Stochastic dynamic model of SARS spreading

Based upon the simulation of the stochastic process of infection, onset and spreading of each SARS patient, a system dynamic model of SRAS spreading is constructed. Data from Vietnam is taken as an example for Monte Carlo test. The preliminary results indicate that the time-dependent infection rate is the most important control factor for SARS spreading. The model can be applied to prediction of the course with fluctuations of the epidemics, if the previous history of the epidemics and the future infection rate under control measures are known.     

Remote intelligent identification system of structural damage

The focus of this paper is to build the damage identify system, which performs “system identification“ to detcct the positions and extents of structural damages. The identification of structural damage can be characterized as a nonlinear process which linear prediction models such as linear regression are not suitable. However. neural network techniques may provide an effective tool for system identification. The method of damage identification using the radial basis function neural network (P, BFNN) is presented in this paper. Using this method, a simple reinforced concrete structure has been tested both in the absence and presence of noise. The resuits show that the RBFNN identification technology can he used with related success for the solution of dynamic damage identification problems, even in the presence of a noisy identify data. Furthermore, a remote identification system based on that is set up with Java Technologies.     

Nonequilibrium Thermodynamic and Dissipative Structure Mechanism of Fluidized Beds

Fluidized beds are nonlinear dynamic systems that exchange mass and energy with outside. They are governed not only by fluid dynamics, but by thermodynamics, especially the second law of thermodynamics as well. According to Prigogine's dissipative structure theory, the following have been concluded: (1) a fixed bed is on thermodynamic blanch, and bubbling, turbulent and fast beds are on the dissipatve structure branches. (2) Entropy in fluidized beds is divided into two parts: entropy production and entropy flux. The latter increases with gas velocity and decreases with pressure of the systems. That means the entropy of a system may reduce and the system with higher gas velocity behaves as dissipative structure characteristics. (3) For a given velocity, a fluidized bed operates stably on the whole, but it is unstable to local gas-solid phases. The unstable phases are described by fluid dynamic equations, While the minimum of system energy function assures whole stability of the system. (4) A transition criterion of a bubbling bed is derived from Prigogine's stability theory.     

Effects of historical land cover changes on climate

In order to explore the influence of anthropogenic land use on the climate system during the last mil- lennium, a set of experiments is performed with an Earth system model of intermediate complexity—— the McGill Paleoclimate Model (MPM-2). The present paper mainly focuses on biogeophysical effects of historical land cover changes. A dynamic scenario of deforestation is described based on changes in cropland fraction (RF99). The model simulates a decrease in global mean annual temperature in the range of 0.09-0.16℃, especially 0.14-0.22℃ in Northern Hemisphere during the last 300 years. The responses of climate system to GHGs concentration changes are also calculated for comparisons. Now, afforestation is becoming an important choice for the enhancement of terrestrial carbon sequestration and adjustment of regional climate. The results indicate that biogeophysical effects of land cover changes cannot be neglected in the assessments of climate change.     

Dynamic prediction of building subsidence deformation with data-based mechanistic self-memory model

This paper describes a building subsidence deformation prediction model with the self-memorization principle.According to the non-linear specificity and monotonic growth characteristics of the time series of building subsidence deformation,a data-based mechanistic self-memory model considering randomness and dynamic features of building subsidence deformation is established based on the dynamic data retrieved method and the self-memorization equation.This model first deduces the differential equation of the building subsidence deformation system using the dynamic retrieved method,which treats the monitored time series data as particular solutions of the nonlinear dynamic system.Then,the differential equation is evolved into a difference-integral equation by the self-memory function to establish the self-memory model of dynamic system for predicting nonlinear building subsidence deformation.As the memory coefficients of the proposed model are calculated with historical data,which contain useful information for the prediction and overcome the shortcomings of the average prediction,the model can predict extreme values of a system and provide higher fitting precision and prediction accuracy than deterministic or random statistical prediction methods.The model was applied to subsidence deformation prediction of a building in Xi’an.It was shown that the model is valid and feasible in predicting building subsidence deformation with good accuracy.     

Dynamic Response during the Online Compensation of Misalignment Based on Auxiliary Electromagnetic Support

A new support structure, named auxiliary electromagnetic support, is introduced to adjust the position of rotor shaft online. The auxiliary electromagnetic support consists of sliding bearing, iron core, radial spring, pedestal and electromagnet that could adjust the rotor position. In a rotor system adopting two auxiliary electromagnetic supports, the online compensation of misalignment was achieved without stopping work. Using the proposed auxiliary electromagnetic support, the analytical solution of dynamic response was obtained by analyzing a simulated single-degree-of-freedom（SDOF） system. And the dynamic response of the multi-degrees-of-freedom（MDOF） system in the experiment is acquired using Newmark variable step-size integration method. Further the new design is tested in a symmetrical single-disk rotor-bearing system. With both the theory analysis and the experimental results, some conclusions are obtained about the relationship between the vibration and the system damping which are related to system stability.     

