Health monitoring and dynamic analysis of an earth-fill dam at the stage of first impounding: case study—Siahoo dam of Iran

Eslami, Abolfazl; Ghorbani, Ali; Shahraini, Seyed Vahid

doi:10.1007/s13349-020-00393-5

Cited by 4 publications

(4 citation statements)

References 10 publications

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“…The dynamic displacement monitoring index of the rockfill dam is calculated by the formula (10). ④ By analysing each displacement component obtained in step ①, the extreme values of the temperature component and the time-dependent component are selected, and the water pressure component under the specified water level is calculated by the formula (8). By combining the displacement values of each component, the maximum total displacement, that is, the static displacement monitoring index of the rockfill dam, is obtained.…”

Section: Establishment Of the Static Displacement Monitoring Index Ba...mentioning

confidence: 99%

“…Based on the statistical analysis of the calculation results, the expressions of the water pressure component and time-dependent component are determined by curve fitting according to formula (8). The fitting effect is shown in Fig.…”

Section: Establishment Of the Sfemh Modelmentioning

confidence: 99%

“…As mathematical models established by combining mathematics, mechanics, and intelligent algorithms, dam monitoring models simulate the complex relationships between the influencing factors (such as water level, temperature, and time) and the affected quantities (such as displacement, seepage flow, and crack opening) to judge whether the changes in the affected quantities are normal [7][8][9][10][11]. According to different theoretical methods, monitoring models can be divided into statistical models, deterministic models, hybrid models, intelligent algorithm models, etc.…”

Section: Introductionmentioning

confidence: 99%

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A hybrid monitoring model of rockfill dams considering the spatial variability of rockfill materials and a method for determining the monitoring indexes

Ran

Yang

Zhang³

et al. 2022

J Civil Struct Health Monit

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To further enhance the prediction accuracy of the monitoring model and improve the rationality of the method for determining the monitoring indexes, this paper considers the impact of the spatial variability of rockfill materials on the displacement of the dam. Based on the stochastic finite element method (SFEM), a new rockfill dam displacement monitoring hybrid model is established, and a method to determine the hybrid index for rockfill dam displacement monitoring is proposed by multiindex amalgamation. First, the SFEM is used to simulate the spatial variability of the rockfill mechanical parameters in the process of calculating the water pressure component and the time-dependent component. On this basis, the expression of each component is fitted to construct a stochastic finite element method hybrid model (SFEMH model) of the rockfill dam. Subsequently, by predicting the displacement of the dam and separating each displacement component, the displacement monitoring hybrid index of the rockfill dam is determined by combining the confidence interval method and the most unfavourable components. Finally, the SFEMH model and hybrid index are applied to analyse the actual monitoring data of a rockfill dam. The results show that the proposed model and the method for determining the displacement monitoring hybrid index are scientific and reasonable. The prediction accuracy and effect of the proposed novel model outperform those of other methods in terms of many evaluation indicators, and the reliability of the monitoring indexes is significantly improved. The proposed hybrid model and hybrid index provide a new method for the efficient operation management and accurate safety performance evaluation of rockfill dams.

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Section: Establishment Of the Static Displacement Monitoring Index Ba...mentioning

confidence: 99%

Section: Establishment Of the Sfemh Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A hybrid monitoring model of rockfill dams considering the spatial variability of rockfill materials and a method for determining the monitoring indexes

Ran

Yang

Zhang³

et al. 2022

J Civil Struct Health Monit

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“…It is well known that crest cracking is closely related to the deformation behavior of earth dams and embankments, specifically the differential settlements [3,[6][7][8][9][10][11][12][13][14]. The deformation of high earth-rockfill dams can be accurately predicted using the Finite Element Method (FEM) with calibrated model parameters based on the in-situ deformation monitoring data [15][16][17][18]. The crest cracking hazard of high earth-rockfill dams can be evaluated with the settlement inclination computed from FEM [3,10].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Risk Evaluation and Early Warning of Crest Cracking for High Earth-Rockfill Dams through Bayesian Parameter Updating

Wang

et al. 2020

Applied Sciences

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Crest cracking is one of the most common damage types for high earth-rockfill dams. Cracking risk of dam crest is closely related to the duration of abnormal deformation state. In this paper, a methodology for dynamic risk evaluation and early warning of crest cracking for high earth-rockfill dams is proposed and mainly consists of: (a) The discrimination of abnormal deformation state related to crest cracking, which is implemented by comparing the crest settlement inclination with the threshold value. (b) Computation of crest cracking probability and estimation of cracking time. The exponential distribution is adopted to represent the probability distribution of the duration TAS of abnormal state before crest cracking. Then the crest cracking probability in a given time can be computed by integration with respect to TAS. Inversely, the cracking time corresponding to a given probability can be estimated. (c) Determination of the values of probability adopted to early warn crest cracking, which are suggested to be selected by statistical analysis of the calculated probabilities at the observed cracking times. (d) Bayesian estimation and updating of probability distribution of the parameter λ in the PDF of TAS, according to observed durations of abnormal state before crest cracking. The methodology is illustrated and verified by the case study for an actual earth-rockfill dam, of which crest cracking and recracking events were observed during the periods of high reservoir level. According to the observed values of TAS, the probability distribution for λ is progressively updated and the dispersion of the distributions of λ gradually decreases. The crest cracking probability increases with the duration of abnormal state and the width of confidence interval of the estimated cracking probability progressively contracts with the updating of the distribution for λ. Finally, the early warning of crest cracking for the dam is investigated by estimating the lower limit of cracking time. It is shown that early warning of crest cracking can be issued from at least 20 days ahead of the occurrence of crest cracking event. The idea of using duration of abnormal state of crest settlement to evaluate crest cracking risk of the earth-rockfill dam in this paper may be applicable to other dams.

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The Effect of Drilling Through an Earthfill Dam on the Occurrence of Fracturing

2022

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Health monitoring and dynamic analysis of an earth-fill dam at the stage of first impounding: case study—Siahoo dam of Iran

Cited by 4 publications

References 10 publications

A hybrid monitoring model of rockfill dams considering the spatial variability of rockfill materials and a method for determining the monitoring indexes

A hybrid monitoring model of rockfill dams considering the spatial variability of rockfill materials and a method for determining the monitoring indexes

Dynamic Risk Evaluation and Early Warning of Crest Cracking for High Earth-Rockfill Dams through Bayesian Parameter Updating

The Effect of Drilling Through an Earthfill Dam on the Occurrence of Fracturing

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