Journal of Hydroelectric Engineering

水力发电学报

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2022 Vol. 41, No. 10 Published: 2022-10-25

	1	Digital concrete for hydropower stations in lower Jinsha River
		HE Yinpeng, ZHANG Mengxi, LI Wenwei, MIN Qiaoling, TIAN Dan, SHEN Yang, LI Mingchao
		DOI: 10.11660/slfdxb.20221001
		Aimed at the goal of safety, high quality, high efficiency, economy and greenness in the construction of high concrete dams, this paper combines data-driven and mechanism-driven features and describes a digital concrete technology of integrating information and mechanism. And differences in the previous digital concrete theories used in China and abroad are discussed, and digital twins of concrete are developed. Then, based on the architecture of digital concrete, we discuss its composition and energizing technology from three aspects: intelligent analysis database, aggregate generation and packing, and hydration dynamic characteristics. Recent advancements in the research of its energizing technology are reviewed. We discuss its applications to data rescue, combined dam construction technology with high percentage fly ash concrete, and low heat cement dam technology, through examining the high concrete dams of Xiluodu, Xiangjiaba and Wudongde in the lower Jinsha River. Finally, its technical difficulties and application prospects are summarized. The digital concrete presented in this paper is a representation of concrete materials in another dimension. It can be used for cross-scale analysis based on the evolution mechanism of structural performance from the perspectives of nano-, micro-, meso- and macro-scales, and provides a reliable data support and decision basis for intelligent dam construction from the material aspect.
		2022 Vol. 41 (10): 1-17 [Abstract] ( 273 ) PDF (3543 KB) ( 835 )

	18	Curtain grouting cement interval prediction using Bootstrap-IGWO-SVM model
		LI Kai, REN Bingyu, GUAN Tao, YU Jia, WANG Jiajun
		DOI: 10.11660/slfdxb.20221002
		Uncertainties exist in the geological parameters, prediction model, and input data of the curtain grouting cement predictions; the traditional point prediction suffers considerable errors and lacks a capability of quantifying the uncertainty level. This study describes a Bootstrap method and an improved grey wolf support vector machine (Bootstrap-IGWO-SVM), and develops an interval prediction model of curtain grouting cement with quantification of its uncertainty. First, a new data set is created from the initial training set sampling using the Bootstrap method; the grey wolf method is used to optimize the penalty factor C, RBF kernel function variance g, and loss factor p so as to improve prediction accuracy. Then, we improve the grey wolf method using the nonlinear convergence factor, dynamic weight factor, probabilistic chaos map, and Levy flight, so that the imbalance between local and global searchings can be eliminated. Finally, we estimate the system error and random error using the IGWO-SVM method and the random forest method respectively, and sum up them as the total error, thereby obtaining a cement interval prediction through building a normal distribution model. Thus, the uncertainty of prediction model is quantified. The results show the prediction accuracy of this improved IGWO-SVM is RMSE = 85.3, R2 = 0.53, and MAE = 45.6, a significant improvement on the GWO-SVM’s values of 96.6, 0.40 and 48.5. It is also superior in prediction accuracy to the back propagation neural network (BPNN) or extreme learning machine (ELM). At the confidence level of 99%, its prediction interval coverage probability (PICP), mean prediction interval width (MPIW), and coverage width-based criterion (CWC) are 98.7%, 363.6 kg/m, and 363.6 kg/m respectively.
		2022 Vol. 41 (10): 18-29 [Abstract] ( 164 ) PDF (2719 KB) ( 355 )

	30	Prediction of rock damage induced by blasting excavation in high rock slope of Baihetan Dam abutment
		SUN Pengchang, LU Wenbo, YANG Zhaowei, MENG Haili, XUE Li
		DOI: 10.11660/slfdxb.20221003
		Rock damage prediction is important for controlling the blasting vibration of high rock slopes. This paper derives a relationship of rock damage versus natural frequency of rock masses using theoretical analysis, and develops a method for predicting rock damage from the natural frequency change of rock masses. We present a case study of Baihetan Dam, predicting the rock damage of its high rock slope of right bank abutment, based on blasting vibration monitoring and acoustic testing. The results show that a prominent linear relationship exists between the change rate of natural frequency and the damage depth of rock masses, and the rock damage prediction model can be adjusted dynamically and becomes more robust with the increasing data samples. For the rock damage depth of this high rock slope, the probabilities of its Bayesian LASSO predictions below the monitoring values are all higher than 0.83. These predictions can cover the observation results in the form of probability and give the uncertainty.
		2022 Vol. 41 (10): 30-41 [Abstract] ( 151 ) PDF (3328 KB) ( 279 )

