A hybrid approach based on an improved gravitational search algorithm and orthogonal crossover for optimal shape design of concrete gravity dams

A hybrid approach based on an improved gravitational search algorithm (IGSA) and orthogonal crossover (OC) is proposed to efficiently find the optimal shape of concrete gravity dams. The proposed hybrid approach is called IGSA-OC. The hybrid of IGSA and the OC operator can improve the global exploration ability of the IGSA method, and increase its convergence rate. To find the optimal shape of concrete gravity dams, the interaction effects of dam–water–foundation rock subjected to earthquake loading are considered in this study. The computational cost of the optimal shape of concrete gravity dams subjected earthquake loads is usually high. Due to this problem, the weighted least squares support vector machine (WLS-SVM) regression as an efficient metamodel is utilized to considerably predict dynamic responses of gravity dams by spending low computational cost. To testify the robustness and efficiency of the proposed IGSA-OC, first, four well-known benchmark functions in literatures are optimized using the proposed IGSA-OC, and provides comparisons with the standard gravitational search algorithm (GSA) and the other modified GSA methods. Then, the optimal shape of concrete gravity dams is found using IGSA-OC. The solutions obtained by the IGSA-OC are compared with those of the standard GSA, IGSA and particle swarm optimization (PSO). The numerical results demonstrate that the proposed IGSA-OC significantly outperforms the standard GSA, IGSA and PSO.     

混凝土水力劈裂的数值模拟

针对混凝土坝越来越高,越来越容易产生水力劈裂的问题,总结已有混凝土水力劈裂问题的研究成果,结合水力劈裂的发生条件、在水压作用下混凝土裂缝的开展以及影响水力劈裂作用的因素,探讨水力劈裂数值模拟的方法.比较有限元法、扩展有限元法和无单元法在水力劈裂数值模拟问题应用上的优点与不足,并分析数值模拟模型建立过程中参数设置的差别.结果表明,必须从坝材料、施工和水压等多方面考虑才能确保水力劈裂数值模拟结果的可靠性.     

Predicting piezometric water level in dams via artificial neural networks

The safety control of dams is based on measurements of parameters of interest such as seepage flows, seepage water clarity, piezometric levels, water levels, pressures, deformations or movements, temperature variations, loading conditions, etc. Interpretation of these large sets of available data is very important for dam health monitoring and it is based on mathematical models. Modelling seepage through geological formations located near the dam site or dam bodies is a challenging task in dam engineering. The objective of this study is to develop a feedforward neural network (FNN) model to predict the piezometric water level in dams. An improved resilient propagation algorithm has been used to train the FNN. The measured data have been compared with the results of FNN models and multiple linear regression (MLR) models that have been widely used in analysis of the structural dam behaviour. The FNN and MLR models have been developed and tested using experimental data collected during 9 years. The results of this study show that FNN models can be a powerful and important tool which can be used to assess dams.     

A novel hybrid artificial intelligent approach based on neural fuzzy inference model and particle swarm optimization for horizontal displacement modeling of hydropower dam

Horizontal displacement of hydropower dams is a typical nonlinear time-varying behavior that is difficult to forecast with high accuracy. This paper proposes a novel hybrid artificial intelligent approach, namely swarm optimized neural fuzzy inference system (SONFIS), for modeling and forecasting of the horizontal displacement of hydropower dams. In the proposed model, neural fuzzy inference system is used to create a regression model whereas Particle swarm optimization is employed to search the best parameters for the model. In this work, time series monitoring data (horizontal displacement, air temperature, upstream reservoir water level, and dam aging) measured for 11 years (1999–2010) of the Hoa Binh hydropower dam were selected as a case study. The data were then split into a ratio of 70:30 for developing and validating the hybrid model. The performance of the resulting model was assessed using RMSE, MAE, and R ². Experimental results show that the proposed SONFIS model performed well on both the training and validation datasets. The results were then compared with those derived from current state-of-the-art benchmark methods using the same data, such as support vector regression, multilayer perceptron neural networks, Gaussian processes, and Random forests. In addition, results from a Different evolution-based neural fuzzy model are included. Since the performance of the SONFIS model outperforms these benchmark models with the monitoring data at hand, the proposed model, therefore, is a promising tool for modeling horizontal displacement of hydropower dams.

     

A weighted normalized difference water index for water extraction using Landsat imagery

Water extraction is one of challenging topics in studies on remote-sensing applications. Spectral profiles and experiments indicate that existing water indices often misclassified turbid water, small waterbodies, and some land features in a shadow area. In this study, a new water index called weighted normalized difference water index (WNDWI) was proposed to reduce those errors and improve the mapping accuracy of waterbodies by using Landsat imagery. To test the performance of the newly proposed water index, two test sites (Tampa Bay, FL, USA and Xiangshan Harbour, Zhejiang, China) were selected and the performances of three existing water indices including the normalized difference water index (NDWI), the modified NDWI (MNDWI), and the automated water extraction index (AWEI) were compared with that of the WNDWI. In addition, a default threshold 0 and automatically thresholding methods including Otsu threshold method and multiple thresholds identified by valley points in a histogram curve were tested to determine an optimal threshold that can be used to separate water and non-water features from grey images created by the four water indices. The experimental results indicate that the overall accuracies (OAs) created with WNDWI were all higher than those created with the three existing water indices: NDWI, MNDWI, and AWEI in both sites. Moreover, the results thresholded by 0 owned or shared the highest OAs with the results segmented by some of non-zero thresholds obtained from Otsu method and multiple thresholds method. Therefore, using an appropriate threshold, the proposed method could extract waterbodies from Landsat TM imagery with a high accuracy.     

