precise.This study shows that the optimal temporal and spatial scales with the lowest CV are month,and 0.5° latitude and 0.5° longitude for O.bartramii in the northwest Pacific Ocean.This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts.We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.

IMPACT OF THE INITIALIZATION ON MESOSCALE MODEL PREDICTION IN SOUTH CHINA

1 INTRODUCTION The initial state of the atmosphere is one of the key factors that affect the result of NWP. With the development of increasingly finer NWP, the quality of initial atmospheric state has been drawing more and more attention . GRAPES 3D- Var （Global and Regional Assimilation and Prediction Enhanced System , a three-dimensional variational data assimilation subsystem developed by the Chinese Academy of Atmospheric Sciences, makes a solution to the issue of NWP data vacancy in China. Owing to it, quantitative application of satellite and radar data in NWP has significant breakthroughs. With the assimilation system of GRAPES 3D-Var and GRAPES regional mesoscale model, this work compares a control and assimilation experiment with regard to a cold air surge affecting south China in late December 2004 and analyzes the sensitivity of mesoscale model forecast on initial values and the effect of initialization on the improvement of forecasting capabilities.

Mesh Size Effect in Numerical Simulation of Blast Wave Propagation and Interaction with Structures

Numerical method is popular in analysing the blast wave propagation and interaction with structures.However,because of the extremely short duration of blast wave and energy trans-mission between different grids,the numerical results are sensitive to the finite element mesh size.Previous numerical simulations show that a mesh size acceptable to one blast scenario might not be proper for another case,even though the difference between the two scenarios is very small,indicating a simple numerical mesh size convergence test might not be enough to guarantee accu-rate numerical results.Therefore,both coarse mesh and fine mesh were used in different blast scenarios to investigate the mesh size effect on numerical results of blast wave propagation and interaction with structures.Based on the numerical results and their comparison with field test re-sults and the design charts in TM5-1300,a numerical modification method was proposed to correct the influence of the mesh size on the simulated results.It can be easily used to improve the accu-racy of the numerical results of blast wave propagation and blast loads on structures.

The multiscale modeling and data mining of high-temperature dielectrics of SiO_2/SiO_2 composites

The high temperature dielectrics of Quartz fiber-reinforced silicon dioxide ceramic （Si02/SiO2 ） composites were studied both theoretically and experimentally. A multi-scale theoretical model was developed based on the theory of dielectrics. It was realized to predict dielectric properties at higher temperature （ 〉 1200 ℃） by experimental data mining for correlative coefficients in model. The results show that the dielectrics of SiO2/SiO2, which were calculated with the theoretical model, were in agreement with experimental measured value.

Numerical Simulation of Torrential Rainfall and Vortical Hot Towers in a Midlatitude Mesoscale Convective System

A cloud-resolving model simulation of a mesoscale convective system （MCS） producing torrential rainfall is performed with the finest horizontal resolution of 444 m. It is shown that the model reproduces the observed MCS, including its rainfall distribution and amounts, as well as the timing and location of leading rainbands and trailing stratiform clouds. Results show that discrete convective hot towers, shown in Vis5D at a scale of 2-5 kin, are triggered by evaporatively driven cold outflows converging with the high-θe air ahead. Then, they move rearward, with respect to the leading rainbands, to form stratiform clouds. These convective towers generate vortical tubes of opposite signs, with more intense cyclonic vorticity occurring in the leading convergence zone. The results appear to have important implications for the improvement of summertime quantitative precipitation forecasts and the understanding of vortical hot towers, as well midlevel mesoscale convective vortices.

IMPACT OF CLOUD DROPLETS SPECTRAL UNCERTAINTY ON MESOSCALE PRECIPITATION

1 INTRODUCTION Cloud radiation is one of the most important and indefinite factors in atmospheric radiation. As shown in a comparative study by Cess et al. with a climate model, differences can be very large in the outcome of varying schemes of cloud parameterization. It is therefore of great significance to have a relatively accurate scheme of cloud parameterization for the atmospheric radiative transfer process. According to the Mie＇s scattering theory, the scale parameter of the particulate has a very important effect on its optical property. It is then seen that the number concentration and size distribution of cloud droplets play an important in the determination of the optical properties of cloud droplets.

EVOLUTION OF MOIST POTENTIAL VORTICITY DURING A WARM-ZONE HEAVY RAINFALL EVENT IN THE PEARL RIVER DELTA

First,based on routine meteorological data,the synoptic characteristics of a heavy warm-sector rainfall that occurred on June 13,2008 in the Pearl River Delta were analyzed.Second,a mesoscale numerical model,Weather Research and Forecasting(WRFV2.2),was used to simulate the heavy rainfall. Diagnostic analyses were done of moist potential vorticity(MPV)for its horizontal components(MPV2) and vertical components(MPV1)based on the simulation results of WRFV2.2 to identify the mechanism of the rainfall development.The results showed that the heavy rainfall occurred when there were high MPV1 in the upper levels and low MPV1 and high MPV2 in the lower levels.Disturbances of high MPV1 in the upper levels came from the southwest or northwest,those of low MPV1 in the lower levels came from the southwest,and those of high MPV2 came from the south.Disturbances of low MPV1 at low levels were the direct cause of convective instability.Enhanced vertical shear of meridional wind led to increased MPV2 at lower levels,strengthened baroclinicity,and active warm and wet flows.These distributions of MPV helped to trigger the release of unstable energy and produce warm-sector heavy rainfall.As it integrates the evolution of dynamic and thermal fields,MPV is able to reveal the development of this heavy rainfall effectively.

