A new bounding surface model for thermal cyclic behaviour

To accurately predict soil volume changes under thermal cycles is of great importance for analysing the performance of many earth structures such as the energy pile and energy storage system. Most of the existing thermo‐mechanical models focus on soil behaviour under monotonic thermal loading only, and they are not able to capture soil volume changes under thermal cycles. In this study, a constitutive model is proposed to simulate volume changes of saturated soil subjected to cyclic heating and cooling. Two surfaces are defined and used: a bounding surface and a memory surface. The bounding surface and memory surface are mainly controlled by the preconsolidation pressure (a function of plastic volumetric strain) and the maximum stress experienced by the soil, respectively. Under thermal cycles, the distance of the two surfaces and plastic modulus increase with an accumulation of plastic strain. By adopting the double surface concept, a new elastoplastic model is derived from an existing single bounding surface thermo‐mechanical model. Comparisons between model predictions and experimental results reveal that the proposed model is able to capture soil volume changes under thermal cycles well. The plastic strain accumulates under thermal cycles, but at a decreasing rate, until stabilization. Copyright © 2017 John Wiley & Sons, Ltd.     

Development of a soil moisture‐based distributed hydrologic model for determining hydrologically based critical source areas

A simple grid cell‐based distributed hydrologic model was developed to provide spatial information on hydrologic components for determining hydrologically based critical source areas. The model represents the critical process (soil moisture variation) to run‐off generation accounting for both local and global water balance. In this way, it simulates both infiltration excess run‐off and saturation excess run‐off. The model was tested by multisite and multivariable evaluation on the 50‐km² Little River Experimental Watershed I in Georgia, U.S. and 2 smaller nested subwatersheds. Water balance, hydrograph, and soil moisture were simulated and compared to observed data. For streamflow calibration, the daily Nash‐Sutcliffe coefficient was 0.78 at the watershed outlet and 0.56 and 0.75 at the 2 nested subwatersheds. For the validation period, the Nash‐Sutcliffe coefficients were 0.79 at the watershed outlet and 0.85 and 0.83 at the 2 subwatersheds. The per cent bias was less than 15% for all sites. For soil moisture, the model also predicted the rising and declining trends at 4 of the 5 measurement sites. The spatial distribution of surface run‐off simulated by the model was mainly controlled by local characteristics (precipitation, soil properties, and land cover) on dry days and by global watershed characteristics (relative position within the watershed and hydrologic connectivity) on wet days when saturation excess run‐off was simulated. The spatial details of run‐off generation and travel time along flow paths provided by the model are helpful for watershed managers to further identify critical source areas of non‐point source pollution and develop best management practices.     

Piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events on the Loess Plateau,China

Establishing a universal watershed‐scale erosion and sediment yield prediction model represents a frontier field in erosion and soil/water conservation. The research presented here was conducted on the Chabagou watershed, which is located in the first sub‐region of the hill‐gully area of the Loess Plateau, China. A back‐propagation artificial neural model for watershed‐scale erosion and sediment yield was established, with the accuracy of the model, then compared with that of multiple linear regression. The sensitivity degree of various factors to erosion and sediment yield was quantitatively analysed using the default factor test. On the basis of the sensitive factors and the fractal information dimension, the piecewise prediction model for erosion and sediment yield of individual rainfall events was established and further verified. The results revealed the back‐propagation artificial neural network model to perform better than the multiple linear regression model in terms of predicting the erosion modulus, with the former able to effectively characterize dynamic changes in sediment yield under comprehensive factor conditions. The sensitivity of runoff erosion power and runoff depth to the erosion and sediment yield associated with individual rainfall events was found to be related to the complexity of surface topography. The characteristics of such a hydrological response are thus closely related to topography. When the fractal information dimension is greater than the topographic threshold, the accuracy of prediction using runoff erosion power is higher than that of using runoff depth. In contrast, when the fractal information dimension is smaller than the topographic threshold, the accuracy of prediction using runoff depth is higher than that of using runoff erosion power. The developed piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events, which introduces runoff erosion power and runoff depth using the fractal information dimension as a boundary, can be considered feasible and reliable and has a high prediction accuracy. Copyright © 2013 John Wiley & Sons, Ltd.     

Site characterization model using least‐square support vector machine and relevance vector machine based on corrected SPT data (Nc)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N_c), N values have been corrected (N_c) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three‐dimensional site characterization model, the function N_c=N_c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N_c value, is to be approximated in which N_c value at any half‐space point in Bangalore can be determined. The first algorithm uses least‐square support vector machine (LSSVM), which is related to a ridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel‐based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright © 2009 John Wiley & Sons, Ltd.     

Jet instability and the stabilizing effect of topography on jets in two-layer rotating systems

Abstract

Laboratory experiments concerning azimuthal jets in two-layer rotating systems in the absence and presence of bottom topography aligned along the jets have been conducted. The jets were forced by the selective withdrawal of fluid from the upper layer of a two-fluid system contained in a circular dishpan geometry. The principal parameters measured in the experiments were the jet Rossby number, Ro, and a stratification parameter F = r ₁/(λ₁λ₂)^1/2 where r ₁ is the radius of the circular disc used for the selective withdrawal (i.e., r ₁ is the approximate radius of curvature of the jet) and λ₁,λ₂ are the internal Rossby radii of deformation in the upper and lower fluids, respectively.

