轴压下两体力学模型的转化条件及影响因素分析

接触界面的相互作用是影响工程稳定的重要因素,基于接触面两侧介质的实际受力状态,采用一体两介质力学模型与两体两介质力学模型加以描述。通过一体和两体模型试件的轴压破坏试验,分析了两种模型的力学响应的差异,并认为：一体两介质力学模型在符合一定条件情况下可以转变为两体两介质力学模型。此外,还对影响两种力学模型性能的参数进行了分析。提出对一体两介质力学模型力学性能产生影响的参量是低强度介质与高强度介质的静载极限强度比k以及两种介质之间的黏结力c;对两体两介质力学模型力学性能产生影响的主要参量除了k之外,尚有两种介质的断裂韧度比? 、体积比? 以及界面的粗糙程度     

Controlling factors of the δ 11B-pH proxy and its research direction

Significant boron isotope fractionation occurs in nature (?70 ‰ to +75 ‰) due to the high geochemical reactivity of boron and the large relative mass difference between ¹⁰B and ¹¹B. Since the 1990s, reconstruction of ancient seawater pH using the isotopic composition of boron in bio-carbonates (δ ¹¹B_carb), and then calculation of the past pCO₂ have become important issues for the international isotope geochemistry community, and are called the δ ¹¹B-pH proxy. Although many achievements have been made by this proxy, various aspects of boron systematics require rigorous evaluation. Based on the previous researches, mechanism of boron isotope fractionation, variation of boron isotope (δ ¹¹B) in nature (especially in bio-carbonates) and controlling factors of the δ ¹¹B-pH proxy, such as the dissociation constant of B(OH)₃ in seawater (pK_a), the δ ¹¹B of seawater (δ ¹¹B_SW), the boron isotopic fractionation factor between B(OH) ₄ ^? and B(OH)₃ (α _4–3), and the incorporated species of boron into bio-carbonates, are reviewed in detail and the research directions of this proxy are proposed. Generally, the controversy about pK_a, δ ¹¹B_sw, and α _4–3 is relatively less, but whether boron incorporated into bio-carbonates only in the form of B(OH) ₄ ^? remains doubtful. In the future, it is required that the physicochemical processes that control boron incorporation into carbonates be rigorously characterized and that the related chemical and isotopic fractionation be quantified. It is also necessary and important to establish a “best-fit empirically equation” between δ ¹¹B_carb and pH of seawater based on the precipitation experiments of inorganic or culture experiments of corals or foraminifera. In addition, extended application of the δ ¹¹B-pH proxy to the earlier part of the Phanerozoic relying on the Brachiopods is worthy of studying. Like other geochemical indicators, there are limiting factors of δ ¹¹B; however, it remains a very powerful tool in the reconstruction of past seawater pH at present.     

Possible Sources of Forecast Errors Generated by the Global/Regional Assimilation and Prediction System for Landfalling Tropical Cyclones. Part Ⅱ: Model Uncertainty

This paper investigates the possible sources of errors associated with tropical cyclone (TC) tracks forecasted using the Global/Regional Assimilation and Prediction System (GRAPES). In Part I, it is shown that the model error of GRAPES may be the main cause of poor forecasts of landfalling TCs. Thus, a further examination of the model error is the focus of Part II. Considering model error as a type of forcing, the model error can be represented by the combination of good forecasts and bad forecasts. Results show that there are systematic model errors. The model error of the geopotential height component has periodic features, with a period of 24 h and a global pattern of wavenumber 2 from west to east located between 60°S and 60°N. This periodic model error presents similar features as the atmospheric semidiurnal tide, which reflect signals from tropical diabatic heating, indicating that the parameter errors related to the tropical diabatic heating may be the source of the periodic model error. The above model errors are subtracted from the forecast equation and a series of new forecasts are made. The average forecasting capability using the rectified model is improved compared to simply improving the initial conditions of the original GRAPES model. This confirms the strong impact of the periodic model error on landfalling TC track forecasts. Besides, if the model error used to rectify the model is obtained from an examination of additional TCs, the forecasting capabilities of the corresponding rectified model will be improved.     

