建立江苏泗洪双沟地质公园的可行性研究

在实地考察和系统收集以往研究成果资料的基础上,对泗洪双沟地区的地质遗迹资源进行了研究,主要有地层层型剖面、古生物和水体景观3个大类。叙述了下草湾组层型剖面等剖面,对下草湾中新世脊椎动物群进行了归纳统计,计有脊椎动物化石5纲19目43科98种,其中的长臂猿类双沟醉猿、森林古猿类江淮宽齿猿是我国特有的。经对比分析,属于国家级地质遗迹有3类5处,省级地质遗迹有2类2处。论述这些地质遗迹的科学价值与科普价值,同时对审美学价值、旅游与社会经济价值、开发建设条件进行评价。泗洪双沟地区具备建设地质公园的条件。     

煤层注水难易程度的BP神经网络评价法

科学评价煤层注水难易程度,既是判定煤层是否可注及可注效果,也是确定煤层注水方式和工艺参数的重要依据。但是,由于煤层注水难易性受多种因素影响,属于极为复杂的非线性问题,很难用传统的数学方法进行定量评价。文献[1]用模糊聚类方法进行定量评价,在实际应用中,由于精度不够,出现过误判。为此,针对影响评价煤层注水难易程度的多种因素,如煤层孔隙率、煤的坚固系数、湿润边角、饱和水份增值等所构成的复杂系统,采用具有非线性映射功能的神经网络评价煤层注水难易程度,将煤层注水难易程度分为4级。并将该方法的评价结果同模糊聚类进行了对比,通过比较和实例验证,其误差为5.6%,提高了10个百分点。此方法评价精度较高,可用于指导实际煤层注水工程。     

GPS PPP技术用于滑坡监测的试验与结果分析

为了研究全球定位系统(GPS)精密单点定位(PPP)技术用于滑坡等地质灾害监测时可能达到的精度和可靠性等问题,结合某类滑坡的大型物理模型试验,在滑坡体上布设了若干GPS监测点进行连续实时动态监测,利用PPP技术对该滑坡从稳定、开始滑动直至产生破坏的全过程监测数据进行了处理与分析,并与GPS单历元差分定位、载波相位实时差分定位技术监测结果进行了对比。结果表明:GPS PPP技术监测结果的内符合精度约为10 mm,外符合精度约为40 mm,且GPS PPP技术具有一些差分GPS无法比拟的优势,如无需基准站支持、作业成本低、效率高、可直接获取监测点在国际地球参考框架下的绝对坐标等。该技术完全可用于滑坡等地质灾害的实时动态监测和预警。     

Study on sustainable water use of the Haihe River Basin using ecological network analysis

Sustainable water use of the Haihe River Basin is studied by using the ecological network analysis (ENA) approach. Two related aspects including socioeconomic and environmental water uses sustainability and network organization inherent in system structures are analyzed. For the study of sustainable water use from each single aspect including water use intensity, water use pressure, and environmental protection, a series of new indicators termed as total system throughput water use intensity (TSTUI), total system throughput pressure (TSTP), and environmental flow indicator (EFI) are set up by incorporating parameters of GDP, population, and environmental flow. Based on these three indices, a new integrated index, intensity-pressure-environment (IPE) is established for synthesized measure of sustainable socioeconomic and environmental water uses. The indices of ascendency and overhead are applied for analyzing and characterizing water use network organization. The four subbasins of the Haihe River during 1999–2002 and 2005–2007 are studied. The results show that (i) the water use intensity in subbasin II is the best, while that in subbasins I and III are the worst; (ii) subbasin II and subbasins I and III suffer the highest and lowest water use pressure, respectively; (iii) the environmental flow situations in subbasins II and III are the worst and that of subbasin I is the best; (iv) as for the integrated socioeconomic and environmental water uses sustainability, subbasin III is the best, and subbasins I and IV are the worst; (v) the organization level of subbasin I is better than the others’, in which that of subbasin IV is the worst. It can be concluded that the application of ENA in sustainable water use study can provide new angles for water resources management to address the challenges of assessing and optimizing options to obtain more sustainable water use.     

CORS网和GNSS技术在地面变形监测中的应用

地面变形对工程建设安全稳定具有一定影响,对工程建设规划、地质灾害防治等具有重要意义。本文利用卫星导航定位基准站（CORS）网全球卫星导航系统（GNSS）连续观测,实现了区域地面大地高、地面重力和地倾斜变化面的监测,通过与部分地质灾害信息进行时空分析,确定了用于地面稳定性变化分析的要素和权重,进而定量分析了地面稳定性变化。该方法在浙江省东南部地区进行了测试验证,获得了较好的效果。利用CORS网连续观测能够定量监测地面变形整个面的变化,分析区域地面稳定性变化情况,可为区域规划和地质灾害防治提供技术支持和参考。     

Petrographic criteria for establishing the copper potential in granitoid plutons

A petrographic investigation and its possible relevance in mineral exploration have been studied for a mineralized granitoid pluton in Malanjkhand. Using a matrix of mineralogical, textural and structural features, the types and intensities of mineralogical changes by post-magmatic metasomatic processes can be deduced from thin sections of the rocks. The resulting petrological score provides a measure of establishing the copper potential of a granitoid pluton.     

