600 MW机组低压转子叶片裂纹分析

针对某台600 MW亚临界参数汽轮机低压转子的末三级叶片(2Cr12NiMo1W1V钢)出汽侧裂纹进行了宏观形貌观察、化学成分分析、金相组织分析、室温冲击韧性试验、硬度试验,并对断口进行了扫描电镜及能谱分析。结果表明：此次开裂的低压转子叶片,是由于其化学成分Mo元素含量低于标准要求,导致材料的KISCC降低,以及硬度偏低造成裂纹扩展所需的外界启动应力降低,进而在运行过程中拉应力和湿蒸汽的氧化腐蚀共同作用下,发生了应力腐蚀开裂。     

地面运动转动分量的合成方法

假设近场地面运动由体波产生（忽略面波的影响）,根据弹性半空间的平面谐波理论,提出了利用平动分量加速度记录合成地面转动加速时程的方法。该方法考虑了由于实际介质的不均匀性而产生的地震波频散现象。     

高强预腐蚀铝合金单轴拉-拉疲劳断口定量分析

目的通过断口定量分析获得7A09铝合金的疲劳裂纹扩展规律,为7A09铝合金结构的寿命评估提供依据。方法使用EXCO溶液对试验件进行预腐蚀,利用疲劳拉伸机进行疲劳加载直至断裂,使用扫描电镜对疲劳断口进行定量化分析。结果疲劳裂纹在试件的腐蚀坑处萌生,从自由界面附近向纵深发展导致试件的断裂。通过断口分析和Paris公式确定了裂纹的萌生寿命和扩展寿命。结论腐蚀之后的试件裂纹萌生寿命占总寿命的比例下降,当裂纹扩展程度较大之后,受腐蚀影响减轻,得出裂纹扩展速率和应力强度因子的关系。     

An Integrated Monte Carlo Methodology for the calibration of water quality models

This paper proposes an Integrated Monte Carlo Methodology (IMCM) to solve the parameter estimation problem in water quality models. The methodology is based on Bayesian approach and Markov Chain Monte Carlo techniques and it operates by means of four modules: Markov Chain Monte Carlo (MCMC), Moving Feasible Ranges (MFR), Statistical Analysis of the Joint Posterior Distribution (SAD) and Uncertainty Propagation Analysis (UPA). The main innovation of the new proposal lies in the combination of MCMC and MFR modules which provides the joint posterior distribution of the calibrated parameters following the classical Bayesian approach. While MCMC module, based on Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm, is specially designed to sample complex joint posterior shapes within certain parameter ranges, the MFR readjusts these ranges until the coverage of the feasible parameter space is guaranteed. Once the joint posterior distribution is properly defined, the SAD provides the parameter statistics and the UPA performs an analysis of the uncertainty propagation through the model. The possibilities of the new proposal have been tested on the basis of a simple model featuring different activated sludge batch experiments. IMCM has been implemented in Matlab and it is prepared to be easily connected to any software package.     

区域生态安全评价的BP神经网络方法

生态安全评价是建立生态安全预警系统及进行环境管理的基础。为确立有效的区域生态安全评价方法,基于压力－状态－响应概念模型,构建了区域生态安全评价指标体系和评价标准;采用BP神经网络的途径,对安徽省17个地级市的生态安全评价问题进行了研究。结果表明：宣城、池州、黄山为Ⅱ级,亳州、宿州、阜阳、滁州、六安、巢湖、安庆为Ⅲ级,合肥、淮北、蚌埠为IV级,淮南、马鞍山、芜湖、铜陵为Ⅴ级。区域生态安全的BP神经网络评价方法涵义明确,计算过程简单,能区分生态安全的等级,可以应用于具有评价标准的其它生态系统综合评价。     

A study on the obstacle-induced variation of the gas explosion characteristics

A study on the variation of the gas explosion characteristics caused by the built-in obstacles was conducted in enclosed/vented gas explosion vessels. It has been well known that the obstacles in pipes and long ducts would accelerate the flame propagation, and cause the transition from deflagration to detonation. In this study, the explosion characteristics and the flame behavior of vented explosions and constant-volume explosions were investigated. Experiments were carried out in a 270-liter and 36-liter hexahedron vessels filled with LPG–air mixture. The explosion characteristics of the gas mixture were determined by using a strain-responding pressure transducer. The flame behavior was recorded by using a high-speed video camera. The shape and the size of the obstacle, and the gas concentration, were adjusted in the experiments.

It can be seen from the experimental results that, instead of being accelerated, the flame propagation inside the explosion vessel is decelerated by the plate obstacles fixed at the bottom of the vessel. Also, the characteristics of the enclosed explosion are not so affected by the built-in obstacles as those of the vented explosion are. It is believed that the eddy-induced turbulence behind the obstacle decelerates the flame propagation.     

