Time filter

Source Type

Fang G.-H.,Hohai University | Wen X.,Hohai University | Yu F.-C.,Anhui and Huaihe River Institute of Hydraulic Research
Fresenius Environmental Bulletin | Year: 2013

Gucheng Lake has been suffering from eutrophication due to increased pollution and nutrient loads discharged into the watershed. Based on artificial neural networks (ANNs) and a 4-year record of water quality data (from 2006 to 2009), this study proposes an early-warning model for eutrophication aiming to predict the concentration of total nitrogen (TN) and total phosphorus (TP) of Gucheng Lake with a lead time of one week. To develop such data-driven models efficiently, a comprehensive sampling strategy is adopted to ensure that most relevant predictors for TN and TP are retained. Factor correlation analysis is then employed to further eliminate noisy predictors. The preferable selecting ranges of correlation coefficient values are proven to be [-1, -0.5] and [0.5, 1]. As a result, 6 and 18 input variables are filtered from 75 potential input variables to develop the TN and TP prediction models, respectively. The prediction models can achieve high performance. The validation results of TN (TP) showed that the correlation coefficient of 0.9915 (0.9945) and the RMSE of 0.0684 (0.0015), which have demonstrated the potential of ANN models to predict TN and TP conditions at Gu-cheng Lake.

Zhang J.,Anhui and Huaihe River Institute of Hydraulic Research | Zhang L.,Hohai University
Earthquake Engineering and Engineering Vibration | Year: 2014

Based on a Chinese national high arch dam located in a meizoseismal region, a nonlinear numerical analysis model of the damage and failure process of a dam-foundation system is established by employing a 3-D deformable distinct element code (3DEC) and its re-development functions. The proposed analysis model considers the dam-foundation-reservoir coupling effect, influence of nonlinear contact in the opening and closing of the dam seam surface and abutment rock joints during strong earthquakes, and radiation damping of far field energy dissipation according to the actual workability state of an arch dam. A safety assessment method and safety evaluation criteria is developed to better understand the arch dam system disaster process from local damage to ultimate failure. The dynamic characteristics, disaster mechanism, limit bearing capacity and the entire failure process of a high arch dam under a strong earthquake are then analyzed. Further, the seismic safety of the arch dam is evaluated according to the proposed evaluation criteria and safety assessment method. As a result, some useful conclusions are obtained for some aspects of the disaster mechanism and failure process of an arch dam. The analysis method and conclusions may be useful in engineering practice. © 2014 Institute of Engineering Mechanics, China Earthquake Administration and Springer-Verlag Berlin Heidelberg.

Yu F.-C.,Anhui and Huaihe River Institute of Hydraulic Research | Fang G.-H.,Hohai University | Shen R.,Anhui and Huaihe River Institute of Hydraulic Research
Environmental Earth Sciences | Year: 2014

Comprehensive early warning of drinking water sources is a multi-target, multi-level and multi-factor system. The complex nonlinear relationship between early-warning indicators and warning limit levels has not been founded. In the present study, the combination weight of early-warning indicators was first determined by combining Delphi–Analytic Hierarchy Process subjective weight and entropy objective weight. For uncertain characteristics of qualitative indicators, the grey weight matrix is obtained through grey evaluation theories. The grey-fuzzy comprehensive early-warning model was established based on advantages of combination weights, grey evaluation and fuzzy comprehensive evaluation theories. Then, a multi-factor and multi-level warning system, of which results were represented by ambiguity warning level, was put forward and applied to Gucheng Lake. The results showed that the comprehensive security degree of Gucheng Lake is 5.43, which is between warning level (degree is 6) and heavy warning level (degree is 4). This indicated that Gucheng Lake needs to improve protection measures and enhance the safety of drinking water source. © 2014, Springer-Verlag Berlin Heidelberg.

Wang Y.-Z.,Anhui and Huaihe River Institute of Hydraulic Research | Wang Y.-Z.,Anhui Province Key Laboratory of Water Conservancy and Water Resources | Yu F.-C.,Anhui and Huaihe River Institute of Hydraulic Research | Yu F.-C.,Anhui Province Key Laboratory of Water Conservancy and Water Resources | And 2 more authors.
Shuili Xuebao/Journal of Hydraulic Engineering | Year: 2013

Using main ditch for farmland drainage is a basic measure to solve waterlogging problem in Huaibei Plain of Auhui Province. However, uncontrolled drainage often results in serious waste of water resources. In the present study, we established two experimental zones (Bazhang Ditch, Chezhe Ditch) with the total area 218km2. Based on the field observations combined with theoretical simulation analysis, the key techniques were studied systematically such as the effect of main ditch control projects on farmland drainage, groundwater depth, rainfall-runoff and groundwater resources regulation in the two zones. The results show that the controlled drainage of main ditch could regulate groundwater depth and increase the groundwater utilization, improving farmland ecological environment and regulating water resources allocation in time and space. In addition, it didn't influence the farmland drainage. This technique has been widely applied in Huaibei Plain and achieved good social, economic and environmental benefits. It can be used as a reference for the construction of control drainage project and regulation of farmland water resources in similar areas.

