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Concrete, gravity and arch dams on rock foundation
\"This book, on the basis of a generalization and critical analysis of materials on constructed concrete dams, accumulated experience in their operation, and current trends, considers a set of problems associated with the design and construction of concrete dams. The modern principles of designing gravity and arch dams and the main provisions of the calculation justification of their reliability in comparison with US standards are outlined. Great attention has been paid to rolled concrete dams, taking into account their specific characteristics. Ways of increasing the efficiency of dams through the improvement of layout and structural solutions, calculation methods, and a more complete consideration of the features of natural conditions are considered. The book presents and analyzes the designs of erected concrete dams, which allows for a better understanding of the approaches and decision-making principles for designing dams, taking into account the specifics of natural, construction and other conditions, and also analyzes a number of new solutions that reflect the various ways that engineering theory and practice has sought further improvement of concrete dams. This work will be useful to hydraulic engineers and professionals involved in the design, construction and operation of concrete dams, as well as in settlement studies; the book can also be used by academics and as a textbook by university students specializing in hydraulic engineering\"-- Provided by publisher.
Book
Constructing statistical models for arch dam deformation
In its lifetime, a dam can be exposed to significant water level variations and seasonal environmental temperature changes. The structural safety control of a concrete dam is supported by monitoring activities and is based on models. In practice, the interpretation of recorded concrete dam displacements is usually based on HST (hydrostatic, seasonal, time) statistical models. These models are widely used and consider that the thermal effect can be represented by a seasonal function. The main purpose of this paper is to present an HTT (hydrostatic, thermal, time) statistical model to interpret recorded concrete dam displacements. The idea is to replace the seasonal function with the use of recorded temperatures that better represent the thermal effect on dam behavior. Two new methodologies are presented for constructing HTT statistical models, both based on principal component analysis applied to recorded temperatures in the concrete dam body. In the first method, principal component analysis is used to choose the thermometers for the construction of the HTT model. In the second method, the thermal effect is represented by the principal components of temperature of selected thermometers. The advantage of these methods is that the thermal effect is represented by real temperature measured in the concrete dam body. The HTT statistical models proposed are applied to the 110 m high Alto Lindoso arch dam, and the results are compared with the HST displacement model. Copyright © 2013 John Wiley & Sons, Ltd.
Journal Article
Safety analysis of selected zoned roller compacted concrete (ZRCC) gravity dam
Roller-compacted concrete (RCC)dams represent a departure from conventional mass concrete (CMC) dams due to differences in construction methods and concrete compositions. The analysis of RCC gravity dam safety is affected by the presence of dynamic seismic activity. The CADAM software was used to examine the seismic and stability characteristics of a Gibe-III Zoned RCC gravity dam. The Gibe-III Zoned RCC gravity dam is segmented into four zones, namely the bottom layer, medium lower, medium upper, and upper layer, with each zone having a different concrete grade. The RCC dam undergoes pseudo-static and pseudo-dynamic analysis, which involves evaluating its response to horizontal and vertical accelerations caused by the Operating Base Earthquake (OBE), Maximum Design Earthquake (MDE), and Maximum Credible Earthquake (MCE) loading conditions. The Gibe-III RCC gravity dam is structurally secure when subjected to pseudo-static stress conditions and satisfies the safety requirements for sliding and overturning as specified by the OBE, MDE, and MCE safety factors. According to the pseudo-dynamic study, the dam is deemed secure against the effects of an OBE (Operating Basis Earthquake). The uppermost layer of the dam gets damaged by MDE accelerations. The accelerations of MCE’s impact the higher and mid-upper layers. The dam must be safeguarded in order to counteract MDE. Retrofit strategies must be employed to ensure that dam can withstand the maximum credible earthquake’s peak accelerations.
