地球物理台网仪器维修信息管理的研究与实现

针对地球物理台网仪器维修信息化薄弱的现状,提出一个规范的地球物理台网仪器维修流程,并对故障仪器的流通和维修订单的处理动作等信息进行研究,设计了满足地球物理台网仪器维修信息管理的数据库结构,设计和实现了基于B/S架构的仪器维修管理系统,并在全国地球物理台网业务中部署使用。该系统具有可视化流程操作、维修资源弹性可扩展、维修信息共享和维修资源协同化的特点,满足地球物理台网仪器维修信息化管理需要,并为其它地震仪器信息化管理系统的设计提供了借鉴。     

Prognosis of TiO2 abundance in lunar soil using a non-linear analysis of Clementine and LSCC data

We suggest a technique to determine the chemical and mineral composition of the lunar surface using artificial neural networks (ANNs). We demonstrate this powerful non-linear approach for prognosis of TiO₂ abundance using Clementine UV-VIS mosaics and Lunar Soil Characterization Consortium data. The ANN technique allows one to study correlations between spectral characteristics of lunar soils and composition parameters without any restrictions on the character of these correlations. The advantage of this method in comparison with the traditional linear regression method and the Lucey et al. approaches is shown. The results obtained could be useful for the strategy of analyzing lunar data that will be acquired in incoming lunar missions especially in case of the Chandrayaan-1 and Lunar Reconnaissance Orbiter missions.     

The High-Resolution Solar Reference Spectrum between 250 and 550 nm and its Application to Measurements with the Ozone Monitoring Instrument

We have constructed a new high resolution solar reference spectrum in the spectral range between 250 and 550 nm. The primary use of this spectrum is for the calibration of the Dutch – Finnish Ozone Monitoring Instrument (OMI), but other applications are mentioned. The incentive for deriving a new high resolution solar reference spectrum is that available spectra do not meet our requirements on radiometric accuracy or spectral resolution. In this paper we explain the steps involved in constructing the new spectrum, based on available low and high resolution spectra and discuss the main sources of uncertainty. We compare the result with solar measurements obtained with the OMI as well as with other UV-VIS space-borne spectrometers with a similar spectral resolution. We obtain excellent agreement with the OMI measurements, which indicates that both the newly derived solar reference spectrum and our characterization of the OMI instrument are well understood. We also find good agreement with previously published low resolution spectra. The absolute intensity scale, wavelength calibration and representation of the strength of the Fraunhofer lines have been investigated and optimized to obtain the resulting high resolution solar reference spectrum.     

公共电话交换网时间认证系统的研制

研制了一种通过公共电话交换网进行时间认证的系统设备,利用电话网为数字时间戳服务机构提供标准时间服务.经实测,时间同步精度可以在±0.3 ms范围内,能满足数字时间戳服务机构为银行、证券、股票和期货交易等电子商务以及电子政务活动提供时间认证服务方面的要求.     

论珠江三角洲河网的人为影响

文章论述了珠江三角洲河网的发育、演变过程和整治方案。由于人类活动影响,珠江三角洲河网区西、北两江下游放射状河系支汊淤断及消亡,使西、北两江正干均成为单一水道;在两江汇流区内又受绥江三角洲南展而分离开来,只留一条狭窄的小河涌(思贤)连接;由于北江正干的淤积、西江正干刷深,使古代(唐代以前)西江合北江同流向东流入番禺(广州)的形势大变,形成江水反向西流入西江,西江水不能过入广州。由此,西、北两江合成的珠江三角洲主体网河区成为浅水狭窄的小河区,以往主要干流多不复存在,生态环境日益变劣。因此,需要修复河网。关键是把西江大量优质水源(沙少、污染少)引回,过入珠江三角洲网河区,北江水源也需截流使其不再西流入西江;开通北江大堤沿途防西水的闸门(如芦苞、西南、沙口等闸),以便通水通航;在思贤建立新型分水闸,可将西、北两江正干水源恢复到良好生态环境     

