Retaining wall optimization using interior search algorithm with different bound constraint handling

Along with the applicability of optimization algorithms, there are lots of features that can affect the functioning of the optimization techniques. The main purpose of this paper is investigating the significance of boundary constraint handling (BCH) schemes on the performance of optimization algorithms. To this end, numbers of deterministic and probabilistic BCH approaches are applied to one of the most recent proposed optimization techniques, named interior search algorithm (ISA). Apart from the implementing different BCH methods, a sensitivity analysis is conducted to find an appropriate setting for the only parameter of ISA. Concrete cantilever retaining wall design as one of the most important geotechnical problems is tackled to declare proficiency of the ISA algorithm, on the one hand, and benchmark the effect of BCH schemes on the final results, on the contrary. As results demonstrate, various BCH approaches have a perceptible impact on the algorithm performance. In like manner, the essential parameter of ISA can also play a pivotal role in this algorithm's efficiency. Copyright © 2017 John Wiley & Sons, Ltd.     

Divergence and flow direction as indicators of subsurface heterogeneity and stage‐dependent storage in alluvial floodplains

Assuming homogeneity in alluvial aquifers is convenient, but limits our ability to accurately predict stream‐aquifer interactions. Research is needed on (i) identifying the presence of focused, as opposed to diffuse, groundwater discharge/recharge to streams and (ii) the magnitude and role of large‐scale bank and transient storage in alluvial floodplains relative to changes in stream stage. The objective of this research was to document and quantify the effect of stage‐dependent aquifer heterogeneity and bank storage relative to changes in stream stage using groundwater flow divergence and direction. Monitoring was performed in alluvial floodplains adjacent to the Barren Fork Creek and Honey Creek in northeastern Oklahoma. Based on results from subsurface electrical resistivity mapping, observation wells were installed in high and low electrical resistivity subsoils. Water levels in the wells were recorded real time using pressure transducers (August to October 2009). Divergence was used to quantify heterogeneity (i.e. variation in hydraulic conductivity, porosity, and/or aquifer thickness), and flow direction was used to assess the potential for large‐scale (100 m) bank or transient storage. Areas of localized heterogeneity appeared to act as divergence zones allowing stream water to quickly enter the groundwater system, or as flow convergence zones draining a large groundwater area. Maximum divergence or convergence occurred with maximum rates of change in flow rates or stream stage. Flow directions in the groundwater changed considerably between base and high flows, suggesting that the floodplains acted as large‐scale bank storage zones, rapidly storing and releasing water during passage of a storm hydrograph. During storm events at both sites, the average groundwater direction changed by at least 90° from the average groundwater direction during baseflow. Aquifer heterogeneity in floodplains yields hyporheic flows that are more responsive and spatially and temporally complex than would be expected compared to more common assumptions of homogeneity. Copyright © 2012 John Wiley & Sons, Ltd.     

Exploring the interaction of surface roughness and slope gradient in controlling rates of soil loss from sloping farmland on the Loess Plateau of China

Surface roughness and slope gradient are two important factors influencing soil erosion. The objective of this study was to investigate the interaction of surface roughness and slope gradient in controlling soil loss from sloping farmland due to water erosion on the Loess Plateau, China. Following the surface features of sloping farmland in the plateau region, we manually prepared rough surfaces using four tillage practices (contour drilling, artificial digging, manual hoeing, and contour plowing), with a smooth surface as the control measure. Five slope gradients (3°, 5°, 10°, 15°, and 20°) and two rainfall intensities (60 and 90 mm/hr) were considered in the artificial rainfall simulation experiment. The results showed that the runoff volume and sediment yield increased with increasing slope gradient under the same tillage treatment. At gentle slope gradients (e.g., 3° and 5°), the increase in surface roughness prevented the runoff and sediment production, that is, the surface roughness reduced the positive effect of slope gradient on the runoff volume and sediment yield to a certain extent. At steep slope gradients, however, the enhancing effect of slope gradient on soil erosion gradually increased and surpassed the reduction effect of surface roughness. This study reveals the existence of a critical slope gradient that influences the interaction of surface roughness and slope gradient in controlling soil erosion on sloping farmland. If the slope gradient is equal to or less than the critical value, an increase in surface roughness would decrease soil erosion. Otherwise, the increase in surface roughness would be ineffective for preventing soil erosion. The critical slope gradient would be smaller under higher rainfall intensity. These findings are helpful for us to understand the process of soil erosion and relevant for supporting soil and water conservation in the Loess Plateau region of China.     