	42	Evaluation of seepage control on left bank of Baihetan hydropower station during impoundment
		QIU Qinyan, RONG Guan, TAN Yaosheng, ZHANG Huqi, XU Lida
		DOI: 10.11660/slfdxb.20221004
		Geological conditions on the left bank of the Baihetan hydropower station are complicated due to its interlayer dislocation zones, intra-layer dislocation zones, columnar jointed basalt, and other weak geological structures. A large-scale seepage-control and drainage system was arranged in the left bank plant area. Reasonable and effective evaluation of its seepage control effect is of great significance to guiding the safe operation of the station. This paper presents an analysis of the monitoring data from the system and its control effect during the impoundment from April 2021 to March 2022. The results show that the total seepage flow, with a peak of 1249.1 L/min, is significantly affected by the change in the upstream water level, and 69.5% of it is contributed by the seepage through the drainage and irrigation corridors on the third and seventh floors. Pressure head at the anti-seepage curtain rises with the decrease in elevation, with a significant rise at C2. The structural layers C3, C3-1, C2 and LS3152 are more permeable and subjected to larger seepage flows, so that they respond more sharply to the changes in the upstream water level and are prone to seepage channel formation. On the whole, the drainage curtain can effectively reduce the pressure head and maintain the total seepage flow within a reasonable range, achieving a good effect of overall seepage control.
		2022 Vol. 41 (10): 42-52 [Abstract] ( 173 ) PDF (3299 KB) ( 376 )

	53	Parallel-over-series fusion model for predicting internal temperature of Xiluodu arch dam
		LIU Chang, LI Qingbin, HU Yu, MA Rui
		DOI: 10.11660/slfdxb.20221005
		Accurate, reliable and efficient prediction of key variables reflecting the working behaviour of dams plays a vital role in safe construction and operation of dams. To predict and analyse the temperature field of a dam, this paper develops a parallel-over-series fusion model driven by both a mechanism model and a data model, and examines its feasibility by using the internal temperature of the Xiluodu arch dam. In series fusion, the camp chain method and the auxiliary technology of principal component analysis are adopted for back-calculating the thermal conductivities of dam concrete, by which optimised outputs of the mechanism model are obtained. In parallel fusion, the explanatory factor method and the linear-Gaussian model are used to construct a prediction model that enables the optimised mechanism model to be mapped to the dam temperature data. Experimental verification shows this fusion model, benefits from the explanatory power of the mechanism-driven model and the predictive advantage of the linear-Gaussian model. It can predict data fluctuations and has advantages in medium- and long-term forecasting. It reduces the overall prediction error by 81% compared with the series fusion model, while the latter reduces the error by 13% relative to the mechanism model.
		2022 Vol. 41 (10): 53-63 [Abstract] ( 177 ) PDF (4966 KB) ( 385 )

	64	Integrated transportation system of lower Jinsha River with land-water coupling and cascade reservoirs as its core. Construction and microscopic dynamic characteristics
		LIU Kejing, WU Baosheng, WANG Yongqiang, ZHONG Deyu
		DOI: 10.11660/slfdxb.20221006
		A combined shipping-ground transport system (CSGTS) is built integrating the river channels and existing ground transportation network based on the theory of intermodal transport and comprehensive transport system, to enhance the integrated regulation of water resources in the background of different developing progress. This system is applied in the scheduling of four cascade reservoirs on the lower Jinsha River, and predicts the impacting scope, freight volume and profit of shipping traffic in 2015-2050 for the condition of a regional economic growth rate of 7%. It reveals the important role of cascade reservoirs in regional traffic economy and their impact increasing with the cascade building. For the system of the lower Jinsha River, its freight traffic volume and freight spreading area are correlated with the daily scheduling of the cascade reservoirs. Under a scheduling scheme that meets the operating standards, a scenario of its daily scale variations is demonstrated for the cases of two reservoirs and four reservoirs in operation. This shows that the reservoir scheduling produces a pulse-type effect on the entire system and affects the spreading of freight cumulatively. For a pulse differential system based on the microscopic scale characteristics of a CSGTS, if an asymptotic stable solution can be obtained, the control strategy (or the scheduling scheme) so obtained will be the optimal pulse-harvesting strategy of the CSGTS.
		2022 Vol. 41 (10): 64-85 [Abstract] ( 183 ) PDF (3268 KB) ( 503 )