Elastoplastic modeling of mechanical behavior of weak sandstone at different time scales

A unified constitutive model is proposed to describe the mechanical behavior of weak sandstone at different time scales.The instantaneous behavior of this material is characterized by the Drucker-Prager elastoplastic model,while the time-dependent deformation is described in terms of the microstructure evolution.This evolution is numerically simulated by progressive degradation of the elastic modulus and failure strength of the material.The proposed model is used to simulate the instantaneous triaxial compression and the multi-loading creep tests.Generally,good concordance is obtained between numerical simulations and experimental data.The proposed model is capable of describing the main features of these rocks,particularly irreversible deformations,pressure dependency,volumetric transition between compaction and dilatancy,and creep behavior.

Evaluating the impact of spatio-temporal scale on CPUE standardization

This study focused on the quantitative evaluation of the impact of the spatio-temporal scale used in data collection and grouping on the standardization of CPUE(catch per unit effort).We used the Chinese squid-jigging fishery in the northwestern Pacific Ocean as an example to evaluate 24 scenarios at different spatio-temporal scales,with a combination of four levels of temporal scale(weekly,biweekly,monthly,and bimonthly)and six levels of spatial scale(longitude×latitude:0.5°×0.5°,0.5°×1°,0.5°×2°,1°×0.5°,1°×1°,and 1°×2°).We applied generalized additive models and generalized linear models to analyze the24 scenarios for CPUE standardization,and then the differences in the standardized CPUE among these scenarios were quantified.This study shows that combinations of different spatial and temporal scales could have different impacts on the standardization of CPUE.However,at a fine temporal scale(weekly)different spatial scales yielded similar results for standardized CPUE.The choice of spatio-temporal scale used in data collection and analysis may create added uncertainty in fisheries stock assessment and management.To identify a cost-effective spatio-temporal scale for data collection,we recommend a similar study be undertaken to facilitate the design of effective monitoring programs.

THREE-DIMENSIONAL VARIABLES ALLOCATION IN MESOSCALE MODELS

Forecasts and simulations are varied owing to different allocation of 3-dimensional variables in mesoscale models. No attempts have been made to address the issue of optimizing the simulation with a 3-dimensional variables distribution that should come to be. On the basis of linear nonhydrostatic anelastic equations, the paper hereby compares, mainly graphically, the computational dispersion with analytical solutions for four kinds of 3-dimensional meshes commonly found in mesoscale models, in terms of frequency, horizontal and vertical group velocities. The result indicates that the 3-D mesh C/CP has the best computational dispersion, followed by Z/LZ and Z/LY, with the C/L having the worst performance. It is then known that the C/CP mesh is the most desirable allocation in the design of nonhydrostatic baroclinic models. The mesh has, however, larger errors when dealing with shorter horizontal wavelengths. For the simulation of smaller horizontal scales, the horizontal grid intervals have to be shortened to reduce the errors. Additionally, in view of the dominant use of C/CP mesh in finite-difference models, it should be used in conjunction with the Z/LZ or Z/LY mesh if variables are allocated in spectral models.

AN AIR POLLUTION PREDICTION TECHNIQUE FOR URBAN DISTRICTS BASED ON MESO-SCALE NUMERICAL MODEL

Taking Shenzhen city as an example, the statistical and physical relationship between the density of pollutants and various atmospheric parameters are analyzed in detail, and a space-partitioned city air pollution potential prediction scheme is established based on it. The scheme considers quantitatively more than ten factors at the surface and planetary boundary layer (PBL), especially the effects of anisotropy of geographical environment, and treats wind direction as an independent impact factor. While the scheme treats the prediction equation respectively for different pollutants according to their differences in dilute properties, it considers as well the possible differences in dilute properties at different districts of the city under the same atmospheric condition, treating predictions respectively for different districts. Finally, the temporally and spatially high resolution predictions for the atmospheric factors are made with a high resolution numerical model, and further the space-partitioned and time-variational city pollution potential predictions are made. The scheme is objective and quantitative, and with clear physical meaning, so it is suitable to use in making high resolution air pollution predictions.

ROBUST SLIDING MODE DECENTRALIZED CONTROL FOR A CLASS OF NONLINEAR INTERCONNECTED LARGE-SCALE SYSTEM WITH NEURAL NETWORKS

A new decentralized robust control method is discussed for a class of nonlinear interconnected largescale system with unknown bounded disturbance and unknown nonlinear function term. A decentralized control law is proposed which combines the approximation method of neural network with sliding mode control. The decentralized controller consists of an equivalent controller and an adaptive sliding mode controller. The sliding mode controller is a robust controller used to reduce the track error of the control system. The neural networks are used to approximate the unknown nonlinear functions, meanwhile the approximation errors of the neural networks are applied to the weight value updated law to improve performance of the system. Finally, an example demonstrates the availability of the decentralized control method.

Reduced Fidelity Susceptibility in One-Dimensional Transverse Field Ising Model

We study critical behaviors of the reduced fidelity susceptibility for two neighboring sites in the onedimensional transverse field Ising model. It is found that the divergent behaviors of the susceptibility take the form of square of logarithm, in contrast with the global ground-state fidelity susceptibility which is power divergence. In order to perform a scaling analysis, we take the square root of the susceptibility and determine the scaling exponent analytically and the result is further confirmed by numerical calculations.