Settlement modeling in central core rockfill dams by new approaches

Behnia, Danial; Ahangari, Kaveh; Goshtasbi, Kamran; Moeinossadat, Sayed Rahim; Behnia, Mazda

doi:10.1016/j.ijmst.2016.05.024

Cited by 13 publications

(4 citation statements)

References 15 publications

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“…[19] showed that deformation increases with decreasing soil density and water content. The prediction with the historical deformation is important to show the Dam's current condition [4].…”

Section: Resistivity and Surface Deformationmentioning

confidence: 99%

Seepage Patterns in an Earth-Rock Fill Dam Evaluation using Electrical Resistivity Tomography (ERT) Method

Fata

Suhartanto

Hendrayanto

et al. 2021

IOP Conf. Ser.: Earth Environ. Sci.

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Seepages in the earth-rock fill dam are usually monitored by pore pressure, seepage water table, and seepage discharge. However, those monitoring are difficult to describe the seepage patterns because they are installed only in certain points. This research evaluated the seepage pattern resulting from Electrical Resistivity Tomography (ERT). The resistivity was measured by installing electrodes upstream of the Dam at every 10 m and downstream at 20 m distances. The seepage pattern was analysed from the resistivity 2 Dimension distribution using the RES2DINV program. The results showed that the seepage pattern resulting from the ERT method’s resistivity data, which was compared with data of surface dam deformation, pore pressure, and seepage water table, could explain the seepage discharge data. Based on those confirming data, the resistivity data of the ERT method was appropriate to explain the seepage pattern in the earth-rock fill dam and can be further utilized for dam stability analysis.

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“…[19] showed that deformation increases with decreasing soil density and water content. The prediction with the historical deformation is important to show the Dam's current condition [4].…”

Section: Resistivity and Surface Deformationmentioning

confidence: 99%

Seepage Patterns in an Earth-Rock Fill Dam Evaluation using Electrical Resistivity Tomography (ERT) Method

Fata

Suhartanto

Hendrayanto

et al. 2021

IOP Conf. Ser.: Earth Environ. Sci.

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show abstract

“…Recently, with the development of artificial intelligence (AI) technology, some new models have been proposed for dam deformation predictions, such as artificial neural network models, gray models, and time series models (Gurbuz 2011;Tasci and Kose 2016;Behnia et al 2016;Nie et al 2017;Salazar et al 2017;Zou et al 2018;Kim and Kim 2018;Zhang et al 2019;Li and Wang 2019;Gu et al 2020;Lawal and Kwon 2021;Liu et al 2021). Kim and Kim (2018) established a neural network model for the prediction of the relative crest settlement of concrete-faced rockfill dams.…”

Section: Introductionmentioning

confidence: 99%

A novel settlement forecasting model for rockfill dams based on physical causes

Chen

Lü

et al. 2021

Bull Eng Geol Environ

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Rockfill dams are generally constructed on thick overburden layers in mountainous and valley areas due to their high adaptability to complex geological and geographical conditions. The safety of rockfill dams is a research focus worldwide, especially with the increase of dam heights. Significant differential settlement may be induced by different embankment materials in a dam body and various stratum properties in thick overburden layers. The accurate prediction of settlement is particularly important to guarantee the serviceability and safety operation of rockfill dams. Therefore, a novel settlement forecasting model is proposed in this study. This model can achieve a successful prediction of dam settlement during the construction and operation periods. Compared with the traditional model, the settlement influential factors in the proposed model are determined based on the existing theory of coarse-grained soil deformation calculation, causing the selection of factors to have clearer physical meanings. Additionally, the geometric characteristics of the dam, the different material properties in various zones of the dam and the foundation, and the complicated external loading conditions are all considered. Then, the improved regression model for forecasting the settlement of dams is proposed. The proposed settlement forecasting model is further employed to estimate the deformation of a high rockfill dam in China. The results prove that this novel method shows high accuracy and agrees well with the monitoring consequences, and this method is superior to the traditional statistical regression model in predicting dam settlement during the construction period.

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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].…”

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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Settlement modeling in central core rockfill dams by new approaches

Cited by 13 publications

References 15 publications

Seepage Patterns in an Earth-Rock Fill Dam Evaluation using Electrical Resistivity Tomography (ERT) Method

Seepage Patterns in an Earth-Rock Fill Dam Evaluation using Electrical Resistivity Tomography (ERT) Method

A novel settlement forecasting model for rockfill dams based on physical causes

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

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