	86	Construction and application of ontology knowledge base for hydropower plant operation and maintenance
		ZHANG Binqiao, YANG Wenjuan, GE Suye, DONG Xiaoying
		DOI: 10.11660/slfdxb.20221007
		The construction and operation of hydropower plants are faced with a large body of multi-source heterogeneous structured and unstructured text data that are difficult to manage and reuse effectively. Aiming at the issue, we apply ontology-based knowledge modeling to knowledge management and knowledge service for hydropower plant operation and maintenance (HPOM), and define an ontology-based knowledge representation model. Then, we construct ontology knowledge representation examples in detail and an ontology knowledge base for the three typical business fields－HPOM, fault warning, and emergency plans. Based on this, the ontology-driven visualization of knowledge retrieval, prediction and warning, and emergency drill, as well as its HPOM application are realized. For this ontology-based construction method and the key technologies of the HPOM knowledge base, their feasibility and effectiveness are demonstrated and verified through practical engineering cases, so as to improve the knowledge management of hydropower plants and its application level.
		2022 Vol. 41 (10): 86-98 [Abstract] ( 213 ) PDF (3132 KB) ( 840 )

	99	Research on SD-ABMS hybrid simulation modeling of high arch dam construction
		REN Bingyu, LI Dong, GUAN Tao, YIN Liang
		DOI: 10.11660/slfdxb.20221008
		Most of the previous simulations of high arch dam construction have adopted a discrete event simulation (DES) modeling method, but it is difficult to describe the individual behaviors in the complex construction system from the micro level, and its simulation model lacks quantitative analysis of the complex relationship between key continuous factors. A SD-ABMS hybrid simulation modeling method of high arch dam construction is proposed. First, the ABMS method is used to abstract, from the real construction process, four agents and a concrete delivery process－including mixing floor, dump trucks, cable machines, and construction bin surface; the behavior of each agent and their interaction are modeled. Then, various continuous factors that affect construction efficiency are modeled based on the SD method; their influences－such as those of fatigue and proficiency on construction efficiency－are analyzed quantitatively. Finally, based on SD-ABMS, a hybrid simulation model is constructed and equipped with the interface variables of working time and cable machine cycle time. Engineering application shows that compared with the traditional DES model or the single ABMS model, this hybrid model reduces the average simulation deviation from the real case by 4.8% and 3.5% respectively, demonstrating a new idea for refined simulations of arch dam construction.
		2022 Vol. 41 (10): 99-111 [Abstract] ( 93 ) PDF (4259 KB) ( 384 )

	112	Predictions of concrete dam deformation using clustering method and deep learning
		LIN Chuan, WANG Xiangyu, SU Yan, ZHANG Ting, CHEN Zeqin
		DOI: 10.11660/slfdxb.20221009
		The deformation prediction of a concrete dam is important to its safe operation. To solve the problem of low prediction accuracy of traditional analysis methods resulted from the difficulty in capturing the characteristics of long-term sequences, this paper uses a combination of Sparrow Search Algorithm (SSA) and the K-Harmonic Mean (KHM) algorithm to cluster the monitored values and capture the long-sequence features. Then, we use methods such as Complete Ensemble Empirical Mode Decomposition (CEEMDAN) to reduce the noise in the clustered data, and a long short-term memory (LSTM) model to predict long sequences. The analysis results show this clustering method has a better capability of identifying long-sequence features. It removes the redundant information from the sequence by cooperating with the CEEMDAN decomposition-based method, and enables the LSTM model to better capture the time-sequence characteristics of dam deformation, thus improving the prediction accuracy significantly. The proposed method is good in accuracy and adaptability and useful for dam deformation prediction.
		2022 Vol. 41 (10): 112-127 [Abstract] ( 151 ) PDF (5716 KB) ( 536 )

	128	Seismic performance assessment of asphalt concrete core sand-gravel dams based on endurance time analysis
		ZHANG Sherong, DU Min, WANG Chao, SHE Lei, LI Jiabei, WANG Ming
		DOI: 10.11660/slfdxb.20221010
		To evaluate the applicability of the endurance time analysis (ETA) in the seismic performance evaluation of asphalt concrete core sand-gravel (ACCSG) dams, this study selects ten records of measured ground motions for incremental dynamic analysis (IDA), and compares the acceleration, dynamic displacement, and relative dam crest settlement ratio for different ground motion intensities. We use a typical 100 m level ACCSG dam as the study case and four endurance time acceleration curves (ETAC) synthesized through optimizing target response spectra as the ground motion inputs. The results show that ETA better predicts the dynamic dam responses to different seismic intensities, and its calculations fall in the enhanced dynamic analysis envelope. The calculated seismic responses feature a narrow scatter range, verifying that ETA can avoid multiple calculations for amplitude modulation and improve computational efficiency and accuracy, and that it is a more efficient and feasible new method for seismic performance assessment of the ACCSG dams in Western China.
		2022 Vol. 41 (10): 128-139 [Abstract] ( 116 ) PDF (4507 KB) ( 281 )