基于BP神经网络的青藏高原土壤养分评价

土壤养分在养分循环和土壤-植物关系中起着重要作用,在高海拔生态系统中,由于缺乏系统的实地观测,土壤养分在高山草原中仍然知之甚少。为了了解青藏高原多年冻土区高寒草地土壤养分的基本情况以及土壤养分的等级划分,利用青藏高原腹地西大滩至安多地区采集的154个土壤样品数据,基于BP神经网络模型建立具有3层网络,10个中间层节点的土壤养分评价模型。在MATLAB软件中进行BP神经网络的训练和验证后,对青藏高原多年冻土区高寒草地土壤养分进行综合评价。结果表明：2009年青藏高原高寒草地的土壤养分综合评价等级为4级,属于较低水平。综合评价结果与基于主成分分析方法的土壤质量指数（SQI）基本一致,说明BP神经网络模型对青藏高原土壤养分的评价结果是合理的。对评价结果与海拔、植被盖度和植被类型的关系分析表明,海拔越高或植被盖度越高,土壤养分的评价等级越高;不同植被类型的评价等级表现出高寒沼泽草甸（2级）>高寒草甸（4级）>高寒草原（5级）的趋势。BP网络作为一种简单又准确的识别方法,不仅可以评估土壤养分等级,还可以比较不同地区的土壤养分高低状况,希望为青藏高原的土地资源管理与保护提供基本的科学依据。     

A New Fracability Evaluation Approach for Shale Reservoirs Based on Multivariate Analysis: A Case Study in Zhaotong Shale Gas Demonstration Zone in Sichuan,China

Fracability characterizes the effectiveness of hydraulic fracturing. The existing assessment methods cannot reflect the actual value of the effectiveness due to a lack of comprehensive consideration and neglect of the influences of engineering factors. This study aims to solve this problem by implementing geological static data and production dynamic data in multivariate analysis in Zhaotong shale gas demonstration zone. First, the reservoir quality index (RQI) was introduced to evaluate the exploration potential by integrating the geological parameters with gray relational analysis. Moreover, the differences in fracturing fluid types and proppant sizes were considered, and the operating parameters were normalized on the basis of the equivalence principle. Finally, the general reservoir fracability index (GRFI) was proposed based on a dimensioned processing of the various parameters. A case study was conducted to verify the accuracy and feasibility of this new approach. The results demonstrate that (1) the organic carbon and gas content are adjusted to contribute the most to the calculation of the RQI, while the effective porosity contributes the least; (2) the fracturing scale is the main operating parameter determining the fracability, which has the strongest correlation with the effectiveness of fracking; and (3) the GRFI has a positive correlation with shale gas production, and the lower limit of the GRFI of 2,000 corresponds to a daily production of 50,000 m3/d; this value is defined as the threshold value of a stripper well. The GRFI is consistent with the productivity trend of shale gas wells in the research block, which suggests that the new model is accurate and practical for well candidate selection.     

基于因子分析的LM-BP网络的盾构施工地表沉降预测

盾构施工引起的地表沉降量的预测与评价具有很强的随机性和不确定性,用常规的数学模型难以准确表达。本文采用因子分析法对影响盾构施工引起地表沉降的9个因素进行了主因子的提取,得到4个主因子。以此数据集对BP神经网络进行训练,并用Levenberg-Marquardt(LM)算法对BP神经网络进行了优化,建立了基于因子分析的LM-BP神经网络预测模型。结合工程实例将预测结果与LM-BP神经网络模型的预测结果进行比较分析,表明本预测模型具有较高的准确性,符合实际工程的需要。     

Discussion on establishing monitoring networks for temperature fields of shallow thermal energy in Shandong,China

In the recent decade, the construction projects related to shallow geothermal energy engineering have undergone rapid development in Shandong Province. The predominant type of these developments and applications was heat exchange through buried tubes and the main targets were residential and office buildings. However, an overwhelming majority of the completed geothermal heat pump projects lacked monitoring devices so that they were unable to comprehensively reflect the background values for the geothermal fields within the province and few researches were conducted on their influence on the geological environment. In this paper, locations for monitoring shallow geothermal energy and their validity of the monitoring point deployment were studied in view of the development and application status as well as geological background conditions of various projects located in multiple cities providing data support for analyzing the fluctuation trend and influence of large-scale shallow geothermal energy applications on the shallow geothermal and the feasibility and parameter designs of newly built systems in Shandong Province in the future.     

Height prediction of water flowing fractured zones based on BP artificial neural network

Factures caused by deformation and destruction of bedrocks over coal seams can easily lead to water flooding(inrush)in mines,a threat to safety production.Fractures with high hydraulic conductivity are good watercourses as well as passages for inrush in mines and tunnels.An accurate height prediction of water flowing fractured zones is a key issue in today's mine water prevention and control.The theory of leveraging BP artificial neural network in height prediction of water flowing fractured zones is analysed and applied in Qianjiaying Mine as an example in this paper.Per the comparison with traditional calculation results,the BP artificial neural network better reflects the geological conditions of the research mine areas and produces more objective,accurate and reasonable results,which can be applied to predict the height of water flowing fractured zones.