Journal of Hydroelectric Engineering

水力发电学报

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2024 Vol. 43, No. 5 Published: 2024-05-25

	1	Analysis of bed material coarsening characteristics during recent continuous erosion in lower Yellow River ^Hot!
		CAO Yuqin, XIA Junqiang, ZHOU Meirong, CHEN Jianguo
		DOI: 10.11660/slfdxb.20240501
		Variations in bed material composition affect suspended load recovery and movable bed resistance. This paper calculates inter-annual variations in bed material proportion at seven hydrological stations in the lower Yellow River (LYR), based on the 1999-2020 bed material data measured at these stations. We examine spatial and temporal coarsening characteristics of different reaches during continuous channel degradation in the past 20 years, and discuss the influence of channel evolution on bed material coarsening. In time variations, coarsening characteristics varied in different periods after the operation of the Xiaolangdi reservoir, with a sharp trend in the early stage 2000-2006 and a slow trend in the later stage 2007-2020. In the later stage, bed material was coarsened with temporal fluctuations at the stations above Gaocun Station, but changed little below; the reach with the highest coarsening degree moved downstream from the braided reach to transitional reach. Spatially, bed material became finer along the stream. The braided reach was dominated by very coarse sediments and the transitional reach by coarse and very coarse sediments, while the medium and fine sediments were not negligible in the meandering reach. The adjustment of bed material composition was characterized by both medium and fine sediment erosion in the early stage, while by medium and coarse sediment erosion and very coarse sediments deposition in the later stage. At the stations above Lijin, the proportion of fine sediments was less than 5%, limiting suspended load recovery; medium and coarse sediments were still eroded, but very coarse sediments had a good supply of the corresponding suspended load. In post-flood period, the median particle size of bed material was power correlated positively with the cumulative erosion volume of the river bed, but its influence on bed material was limited due to a considerable degree of coarsening in the later stage. The results reveal the current situation of bed material coarsening in LYR and help predict the channel deformation.
		2024 Vol. 43 (5): 1-12 [Abstract] ( 98 ) PDF (1627 KB) ( 246 )

	13	Remote sensing assessment of trophic state of large lakes by integrating multi-source information
		MENG Dinghua, MAO Jingqiao, LI Weifeng, GAO Huan, SHENG Luyao
		DOI: 10.11660/slfdxb.20240502
		The trophic state of lakes is a direct reflection of the water quality, but its comprehensive, accurate assessment is often a challenge if a large lake is influenced by complex environmental factors. This study synthesizes multi-source information such as remote sensing data and on-site measured data, and cleans the data outlines using the methods of spectral curves and the interquartile range principle (IQR), so as to invert lake trophic state characterization metrics: chlorophyll-a concentration (Chl-a) and the trophic state index (TSI). Key environmental factors－including pH, temperature, average wind speed, and sediment content－are selected through statistical analysis; A trophic state inversion model SSA-BP-NN is constructed based on the back-propagation neural network (BP-NN) and sparrow search algorithm (SSA). The results show that the inversion accuracies of Chl-a and TSI based on the BP-NN model are 0.843 and 0.834 respectively, while they are improved to 0.918 and 0.936 through optimization using the SSA algorithm. In the case study of Hongze Lake, this model has been applied to analysis of the spatiotemporal distribution characteristics of the trophic state: TSI is higher in the western and northern lake than the eastern lake. An analysis of raster point data shows that Chl-a and TSI are closely correlated, and the range of TSI change is more stable. In this lake, water blooms are complex due to their highly transient nature and the influence of various factors; TSI, as a comprehensive indicator that can reflect the basic situation of eutrophication in water bodies, provides as background information for early warning of water bloom risks. This study verifies that the assessment accuracy of a remote sensing inversion model can be improved significantly by introducing environmental factors correlated closely with the lake trophic state, so as to help useful assessment of the health state of lake ecosystems and risk early warning.
		2024 Vol. 43 (5): 13-23 [Abstract] ( 103 ) PDF (5034 KB) ( 237 )

	24	Study on water temperature structure and hydrodynamic mechanism of river-type reservoirs in southwest China
		HE Yubin, SHI Xiaoyan, ZHOU Hongju, LI Xinghao, WAN Xin, ZHANG Hong, LIU Zhaowei, REN Huatang
		DOI: 10.11660/slfdxb.20240503
		For a large river-type reservoir that is operating for hydroelectric benefits, the impact of its unique water temperature stratification on the water environment cannot be neglected. Most of the previous studies focus on the vertical variation in water temperature and its temporal evolution, lacking an in-depth examination on the hydrodynamic effect during its formation. This study uses mathematical models to simulate and examine the varying process of water temperature structure in the Wudongde reservoir, a typical river-type reservoir in the southwest region. We find that hydrodynamic conditions are the decisive factor in forming certain water temperature structures, and the formation and evolution of the main thermoclines depend on the hydrodynamic mechanism caused by thermal density flow. From February to March, the incoming water plunges into the reservoir bottom, forming a main thermocline at the interface between the two layers, and continuously developing as it advances further downstream at the bottom; From April to June, the inflow plunges down as an intermediate layer, with two thermocline layers formed at its upper and lower edges separately; In July, the inflow stays on the surface as an upward floating flow with a main thermocline below it. In the case of the water intakes, the dynamic suction effect of its orifices causes the main thermoclines to contract locally in certain areas near the dam.
		2024 Vol. 43 (5): 24-34 [Abstract] ( 78 ) PDF (3866 KB) ( 335 )