	140	Key parameters optimization of seismic liquefaction replacement materials for earth-rock dam foundation
		CHEN Yingbo, LI Mingchao, REN Qiubing, YANG Lin, ZHAO Yu
		DOI: 10.11660/slfdxb.20221011
		Seismic liquefaction of earth-rock dams may cause structural instability, foundation failure or other problems, severely threatening the safety of dam projects. New anti-liquefaction measures of soil removal and replacement should be designed, as the previous design of soil replacement schemes was usually based on engineering experiences, lacking quantitative optimization analysis of the soil replacement materials (SRMs). This paper presents an optimization analysis method of the key SRM parameters, considering the liquefaction of earth-rock dam foundation under earthquake action. Based on real project data, numerical simulations and optimization analysis of SRMs are carried out, revealing variations in seismic liquefaction under the influence of the four groups of SRM parameters, i.e., porosity, density, bulk modulus and shear modulus, as well as cohesion and internal friction angle. We find that in the common range of soil parameters, the anti-liquefaction effect is poor for a scheme using too small or too large porosity and density, while it is better for a scheme using a large modulus and a large internal friction angle. The key SRM parameters can be optimized through a procedure of comparison, selection, and optimization of the schemes. This can achieve a significant improvement in the vertical displacement of a dam body, as shown in our case study: an optimization rate of 53.9% for the downstream dam slope ratio, and 69.6% for the residual liquefaction volume at the end of dynamic analysis. This demonstrates our method is effective and applicable to optimization analysis of earth-rock dam replacement materials, along with its great significance for improving anti-liquefaction performance of earth-rock dams.
		2022 Vol. 41 (10): 140-151 [Abstract] ( 135 ) PDF (3716 KB) ( 236 )

	152	Study on FEM-HST hybrid prediction model for displacement of concrete dams
		LIU Changwei, ZHOU Tianyu, FEI Xinfeng, KONG Qingmei, WANG Jinting, PAN Jianwen
		DOI: 10.11660/slfdxb.20221012
		A dam safety monitoring model can provide an early warning of the monitored outliers, which helps monitor the operation status of a dam to ensure its safe operation. Based on the prototype monitoring data of a concrete dam and combined with analysis of finite element method (FEM) and traditional statistical analysis (HST), a FEM-HST hybrid prediction model of concrete dam displacement in long-term operation is developed in this paper. It calculates hydrostatic pressure components using a finite element model, and back-calculates material parameters from the monitoring data. Additionally, temperature components are calculated by a simple harmonic temperature model; time components by a linear combination model of a linear function and a logarithmic function. This hybrid model is a significant improvement on the HST model in prediction accuracy and model stability, better describing the structural and material characteristics of a dam and its foundation and better predicting its displacement under extreme loads. This helps monitor the working behavior of a dam under extreme conditions.
		2022 Vol. 41 (10): 152-159 [Abstract] ( 101 ) PDF (2771 KB) ( 458 )

	160	Orthogonal numerical experiment method and application for shape optimization of desilting channel with swirling flow
		NAN Junhu, LUO Han, MA Kangning, GAO Huan, WANG Chaoqun
		DOI: 10.11660/slfdxb.20221013
		A new type of desilting channel with swirling flows is developed to optimize the gradation of sediment for water diversion from a heavy sediment-laden river and to improve its sediment sorting effect. Based on the orthogonal experimental design, its key parameters are optimized by combining numerical simulations and model tests, using objective functions of the flow diverting ratio and average flow velocity in the sediment transport pipe; its hydraulic characteristics and desilting characteristics before and after shape optimization are compared and analyzed. The results show that the approach of orthogonal experimental design and numerical simulation effectively improves the optimization efficiency of the channel structure and achieves a good performance of the swirling flows. When the shape-optimized channel has an inflow of 30 L?s-1, the sediment pipe has an outflow reduced by 21.5% relative to the original shape and a diverting ratio reduced by 4.6%. Its maximum outflow velocity is increased by 10.8%, enhancing its sediment carrying capacity, and a rotating flow condition more conducive to its sediment movement is formed. For the desilting channel with swirling flows carrying sediment with the particle size of 0.075 - 3.0 mm, its overall sediment interception rate is as high as 90% and 88% before and after the shape optimization respectively, indicating it has good sediment desilting characteristics; sediment deposition in the optimized transport pipe is 61.8% lower than that of the original shape. The results help optimize the shape of desilting channels and make use of swirling flows for water diversion projects.
		2022 Vol. 41 (10): 160-169 [Abstract] ( 111 ) PDF (1482 KB) ( 231 )