Modeling dam deformation using independent component regression method

In the application of regression analysis method to model dam deformation, the ill-condition problem occurred in coefficient matrix always prevents an accurate modeling mainly due to the multicollinearity of the variables. Independent component regression （ICR） was proposed to model the dam deformation and identify the physical origins of the deformation. Simulation experiment shows that ICR can successfully resolve the problem of ill-condition and produce a reliable deformation model. After that, the method is applied to model the deformation of the Wuqiangxi Dam in Hunan province, China. The result shows that ICR can not only accurately model the deformation of the dam, but also help to identify the physical factors that affect the deformation through the extracted independent components.

Application of neural network merging model in dam deformation analysis

In order to improve the prediction accuracy and test the generalization ability of the dam deformation analysis model, the back-propagation（BP） neural network model for dam deformation analysis is studied, and the merging model is built based on the neural network BP algorithm and the traditional statistical model. The three models mentioned above are calculated and analyzed according to the long-term deformation observation data in Chencun Dam. The analytical results show that the average prediction accuracies of the statistical model and the BP neural network model are ~ 0.477 and ＋- 0.390 mm, respectively, while the prediction accuracy of the merging model is ~0. 318 mm, which is improved by 33% and 18% compared to the other two models, respectively. And the merging model has a better generalization ability and broad applicability.

Cloud-Verhulst hybrid prediction model for dam deformation under uncertain conditions

Uncertainties existing in the process of dam deformation negatively influence deformation prediction. However, existing deformation pre- diction models seldom consider uncertainties. In this study, a cloud-Verhulst hybrid prediction model was established by combing a cloud model with the Verhulst model. The expectation, one of the cloud characteristic parameters, was obtained using the Verhulst model, and the other two cloud characteristic parameters, entropy and hyper-entropy, were calculated by introducing inertia weight. The hybrid prediction model was used to predict the dam deformation in a hydroelectric project. Comparison of the prediction results of the hybrid prediction model with those of a traditional statistical model and the monitoring values shows that the proposed model has higher prediction accuracy than the traditional sta- tistical model. It provides a new approach to predicting dam deformation under uncertain conditions.

Dam deformation analysis based on BPNN merging models

Hydropower has made a significant contribution to the economic development of Vietnam,thus it is important to monitor the safety of hydropower dams for the good of the country and the people.In this paper,dam horizontal displacement is analyzed and then forecasted using three methods:the multi-regression model,the seasonal integrated auto-regressive moving average(SARIMA)model and the back-propagation neural network(BPNN)merging models.The monitoring data of the Hoa Binh Dam in Vietnam,including horizontal displacement,time,reservoir water level,and air temperature,are used for the experiments.The results indicate that all of these three methods can approximately describe the trend of dam deformation despite their different forecast accuracies.Hence,their short-term forecasts can provide valuable references for the dam safety.

Deformation Monitoring of Dam Using GPS:Case Study Letsibogo Dam,Botswana

All civil engineering structures are susceptible for deterioration over a period of time after been constructed.Dams,bridges,tunnels,high rise buildings deteriorate due to different factors such as stress,unstable slopes,low foundation shearing strength,settlement,expansion from temperature changes,and age.As a results of these effects,long and short term deformation monitoring of these structures is very important to validate the construction specifications and safety measures.Long term defonnation monitoring is mainly based on measurements of horizontal and vertical movement of the entire structure to ensure that every part of the structure is stable.In this work we present the first deformation monitoring of Letsibogo dam in Botswana by establishing baseline points using Global positioning Systems(GPS)which is capable of detecting structural movement in three dimension.The results obtained shows that the established reference and monitoring points measured by using GPS are reliable with standard deviations of 0.004m and 0.007m in x and y respectively and horizontal displacement of 1cm.In addition,the correlation coefficient for the observations was p=0 which confirms that the GPS measurements of reference and monitoring points are correlated.The position accuracy obtained is suitable for dam deformation monitoring for the first epoch which is expected to take place in 2020.

Seismic Deformation and Seismic Resistance Analysis of Shapai Roller Compacted Concrete Arch Dam Based on Field Monitoring and Dynamic Finite Element Method

Shapai Roller Compacted Concrete(RCC) Arch Dam is the highest RCC arch dam of the 20th century in the world with a maximum height of 132m,and it is the only concrete arch dam near the epicentre of Wenchuan earthquake on May 12th,2008.The seismic damage to the dam and the resistance of the dam has drawn great attention.This paper analyzed the response and resistance of the dam to the seismic wave using numerical simulations with comparison to the monitored data.The field investigation after the earthquake and analysis of insitu data record showed that there was only little variation in the opening size at the dam and foundation interface,transverse joints and inducing joints before and after the earthquake.The overall stability of the dam abutment resistance body was quite good except a little relaxation was observed.The results of the dynamic finite element method(FEM) showed that the sizes of the openings obtained from the numerical modeling are comparable with the monitored values,and the change of the opening size is in millimeter range.This study revealed that Shapai arch dam exhibited high seismic resistance and overload capacity in the Wenchuan earthquake event.The comparison of the monitored and simulated results showed that the numerical method applied in this paper well simulated the seismic response of the dam.The method could be useful in the future application on the safety evaluation of RCC dams.