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The study on developing the reasonable safety monitoring indexes plays a most importantly role in the health monitoring of high core rockfill dams. However, researches on this topic are relatively scarce both at home and abroad. In this paper, the characteristics and failure modes of seepage in high core rockfill dam are analyzed firstly. Then, a safety monitoring index based on seepage quantity, which reflects the overall seepage behavior, is developed, using the real-time monitoring data and its safety monitoring model. Moreover, another safety monitoring index based on seepage gradient, reflecting the local seepage behavior, is proposed, combining the spatial layout of osmo- meters and local failure mechanisms of core wall. Additionally, one more safety monitoring index based on permeability coefficient, which considers the overall and local seepage behaviors, is developed, on the basis of establishing the finite element analysis model and real-time seepage coefficient inversion analysis model of high core rockfill dam. A case study on these indexes of Nuozhadu high core rockfill dam is developed, which improves the reliability of seepage safety evaluation of the dam.

A number of high core rockfill dams, such as Nuo Zhadu (261.5 m), Shuangjiangkou (314 m), Liang Hekou (293 m) and so on, are being or to be built in China. These extra high core rockfill dams around 300 m have broken through the applicable scope of the current norms. The internal mechanisms of them are complex. What’s worse, they will be faced with disadvantage loading conditions, such as high water head, high stress and eventual earthquake for a long time in the process of service period. Therefore, it is of great difficult to ensure the safety of these water conservancy and hydropower projects [

Safety monitoring indicator is a key to quickly determine the dam’s safety state, assess and monitor the safety of a dam. At present, both domestic and foreign researches on dam safety monitoring index mainly concentrate in the concrete dam deformation monitoring indexes [

In order to control the safety state of extra high core rockfill dams, ensure the long-term healthy service of the structures and feedback to guide the design theory of high core rockfill dam and the scientific development of damming technology, this article will focus on the change of real-time dam seepage flow, the seepage gradient and local mean soil permeability coefficient, developing three seepage safety monitoring indexes for extra high core rockfill dam.

Seepage failure is one of the main crash modes of high core rockfill dam, and the monitored seepage quantity is a comprehensive effect of the seepage state. Therefore, develop a seepage quantity monitoring index will provide a technical guidance for the safety of high core rockfill dam. In the process of developing a seepage quantity monitoring index, a number of factors should be taken into consider, including reservoir level, rainfall, and the role of material time-varying effect for seepage flow, as well as statistical characteristics of the monitoring data. In the following part, the seepage statistical model are used for fitting the relation between the monitoring effect values and the corresponding loads, environmental factors, predicting the development law of seepage quantity. The confidence interval is used to consider the false alarm caused by the monitoring errors, and the seepage safety monitoring work is carried out then.

quantity monitoring index by the above model and confident interval method.

The monitored seepage quantity of the high core rockfill dam is mainly affected by the reservoir level, the downstream water level, the rainfall infiltration and the time-varying factors of the impervious body. Therefore, the statistical model for seepage flow of high core rockfill dam can be expressed by water level component

where: ^{th} day before the observation;

The samples of monitoring effect values can be divided into fitting sets and forecasting sets. Then a mathematical model between fitting set data of monitored effect values and loads can be established. After establishing the statistical model of monitored seepage quantity, the predicted value of the effect

According to the statistical theory, the above error event is a small probability event when the significance level

where:

By the above method, the seepage safety monitoring index of high core rockfill dam can be obtained

1) When

2) When

3) When

High core rockfill dam is mainly composed of rockfill body and impervious core wall, which is shown in

Through the seepage pressure monitoring, the level and distribution of the seepage pressure in dam foundation can be timely monitored, the possibility of local penetration failure can be determined and the performance of overall anti- seepage can be evaluated. The conventional seepage pressure monitoring of the high core rockfill dam includes seepage pressure monitoring of dam body and foundation. The former mainly laids osmometers in 3 - 5 main observation elevation section, which is generally located in the center line of core wall, its upstream and downstream sides and the downstream fine filter, focusing on the pressure distribution and the location of saturation line of the section. Seepage

pressure monitoring of dam foundation laids osmometer in the contact area between core wall and concrete cushion and excavation surface, focusing on the seepage pressure in the contact surface and foundation after water storage.

The monitoring indexes could be designed corresponds to the alarm values which is developed under the most unfavorable loads combination. Then these indexes can be used to evaluate and predict the loads with stranding ability of a dam. Based on this philosophy, the idea that controling of monitoring permeability gradient without exceeding its allowable value, can be used as a method to monitor the seepage stability of core wall and foundation.

