Application of copula method and neural networks for predicting peak outflow from breached embankments

The limited number of available data is a common problem in most hydrologic and hydraulic studies, typically dam breach analysis. Construction of a probabilistic model is a key step in most decision making analyses to overcome such limitation. To analyze peak outflow from breached embankments, this paper has utilized two sets of data, original and synthetic datasets. Original datasets were collected from numerous historical dam failures and synthetic datasets were generated by copula method after incorporating the dependence structure among effective variables (height and volume of water behind the dam at failure and peak outflow discharge). The databases were separately employed to train two artificial neural networks (ANNs) as well as two statistical relations. Analyzing the results showed that the ANN model trained with synthetic datasets was the most competitive model for predicting peak outflows having R² of 0.96 and 0.95 for calibration and testing steps, respectively. The other ANN model was also better than statistical relations with R² of 0.94 and 0.87 respectively for calibration and testing steps.     

基于C/S体系结构的大坝在线安全监控系统

该文结合作者在参加"二滩拱坝安全在线监控系统"的开发实践,详细讨论了基于Ｃ／Ｓ体系结构的大坝安全监控系统的系统设计、功能设计与实现。     

观音阁水库选坝过程中岩溶勘察与研究

观音阁水库位于太子河沉降带,广泛发育有寒武系、奥陶系灰岩,岩溶十分发育,在选坝过程中先后选择了六条对比坝线,可研阶段对三、四、六三条坝线进行了对比,通过区域及坝址的岩溶研究,论证了库首及坝下渗漏问题,并对三条坝线的岩溶发育特点及帷幕处理进行了评价,最后选出六坝线作可研阶段的推荐坝线,利用张夏灰岩作持力层,凤山组页岩作隔水层。水库建成后,没有发现坝下及绕坝渗漏问题。     

构皮滩拱坝接缝灌浆串并灌工艺

接缝灌区封闭性是影响接缝灌浆质量的重要因素,多区串通情况下的灌浆施工更是具有工艺复杂、难度大、风险高的特点。本文结合构皮滩拱坝工程实践,对多区串通情况下接缝灌浆的施工难点进行了分析,并对一些实践证明行之有效的施工原则、控制指标确定原则和施工工艺流程进行了总结和探讨     

Multi-block synchronous prediction of concrete dam displacements using MIMO machine learning paradigm

The integration of numerous monitoring points poses a significant challenge to the efficient modeling of dam displacement behavior, and multi-point synchronous prediction is an effective solution. However, traditional approaches usually construct site-specific data-driven models for each monitoring point individually, which focus on single-target regression and discard the underlying spatial correlation among different displacement monitoring points. This study therefore proposes a multi-input multi-output (MIMO) machine learning (ML) paradigm based on support vector machine (SVM) for synchronous modeling and prediction of multi-point displacements from various dam blocks. In this method, a novel multi-output data-driven model, termed as multi-target SVM (MSVM), is formulated through a deep hybridization of classical SVM architecture and multi-target regression. During the initialization of MSVM, the intercorrelation of multiple target variables is fully exploited by decomposing and regulating the weight vectors. The proposed MSVM is designed to capture the complex MIMO mapping from influential factors to multi-block displacements, while taking into account the correlation between multi-block displacement outputs. Additionally, in order to avoid obtaining the unreliable prediction results due to the empirical selection of parameters, an efficient optimization strategy based on the parallel multi-population Jaya (PMP-Jaya) algorithm is used to adaptively tune the hyperparameters involved in MSVM, which contains no algorithm-specific parameters and is easy to implement. The effectiveness of the proposed model is verified using monitoring data collected from a real concrete gravity dam, where its performance is compared with conventional single-target SVM (SSVM)-based models and state-of-the-art ML-based models. The results indicate that our proposed MSVM is much more promising than the SSVM-based models because only one prediction model is required, rather than constructing multiple site-specific SSVM-based models for different dam blocks. Moreover, MSVM can achieve better performance than other ML-based models in most cases, which provides an innovative modeling tool for dam multi-block behavior monitoring.     