Biological control experiment of excess propagation of Cyclops for drinking water security

Cyclops of zooplankton propagated excessively in eutrophic water body and could not be effectively inactivated by the conventional disinfections process like chlorination due to its stronger resistance to oxidation. In this study, an ecological project was put forward for the excess propagation control of Cyclops by stocking the filter-feeding fishes such as silver carp and bighead carp under the condition of no extraneous nutrient feeding. The results of experiments with different stocking biomass showed that the propagation of Cyclops could be controlled effectively, and the water quality was improved simultaneously by impacting on nutriment level and plankton community structure at proper stocking density of 30 g/m^3 of water. The growth of Cyclops may not be effectually controlled with lower biomass of fish （10 g）, and the natural food chain relation may be destroyed for Cyclops dying out in water while the intense stocking of 120 g per cubic meter of water. In addition, the high predator pressure may accelerate supplemental rate of nutrients from bottom sediments to water body to add the content of total nitrogen and phosphorus in water.     

ABR处理硫酸盐有机废水的BP神经网络建模

通过厌氧折流板反应器(ABR)处理硫酸盐有机废水的实验数据对BP神经网络进行训练,建立了ABR处理硫酸盐有机废水的BPNN模型,通过测试对比,找出了较优训练函数为traingda,较优训练次数为1 900.利用分割连接权值法(PCW)对影响出水SO42-和COD的主要因素进行分析,结果显示进水COD、SO42-、pH、COD/SO42-和HRT对出水SO42-和COD均产生一定影响,其中进水pH对出水SO42-和COD的影响最大,相对重要性(RI)指数分别为30.79％和23.44％;并通过样本试验数据分别建立了对SO42-和COD去除率的限制因子仿真模型,为预测硫酸盐有机废水的厌氧处理过程提供指导.     

水稻烤田期间N2O排放及其影响因素

水稻田间实验研究了烤田期间的土壤温度、Eh、含水量和裂缝基本性质,矿质态氮以及与氮有关的酶活性的演变规律,及其对N2O排放的影响.试验表明,在水稻分蘖期间烤田,N2O有一个排放高峰,其最高值可达75.6μg·m-2·h-1.在排放高峰后,即使继续烤田,N2O的排放值也将降低.N2O排放与尿素氮肥的施用量没有明显关系.裂缝的生成,改变了N2O的日排放规律.随着烤田时间的延长,脲酶和羟胺还原酶活性呈波动变化,硝酸还原酶活性递减,亚硝酸还原酶活性极低.硝酸还原酶活性与N2O排放之间没有显著相关性.土壤中的脲酶活性与N2O日排放通量呈显著的线性正相关.在烤田期间,NO-3含量呈增加趋势.土壤中的硝态氮含量与N2O排放通量之间呈显著正线性关系.土壤中的铵态氮含量与N2O排放通量之间呈显著负线性相关.     

Short-term Model of the Production of Construction Aggregates in Taiwan Based on Artificial Neural Networks

BACKGROUND: Taiwan's geography and limited stock of sandstone have caused sandstone resources to gradually decline to the point of exhaustion after long-term excavation. Moreover, the Taiwanese government has continuously increased the amount of land area near rivers that cannot be excavated to facilitate riverbed remediation and promote conservation of water resources. Accordingly, predicting and managing the annual production of construction aggregates in future construction projects, and dealing appropriately with some thorny problems, for instance, demand that excess supply, excessive excavation, unregulated excavation, and the consequent environmental damage, will significantly affect the efficient use of natural resources in a manner that accords with the national policy of Sustainable Development (SD). METHODS:. This study establishes an empirical model for forecasting the annual production of future construction aggregates using Artificial Neural Networks (ANN), based on 15 relevant socio-economic indicators, such as indicator of annual consumption of cement. A sensitivity analysis is then performed on these indicators. RESULTS AND DISCUSSION: This work applies ANN to estimate the annual production of construction aggregates; the estimates, the verification of the model and the sensitivity analysis are all acceptable. Furthermore, sensitivity analysis results indicate that the annual consumption of cement is the indicator that most strongly influences the production of construction aggregates, as well as whether construction waste can be recycled and steel structures can be used in buildings, helping to reduce the future production of construction aggregates in Taiwan. CONCLUSIONS: The elaborate prediction methodology presented in this study avoids some of the weaknesses or limitations of conventional linear statistics, linear programming or system dynamics. Additionally, the results not only provide a short-term prediction of the production of construction aggregates in Taiwan, but also provide a viable and flexible means of verifying quality certification of the production data of construction aggregates in the future by incorporating those relevant socio-economic indicators. RECOMMENDATIONS AND OUTLOOK: The continuity and quality of the database of relevant indicators used in this study should be closely scrutinized in order to ensure the SD means of exploiting resources.