According to the monitoring values of the measured points which is in the same height in the main observation section, the monitoring permeability gradient

where: ^{th} and the (i + 1)^{th} osmometer;

^{th} osmometer.

In accordance with the dam desination principles, the local permeability gradient of the core wall should be less than allowance value

above values.

It should be noted that, the permeability gradient between adjacent osmometer calculated from the above process belongs to the average one. It is not conservative to use this value carrying out the safety monitoring tasks. Considering the effect of this factor, a reasonable selection of safety coefficient

Therefore, the safety monitoring index is expressed as follows:

where:

(1) When

(2) When

(3) When

In the long-term service of the core rockfill dam, the dam has to withstand the static & dynamic cycle load, all kinds of sudden disaster, and corrosion from harsh environment. These factors may lead to the changes in the physical and mechanical properties of the dam material and structural properties of the dam, which results in a tendency to bring about a declining safety performance. The average permeability coefficient of the core wall is an important parameter of the seepage field in the high core rockfill dam, and it will presents time variation behavior with the service of the project. Therefore, it is of great value to judge the health status of dams from the perspective of the permeability coefficient of the core wall filling material. The monitoring index of the average permeability coefficient of the core wall can guide the safety management of the high core rockfill dam. Here, the permeability coefficient refers to the average value of the regional permeability coefficient selected in the structural numerical analysis.

The permeability coefficient is defined as the unit flow rate under unit hydraulic gradient, which comprehensively reflects the permeability of soil. The permeability coefficient is related to the shape, size, unevenness coefficient and water viscosity of soil particles. In addition to the indoor test and the field pumping and water injection test, we can also use the finite element calculation combined with the prototype monitoring data to invert the permeability coefficient. First of all, we make use of the upstream water level

It is assumed that the effect of seepage-prevention wall in the core rockfill dam is good enough and monitored most of the seepage quantity through the core wall. The core wall is divided into

where:

After obtaining the inversion analysis results of a large number of permeability coefficients, the

Firstly, we select the appropriate neural network such as the least squares support vector machine, the head H and total flow rate Q as the input vector, the permeability coefficient K as the output vector to establish the nonlinear relationship among K, H and Q. Then H and Q are input into the trained neural network model, the inversion value of K can be obtained.

Based on the above method, we inverse permeability coefficient for each group of upstream water level and total seepage. The impermeability of the core wall material is analyzed by comparing K and the allowable value [K]. The safety monitoring index of soil permeability coefficient can be expressed as:

where:

1) When

2) When

The Nuozhadu Hydropower Station is located in the junction area of Lancang County and Cuiyun district in Simao City, Yunnan province, the downstream of Lancang River. The project is a large (1) type engineering, mainly for power generation. The main water-containing structure is a core wall rockfill dam with a maximum height of 261.5 meters, third at the same type of dams in the world. The normal water level is 812.0 m and dead water level is 765.0 m.

The weir point DB-WE-02 near the 7# grouting hole in the right bank of Nuozhadu dam is selected in this case. The statistical model of seepage quantity is established as follows, based on the monitoring data and Equation (1) in this paper:

the complex correlation coefficient of the statistical model is 0.88, which is in high accuracy. Therefore, the above monitoring model will reflect the changing behavior of seepage quantity of DB-WE-02, and the seepage monitoring indexes can be developed using this model. The developed seepage quantity monitoring indexes is shown in

The internal osmotic pressure gauges, DB_C_P_50~52, DB_A_P_24 ~ 26, DB_ D_P_24 ~ 26, on the 780m elevation of three sections (A, C and D subjective monitoring section) in core wall of Nuozhadu dam is selected here. Then, the gradient between adjacent monitoring points according to is calculated according to Formula (4).

According to the planar seepage analysis and 3D seepage analysis results from feasibility study report of Nuozhadu dan, the maximum permeability gradient

Number | Complex correlation coefficient R | Standard deviation | Monitoring index/(L・s^{−1}) | ||
---|---|---|---|---|---|

Safe | Abnormal | Dangerous | |||

DB-WE-02 | 0.88 | 0.071 |

in the downstream location of the core wall is 7 - 8, and this value satisfies with the requirements of seepage control and seepage stability. Therefore, the maximum seepage gradient is chosen to be the allowance seepage gradient when developing the seepage gradient safety monitoring index, namely

The seepage gradient monitoring indexes are developed in

A finite element model of the highest section C-C of Nuozhadu dam is established by Geo studio firstly, which is shown in ^{−9} ~ 2 × 10^{−7}m/s.