GPS多天线数据采集与控制系统

针对常规GPS应用中成本较高的问题，文中研究了GPS多天线数据采集与控制系统，实现了一机对多点的监测。实验和实际应用表明，该系统对GPS信号的衰减，GPS测量精度几乎没有影响。该技术使得GPS监测局部区域人工和自然结构形变（如大坝，建筑等）的监测费用大大降低，具有重要的实用价值。     

Effect of superficial insulation on roller-compacted concrete dams in cold regions

Superficial insulation is often used to prevent cracking of concrete dams located in cold regions. In this study, surface temperatures with and without heat insulation during the overwintering period are calculated. Using the material properties of roller-compacted concrete (RCC) as bases, we simulate and analyse the temperature field and thermal stress of certain RCC gravity dams in cold regions. The simulation and analysis are performed by three-dimensional finite element relocating mesh method under the following conditions: under the absence of heat insulation, and with the application of a 5 or 8 cm polystyrene slab for heat conservation. Moreover, the effects of superficial insulation and different thicknesses on the temperature field and thermal stress are analysed. Results show that superficial insulation can considerably increase the superficial temperature of RCC dams in cold regions, thereby decreasing superficial temperature difference and maximal tensile stress. These conditions prevent surface cracks from forming.     

Cubic spline interpolation to develop contours of large reservoirs and evaluate area and volume

The paper describes the development of an algorithm that uses spline interpolation methods in order to calculate the ground relief contours, the area and the volume reservoir associated with a large dam. This algorithm is a great help to the engineer who designs dams in calculating the area and the volume of the reservoir for dams with specific positions and geometric characteristics, for different water levels and over a ground relief with elevation contours which one evaluates, smoothes and draws using cubic splines. The advantages of the algorithm are significant not only for specific computer programs that refer to reservoirs, but also for computer programs relevant to hydraulic calculations of reservoirs and associated structures.     

高性能差动电阻式传感器自动化测量系统的研制

差动电阻式传感器具有防潮、长期测量、测值稳定、可靠性高、测试原理简单、适用范围广等优点 ,在我国水利行业中得到了广泛的应用 .这类传感器同时又有内阻低的缺点 ,使得信号传输和测量非常困难 .本文介绍的FWC2 0 0 0型差动电阻式网络测量系统在引入独创性的测量技术基础上 ,采用先进的电子测量技术 ,很好地解决了信号传输和高精度测量难题 .该测试系统在许多桥梁、大坝的安全监测工程中的得到了应用 ,并取得了良好的使用效果     

基于北斗/GNSS 与 InSAR 的水库群坝体表面变形监测体系

面向城市水库群安全监测的需求,提出基于北斗/GNSS与InSAR技术构建城市水库群坝体表面变形监测体系的概念,利用InSAR技术大范围、高精度的优势,研究实现水库群坝体表面变形监测高效率的方法,同时提出基于北斗/GNSS基准网实现区域内测点实时和应急监测的策略。通过2种技术手段的结合,可形成自动、高效、经济、综合的水库坝体表面变形监测作业新模式,实现对城市水库群高时间分辨率和高空间分辨率,普查性监测和重点在线监测的有机统一。     

淤地坝水资源调控三维仿真系统

淤地坝对水资源调控过程是一种动态变化的过程,只用文字描述,无法给研究人员形象直观的展示,本文提出一种基于Unity3D的降雨过程与淤地坝调控水资源过程的模拟方法。采用3DsMax对淤地坝系主要模型进行三维建模,使用Unity3D引擎进行场景交互设计,采用粒子系统进行降雨的模拟,设计并实现了水资源收集仿真算法,利用多层次细节技术和剔除遮挡技术等进行渲染优化。借助这一方法,开发了淤地坝水资源调控虚拟再现仿真系统。实例表明,该方法可以形象逼真的再现降雨径流过程,还能表现淤地坝等组件对于水资源的调控过程,使展示的效果更加逼真。     