The no-topography experiments show that for a sufficiently small F, the particular value depending on Ro, the jet is stable for the duration of the experiment. For sufficiently large F, again as a function of Ro, the jet becomes unstable, exhibiting horizontal wave disturbances from modes three to seven. An Ro against F flow regime diagram is presented.

Experiments are then conducted in the presence of a bottom topography having constant cross-section and extending around a mid-radius of the dishpan. The axis of the topography is in the vicinity of the jet axis forced in the no-topography experiments and the crest of the topography is in the vicinity of the interface between the two fluids (i.e., the front associated with the jet). The experiments show that in all cases investigated the jet tends to be stabilized by the bottom topography. Experiments with the topography in place, but with the interface between the fluids being above the topography crest, are shown to be unstable but more irregular than their no-topography counterparts.

Various quantitative measurements of the jet are presented. It is shown, for example, that the jet Rossby number defined in terms of the fluid withdrawal rate from the tank. Q, can be well correlated with a dimensionless vorticity gradient, V_G , across the upper layer jet. This allows for an assessment of the stability characteristics of a jet based on a knowledge of V_G (which can be estimated given a jet profile) and F.     

试析GIS技术在房产测绘中的作用

以GIS技术在房产测绘中的作用探索研究为题展开论述。首先,介绍了GIS技术操作简单、工作效率高、功能全面,可以实现全天候工作的优势特点。然后,结合测绘行业方面的相关经验,提出该技术在房产测绘中的作用。最后,对GIS技术的改进做了简单分析。希望可以提高GIS技术在房产测绘中的工作效率,促进我国房产事业的长期、稳定发展。     

基于地性线分级的DEM信息量计算方法研究

主要对基于DEM提取的地性线进行信息量的定量分析,探讨地性线的信息量与分辨率、地形单元的关系。这个过程中首先利用河网的自相似理论研究与当前DEM所代表的地貌详细程度相适宜的地性线提取的阈值区间,并讨论此阈值下地性线的分级,以此为基础通过以该分级为权重进行DEM地形信息量的计算。实践证明,这种顾及地性线等级的DEM信息量计算方法能较准确地反映地性线的分布规律和不同等级的要素造成的信息量度量差异。     

车载移动测量系统应用于城市大比例尺地形图更新

将车载移动测量系统与城市大比例尺数字地形图测图相结合,成功地将车载移动测量系统运用于城市大比例尺测图更新应用中。通过在测区内布设靶标控制点,对比靶标的点云量算坐标与全站仪实测实际坐标,统计分析车载移动测量系统的测图精度。实验结果表明,车载移动测量系统能够满足城市大比例尺地形图测图要求。     

基于等高线隔断线确定DEM适宜分辨率的方法研究

分辨率是等高线数据插值生成格网DEM数据过程中需要考虑的一个重要参数,适宜的分辨率既能将等高线高程信息尽可能保留,又不会因插值造成数据冗余及误差。基于对格网DEM生成方式的理解,提出了等高线隔断线的相关概念,分析了基于地形图矢量化的等高线数据插值生成格网DEM数据,由不同长度等高线隔断线频率统计来确定格网适宜分辨率参考值的方法。同时,不同长度等高线隔断线的长度与其频率相乘得到标准长度,以及等高线隔断线中心点生成的密度分析图,均可在频率特征决定适宜分辨率参考值时起到一定的参考作用。通过样区实验验证,实现简便,可度量性强,与其他相关研究具有一致性,对确定适宜格网分辨率参考值具有一定的借鉴意义。     

地基探测与NCEP GFS模式预报云量在ARM SGP站点对比

使用大气辐射测量实验(Atmospheric Radiation Measurements:ARM)在美国南部大平原站点(Southern Great Plains:SGP)长时间序列(2001 2010年)的地基主动遥感云(Active Remote Sensing of Clouds:ARSCL)和美国国家环境预报中心(National Centers for Environmental Prediction:NCEP)全球预报系统(Global Forecast System:GFS)模式预报资料,对比分析了两者云量在不同时间尺度内(年际、月份和季节)的差异。结果表明,GFS模式预报总云量为83.8%,略高于地基观测结果(78.1%);两者总云量差异在秋季最大(8.8%),春季最小(2.2%)。在低垂直高度分辨率(≥3 km)时,地基探测低云、中云和高云的云量分别为46.1%、43.5%和61.2%;模式预报三类云的云量均要高于地基探测的云量,差异分别为9.6%、17.2%和9.1%。但是,在高垂直分辨率(250 m)时,地基探测云量在大多数高度层上要高于模式预报结果。这应该是两种资料廓线中有云出现的高度层数目存在差异引起的。地基观测和GFS模式预报同时表明,SGP站点上空云量垂直廓线呈现双峰结构,在边界层附近(1 km)和上对流层区域(8-12 km)云量较大,2-3 km高度范围内云量较小。在春夏秋冬四个季节内,两种资料在低层边界层附近的最大云量偏差分别为9.5%、8.8%、7.8%和11.2%。