电石灰改良滨海地区盐渍土路基可行性研究

滨海盐渍土作为一种特殊土,具有溶陷、盐胀、腐蚀等不良的工程特性,而滨海地区用盐渍土作为路基填料是交通建设需要解决的重大岩土工程问题之一。为了解决滨海盐渍土的工程问题,分析了电石灰改良盐渍土路基填料的液塑限试 验、击实试验、室内CBR试验和不同条件的不固结、不排水三轴试验结果,从工程技术、降低造价和环境保护等方面对滨海高速公路路基填料改良利用的可行性进行了研究论证,研究成果对滨海地区盐渍土路基的修筑具有参考价值。     

A resource-based framework for establishing freshwater inflow requirements for the Suwannee River estuary

The availability of methods for establishing freshwater inflow requirements for estuaries lags behind those for establishing flow requirements in riverine ecosystems. Some of the basic principles and approaches for establishing riverine flow requirements may be applicable to estuaries. An emerging approach for establishing freshwater inflow needs for the Suwannee River estuary involves maintaining a natural inflow regime (in terms of magnitude, frequency, duration, and timing of freshwater flows) and identifying important habitat targets to be protected. The salinity-river flow conditions needed to sustain the habitat targets in their existing condition are then identified. A variety of tools are employed, such as salinity metrics, biological metrics, limits of distribution of communities or habitats, and landscape-scale characteristics to define the salinity and corresponding flow ranges needed to protect and maintain the resource targets. With this information, combined with use of models to evaluate flow-salinity relationships and various withdrawal scenarios, river flow criteria can be set which address the freshwater inflow requirements to maintain these ranges. Subsequentmonitoring and research is undertaken to evaluate the effectiveness of the river flow criteria in protecting the estuarine resource targets. This information can be used to subsequently confirm, refine, or modity the flow criteria.     

一种快速建立上覆岩层压力体的方法

上覆岩层压力是地层沉积压实作用的源动力,也是地层孔隙压力计算的重要基础数据。本文通过Eaton公式推导出密度变化与上覆岩层压力和孔隙压力的计算模型,验证了不同厚度下低密度泥岩对上覆岩层压力以及孔隙压力的影响关系,证实密度差异为0.3 g/cm 3、厚度从100~500 m的低密泥岩对孔隙压力的影响最大仅为0.02 psi,从3~250 Hz的频率扫描密度曲线计算得到的上覆岩层压力几乎无差别,证实上覆岩层压力仅代表沉积地层的低频成分,因此根据正常压实地层有效应力和上覆岩层压力的关系确定了基于井控地震层速度场转换上覆岩层压力体的快速方法。以渤海西部某构造为例,新方法求取的上覆岩层压力体被多口钻井一一验证,满足了快速勘探评价的需求。     

Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.     

用神经网络评价边坡稳定性

影响边坡稳定性因素是复杂且具有随机和模糊特性。神经网络的性能特征使适用于解决非性的边坡稳定性评价问题，本文建立了边坡稳定性评价的复合网络模型，并利用边坡工程的失稳及稳定实例对网络进行了训练和测试，计算分析表明，网络模型对于评价边坡的稳定性有较好的适用性。     

Importance of establishing sources of uncertainty for the derivation of reliable SHRIMP ages

The ion microprobe, as exemplified by SHRIMP, has long been an invaluable resource for the derivation of geological ages. The derivation of those ages is critically dependent on the identification and individual quantification of all sources of contributing uncertainty. In recent years, it has been proposed that the only component of uncertainty arising from the instrument itself is predictable from counting statistics. The adoption of that approach has led to several conclusions including: (i) that zircon U–Pb ages are relatively easily reset, which necessitates the enhanced editing of individual analyses before a grouped age can be obtained; and (ii) that other studies have overestimated analytical uncertainties and, as a consequence, have reported incorrect and/or overly imprecise ages. We present evidence for the presence of additional sources of instrument‐related uncertainty that necessitates a different (but not new) approach for the processing of SHRIMP data. Fortunately, this complication does not represent a serious problem, provided that a high‐quality zircon‐calibration standard has been used for Pb/U calibration. SHRIMP ages obtained some time ago from the Crudine Group of the Hill End Trough (New South Wales) have recently been placed at the centre of this controversy. A significant part of the problem is that most of those ages were based on a standard (SL 13) that is now known to be heterogeneous. The more reliable parts of the original data have been re‐reprocessed on the basis of the new evidence. They fail to detect a significant age difference between the bottom and the top of the Merrions Formation, a conclusion that is contrary to earlier expressed opinions.     

