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Searching for the precise solution of the free surface has remained the main bottleneck in analyzing the unconfined seepage problem for earth-rock dams. This paper proposes an approach to solve classic earth-rock dams using the smoothed finite element method (S-FEM). To overcome the problems of complex calculation and accuracy loss caused by integrating the area of intersecting elements in saturated seepage, this paper optimizes the shape function calculation by reducing the area integral to a line integral along the elements. To achieve a balance between efficiency and accuracy, we investigated the distinct effects of various smooth elements on computational efficiency, which included computation time and iteration times. Moreover, we first explored the extensive effect of seepage anomalies and their positional changes on hydrological state variables, including head, free surface, overflow point, seepage velocity, and fluid pressure. This exploration presented could provide a potential for developing multi-parameter seepage inversion and serve as constraints for hydro-geophysical inversion. [ABSTRACT FROM AUTHOR]

Climate change poses significant threats to the water reservoir, with potential repercussions for Pakistan's economy. This study investigates the impact of climatic variations on seepage in Tarbela dam, Pakistan, by analyzing hydro-climatological factors. The research employs statistical multivariant time series (SARIMA and ARDL) and machine learning (ANN and Catboost) modeling techniques to assess the influence of climatic variability on seepage dynamics. The analysis focuses on annual and seasonal climatic variables from a data set spanning from 2003 to 2015, aiming to explore the relationship between climatic variability and dam seepage. The SARIMA model is utilized to estimate water inflow, temperature, rainfall, and reservoir level, validating the integration of multiple data sets. Machine learning models demonstrate superior performance, achieving high R2 scores during the training, validation, and testing. The findings derived from the ARDL analysis reveal a significant increase in seepage with rising water inflow, rainfall, and reservoir level. Among the machine learning models, CatBoost performs the best. The study recommends implementing appropriate adaptive approaches to mitigate any negative impact on Tarbela dam seepage. Moreover, this research serves as a guide for enhancing the dam's power generation capacity and improving irrigation water management in the face of existing crises in Pakistan. [ABSTRACT FROM AUTHOR]

The research investigates the significance of identifying structure discontinuities, such as cracks, in concrete dams to ensure dam safety and stability. A novel automatic image classification method is developed, employing Deep Dense Transfer Learning (DDTL) with pre-trained models, including EfficientNetB1, ResNet50, and a hybrid model to identify the detection of cracks in sub-surfaces at pillow dams in Sichuan province, China. The developed model was trained, validated, and tested, with the Hybrid model demonstrating superior performance. The results showed that the DDTL models had high classification accuracies, surpassing Convolutional identification techniques for sub-surface cracks. Consequently, this study suggests that automatic image classification techniques can effectively identify and localize structural defects in concrete dams. This is an innovative approach to predicting normal borehole images and crack recognition using CCTV borehole images. [ABSTRACT FROM AUTHOR]

2D electrical resistivity inversion is a complicated nonlinear optimization problem, which is high-dimensional and non-convex. Using traditional neural networks to solve resistivity inversion problem is cost effective but suffers from trapping in local minima. In order to solve the above problem, a multi-output support vector regression (MSVR) nonlinear inversion method with limited ERI learning samples is researched in this paper, which considers the combined fitting errors of all outputs. Moreover, a Cauchy random and chaotic oscillation shuffled frog leaping algorithm is applied to optimize the RBF kernel widths and penalty coefficients of MSVR for improving the inversion accuracy and the computational efficiency. The key issues of data sets generation, data preprocessing and inversion flowchart are analyzed. The experimental results based on the synthetic and field examples demonstrated that the proposed algorithm is accurate, efficient and can be applied in practical engineering applications. [ABSTRACT FROM AUTHOR]

This paper describes a series of plugging agents which have been developed these years by the authors. The features of these agents can bestated as: (1) Stopping losses without stopping driling; (2) High ratio of success; (3) Improving fluids properties; (4) Suiting to many types of losses, even large cracks and caves; (5) Perfect efficiency in different conditions of pollution such as calcium, salt pollution and high temperature; (6) Sufficient resources of raw materials, no-poison, no-harm, no pollution to the environment; (7) Convenience in use; (8) Lower cost. The properties, mechanisms and applications of these agents are also described in this paper. [ABSTRACT FROM AUTHOR]

One of the great challenges of unconfined seepage through a dam lies in the accurate determination of free surface that depends on the complexity of the seepage model, especially if the model is characterized with complex geometry and sharp variations in permeability distribution. This study presents a practical methodology that combines the adaptive moving-mesh algorithm and the Galerkin finite element method (FEM) to solve an unconfined seepage problem with high efficiency and precision. The methodology employs a set of improvement terms, such as remainder factor, step-size parameter and termination condition, all of which guarantee that the simulation and the refinement fitting can be implemented efficiently until the free surface converges within a given allowable error. In particular, a specialized discussion is presented for the significant relation between the location of the exit point and the corresponding grid fineness. To validate the practicability of the proposed method, a series of examples are performed. Comparing the result with those of other numerical approaches, we conclude that even though the unconfined seepage model may be complicated with arbitrary complex geometry and sharp variations in permeability distribution, the proposed algorithm provides a great improvement in efficiency and accuracy in free-surface searching. [ABSTRACT FROM AUTHOR]