Journal Article
Determination of Safety Monitoring Indices for Roller-Compacted Concrete Dams Considering Seepage–Stress Coupling Effects
Analyzing the working conditions of a dam using safety monitoring indices (SMIs) is a relatively intuitive and effective method for dam safety evaluation. Therefore, a reasonable and accurate method for determining the SMIs of a dam is of vital importance for dam safety assessment. However, the current methods for determining the SMIs of dams, especially roller-compacted concrete (RCC) dams, have many shortcomings, such as ignoring the construction process of the dam, the coupling effect among multiple physical fields, etc. In this paper, a novel SMI determination method considering the seepage–stress coupling effects was proposed for RCC dams with the assistance of a constructed seepage and stress coupling model so as to address the deficiency of existing RCC dams in determining SMIs. The coupled mathematical model was developed in COMSOL Multiphysics to establish a finite element analysis model of an RCC gravity dam in Henan Province, China. Moreover, the seepage anisotropy of the RCC construction layers was also considered in the model. Finally, the seepage, stress, and deformation characteristics of the RCC dam were analyzed based on the model, and the seepage and deformation SMIs of the dam were determined and compared with traditional methods. The results show that seepage, stress, and displacement fields are distributed similarly for both coupled and uncoupled models. However, in contrast to the uncoupled model, the hydraulic head contour distribution is more dispersed in the coupled model. Additionally, the stress and displacement simulated by the coupled model increase at different rates, with a more pronounced stress concentration near the dam heel. Comparing the seepage and stress SMIs of RCC dam obtained from different methods, it was found that the indices of dam seepage discharge and crest displacement that are calculated by considering the seepage–stress coupling effect and anisotropic characteristics of RCC construction layers are 34.78% and 31.98% lower than results obtained by ignoring these two effects, respectively. Therefore, it is crucial to consider the seepage–stress coupling effect and the anisotropic characteristics of RCC when determining the SMIs for RCC dams.
Journal Article
Concrete dam deformation prediction model considering the time delay of monitoring variables
Concrete dam structures respond to various influencing factors with complex nonlinear characteristics and notable time lags. Deformation serves as a crucial monitoring metric, providing a direct indication of the structural response of these dams. An effective deformation analysis and prediction model is essential for accurately assessing the health of concrete dam structures. Current deformation prediction models have limitations in simulating time-delay effects. This study introduces time-shifted correlation coefficients and time-delayed transfer entropy to analyze the direction of information transmission and the time delays among environmental temperature, dam body temperature, and deformation monitoring variables. A methodology is proposed to determine the dimensions of temperature factors and their respective time delays. Utilizing a long short-term memory (LSTM) neural network integrated with Dropout regularization, a concrete dam deformation prediction model that accounts for the time delay effect of environmental temperature is developed. The results demonstrate that the proposed deformation prediction model offers superior fitting accuracy and predictive capability, effectively elucidating how environmental and dam body temperatures influence dam deformation.
Journal Article
Comparative analysis of twelve transfer learning models for the prediction and crack detection in concrete dams, based on borehole images
Disaster-resilient dams require accurate crack detection, but machine learning methods cannot capture dam structural reaction temporal patterns and dependencies. This research uses deep learning, convolutional neural networks, and transfer learning to improve dam crack detection. Twelve deep-learning models are trained on 192 crack images. This research aims to provide up-to-date detecting techniques to solve dam crack problems. The finding shows that the EfficientNetB0 model performed better than others in classifying borehole concrete crack surface tiles and normal (undamaged) surface tiles with 91% accuracy. The study's pre-trained designs help to identify and to determine the specific locations of cracks.
Journal Article
Deformation Prediction System of Concrete Dam Based on IVM-SCSO-RF
Deformation prediction is an important part of concrete dam safety monitoring. In recent years, the random forest (RF) algorithm has attracted more and more attention in the field of dam safety monitoring because of its fast speed and strong generalization ability. However, the performance of RF is easily affected by many factors, such as the drift of measured value in displacement and the inappropriate setting of parameters of RF. To solve the above problems, the indicator variable model (IVM) is used to identify and eliminate the drift of measured values in this paper, and the sand cat swarm optimization (SCSO) is applied to optimize RF for the first time. On the grounds of this, a deformation prediction system of a concrete dam based on the IVM and RF algorithm optimized by SCSO is proposed. The case study shows that IVM can correct the interference of monitoring data accurately, and the maximum error rate is less than 3%; in the aspect of parameter optimization of RF, the results of the SCSO algorithm are obviously better than those of the TAE method and PSO algorithm, and the corresponding OOB error is the minimum; in terms of prediction performance, compared with TAE-RF, PSO-RF, LSTM and SVM, SCSO-RF has higher accuracy and stronger stability, and its SSE and MSE are reduced by at least 91%, MAE and RMSE are reduced by at least 71%, and R2 is very close to 1. The results of study provide a new method for the automatic online evaluation of dam safety performance.
