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Prediction of uniaxial compression PFC3D model micro‐properties using artificial neural networks

Artificial neural networks are used to predict the micro‐properties of particle flow code in three dimensions (PFC3D) models needed to reproduce macro‐properties of cylindrical rock samples in uniaxial compression tests. Data for the training and verification of the networks were obtained by running a large number of PFC3D models and observing the resulting macro‐properties. Four artificial networks based on two different architectures were used. The networks used different numbers of input parameters to predict the micro‐properties. Multi‐layer perceptron networks using Young's modulus, Poisson's ratio, uniaxial compressive strength, model particle resolution and the maximum‐to‐minimum particle ratio showed excellent performance in both training and verification. Adding one more variable—namely, minimum particle radius—showed degrading performance. Copyright © 2009 John Wiley & Sons, Ltd.     

Application of the SHETRAN basin‐scale,landslide sediment yield model to the Llobregat basin,Spanish Pyrenees

The first application of the SHETRAN basin‐scale, landslide erosion and sediment yield model is carried out for a major landsliding event in the upper 505 km² of the Llobregat basin, in the eastern Spanish Pyrenees, in November 1982. The model simulates the spatial distribution of shallow landslides and their sediment yield. Acknowledging uncertainty in the model parameter evaluation, the aim of the application was not to reproduce the observed occurrence of landslides as accurately as possible with one simulation, but to bracket the observed pattern with several simulations representing uncertainty in the key input conditions. Bounds on the landslide simulations were thus determined as a function of uncertainty in the vegetation root cohesion (used in the model factor of safety calculations). The resulting upper bound considerably overestimates the observed pattern (17 000 landslides compared with an observation of around 700), but it reproduces several of the principal clusters in the observed pattern. The lower bound contains around 500 landslides. The sediment yield estimates (2670–14 630 t km^?2) are comparable to measurements elsewhere in the Pyrenees for extreme events. The results demonstrate an ability to simulate the basin‐scale landslide response to a rainfall event and the resulting sediment yield. They also highlight the need for further research in setting the uncertainty bounds and in avoiding large overestimates of landslide occurrence arising in part from a current inability to model small‐scale controls for a basin of the given size. Copyright © 2006 John Wiley & Sons, Ltd.     

Assessing the Measurement Consistency Between the Jason-2/AMR and SARAL/AltiKa/DFMR Microwave Radiometers Using Simultaneous Nadir Observations

SARAL/AltiKa has a Dual Frequency Microwave Radiometer (DFMR), and Jason-2 has an Advanced Microwave Radiometer (AMR). Both microwave radiometer sensors include a 23.8 GHz primary water sensing channel. The measurement consistencies between DFMR and AMR are important for establishing a consistent altimetry data set between SARAL/AltiKa and Jason-2 in order to accurately assess sea level rise in a long-term time series. This study investigates the measurement consistency in the 23.8 GHz channel between DFMR and AMR at the Simultaneous Nadir Overpasses (SNO's) between the two satellites and also at coldest ocean brightness temperature locations. Preliminary results show that while both instruments show no significant trends over the one year since the launch of SARAL, a consistent relative bias of 2.88 K (DFMR higher than AMR) with a standard deviation of 0.98 K is observed. The relative bias at the lowest brightness temperature from the SNO method (-3.82 K) is consistent with that calculated from coldest ocean method (-3.74 K). The relative bias exhibits strong latitude (and scene temperature) dependency, changing from -3.82 K at high latitudes to -0.92 K near the equator. There also exists an asymmetry between the northern and southern hemisphere. The relative bias increases toward the lower end of brightness temperature.     

The 2013 Ibiza Calibration Campaign of Jason-2 and SARAL Altimeters

This study presents the results of the 2013 Ibiza (Western Mediterranean) calibration campaign of Jason-2 and SARAL altimeters. It took place from 14 to 16 September 2013 and comprised two phases: the calibration of the GNSS (Global Navigation Satellite System) buoys to estimate the antenna height of each of them and the absolute calibration to estimate the altimeter bias (i.e., the difference of sea level measured by radar altimetry and GNSS). The first one was achieved in the Ibiza harbor at a close vicinity of the Ibiza tide gauge and the second one was performed at ～ 40 km at the northwest of Ibiza Island at a crossover point of Jason-2 and SARAL nominal groundtracks. Five buoys were used to delineate the crossover region and their measurements interpolated at the exact location of each overflight. The overflights occurred two consecutive days: 15 and 16 September 2013 for Jason-2 and SARAL, respectively. The GNSS data were processed using precise point positioning technique. The biases found are of (?0.1 ± 0.9) and (?3.1 ± 1.5) cm for Jason-2 and SARAL, respectively.     

Numerical and Experimental Analysis of A Ducted Propeller Designed by A Fully Automated Optimization Process Under Open Water Condition

A fully automated optimization process is provided for the design of ducted propellers under open water conditions, including 3D geometry modeling, meshing, optimization algorithm and CFD analysis techniques. The developed process allows the direct integration of a RANSE solver in the design stage. A practical ducted propeller design case study is carried out for validation. Numerical simulations and open water tests are fulfilled and proved that the optimum ducted propeller improves hydrodynamic performance as predicted.     

轨道扣件病害自动化检测研究及应用

传统扣件检查基本采用人工检查方式,不仅工作效率低、劳动强度大,而且人为干扰因素多、检查采样率低。针对以上问题,本文提出了一种基于线结构光传感器的轨道扣件损伤和松动检测方法,并开发了轨道扣件智能监测系统以实现扣件病害自动检测。最终将研究成果应用于徐州市某地铁区间轨道扣件检测,验证了该方法的可行性和准确率,为地铁轨道扣件检查提供了新方法。     

督察区域地类图斑自动套合方法

自然资源督察工作中,为确定目标区域是否存在土地利用违法行为,需要利用ArcGIS软件对目标区域和地类图斑数据进行空间计算、汇总统计等套合工作,为督察工作实施提供数据支撑。目前,人工套合存在制作成本高、工作量大、准确性低、数据命名存储格式不一致等问题。为此,本文基于Python实现了地类图斑自动套合的方法,该方法可以自动完成目标区域与地类图斑的空间计算、字段计算、Excel导出,以及生成数据透视表等工作,极大地减小了技术人员的工作量,有效缩短了督察工作的数据准备时间,对提高自然资源督察工作的效率具有实践意义。     

大光斑波形数据在土地覆盖分类的适用性分析

针对GLAS地学激光测高系统是冰、云和陆地高程卫星(ICESat)的唯一监测工具,能够记录地表光斑内的地物信息,是否能应用于黄土高原土地覆盖分类的问题进行了研究。利用粒子群和最小二乘法相结合的方法对GLAS波形数据进行高斯分解,获取高斯波个数、波形总能量、波形信号起始和信号结束位置4个波形参数;基于波形自动分类方法对黄土高原水体、森林、城市用地、其他地类(裸地、低矮植被等)进行分类。通过基于覆盖相同研究区域的30 m地表覆盖数据(Globe Land30),验证分类的准确性。结果表明,GLAS大光斑波形数据对黄土高原的4种地类能够很好地进行区分,总分类精度高达87.68%,Kappa系数为65.79%。研究表明,GLAS波形数据可以作为获取土地覆盖信息的有效数据源,为研究黄土高原土地覆盖变化提供更丰富的数据支持。