It is necessary to convert the unit width quantity of the cross-section C-C into the total seepage quantity of the dam. Here, the dam body is divided into several

Number | Monitoring index/(L・s^{−1}) | ||||
---|---|---|---|---|---|

Safe | Abnormal | Dangerous | |||

DB-C-P-50_51 | 2.47 | 0.00 | |||

DB-C-P-51_52 | 0.84 | −0.09 | |||

DB-A-P-24_25 | 1.35 | −2.04 | |||

DB-A-P-25_26 | 2.24 | −1.05 | |||

DB-D-P-24_25 | 3.00 | −0.23 | |||

DB-D-P-25_26 | 0.5 | −0.41 |

Dam material | Permeability coefficient /(m・s^{−1}) | Dam material | Permeability coefficient /(m・s^{−1}) |
---|---|---|---|

Core wall | 2 × 10^{−9}～2 × 10^{−7} | Fine rock transition material | 2 × 10^{−3} |

I anti (Dr = 0.8) | 2 × 10^{−5} | Upstream and downstream cofferdam | 1 × 10^{−2} |

II anti (Dr = 0.85) | 2 × 10^{−3} | Curtain | 5 × 10^{−8} |

Ⅰarea of rockfill | 1 × 10^{−2} | Weakly weathered rock mass | 5 × 10^{−7} |

Ⅱarea of rockfil | 8 × 10^{−4} | New rock mass | 1 × 10^{−7} |

sections along the axis due to the geometry of each dam section. It is assumed that the underwater area is proportional to the unit width quantity. The total seepage quantity of the dam can be expressed as:

where:

The finite element calculation results of total seepage quantity and the total seepage quantity of dam after conversion are obtained accordingly. The results indicate that when the total seepage quantity is 11.57L/s, the inversion value of permeability coefficient is 1.71 × 10^{−8} m/s. The average values of DB-C-P-20, DB-C-P-22, DB-C-P-30 and DB-C-P-31 in November 2015 were used to test the inversion reliability of permeability coefficient.

According to the “design specifications of roller compacted earth dam”, the permeability coefficient of the core wall should satisfy the norm that it should be lower than 1.0 × 10^{−7} m/s. A safety factor K = 2 is taken as well. Then, the permeability coefficient monitoring indexes is developed in

In this paper, three safety monitoring indexes: seepage quantity monitoring in-

Number | Elevation/m | Measured average /m | Calculated average /m | Relative error |
---|---|---|---|---|

DB-C-P-20 | 660 | 130.8028 | 131.1199 | 0.24% |

DB-C-P-22 | 660 | 130.2152 | 131.1181 | 0.69% |

DB-C-P-30 | 701 | 87.4643 | 90.1198 | 3.04% |

DB-C-P-31 | 701 | 87.4967 | 90.1199 | 3.00% |

Time | Permeability coefficient K/(m・s^{−1}) | Monitoring index/(m・s^{−1}) | |
---|---|---|---|

safe | abnormal | ||

November 2015 | 1.71 × 10^{−8} |

dex, permeability gradient monitoring index and local average permeability coefficient monitoring index are developed from the perspective of the seepage characteristics and the failure mechanisms of the high core rockfill dam. Among them, the seepage quantity safety monitoring index, based on the whole seepage quantity monitoring data, is simple and easy to developed, on basis of obtaining high reliability, long series and good integrity monitoring data. The permeability gradient safety monitoring index, describing the spatial seepage pressure distribution of main monitoring sections, owns the ability of monitoring the local abnormality of core wall and dam foundation. The local average permeability coefficient safety monitoring index, based on structural simulation and inversion analysis of monitoring data, takes into account of the overall and local seepage state in high core rockfill dam.

The three indexes drop different aspects of emphases and complement each other. They can be used synthetically, to evaluate the seepage safety of the high core rockfill dam. However, it is necessary to develop a comprehensive and reliable indicator in the further study, for providing decision references in the safety evaluation and early warning of high core rockfill dam.

This work was supported by research funds from National Natural Science Foundation of China (Grant Nos. 51379068, 51279052, 51179066), Jiangsu Natural Science Foundation (Grant Nos. BK20140039), Jiangsu Basic Research Program (Grant Nos. BK20160872), Priority Academic Program Development of Jiangsu Higher Education Institutions (Grant No. YS11001), and Key Laboratory of Earth-Rock Dam Failure Mechanism and Safety Control Techniques, Ministry of Water Resources (Grant Nos. YK914002).

Chen, B., Zhang, L., Qian, Q.P., Dou, Y.H. and Ji, Z.H. (2017) Research on the Seepage Safety Monitoring Indexes of the High Core Rockfill Dam. World Journal of Engineering and Technology, 5, 42-53. https://doi.org/10.4236/wjet.2017.53B006