Zhiping Wen

Service Life Predicting of Dam Systems with Correlated Failure Modes

AbstractThe 50-year design reference period is coming to an end for many dam projects in China. In the last decade, it has become clear that remaining service life analysis of existing dams must be used to optimally manage the growing number of aging and deteriorating structures. The uncertainties associated with deteriorating dams require the use of probabilistic methods to properly assess their lifetime performance. A dam system involves multiple failure modes; however, conventional assessment and prediction models often neglect the correlations among failure modes. As a result, the remaining service life predicted by these methods is relatively rough. First, in this paper, conventional lifetime distribution functions are introduced. The influences of the correlations among failure modes on series, parallel, or series-parallel structure are discussed, respectively, and the approach for calculating correlation coefficients is proposed. Second, on the basis of the analysis of dam failure causes, failure m...

Rate effect on mechanical properties of hydraulic concrete flexural-tensile specimens under low loading rates using acoustic emission technique.

Acoustic emission (AE) waveform is generated by dislocation, microcracking and other irreversible changes in a concrete material. Based on the AE technique (AET), this paper focuses on strain rate effect on physical mechanisms of hydraulic concrete specimens during the entire fracture process of three point bending (TPB) flexural tests at quasi-static levels. More emphasis is placed on the influence of strain rate on AE hit rate and AE source location around peak stress. Under low strain rates, namely 0.77×10(-7)s(-1), 1×10(-7)s(-1) to 1×10(-6)s(-1) respectively, the results show that the tensile strength increases as the strain rate increases while the peak AE hit rate decreases. Meanwhile, the specimen under a relatively higher strain rate shows a relatively wider intrinsic process zone in a more diffuser manner, lots of distributed microcracks relatively decrease stress intensity, thus delay both microcracking localization and macrocrack propagation. These phenomena can be attributed to Stéfan effect. In addition, further tests, namely the combination of AE monitoring and strain measuring systems was designed to understand the correlation between AE event activity and microfracture (i.e., microcracking and microcracking localization). The relative variation trend of cumulative AE events accords well with that of the load-deformation curve.

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.

Analysis and Back-Analysis for Temperature Field of Concrete Arch Dam During Construction Period Based on Temperature Data Measured by DTS

Based on the observed temperature information of arch dam, the mathematical and mechanical methods are combined usually with dam engineering theory to capture in real time and evaluate in time the developing status and space-time distribution of arch dam temperature, and implement the back analysis for temperature control measures. It is an important step for dam construction and safe operation. Some methods, namely transient temperature-field simulation, thermodynamic parameters back-calculation, and model correction, are used synthetically to solve the above problem. A method is proposed to back calculate the thermodynamic parameters of arch dam by use of the temperature data obtained by the distributed optical fiber temperature sensor (DTS). A problem is studied to couple the simulated temperature field by finite element method (FEM) and the observed temperature field by the DTS. A method is presented to update dynamically the FEM model on the basis of the observed temperature field. An actual engineering is analyzed by the proposed method. It is shown that the DTS system can implement the real-time observation of concrete arch dam temperature field. According to the observed temperature field by the DTS and the updated numerical simulation model of the temperature field, scientific guidance can be given during the pouring process of the arch dam, and reliable data can be provided to analyze and evaluated arch dam safety.

Dam safety prediction model considering chaotic characteristics in prototype monitoring data series

Support vector machine, chaos theory, and particle swarm optimization are combined to build the prediction model of dam safety. The approaches are proposed to optimize the input and parameter of prediction model. First, the phase space reconstruction of prototype monitoring data series on dam behavior is implemented. The method identifying chaotic characteristics in monitoring data series is presented. Second, support vector machine is adopted to build the prediction model of dam safety. The characteristic vector of historical monitoring data, which is taken as support vector machine input, is extracted by phase space reconstruction. The chaotic particle swarm optimization algorithm is introduced to determine support vector machine parameters. A chaotic support vector machine–based prediction model of dam safety is built. Finally, the displacement behavior of one actual dam is taken as an example. The prediction capability on the built prediction model of dam displacement is evaluated. It is indicated that the proposed chaotic support vector machine–based model can provide more accurate forecasted results and is more suitable to be used to identify efficiently the dam behavior.