	35	Influence of radial installation deviation on flow characteristics of 1000 MW hydro turbine runner
		WU Siyuan, WANG Yifan, LIU Xingmin, HUANG Xingxing, DU Qingpin, ZHOU Lingjiu, CHEN Duan, WANG Zhengwei,
		DOI: 10.11660/slfdxb.20240504
		Focused on a 1000 MW huge-capacity hydraulic turbine unit, this paper conducted three-dimensional steady internal flow numerical simulation using commercial code ANSYS. The impact of uneven clearance distribution on its internal flow characteristics of the turbine under the design operating point was investigated, considering radial installation deviations of 0.1 mm, 0.3 mm, 0.5 mm, 1.5 mm, and 2.5 mm on the negative y-direction. The results revealed that within a certain range of deviation, the pressure in the corresponding region gradually rises with the decrease in clearance. However, once the deviation exceeded a certain threshold, water was unable to flow in, thus resulting in the formation of a low-pressure area. Furthermore, both the upper crown chamber and the bottom ring chamber exhibited an equal number of vortex evolving cycles with different vortex intensity, and the vortex was more intense in the upper crown chamber; The number of vortices is not an integer multiple of the blade number. Finally, we clarify that the vortex flow impact was greater on the inner wall of the bottom ring chamber than that of the upper crown chamber. This study is applicable to the design and installation of other large or medium size Francis turbines for improving their operational quality, reducing operating costs, and enhancing the overall efficiency of hydropower plants.
		2024 Vol. 43 (5): 35-42 [Abstract] ( 70 ) PDF (1689 KB) ( 262 )

	43	Optimal scheduling of cascade pumping stations based on sparrow search algorithm
		MA Xiamin, ZHANG Leike, LIU Xiaolian, TIAN Yu, WANG Xueni, DENG Xianyu
		DOI: 10.11660/slfdxb.20240505
		Aimed at the problems of low operating efficiency and high energy consumption loss, an optimal scheduling model of cascade pumping stations is developed. This model adopts the sparrow search algorithm (SSA) of strong searching ability and high exploratory accuracy, and compares and selects its two parameters: safety threshold and scout ratio. Then, based on this algorithm, we formulate a new optimal scheduling method for cascade pumping stations, and apply it in the case study of a three-stage pumping station in the Miyun Reservoir regulation and storage project. The results show that under three different flow conditions, compared with the current scheme, the system efficiency of the optimized scheme obtained by the particle swarm optimization (PSO) and Pareto-archived (GA) algorithm are increased by 0.03% - 0.18%, and the annual operating cost is saved by ￥9,700 - ￥69,500. More prominent is the SSA optimized scheme in ameliorating the two indexes mentioned above, which can achieve an efficiency increase of 0.98% - 1.20% and an annual operating cost saving of ￥369,000 - ￥443,900. This verifies the feasibility and efficiency of SSA in the optimal scheduling of cascade pumping stations, along with its application to the scheduling as a reasonable and reliable method.
		2024 Vol. 43 (5): 43-53 [Abstract] ( 86 ) PDF (2758 KB) ( 245 )

	54	Study on parameter inversion of rockfill dams considering time series features and spatial distribution of monitoring data
		CHENG Xinyue, MA Gang, ZHANG Guike, AI Zhitao, CHENG Yonggang, WANG Qiao, ZHOU Wei
		DOI: 10.11660/slfdxb.20240506
		With the advancement of safety monitoring technology, new technologies, such as the flexible intelligent displacement meter and pipeline robot, have been increasingly employed in the safety monitoring of rockfill dams. Over the lifespan of a high rockfill dam, an extensive amount of monitoring data has been accumulated. Using these data to conduct parameter inversion analysis can help enhance the accuracy of numerical simulations of rockfill dams and improve assessment of dam safety. This study develops a new method for using time series clustering to identify the representative and diverse sets of measurement points from the vast monitoring data. This method extracts time series features to construct an objective function that captures the spatiotemporal evolution characteristics of deformation in rockfill dams, and adopts a multi-objective optimization algorithm to perform material parameter inversion for each zone of the rockfill dam. Compared to the conventional methods of parameter inversion, it enables systematic use of a substantial amount of rockfill dam monitoring data, effectively capturing the deformation development and spatial distribution characteristics in the filling, impounding, and operational stages. The calculations of dam settlement obtained through the inversion analysis exhibit a favorable agreement with the measurements, demonstrating a significant improvement in the accuracy of parameter inversion.
		2024 Vol. 43 (5): 54-67 [Abstract] ( 75 ) PDF (3649 KB) ( 236 )