Study on seal improvement and rotor thrust control of centrifugal compressor

Fluid pressure variations due to process fluctuations or balance drum seal degradation can result in rotor thrust increasing that may jeopardize thrust bearing and compressor’s reliability. Also, the leakage flow through balance drum seal can seriously affect the efficiency of compressor. A method that can improve both the efficiency and reliability of centrifugal compressor is presented. The method focused on rotor thrust control and balance drum seal upgrading. The low leakage feature of Dry-Gas-Seal（DGS）, high reliability of labyrinth, and the feasibility of upgrading existing structure are taken into account at the same time to design a combined labyrinth-dry gas seal system on the balancing drum. Based on the combined seal system, a Fault Self-Recovering（FSR） system for the fault of rotor shaft displacement is introduced to assure the safety and reliability of centrifugal compressor. The modern Computational Fluid Dynamics（CFD） is used to validate this envision. The numerical result and relevant information indicate that the combined sealing system could improve the efficiency of the centrifugal compressor by about 4%.     

Computational Unified Set Theory and Application

The computational unified set model （CUSM） as the latest progress of Unified Set theory is introduced in this paper. The model combines unified set theory, information granule, complex adaptive system and cognitive science to present a new approach to simulate the cognition of human beings that can be viewed as the evolutionary process through the automatic learning from data sets. The information granule, which is the unit of cognition in CUSM, can be synthesized and created by the basic operators. It also can form the granule network by linking with other granules. With the learning from database, the system can evolve under the pressure of selection. As the adaptive results, fuzzy sets, vague sets and rough sets, etc can emerge out spontaneously. The CUSM answers the question of the origin of the uncertainties in thinking process described by unified set theory, that is due to the emergent properties of a holistic system of multiple cognitive units. And also the CUSM creates a dynamic model that can adapt to the environment. As a result, the ＂closed world＂ limitation in machine learning may be broken. The paper also discusses the applications of CUSM in roles discovery, problem solving, clustering analysis and data mining etc. The main features of the model comparing with the classical approaches toward those problems are its adaptability, flexibility and robustness but not accuracy.     

Global analysis theory of climate system and its applications

The idea and main theoretical results of the global analysis theory of climate system are briefly summarized in this paper. A theorem on the global behavior of climate system is given, i.e. there exists a global attractor in the dynamical equations of climate, any state of climate system will be evolved into the global attractor as time increases,indicating the nonlinear adjustment process of climate system to external forcing. The different effects of external forcing, dissipation and nonlinearity on the long-term behavior of solutions are pointed out, and some main applications of the global analysis theory are also introduced. Especially, three applications, the adjustment and evolution processes of climate, the principle of numerical model design and the optimally numerical integration, are discussed.     

P systems based multi-objective optimization algorithm

Based on P systems, this paper proposes a new multi-objective optimization algorithm (PMOA). Similar to P systems, PMOA has a cell-like structure. The structure is dynamic and its membranes merge and divide at different stages. The key rule of a membrane is the communication rule which is derived from P systems. Mutation rules are important for the algorithm, which has different ranges of mutation in different membranes. The cooperation of the two rules contributes to the diversity of the population, the conquest of the muhimodality of objective function and the convergence of algorithm. Moreover, the unique structure divides the whole population into several sub populations, which decreases the computational complexity. Almost a dozen popular algorithms are compared using several test problems. Simulation results illustrate that the PMOA has the best performance. Its solutions are closer to the true Pareto-optimal front     

超熵产生在一维自组织气候模型中的应用

该文给出了包含云和辐射动态反馈的一维气体气候模型，根据Ｌｉａｐｕｍｏｖ稳定性理论，以超熵产生作为气候为判据，讨论了云重温度变化率，太阳辐射、地表反照率和大气有效发射率与气候突变的关系，所得结论与实际定性一致。     

短期区域气候预测系统及回报试验

为了提高短期区域气候预测准确率,针对我国大陆区域及周边海域,通过国家气候中心全球海气耦合模式嵌套一个区域大气-海洋耦合模式,建立了一套短期区域气候预测系统。利用该预测系统对2006-2011年逐年7月的气候特征进行了回报试验,对比分析了区域模式相对于全球模式预测高空形势场的差异,评估了预测系统对地面温度和降水的预测能力。试验表明:同化后,初估场质量显著提高;区域模式在预测高空形势场方面优于全球模式;相对于单独的大气模式,海气耦合模式在预测中低空的温度和湿度方面有一定的改善;系统对地面气温和降水均具有一定的预报能力,其中降水预测稍好。     

杭州湾地区生态-气候监测预警系统及其应用

基于3S技术、中尺度模式及动态植被模式建立了生态-气候监测预警系统,其中包括4个子系统:土地覆盖动态监测系统、城市热岛动态监测系统、城市气候监测系统和植被NPP模拟与监测系统.利用土地覆盖监测系统可以精确地获取各种土地覆盖类型,并分析土地利用覆盖变化;利用土地覆盖监测系统结果、Landsat-TM红外影像及常规气象资料构建城市热岛监测系统,分析该地区城市热岛效应的时空变化:利用土地覆盖分类结果,对改变下垫面进行敏感性试验,模拟城市发展对城市气候的影响,构建城市气候监测系统:利用LPJ模拟杭州湾地区植被NPP及对气候变化的响应,构建植被NPP模拟与监测系统.生态预警系统可以实时监测土地覆盖、城市热岛、城市气候、植被NPP变化.对保护耕地资源、改善生态环境、提高城市人居环境、合理利用气候资源、保持农林业的可持续发展有着重要的指导和现实意义.     