长江三峡坝区地壳稳定性研究

长江三峡大坝座落于黄陵断块南端由闪长花岗岩组成的完整岩体上。黄陵断块作为中国内陆的次级板块具有典型的双层结构（结晶基底和沉积盖层），自印支运动形成以来一直呈持续、缓慢的整体抬升，断块除向东南轻微倾斜外，内部构造变形不明显。断块为多条活动构造所围限，其中近南北向的远安和仙女山两条深大断裂为主要强震发生带。远安断裂带为豫西、鄂西、湘西山地和南阳、江汉、洞庭盆地的一条区域性分界线，全长约1000 km，该断裂带历史上曾发生过两次6.5级地震（常德、南阳），两次地震震中相距约500km；仙女山断裂带沿香溪河向北延伸终止于青峰断裂，向南越过渔洋关后，形迹不明，全长达220 km，该断裂带具有发生6.0级地震的构造条件。大坝可能遭遇到的地震危险主要来自这两条强震发生带，对大坝的影响烈度预计为6°～7°，水平峰值加速度0.1～0.15g。     

糯扎渡心墙堆石坝超大粒径掺砾土料击实特性及压实质量检测方法研究

糯扎渡心墙堆石坝心墙防渗土料由天然混合土掺入35%的人工碎石而成,最大粒径达150mm。超大粒径掺砾土料应用于260 m级高土石坝在国内尚属首次,其全料击实特性、细料压实标准、压实质量检测方法等均无先例可循。本文在使用直径600 mm的超大型击实仪进行全料击实试验中,掌握了掺砾土料的击实特性,确定了填筑压实标准,研究应用了全料、细料压实度检测方法。     

柬埔寨甘再重力坝深层抗滑稳定分析

结合柬埔寨甘再重力坝工程,采用弹塑性有限元强度折减法,根据特征点位移突变及坝基整体塑性区贯通情况,得到正常蓄水位下的该坝坝基深层抗滑稳定安全系数。计算结果表明,甘再重力坝深层抗滑稳定安全度较高,满足规范要求。     

长江水库大坝渗流稳定分析

通过对长江水库大坝渗流观测资料和5种工况下大坝渗流稳定分析,综合分析结果表明：大坝各断面浸润线均进入反滤体内,出口渗流是安全的,大坝渗流正常。     

THE RELATIONSHIP BETWEEN THERMAL REGIME ALTERATION AND SPAWNING DELAY OF THE FOUR MAJOR CHINESE CARPS IN THE YANGTZE RIVER BELOW THE THREE GORGES DAM

Large dams often alter flow and thermal regimes downstream, resulting in fish spawning delays and larval abundance declines. Accurate prediction of the delayed spawning period under changed thermal regime is critical for selecting a correct timing to modify dam operation and to release the environmental flow needed to enhance fish spawning. We used correlation analysis to investigate the relationship between thermal regime alteration and spawning delay of the four major Chinese carps (FMCC) below the Three Gorges Dam in the Yangtze River, China, using a 13‐year ecological data series (1997–2009). Eighteen variables were defined to quantify thermal regime and related to two variables representing spawning timing. Our results demonstrate that the start of FMCC spawning has been delayed from early May to middle June since the Three Gorges Dam initiated operation in 2003. Water temperature declines of 2 °C–4 °C in March, April and May (a critical period for gonad development) were the principal reason for the observed spawning delay. The variable most associated with spawning timing was the arrival date of the cumulative temperature needed for gonad development from stages IV to V (D_DegDayIV–V), which describes the long‐term impacts of the timing, magnitude and duration of thermal regime upon gonad development. Only the cumulative temperature for gonad development and the minimum temperature for FMCC spawning (18 °C) are both satisfied, the occurrence of suitable flow conditions, that is, flow increase or flash flood, would produce a successful spawning event. Consequently, we suggest that the experimental flow increase process of the Three Gorges Reservoir aimed at enhancing FMCC spawning should initiate after 15 June when the requisite thermal regime can be met. Copyright © 2013 John Wiley & Sons, Ltd.