Optimized height of noise barrier for non-urban highway using artificial neural network

This study applies artificial neural network (ANN) for the determination of optimized height of a highway noise barrier. Field measurements were carried out to collect traffic volume, vehicle speed, noise level, and site geometry data. Barrier height was varied from 2 to 5 m in increments of 0.1 m for each measured data set to generate theoretical data for network design. Barrier attenuation was calculated for each height increment using Federal Highway Administration model. For neural network design purpose, classified traffic volume, corresponding traffic speed, and barrier attenuation data have been taken as input parameters, while barrier height was considered as output. ANNs with different architectures were trained, cross validated, and tested using this theoretical data. Results indicate that ANN can be useful to determine the height of noise barrier accurately, which can effectively achieve the desired noise level reduction, for a given set of traffic volume, vehicular speed, highway geometry, and site conditions.     

Landslide detection using visualization techniques for deep convolutional neural network models

Natural Hazards - Landslides occur when masses of rock, earth, and other debris move down a slope. The slope of an area is directly responsible for the magnitude of the landslide. Being...     

Seismic human loss estimation for an earthquake disaster using neural network

In Iran, earthquakes cause enormous damage to the people and economy. If there is a proper estimation of human losses in an earthquake disaster, it could be appropriately responded and its impacts and losses will be decreased. Neural networks can be trained to solve problems involving imprecise and highly complex nonlinear data. Based on the different earthquake scenarios and diverse kind of constructions, it is difficult to estimate the number of injured people. With respect to neural network’s capabilities, this paper describes a back propagation neural network method for modeling and estimating the severity and distribution of human loss as a function of building damage in the earthquake disaster. Bam earthquake data in 2003 were used to train this neural network. The final results demonstrate that this neural network model can reveal much more accurate estimation of fatalities and injuries for different earthquakes in Iran and it can provide the necessary information required to develop realistic mitigation policies, especially in rescue operation.     

Comparison of testing techniques and models for establishing the SWCC of riverbank soils

The soil water characteristic curve (SWCC), also known as soil water retention curve (SWRC), describes the relationship between water content and soil suction in unsaturated soils. Water content and suction affect the permeability, shear strength, volume change and deformability of unsaturated soils. This paper presents results of the laboratory determination of the SWCC for soil samples obtained from the riverbank of the Lower Roanoke River in North Carolina. Six different testing methods were used to establish the SWCC including the filter paper, dewpoint potentiameter, vapor equilibrium, pressure plate, Tempe cell and osmotic methods. It is concluded that each suction measurement technique provides different measurable ranges of suction values, and the combined results from the different tests provide continuous SWCCs. Three widely available models were also shown to adequately fit the experimental SWCC data, particularly for matric suction values under 1500 kPa. These results will be valuable to practitioners in deciding which methods to use to establish the SWCC, and which empirical relationship to use for modeling the SWCC of riverbank soils.     

水化学溶液下灰岩力学特性及神经网络模拟研究

基于水化学溶液浸泡的饱和灰岩三轴压缩试验结果,分析了影响灰岩变形及强度等力学特性的主要因素,认为随溶液酸碱度增加,弹性模量及峰值强度均有降低的趋势;相同pH值,Na2SO4溶液、蒸馏水和CaCl2溶液对灰岩强度的弱化程度依次降低;随着围压的增加,岩石强度逐渐增大,岩石到达峰值强度时的轴向变形也越来越大,塑性变形明显增加。考虑应力路径和化学溶液的影响,利用遗传算法优化神经网络结构,建立了进化神经网络本构模型。通过样本学习模型能较好地描述化学环境下灰岩的力学性能,5种不同化学环境下的力学试验验证了进化神经网络模型模拟结果的可靠性,该方法可以推广到化学环境下其他岩石的力学试验模拟。     

闪长岩强风化带做高层建筑天然地基的可行性研究

借助于中国工商银行山东省分行营业办公楼的工程实践,将常规勘察与原位测试相结合,运用野外钻探、室内试验、原位测试多种手段,对闪长岩强风化带的物理力学性质进行了测试分析和深入地研究,并通过对承载力、沉降变形的验算,得出其作为高层建筑的天然地基是可行的。实践证明,与桩基础处理方案相比,节省资金近200万元,大大加快了施工进度,减少了基础施工难度,取得了巨大的经济效益与社会效益;同时,也提出了研究岩石风化带所遇到的问题:由于采取原状试样及制样难,导致对其物理力学性质了解不够。     

Probabilistic neural network algorithm for using radon emanations as an earthquake precursor

The investigation throughout the world in past two decades provides evidence which indicate that significance variation of radon and other soil gases occur in association with major geophysical events such as earthquake. The traditional statistical algorithm includes regression to remove the effect of the meteorological parameters from the raw radon and anomalies are calculated either taking the periodicity in seasonal variations or periodicity computed using Fast Fourier Transform. In case of neural networks the regression step is avoided. A neural network model can be found which can learn the behavior of radon with respect to meteorological parameter in order that changing emission patterns may be adapted to by the model on its own. The output of this neural model is the estimated radon values. This estimated radon value is used to decide whether anomalous behavior of radon has occurred and a valid precursor may be identified. The neural network model developed using Radial Basis function network gave a prediction rate of 87.7%. The same was accompanied by huge false alarms. The present paper deals with improved neural network algorithm using Probabilistic Neural Networks that requires neither an explicit step of regression nor use of any specific period. This neural network model reduces the false alarms to zero and gave same prediction rate as RBF networks.