我国动力气候模式预测系统的研制及应用

动力气候模式是目前国际上开展气候预测的主要工具。经过8年多的研制和发展,国家气候中心已建立起第一代动力气候模式预测业务系统,并以此为平台,形成了一套包括月、季节到年际时间尺度的模式预测业务。20年历史回报试验和1年多的试验性业务运行结果表明,该系统对东亚区域的季节预测具有较好的预测能力,其预测结果巳经成为我国短期气候预测业务的重要参考信息。     

Advancement and prospect of short-term numerical climate prediction

The defects of present methods of short-term numerical climate prediction are discussed in this paper, and four challenging problems are put forward. Considering our under developed computer conditions, we should innovate in the approcuch of numerical climate prediction on the basis of our own achievements and experiences in the field of short-term numerical climate prediction. It is possibly an effective way to settle the present defects of short-term numerical climate prediction.     

水文水资源管理经济中气候变化影响评估的不确定性问题

大多数关于气候变化对水文过程影响评估的文献中,对大气模型中存在的显著的不确定性往往考虑不足.在很多重要的领域,GCM生成的长期预测很少能用于未来水资源规划与管理,因为其结果无法对变化趋势进行准确的描述,也就是对水文变量增加或减少趋势的预测缺乏可信度.一项借助于14个GCM模型以及不同发展情景(包括基准情景)开展的径流预报集合分析研究验证了这一点.GCM的输出情景作为水平衡模型的输入这种方法用于多瑙河上游未来水文变化的预测.如果将这种预测情景用于预测由气候变化引起的水文变化经济成本,更大的不确定性将会在经济数学模型中产生.著名的Stern"气候变化经济学"评论在水资源管理领域被广泛的应用.在经济学文献中对Stern评论的观点存在很多争议,很多专家对方法的使用和结论提出了一些质疑,本文的实例也证明了这一点.因此,进行气候变化对水文和水资源影响评估的学者们应该意识到不仅在GCM中存在很大的不确定性,大气-水文-经济模型的耦合过程可能会导致更大的不确定性.     

Introduction and systematic assessment for IAP numerical annual climate prediction system

The IAP numerical annual climate prediction system has been presented in this paper. In order to evaluate this annual prediction system, annual ensemble hindcast experiments over a 21-year period from 1980 to 2000 have been done. Systematic assessment shows that this annual prediction system has higher predictability for summer climate in tropic than in extra-tropic area, and higher predictabilities over ocean than over land for the fields of precipitation, sea level pressure and surface air temperature; for 500 hPa geopotential height field, the predictability assuming a zonal distribution decreases from tropic to middle-high latitudes, and in China it is the highest among those of all fields. Correlation analysis shows that the prediction ability of IAP annual prediction system to summer temperature is higher than that to precipitation, and the prediction skill can be remarkably improved by the correction system. Furthermore, the comparison between annual and extraseasonal hindcasts indicates that precipitation hindcasted extraseasonally is better than that done annually, and the major discrepancy exists in middle-high latitudes.     

内蒙古灌木群落物种丰富度与气候的关系

为了验证几种重要的物种多样性地理格局假说(水分能量动态假说、生产力假说、寒冷忍耐假说、生态学代谢假说)在干旱、半干旱地区灌木群落中的适用性, 对内蒙古中西部地区1100 km样线内的灌木群落进行调查, 结合气候数据、植被归一化指数研究不同气候或生产力因子对群落物种丰富度的解释能力。同时研究了不同功能型的植物在物种多样性?气候关系方面的差异, 包括不同的生活型(木本、草本)、水分生态型(旱生、中旱生、中生)。结果表明: 1) 水分能量动态假说能较好地解释本研究区灌木群落多样性的地理格局, 植物能获得的有效水分是影响物种丰富度的主要因素; 2) 研究结果与代谢假说的预测相反, 该假说无法解释干旱、半干旱区的群落多样性格局, 结果不支持寒冷忍耐假说在研究区的适用性, 而生产力也只能解释部分功能型的物种丰富度; 3) 不同功能型的植物对气候、 生产力梯度的响应表现出很大的差异, 物种的生态特性以及种间相互作用对物种丰富度格局有着重要的影响, 深入理解群落的构建机制可能是理解生物多样性的地理格局所必需的。