黑龙江哈尔滨白渔泡国家湿地公园沼泽、林地和农田土壤物理、化学和生物性质差异

为了揭示黑龙江哈尔滨白渔泡国家湿地公园沼泽、林地和农田土壤物理、化学和生物性质的差异,于2018年7月25日~8月2日,在湿地公园内,在天然芦苇(Phragmites australis)沼泽、林地、旱田和水田中设置采样地,采集不同深度(0~10 cm、10~20 cm和20~30 cm)的土壤样品,测定土壤样品的物理、化学和生物指标。研究结果表明,白渔泡国家湿地公园不同采样地土壤指标存在差异;与天然芦苇沼泽土壤相比,其它采样地土壤的含水量明显偏低,土壤全氮、全磷、碱解氮和有机质含量都明显偏小,水田土壤速效磷含量偏大;天然芦苇沼泽土壤脲酶、硝酸还原酶、纤维素酶、蛋白酶和β-葡萄糖苷酶活性都高于林地和农田土壤,水田0~10 cm和10~20 cm深度土壤的硝酸还原酶活性显著高于旱田和林地;与天然芦苇沼泽土壤相比,旱田土壤小于0.25 mm的小团聚体含量偏大,而其它采样地土壤的各粒级团聚体的比例变化较小,水田土壤团聚体平均重量直径比天然芦苇沼泽和旱田土壤低。     

Transient‐state groundwater flow in various geometries with wells at arbitrary positions: analytical methods

We have developed a method for analytically solving the porous medium flow equation in many different geometries for horizontal (two‐dimensional), homogeneous and isotropic aquifers containing impermeable boundaries and any number of pumping or injection wells located at arbitrary positions within the system. Solutions and results are presented for rectangular and circular aquifers but the method presented here is easily extendible to many geometries. Results are also presented for systems where constant head boundary conditions can be emulated internal to the aquifer boundary. Recommendations for extensions of the present work are briefly discussed. Copyright © 2003 John Wiley & Sons, Ltd.     

用遗传算法对自动控制系统数学模型寻优

探讨用遗传算法对数学模型进行优化。考虑到控制系统稳健性的要求 ,用遗传算法寻找出控制系统最佳稳定域 ,实现控制系统数学模型的寻优。阐述了用遗传算法求解问题的步骤和参数的取值 ,并用仿真实验对优化结果进行了检验。结果表明 :在控制系统数学模型的优化中 ,遗传算法具有其他算法无可比拟的优越性。     

青藏块体东北缘地壳水平运动状态

应用青藏块体东北缘1999～2003年多期GPS观测资料，计算了不同时段GPS点水平运动速率。通过分析发现：甘青块体可分为东部块体和西部块体，东、西部块体的运动状态存在明显的差异；受2001年11月14日昆仑Ms8．1地震的影响，震后地壳运动状态发生了明显的改变。     

广西芒场锡多金属矿田稳定同位素组成对矿床成因探讨

笔者曾对广西芒场锡多金属矿田的稳定同位素进行研究。本文根据硫、铅、氢、氧、碳等稳定同位素组成和锶的初始值提供的信息.探讨了矿床成因。并结合矿田矿床地质特征、控矿条件及有关统计参数,参考前人对矿床认识的基础上,修正提出了该矿田混合热液成矿模式,可供类似矿床研究和找矿的参考。     

Numerical prediction of blast‐induced stress wave from large‐scale underground explosion

This paper presents a numerical model for predicting the dynamic response of rock mass subjected to large‐scale underground explosion. The model is calibrated against data obtained from large‐scale field tests. The Hugoniot equation of state for rock mass is adopted to calculate the pressure as a function of mass density. A piecewise linear Drucker–Prager strength criterion including the strain rate effect is employed to model the rock mass behaviour subjected to blast loading. A double scalar damage model accounting for both the compression and tension damage is introduced to simulate the damage zone around the charge chamber caused by blast loading. The model is incorporated into Autodyn3D through its user subroutines. The numerical model is then used to predict the dynamic response of rock mass, in terms of the peak particle velocity (PPV) and peak particle acceleration (PPA) attenuation laws, the damage zone, the particle velocity time histories and their frequency contents for large‐scale underground explosion tests. The computed results are found in good agreement with the field measured data; hence, the proposed model is proven to be adequate for simulating the dynamic response of rock mass subjected to large‐scale underground explosion. Extended numerical analyses indicate that, apart from the charge loading density, the stress wave intensity is also affected, but to a lesser extent, by the charge weight and the charge chamber geometry for large‐scale underground explosions. Copyright © 2004 John Wiley & Sons, Ltd.     

Reliability assessment of serviceability performance of braced retaining walls using a neural network approach

In urban environments, one major concern with deep excavations in soft clay is the potentially large ground deformations in and around the excavation. Excessive movements can damage adjacent buildings and utilities. There are many uncertainties associated with the calculation of the ultimate or serviceability performance of a braced excavation system. These include the variabilities of the loadings, geotechnical soil properties, and engineering and geometrical properties of the wall. A risk‐based approach to serviceability performance failure is necessary to incorporate systematically the uncertainties associated with the various design parameters. This paper demonstrates the use of an integrated neural network–reliability method to assess the risk of serviceability failure through the calculation of the reliability index. By first performing a series of parametric studies using the finite element method and then approximating the non‐linear limit state surface (the boundary separating the safe and ‘failure’ domains) through a neural network model, the reliability index can be determined with the aid of a spreadsheet. Two illustrative examples are presented to show how the serviceability performance for braced excavation problems can be assessed using the reliability index. Copyright © 2005 John Wiley & Sons, Ltd.     

Methane‐related microbial gypsum calcitization in stromatolites of a marine evaporative setting (Münder Formation,Upper Jurassic,Hils Syncline,north Germany)

Fossil stromatolites may reveal information about their hydrochemical palaeoenvironment, provided that assignment to a specific microbial community and a corresponding biogeochemical mechanism of formation can be made. Tithonian stromatolites of the Münder Formation at Thüste, north Germany, have traditionally been considered as formed by intertidal cyanobacterial communities. However, thin sections of the stromatolites show elongated angular traces of former gypsum crystals in a dense arrangement, but no algal or cyanobacterial filament traces. Moreover, high Fe²⁺ and Mn²⁺ contents, oxygen‐isotope and sulphur‐isotope ratios of carbonate‐bound sulphates, and sulphurized hydrocarbon biomarkers of the stromatolitic carbonate indicate that CaCO₃ precipitation occurred near the oxic–anoxic interface as a result of intensive bacterial sulphur cycling rather than photosynthetic activity. Furthermore, anaerobic oxidation of methane by Archaea may have driven CaCO₃ precipitation in deeper parts of the biofilm community, as reflected by high concentrations of squalane with a strongly negative δ¹³C in conjunction with evaporite pseudomorphs showing extremely low δ¹³C_Carb ratios. Consequently, the Thüste stromatolites are now interpreted as having initially formed by gypsum impregnation of biofilms. Subsequently, early Mg‐calcitic calcitization within the biofilms occurred because of combined bacterial iron, manganese and sulphate reduction, with an increasing contribution of anaerobic oxidation of methane with depth. This model plausibly explains the prominent preservation of signals derived from oxygen‐independent metabolic pathways, whereas virtually no geochemical record exists for an aerobic community that may, nevertheless, have prevailed at the stromatolite surface. Photic‐zone stromatolites with a prominent signal of anaerobic oxidation of methane may be common in, and indicative of, oxygen‐depleted sulphate‐bearing environments with high rates of methane production, conditions that possibly were fulfilled at the Archaean to Proterozoic transition.