Journal Article
Experimental and Numerical Study of the Tensile Behavior of Dam Concrete
Tensile behavior governs the seismic safety of high concrete dams. This study integrates testing with mesoscale simulation to elucidate the tensile-failure mechanisms of dam fully graded concrete. Uniaxial tension, splitting tension, and flexural tests were performed on 450 mm-scale specimens using a 15 MN servo-hydraulic system. A two-dimensional random-aggregate model was then developed with globally inserted cohesive interfaces, and parameters were calibrated against the tests. Across ten random aggregate mesoscale models per loading case, simulations reproduced the measured responses. Predicted failure patterns matched observations, with cracks initiating along interfacial transition zones (ITZs), linking through mortar, and forming through-cracks. Quantified damage evolution revealed three stages—elastic response, ITZ crack initiation and extension, and mortar penetration—with >80% of cumulative damage localized in ITZs. One-at-a-time sensitivity analyses showed that (i) mortar tensile strength primarily controls peak strength but increases brittleness; (ii) ITZ tensile strength governs crack-initiation stress, ITZ shear strength shapes splitting-failure mode, and fracture energies mainly delay post-peak softening; and (iii) aggregate parameters exert comparatively weak influence on macroscopic behavior. The combined experimental–mesoscale framework provides mechanism-based guidance for selecting material parameters in seismic analyses, supporting performance-informed design and assessment of high dams.
Journal Article
Temperature Field Reconstruction of Concrete Dams based on Distributed Optical Fiber Monitoring Data
Mastering the real temperature distribution of the concrete dam is the basis for solving the problem of temperature control and crack prevention. In this paper, Distributed Temperature Sensing (DTS) technology was applied to temperature monitoring of a high-arch dam under construction in southwest China. In order to obtain a more comprehensive temperature distribution of the dam, optical fiber layout principles for arch dams were studied, and horizontal and vertical optical fiber layout schemes were first proposed according to these principles. The real temperature variation processes of the dam were obtained in real time with a line temperature measurement pattern instead of a point temperature measurement pattern. Additionally, a framework of distributed optical fiber data acquisition and remote transmission was proposed. Interconnection of multiple DTS hosts and remote transmission of temperature data were realized. Then, two-dimensional temperature fields of a typical dam block in different ages and longitudinal profiles of dam blocks with embedded fibers were reconstructed based on large amounts of temperature monitoring data and the Kriging difference algorithm. Temperature field reconstruction results showed that the temperature distribution law of the concrete arch dam was in accordance with the actual situation.
Journal Article
Efficient Global–Local Context Fusion with Mobile-Optimized Transformers for Concrete Dam Crack Inspection
To address the difficulties in characterizing fine crack morphology, the limitations of detection accuracy, and the challenge of real-time deployment caused by large model parameter counts in concrete dam crack detection, this paper constructs DamCrackSet-1K, a high-resolution dataset with pixel-level annotations covering multiple crack scenarios; proposes a lightweight semantic segmentation framework, MTC-Net, which integrates a MobileNetV2 encoder with Enhanced Transformer modules to achieve global–local feature fusion and enhance feature extraction; and designs a geometry-sensitive Curvature-Aware loss function to effectively mitigate pixel-level class imbalance for fine cracks. Experiments show that, while significantly reducing the number of model parameters, the method greatly improves crack detection accuracy and inference speed, providing a feasible solution for efficient, real-time crack detection in dams.
Journal Article