基于地球大数据的“美丽湖泊”SDG 6.3.2综合评价体系构建

湖泊等水体水质状况直接关系到人类社会的可持续发展。传统的水环境质量评价体系大都基于统计数据和原位测量数据,存在周期过长和时效性差等问题,难以实现大范围、连续地湖泊水环境质量评价。遥感技术的发展为高时空分辨率的湖泊水环境质量评价提供了可能。在总结现有湖泊水环境质量评价体系的基础上,以联合国可持续发展目标(Sustainable Development Goals,SDGs)中指标SDG 6.3.2(环境水质良好的水体比例)为导向,结合统计数据、野外实测数据和卫星遥感数据等地球大数据构建了"美丽湖泊"综合评价体系,以期在联合国可持续发展目标框架下,推进我国湖泊水环境质量综合评价,为美丽中国评价提供技术参考。     

Optimal design of arch dams subjected to earthquake loading by a combination of simultaneous perturbation stochastic approximation and particle swarm algorithms

An efficient optimization procedure is introduced to find the optimal shapes of arch dams considering fluid–structure interaction subject to earthquake loading. The optimization is performed by a combination of simultaneous perturbation stochastic approximation (SPSA) and particle swarm optimization (PSO) algorithms. This serial integration of the two single methods is termed as SPSA–PSO. The operation of SPSA–PSO includes three phases. In the first phase, a preliminary optimization is accomplished using the SPSA. In the second phase, an optimal initial swarm is produced using the first phase results. In the last phase, the PSO is employed to find the optimum design using the optimal initial swarm. The numerical results demonstrate the high performance of the proposed strategy for optimal design of arch dams. The solutions obtained by the SPSA–PSO are compared with those of SPSA and PSO. It is revealed that the SPSA–PSO converges to a superior solution compared to the SPSA and PSO having a lower computation cost.     

Multifractal scaling behavior analysis for existing dams

The fractal theory was used to describe long term behavior of dam structures by means of determining (mono-) fractal exponents. Many records do not exhibit a simple monofractal scaling behavior, which can be accounted for by a single scaling exponent. In this paper the multifractal detrended fluctuation analysis (MF-DFA) is employed to analyze the time series of in situ observed data of existing dam which intrinsically reflects its long term behavior and structural evolution law. Deformation analysis of one gravity dam is taken as an example, the multifractal characteristic of the time series is obtained. The results show that this method can reliably determine the multifractal scaling behavior of time series of existing dams. The fractal theory can be applied to predict and diagnose dam behavior.     

Construction of “Beautiful Lakes” Comprehensive Assessment System based on Big Earth Data and SDG 6.3.2

Lake water quality is directly related to the survival and development of human beings and society. Most of the existing assessment systems are based on statistical data and in-situ measurement data. Due to the long cycle and poor timeliness, these assessment systems are hard to achieve large-scale and continuous assessment of lake water environment. The development of remote sensing technology has made it possible to evaluate the quality of lake water environment with high spatial and temporal resolution. Thus, after summarizing the existing lake water environment quality assessment system, a new assessment system called “Beautiful Lakes” comprehensive assessment system was developed. A novel index system based on Big Earth Data (such as statistical data, field measured data and satellite remote sensing data) was first developed and integrates human activities, water quality, biology and hydrology indexes. Then, the threshold of each index was determined and the Percentage Compliance of Water Quality Index (c_wq) was calculated. Following UN water, the threshold 80% of c_wq was used to classify the water quality, which means if a certain water body is with c_wq greater than 80%, the water quality is “good”; otherwise, the water quality is poor. Finally, the Percentage of Water Bodies of Good Quality (WBGQ) was calculated to attain the comprehensive assessment of water quality on a large scale (basin scale or national scale). The new assessment system will promote the comprehensive assessment of lake water environment quality in China under the framework of the UN Sustainable Development Goals and provide a technical reference for the evaluation of beautiful China.     

基于PLC的堵板密封装置控制系统设计

为保证核电厂反应堆压力容器与蒸汽发生器检修工作能够同时进行,需使用堵板密封装置对主管道进行封堵。这可以使得反应堆一回路水位的升降不影响蒸汽发生器的检修工作,同时也可保证人员和设备安全,避免人员或异物掉入主管道。使用西门子S7-1200 PLC作为控制器,采用全集成自动化博途软件进行编程设计。根据工艺流程,设计了可编程逻辑控制器(PLC)控制系统程序,实现了对堵板密封胶囊各腔室压力的监控。相较于市场上现有的手动调节系统,所设计的系统具有密封胶囊压力自动控制、故障远程报警功能。控制系统操作画面简洁,易于操作等特点。试验结果表明,该系统操作方便、运行可靠,可为用户在核电厂检修期间,提供一回路主管道和蒸汽发生器一次侧之间安全、可靠的隔离效果。使用该系统对充气式密封胶囊进行耐久性测试,通过对测试数据的分析,可用于优化密封胶囊的生产工艺。     

在线式吸收型光纤干度传感器的研制

介绍了稠油开采时蒸气干度测量重要性与现有测量手段,分析现有的测量方式固有缺陷。提出了利用蒸气与液态水红外吸收峰值的差异研制光纤干度传感器的设计思路,在线式传感器的信号拾取部分采用双光路对射式结构,调制信号经高温光纤传输,信号经光电转换、放大与软件等解调处理,显示干度值或绘出干度变化曲线。