Macro-comprehensive evaluation method of high rock slope stability in hydropower projects

Combining with the characteristics of the rock slope in hydropower engineering, the evaluation index system of rock slope stability in hydropower projects is determined based on multiple factors, and based on this, research, collect and establish the typical rock slope database of hydropower projects. Based on the fuzzy optimal recognition theory and Case-Based Reasoning, two different methods of slope stability evaluation are established respectively. Analyzing the rock slope stability of one hydropower project by the two methods, a comparison is made between the two methods and the effectiveness of the methods is verified.

Dam structural behavior identification and prediction by using variable dimension fractal model and iterated function system

Display OmittedThe better forecast effect can be obtained by the combination of IFS and variable dimension fractal model. The method has the certain adaptive ability with high forecasting speed and without convergence problem. Fractal characteristic of dam structural behavior is identified with MF-DFA method.IFS is introduced to build the model fitting the measured dam structural behavior.The variable dimension fractal model and IFS are combined to forecast the dam structural behavior. According to the observations of dam structural health monitoring, iterated function system is adopted to implement the analysis and forecast for dam structural behavior. Firstly, the multifractal detrended fluctuation analysis (MF-DFA) method is employed to identify the fractal characteristics in the measured data series of dam structural behavior. Secondly, the iterated function system algorithm is studied to build the fitting model. The ways to determine the interpolating points (position and number) and vertical scaling factors are given in detail. Thirdly, the variable dimension fractal model and iterated function system are combined to forecast the dam structural behavior. Lastly, the displacement behavior of one concrete gravity dam is analyzed and predicted by the proposed approach. It is shown that the whole trend and detail characteristics of dam structural behavior observed can be described well, and the prediction precision can be improved.

Multi-Layer Multi-Index Comprehensive Evaluation for Dike Safety

Dike safety is influenced by many factors. The contribution of every factor can be reflected with multiple indexes. To implement the reasonable evaluation for dike safety, a multiple indexes-based layer-by-layer evaluation approach is proposed in this paper. Extension theory, genetic algorithm and analytical hierarchy process are combined to identify the effects of all indexes on dike safety. First, a multi-layer system is built to describe the relationship between dike safety and its main influencing factors, evaluation indexes. Safety level and corresponding quantitative criteria of evaluation indexes are given. Second, the matter element analysis method in extension theory is introduced to establish the multi-index evaluation model. The relative importance of evaluation indexes can be determined and dike safety can be evaluated dynamically with the model. Third, to decrease artificial participation during the evaluating process and make the assessment result more objective, an accelerating genetic algorithm is integrated into analytical hierarchy process to calculate the weights of lower layer indexes in multi-layer evaluation system of dike safety. Finally, the proposed approach is applied to an actual dike case. Results show that the methodology is capable of more objectively judging whole dike safety, can help with identifying potential risk and hazard level.

Assessment and prediction for service life of water resources and hydropower engineering

Abstract There are a large number of in-service water resources and hydropower engineering in the aging stage. It is an urgent problem how to assess and predict service life of water resources and hydropower engineering. The related theory and method need to be proposed to improve the safety management level and make the reinforcing, removing or downgrading decisions. The current achievements in the research are reviewed. The assessment criteria and system are analyzed. The methodological progress for assessment and prediction of service life is summarized. The future development direction is stated. The key problems and their approaches are related and analyzed. It is shown that the assessment and prediction for service life of water resources and hydropower engineering is a comprehensive research topic. To solve the problems in above field, it is necessary to integrate many theories, methods and techniques in other fields such as water resources and hydropower engineering, geotechnical engineering, construction materials, environmental engineering, cybernetics and computer engineering.

Blind Source Separation Model of Earth-Rock Junctions in Dike Engineering Based on Distributed Optical Fiber Sensing Technology

Distributed temperature sensing (DTS) provides an important technology support for the earth-rock junctions of dike projects (ERJD), which are binding sites between culvert, gates, and pipes and dike body and dike foundation. In this study, a blind source separation model is used for the identification of leakages based on the temperature data of DTS in leakage monitoring of ERJD. First, a denoising method is established based on the temperature monitoring data of distributed optical fiber in ERJD by a wavelet packet signal decomposition technique. The temperature monitoring messages of fibers are combined response for leakages and other factors. Its character of unclear responding mechanism is very obvious. Thus, a blind source separation technology is finally selected. Then, the rule of temperature measurement data for optical fiber is analyzed and its temporal and spatial change process is also discussed. The realization method of the blind source separation model is explored by combining independent component analysis (ICA) with principal component analysis (PCA). The practical test result in an example shows that the method could efficiently locate and identify the leakage location of ERJD. This paper is expected to be useful for further scientific research and efficient applications of distributed optical fiber sensing technology.