基于Excel的Q=f（S）及q=f（S）曲线判别

鉴于传统的手工方法或CAD绘制抽水试验过程中Q=f（S）及q=f（S）曲线中出现的效率低、精度不高的问题,利用Excel的计算、图表功能．以内蒙古鄂尔多斯某井田203孔8煤至17煤抽水试验资料为例,详细阐述了图表法和数值法绘制Q=f（S）及q=f（S）曲线的具体步骤及判别啦线是否正常的方法,为野外水文地质技术人员提供了一个很好的参考范本。     

遥感影像快速正射处理系统测试方案探讨

在Ortho系统发布前的软件测试中设计了一套测试方案,按照该方案中的测试路线和方法,通过采用各种基础资料进行试生产和与PCI软件的比对,测定了Ortho系统存在的缺陷和不足,并结合实际情况,给出了恰当的分析意见和验证了方案的正确性。     

双能CT成像基材料分解法的理论误差分析

双能X射线计算机断层成像技术(DECT)能够准确地重建物质的有效原子序数和电子密度信息,是一种有效的物质辨别技术.基材料分解法是求解DECT重建问题的主要方法之一.但目前应用此方法得到的重建结果误差较大,并且对于金属伪影抑制能力也较差.本文分析了DECT基材料分解法重建结果的误差来源和形成机制,阐释了其对金属伪影抑制作...     

冻土中几类力学试验方法的探讨

获取寒区工程设计中冻土的物理力学指标及冻土本构模型中的模型参数都离不开冻土的力学试验.随着对冻土力学性质研究的深入,需要考察更多加载路径下冻土的力学行为,这也是检验已有冻土本构模型的有效途径.因此,精确的冻土力学试验是认识冻土力学性质的基本手段.为进一步考察冻土的力学性质,提高冻土力学试验的精度,应用MTS-810低温...     

基于PHC3.0数据集的北冰洋水团分析

基于PHC3.0极地科学中心水文气候数据集(简称PHC3.0数据集)的温度和盐度资料,使用聚类分析和Bayes判别分析的方法,对北纬70°以北海域的水团结构进行了分析,在北冰洋区域划分出4个水团:北冰洋表层水(ASW)、大西洋中层水(AIW)、太平洋水(PW)和北冰洋深层水(ADW)。北冰洋表层水(ASW)遍布于欧亚海盆和加拿大海盆,以低温低盐为特征。大西洋中层水(AIW)位于约200～900m深度,在北冰洋环极边界流的作用下,其影响可达到加拿大海盆。太平洋水(PW)受经白令海峡进入北冰洋的海水影响,相对高温低盐,夏季时影响显著。北冰洋深层水(ADW)在海盆中相当均匀,几乎没有季节变化,盐度约在34.95psu,温度在加拿大海盆约为-0.3℃,欧亚海盆约为-0.7℃。     

Trend analysis and ARIMA modelling of pre-monsoon rainfall data for western India

Spatial and temporal variability of rainfall over different seasons influence physical, social and economic parameters. Pre-monsoon (March, April and May – MAM) rainfall over the country is highly variable. Since heat lows and convective rainfall in MAM have an impact on the intensity of the ensuing monsoons, hence the pre-monsoon period was chosen for the study. The pre-whitened Mann Kendall test was used to explore presence of rainfall trend during MAM. The results indicate presence of significant (at 10% level) increasing trend in two stations (Ajmer, Bikaner). The practical significance of the change in rainfall was also explored as percentage changes over long term mean, using Theil and Sen's median slope estimator. Forecast using univariate ARIMA model for pre-monsoon months indicates that there is a significant rise in the pre-monsoon rainfall over the northwest part of the country.     

核爆炸与地震识别研究进展

综述了近年来核爆炸与天然地震识别研究的进展, 揭示了从频谱比、震级比到综合因素的概率方法的发展过程, 特别指出小当量核爆炸识别的重要性. 文章借助量子场论和相变理论分析讨论了地震波波长与动量的关系. 同时, 根据地壳介质的复杂性, 指出地震波传播过程中由于介质的非线性与弥散的联合作用, 导致产生孤波的可能性.     

Classification of seismic signals at Villarrica volcano (Chile) using neural networks and genetic algorithms

Each volcano has its own unique seismic activity. The aim of this work is to construct a system able to classify seismic signals for the Villarrica volcano, one of the most active volcanoes in South America. Since seismic signals are the result of particular processes inside the volcano's structure, they can be used to forecast volcanic activity. This paper describes the different kinds of seismic signals recorded at the Villarrica volcano and their significance. Three kind of signals were considered as most representative of this volcano's activity: the long-period, the tremor, and the energetic tremor signals. A classifier is implemented to read the seismic registers at 30-second intervals, extract the most relevant features of each interval, and classify them into one of the three kinds of signals considered as most representative of this particular volcano. To do so, 1033 different kinds of 30-s signals were extracted and classified by a human expert. A feature extraction process was applied to obtain the main characteristics of each of them. This process was developed using criteria which have been shown by others to effectively classify seismic signals, based on the experience of a human expert. The classifier was implemented with a Multi-Layer Perceptron (MLP) artificial neural network whose architecture and training process were optimized by means of a genetic algorithm. This technique searched for the most adequate MLP configuration to improve the classification performance, optimizing the number of hidden neurons, the transfer functions of the neurons, and the training algorithm. The optimization process also performed a feature selection to reduce the number of signal features, optimizing the number of network inputs. The results show that the optimized classifier reaches more than 93% exactitude. identifying the signals of each kind. The amplitude of the signals is the most important feature for its classification, followed by its frequency content. The described methodology can be used to classify more seismic signals to improve the study of the activity of this volcano or to extend the study to other active volcanoes of the region.     

弹性地基条件下狭窄煤柱岩爆的突变理论分析

将未采煤层视为弹性地基条件下,运用maple9.5符号运算软件解得岩梁的挠曲线方程。根据能量守恒原理得到的功、能增量平衡关系式,求得岩梁–煤柱系统作准静态形变时的平衡方程--折迭突变模型平衡方程;用折迭突变总势能函数所作的稳定性判别表明,岩爆前兆阶段岩梁–煤柱系统处于不稳定平衡状态;煤柱岩爆的条件是Cook刚度准则,该准则可以动态地用煤柱形变增大时所需外界的能量输入率趋于0来表示;计算了煤柱岩爆地震能释放量,阐明煤柱岩爆机制是由于岩梁弹性能释放量超过峰后软化煤柱形变所耗的能量。通过岩梁弹性势能变化率曲线和煤柱耗能曲线,以几何形式描述了所得研究结果。计算表明,未开采煤层刚度变化对岩梁的等效刚度影响微弱。工作面开挖和采空区增大,将显著减小岩梁刚度Ke,对煤柱岩爆有重要影响。