Causes of the abnormal seepage field in a dam with asphaltic concrete core

Zhang, Jiafa; Wang, Jinlong; Cui, Haodong

doi:10.1007/s12583-016-0623-6

Cited by 8 publications

(7 citation statements)

References 4 publications

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“…The International Commission on Large Dams (ICOLD) [9], Höeg [10], and Wang [11] summarized the knowledge of ACCRDs in terms of design, construction, and performance. With the depth of research and the accumulation of damming experience [12][13][14][15][16][17][18][19][20][21][22][23], the Quxue Dam [24] was built in China in 2017 (the dam height is 174.2 m and the core height is 132 2 of 22 m), which is the highest asphalt concrete core rockfill dam (ACCRD) in the world. China has made a remarkable contribution to the development of ACCRDs.…”

Section: Introductionmentioning

confidence: 99%

Improvement Methods for Reduction of the High Stress of Ultra-High Asphalt Concrete Core Dams

Gao

Dang

et al. 2019

Applied Sciences

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With the rapid development of asphalt concrete core rockfill dams (ACCRDs), the construction of ultra-high asphalt concrete core rockfill dams (UACCRDs) has been improved significantly. However, the security problems of asphalt concrete core (ACC) become very prominent with the increase of dam height. The shear failure control standard and tensile failure control standard of ACC are suggested. The mechanisms of ACC that generate high shear stress and high tensile stress are investigated. Based on the definition of stress level and the transmission mechanism of arch structures, the improvement methods that reduce the high shear stress and high tensile stress of ultra-high asphalt concrete core (UACC) are proposed and investigated. The results show that the stress level of ACC can be reduced significantly by the increase of the strength parameters of ACC (failure ratio, cohesion, and internal friction angle). The following value ranges of the failure ratio, cohesion, and internal friction angle of ACC for the suitable construction of UACCRDs are recommended: Rf ≥ 0.75, C ≥ 0.30 MPa, and φ ≥ 28.5° (h = 150 m), with the growth gradient adjusted by 5%, 15%, and 5%/25 m. The tensile stress and tensile stress area can be reduced obviously by the new type of dams (curved asphalt concrete core rockfill dams (CACCRDs)). The value ranges of the curvature of CACC (k ≥ 1.0 × 10−3) for the suitable construction of UACCRDs are recommended.

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Section: Introductionmentioning

confidence: 99%

Improvement Methods for Reduction of the High Stress of Ultra-High Asphalt Concrete Core Dams

Gao

Dang

et al. 2019

Applied Sciences

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“…Let I p1 , I b1 , and I b2 denote the MI values between F p1 and upstream water level, between F b1 and upstream water level, and between F b2 and upstream water level, correspondingly, during the period of 1995-2014. In (8), the probability density function of each PC and upstream water level can be obtained from the KDE when the bandwidth is set to 1.0, 0.5, and 0.1. The image is displayed in Figure 7.…”

Section: Between Pcs and Upstream Water Levelmentioning

confidence: 99%

“…Abnormal seepage behavior is detected by comparing the calculated and measured values of the finite element model. Zhang et al [8] established a finite element model for earth dam. The seepage parameters for the different parts of the dam were calculated by using seepage monitoring data, and the seepage field of the dam was simulated under various operating conditions.…”

Section: Introductionmentioning

confidence: 99%

Detection Model for Seepage Behavior of Earth Dams Based on Data Mining

Jiang

2018

Mathematical Problems in Engineering

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Seepage behavior detecting is an important tool for ensuring the safety of earth dams. However, traditional seepage behavior detection methods have used insufficient monitoring data and have mainly focused on single-point measures and local seepage behavior. The seepage behavior of dams is not quantitatively detected based on the monitoring data with multiple measuring points. Therefore, this study uses data mining techniques to analyze the monitoring data and overcome the above-mentioned shortcomings. The massive seepage monitoring data with multiple points are used as the research object. The key information on seepage behavior is extracted using principal component analysis. The correlation between seepage behavior and upstream water level is described as mutual information. A detection model for overall seepage behavior is established. Result shows that the model can completely extract the seepage monitoring data with multiple points and quantitatively detect the overall seepage behavior of earth dams. The proposed method can provide a new and reasonable means of quantitatively detecting the overall seepage behavior of earth dams.

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“…Also abnormal seepage phenomena may occur in earth dams due to the construction defects and material aging [14]. Zhang et al [15], investigated the seepage field and analyzed the main causes of the abnormal seepage field in a dam with asphaltic concrete core and concluded that the main cause of the abnormal leakage might be the defect in the integrity of the anti-seepage system.…”

mentioning

confidence: 99%

“…At the time of experiencing such critical phenomenon, first and foremost, the precise origin of the abnormal leakage should be detected and a review of the water-sealing system efficiency is necessary for the assessment of the leakage harmfulness and the overall stability of the dam for the decision of whether and how to treat it, because this phenomenon can cause seepage damage and lead to dam breakage. In this condition, the usage of inverse modeling concept to control dam safety by means of different instrumental readings collected continuously during its construction and operation is inevitable [7,12,14,15].…”

mentioning

confidence: 99%

A Hybrid of Artificial Neural Networks and Particle Swarm Optimization Algorithm for Inverse Modeling of Leakage in Earth Dams

2019

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A new intelligent hybrid method for inverse modeling (Parameter Identification) of leakage from the body and foundation of earth dams considering transient flow model has been presented in this paper. The main objective is to determine the permeability in different parts of the dams using observation data. An objective function which concurrently employs time series of hydraulic heads and flow rates observations has been defined to overcome the ill-posedness issue (nonuniqueness and instability of the identified parameters). A finite element model which considers all construction phases of an earth dam has been generated and then orthogonal design, back propagation artificial neural network and Particle Swarm Optimization algorithm has been used simultaneously to perform inverse modeling. The suggested method has been used for inverse modeling of seepage in Baft dam in Kerman, Iran as a case study. Permeability coefficients of different parts of the dam have been inspected for three distinct predefined cases and in all three cases excellent results have been attained. The highly fitting results confirm the applicability of the recommended procedure in the inverse modeling of real large-scale problems to find the origin of leakage channels which not only reduces the calculation cost but also raises the consistency and efficacy in such problems.

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Causes of the abnormal seepage field in a dam with asphaltic concrete core

Cited by 8 publications

References 4 publications

Improvement Methods for Reduction of the High Stress of Ultra-High Asphalt Concrete Core Dams

Improvement Methods for Reduction of the High Stress of Ultra-High Asphalt Concrete Core Dams

Detection Model for Seepage Behavior of Earth Dams Based on Data Mining

A Hybrid of Artificial Neural Networks and Particle Swarm Optimization Algorithm for Inverse Modeling of Leakage in Earth Dams

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