Zhang J.-K.,Anhui and Huaihe River Institute of Hydraulic Research | Yan W.,General Electric | Cui D.-M.,Anhui and Huaihe River Institute of Hydraulic Research
Sensors (Switzerland) | Year: 2016

The impact-echo (IE) method is a popular non-destructive testing (NDT) technique widely used for measuring the thickness of plate-like structures and for detecting certain defects inside concrete elements or structures. However, the IE method is not effective for full condition assessment (i.e., defect detection, defect diagnosis, defect sizing and location), because the simple frequency spectrum analysis involved in the existing IE method is not sufficient to capture the IE signal patterns associated with different conditions. In this paper, we attempt to enhance the IE technique and enable it for full condition assessment of concrete elements by introducing advanced machine learning techniques for performing comprehensive analysis and pattern recognition of IE signals. Specifically, we use wavelet decomposition for extracting signatures or features out of the raw IE signals and apply extreme learning machine, one of the recently developed machine learning techniques, as classification models for full condition assessment. To validate the capabilities of the proposed method, we build a number of specimens with various types, sizes, and locations of defects and perform IE testing on these specimens in a lab environment. Based on analysis of the collected IE signals using the proposed machine learning based IE method, we demonstrate that the proposed method is effective in performing full condition assessment of concrete elements or structures. © 2016 by the authors; licensee MDPI, Basel, Switzerland.

Ben P.,Anhui and Huaihe River Institute of Hydraulic Research | Yu B.,Anhui and Huaihe River Institute of Hydraulic Research | Ni J.,Anhui and Huaihe River Institute of Hydraulic Research | Xia D.,Anhui and Huaihe River Institute of Hydraulic Research
Advances in Science and Technology of Water Resources | Year: 2013

In order to investigate the flood discharge capacity, river regulation project and flood operation mode in the main reach of Huaihe River from Zhengyangguan to Wujiadu, a hydrodynamic numerical model was developed to simulate the flood routing based on the characteristics of this reach. This model is verified by the measured flood data in the year of 2005 and 2007. The verification results show that the model is accurate and provides a computing platform for the comprehensive treatment and optimal dispatching in flood detention areas of the main reach from Zhengyangguan to Wujiadu. The effect of the Jingshanhu flood detention area during the flood process in 2007 was analyzed by using this model. The computed results show that the use of the Jingshanhu flood detention area can reduce the water level at Tianjia'an station and increase the concentration velocity of the flood.

Yu B.-Y.,Anhui and Huaihe River Institute of Hydraulic Research | Yang X.-J.,Anhui and Huaihe River Institute of Hydraulic Research | Ni J.,Anhui and Huaihe River Institute of Hydraulic Research | Ben P.,Anhui and Huaihe River Institute of Hydraulic Research
Shuidonglixue Yanjiu yu Jinzhan/Chinese Journal of Hydrodynamics Ser. A | Year: 2014

The flood-flowing zone of the Middle Reach of the Huihe River is one of important components of the flood protection system of the Huihe River. The existing flood-flowing zones of the Huihe River consist of a lot of individual flood-flowing zones which are often used for flood flowing. However, the existing flood flowing zones are neither efficient nor economic. Further river engineering work for the Huihe River requires regulation of the flood-flowing zones of the Middle Reach of the Huihe River. After regulation of the flood-flowing zones, the discharge capacity of the flood-flowing zones of the Middle Reach of the Huihe River will affect the reallocation of river engineering work and the optimal allocation of flood-flowing zones. Key factors affecting the discharge capacity of the flood-flowing zones are: Geometry of flood-flowing zone, size and layout of the inlet-and-outlet gates for flood storage, hydraulic parameters of the inlet-channel to the flood-flowing zone and outlet-channel from the flood-flowing zone, etc. In this paper, both hydrodynamic simulation and physical experiments have been carried out to study the discharge capacity of 5 flood-flowing zones along the river reach from Zhengyangguan to Fushan of the Huaihe River. The results of the calculation and verified test show that the discharge capacities of these 5 flood-flowing zones in regulation have been determined.

Li R.-Z.,Hefei University of Technology | Huang Q.-F.,Hefei University of Technology | Yang J.-W.,Anhui and Huaihe River Institute of Hydraulic Research | Zhang R.-G.,Hefei University of Technology | Jin J.-L.,Hefei University of Technology
Zhongguo Huanjing Kexue/China Environmental Science | Year: 2016

A typical agricultural headwater stream was chosen as the representative to investigate the dynamic characteristics of effective flow for nutrient retention over a longer time scale, based on the change of regional hydrology, from the perspective of coupling the discharge probability density function and nutrient retention efficiency. Through the Monte Carlo simulation for discharge probability density function, the overall level of nutrient retention for the target stream was quantitatively evaluated as well as the most effective flow and the functionally equivalent discharge were calculated, according to the nutrient uptake velocity derived from field tracer experiments. The overall levels of retention capability for NH4 + and PO4 3- were quite low. The expected values of the retention efficiency of NH4 + and PO4 3- were 0.0671 (6.71%) and 0.0541 (5.41%), respectively. The most effective flow for NH4 + and PO4 3- were 0.0051m3/s and 0.0049m3/s, and the functionally equivalent discharge for them were 0.044m3/s and 0.043m3/s, respectively. In view of the fact of low nutrient uptake velocity in the stream, it is necessary to improve the nutrient retention efficiency of the target stream by reconstructing stream morphology and streambed geomorphology. © 2016, Editorial Board of China Environmental Science. All right reserved.

Loading Anhui and Huaihe River Institute of Hydraulic Research collaborators
Loading Anhui and Huaihe River Institute of Hydraulic Research collaborators