Parallelized combined finite-discrete element (FDEM) procedure using multi-GPU with CUDA

This paper focuses on the efficiency of finite discrete element method (FDEM) algorithmic procedures in massive computers and analyzes the time-consuming part of contact detection and interaction computations in the numerical solution. A detailed operable GPU parallel procedure was designed for the element node force calculation, contact detection, and contact interaction with thread allocation and data access based on the CUDA computing. The emphasis is on the parallel optimization of time-consuming contact detection based on load balance and GPU architecture. A CUDA FDEM parallel program was developed with the overall speedup ratio over 53 times after the fracture from the efficiency and fidelity performance test of models of in situ stress, UCS, and BD simulations in Intel i7-7700K CPU and the NVIDIA TITAN Z GPU. The CUDA FDEM parallel computing improves the computational efficiency significantly compared with the CPU-based ones with the same reliability, providing conditions for achieving larger-scale simulations of fracture.     

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.     

极化干涉SAR森林树高提取算法的对比分析

在对极化干涉SAR森林树高反演的DEM差值算法、相干相位-幅度综合反演算法进行分析的基础上,对基于极化干涉相干优化方法的改进算法进行了探讨。利用黑龙江大兴安岭地区的一对ALOS全极化干涉SAR数据进行实验,并对比分析各算法的反演结果。结果表明,在使用改进的算法进行森林树高反演时可以获取精度较高的反演结果,并且在一定程度上提高了森林树高反演的稳定性,为森林树高反演工作的业务化运行提供一定的依据。     

基于光谱角匹配算法的水体信息提取研究

针对水体信息提取时,传统算法不能较好地解决山体阴影被误提为水体的问题,引入多用于高光谱数据处理的光谱角匹配算法,以Land-sat8 OLI(band1-band7)为数据源,以黄河小浪底水库周边区域为实验区,开展水体信息提取研究,结果显示:水体指数法和波段关系提取的结果中有大量的山体阴影信息,提取精度不超过30%,而光谱角匹配法提取结果受阴影的影响较小,提取精度在99%以上。     

庐山地区地表温度反演分析

研究庐山地区的地表温度,对于本地区的生态保护和开发具有重要意义。本文使用了目标区域内Landsat TM/ETM+从2000~2010年间共8幅影像数据,利用单通道算法和NDVI地表辐射率估算方法反演了区域内的温度场,并生成了历年温度对比效果图。分析推断目标区域内的温度场可能存在一个短年限的温度变化起伏规律,对庐山周边山区的影响有待进一步研究。     

InSAR相位解缠算法的比较

相位解缠作为合成孔径雷达干涉测量(InSAR,Interferometric Synthetic Aperture Radar)中一个关键的步骤,为获取地形高程提供了基础。相位解缠的质量将直接影响着DEM生成的质量。对现有的几类算法进行实验分析,并对解缠结果的质量进行比较,分析其精确性。结果表明:统计耗费网络流算法具有较好的解缠连续性以及较高的精度,可以获得一个较优的全局解。     

PEIV模型参数估计新算法

PEIV(Partial Errors-In-Variables)模型是EIV模型的扩展,它能解决系数矩阵含有非随机元素或存在结构特性的问题。针对常规PEIV模型算法的复杂性,提出了一种PEIV模型参数估计的新算法。该算法将系数矩阵含误差的元素看成是一类观测值,与平差模型原观测值构成两类观测值,将PEIV平差模型表示为类似于传统的最小二乘间接平差模型,再通过非线性最小二乘平差理论,推导出了算法的迭代公式和精度评定公式。算法迭代格式与间接平差类似,通过算例验证了算法的可行性和正确性。