基于小波分解的动态变形预报

阐述了小波变换和多分辨率分析的基本原理,简要地介绍了离线预报和在线预报两种不同的变形预报方式,并在此基础上提出了基于小波分解的动态变形预报的方法,并通过实际算例证明了这种方法的有效性。     

Comparison of parameter uncertainty analysis techniques for a TOPMODEL application

Parameter uncertainty in hydrologic modeling is crucial to the flood simulation and forecasting. The Bayesian approach allows one to estimate parameters according to prior expert knowledge as well as observational data about model parameter values. This study assesses the performance of two popular uncertainty analysis (UA) techniques, i.e., generalized likelihood uncertainty estimation (GLUE) and Bayesian method implemented with the Markov chain Monte Carlo sampling algorithm, in evaluating model parameter uncertainty in flood simulations. These two methods were applied to the semi-distributed Topographic hydrologic model (TOPMODEL) that includes five parameters. A case study was carried out for a small humid catchment in the southeastern China. The performance assessment of the GLUE and Bayesian methods were conducted with advanced tools suited for probabilistic simulations of continuous variables such as streamflow. Graphical tools and scalar metrics were used to test several attributes of the simulation quality of selected flood events: deterministic accuracy and the accuracy of 95 % prediction probability uncertainty band (95PPU). Sensitivity analysis was conducted to identify sensitive parameters that largely affect the model output results. Subsequently, the GLUE and Bayesian methods were used to analyze the uncertainty of sensitive parameters and further to produce their posterior distributions. Based on their posterior parameter samples, TOPMODEL’s simulations and the corresponding UA results were conducted. Results show that the form of exponential decline in conductivity and the overland flow routing velocity were sensitive parameters in TOPMODEL in our case. Small changes in these two parameters would lead to large differences in flood simulation results. Results also suggest that, for both UA techniques, most of streamflow observations were bracketed by 95PPU with the containing ratio value larger than 80 %. In comparison, GLUE gave narrower prediction uncertainty bands than the Bayesian method. It was found that the mode estimates of parameter posterior distributions are suitable to result in better performance of deterministic outputs than the 50 % percentiles for both the GLUE and Bayesian analyses. In addition, the simulation results calibrated with Rosenbrock optimization algorithm show a better agreement with the observations than the UA’s 50 % percentiles but slightly worse than the hydrographs from the mode estimates. The results clearly emphasize the importance of using model uncertainty diagnostic approaches in flood simulations.     

考虑土-结构相互作用的振动台实时子结构试验仿真分析

本文基于状态空间方程进行了实时子结构试验的初步探索,提出了一种新的实时子结构试验方法。通过simulink仿真发现,这种方法能很好地再现整体分析的结构反应。最后,对考虑土-结构相互作用的振动台实时子结构试验进行了仿真分析。     

The first Surijokocixiidae (Insecta: Hemiptera: Fulgoromorpha) from the Triassic of China

A planthopper originally assigned to the genus Boreocixius in Surijokocixiidae (Surijokocixioidea, Fulgoromorpha) from the Ladinian (Middle Triassic) of Tongchuan in Shaanxi, northwestern China is described as Boreocixius tongchuanensis Zhang et al. sp. nov. As the third species ascribed to the genus, it differs from its congeners in having the much larger tegmen with postnodal veinlets and pigmented bands, providing new morphological information for Boreocixius. The establishment of the new species further increases the diversity of Boreocixius and Surijokocixiidae as well.     

一种基于马尔可夫随机场的影像纹理分类方法

针对纹理影像先估计出其马尔可夫随机场参数,后运用多元统计分析中模糊聚类分析的数学方法进行定量分类,从而为解决划分上的不确定性现象找出描述方法,获得客观的分类结果。     

南海夏季风爆发日期和强度的短期气候预测方法研究

利用合成及相关统计方法，研究冬季南海季风指数与850hPa风场、500hPa高度、海表温度、OLR等环境场的相互关系及其影响南海夏季风活动的可能机制。指出冬季南海季风指数及环境场的异常特征可以作为预测南海夏季风活动的前兆信号。在此基础上建立了预测南海夏季风爆发日期和强度的概念模型，1998－2001年的预测试验取得了较好成绩。     

上高县紫皮大蒜种植气候适宜性区划

基于紫皮大蒜生长周期和当地农业气象条件,得到上高县紫皮大蒜气候适宜性指标：10—11月的最低气温、10月至次年4月的平均气温和平均降水量以及2—4月的累计日照时数。利用1970—2020年宜春市和新余市辖区内共12个地面观测站的气象资料,采用GIS建立上高县紫皮大蒜种植区划因子地理空间分析模型。依据分区等级指标,将上高县划分为最适宜、一般适宜和不适宜3个紫皮大蒜气候种植区。