	68	Radial basis function model for predicting peak outflow caused by landslide dam failure
		WANG Lin, ZHANG Runyu, YUAN Pengfei, WANG Sangpeng
		DOI: 10.11660/slfdxb.20240507
		A landslide dam is formed by natural landslide and is extremely vulnerable to dam failure due to flow scour and seepage, thereby posing a severe threat to human lives and property downstream. Rapid and accurate prediction of the peak flow rate through the breach is the most important task in the rescue work of landslide dam breaching. In previous studies, a series of landslide dam peak flow prediction models were developed based on the idea of the database-statistical regression-breaching model, but none of them took into account the effects of dam erosion characteristics or particle composition on the breaching flow. With continuous expansion of the data, it is difficult yet for these prediction models to achieve the expected results. This study is based on a database of 2060 cases of landslide dam failure in China and abroad, and takes into account the landslide dam geometrical characteristics, erosive characteristics and particle composition, through extracting seven parameters－weir height (Hd), weir width (Wd), weir volume (Vd), reservoir capacity (Vl), failure depth (Hw), average width of failure (Wb), and median particle size (d50). We classify the degree of dam erosion into five categories, and establish a peak flow prediction model of landslide dam failure that includes a factor of erosion characteristics. Then, we validate the model by selecting 120 cases with complete data from the database, and achieve a root mean square error (RMSE) of 9581 m3/s and a correlation coefficient (R2) of 0.965, with a comparison with the typical parameter models available in China and abroad. The results show that considering the landslide dam erosion characteristics and the d50 parameter improves the model significantly in predicting the peak breaching flow, and our model is satisfactory in accuracy and applicable to the peak flow predictions aimed at rescue and relief work. It would also help the routing of such outburst floods and the division of the affected areas downstream.
		2024 Vol. 43 (5): 68-79 [Abstract] ( 54 ) PDF (2249 KB) ( 172 )

	80	Intelligent prediction method of harmful gas concentrations in underground caverns driven by construction-geological joint impacts
		LU Gengyang, CHEN Yun, NIE Benwu, CHEN Shu, JIN Lianghai
		DOI: 10.11660/slfdxb.20240508
		The concentration of harmful gases in underground caverns is closely related to excavation schemes and geological conditions; its accurate prediction under construction-geological impacts is crucial to construction safety management. However, it is challenging to extract useful information from harmful gas monitoring data due to the nonlinear coupling between features such as blasting parameters, bedrock types, and gas concentrations. This study presents an intelligent prediction method for harmful gas concentrations using integrated learning, incorporating the theory of SHapley Additive exPlanations (SHAP). The method conducts feature preprocessing using Principal Component Analysis (PCA), and uses the Tree-structured Parzen Estimator (TPE) algorithm to iteratively seek the optimal hyperparameters for the CatBoost (Categorical Boosting) model that is used to predict harmful gas concentrations. The SHAP explanatory framework is introduced to identify key factors affecting gas emission concentrations. Application in a case study of the diversion tunnel at the Xulong hydropower station shows that compared with the models of CatBoost, TPE-XGBoost, and TPE-LightGBM, the TPE-CatBoost model reduces the root mean square error by 48.9%, 40.2%, and 36.8% respectively, demonstrating a higher prediction accuracy. Integrating the SHAP theory reveals that PM10 and PM2.5 concentrations are more closely associated with blasting schemes, while CO and CO2 concentrations are more influenced by geological conditions such as groundwater state.
		2024 Vol. 43 (5): 80-93 [Abstract] ( 69 ) PDF (5169 KB) ( 296 )

	94	Failure criterion of copper water-stops under three-dimensional deformation
		WANG Li’an, FU Zhongzhi, DING Qiangsheng, WANG Yongsheng
		DOI: 10.11660/slfdxb.20240509
		Copper water-stop is the most important component for preventing water leak through the joints of hydraulic concrete structures. Concrete structures often experience uneven deformation under gravity and hydrostatic pressure, resulting in tension (or compression), settlement, and shear deformation (relative displacement) between the two wings of a copper water-stop. Its safety depends on the magnitude of the three-dimensional deformation, which is often judged by the displacement in each direction separately, without considering the coupling of different directions. This paper presents an experimental study of shear tests on copper water-stops under different tensile and settlement displacements, using a test stand that allows independent control of three directions and a total of 40 specimens in two different sizes are designed and fabricated. We examine shear deformation, its variations, and the failure modes of the specimens, and obtain a failure envelope surface in the three-dimensional displacement space. A failure criterion is derived for copper water-stops under three-dimensional displacement for judging the safety of similar water-stops.
		2024 Vol. 43 (5): 94-102 [Abstract] ( 35 ) PDF (1999 KB) ( 134 )

	103	Interval field analysis of dam settlement using Karhunen-Loève decomposition
		ZHOU Ting, JIE Yuxin, ZHANG Yanyi
		DOI: 10.11660/slfdxb.20240510
		The settlement analysis of a dam faces a complicated nonlinear problem due to the coupling of internal and external factors during its construction and operation. The dam settlement interval established using the non-probability method helps the quantitative description of multi-source uncertain information, making the calculation more agreeable with the real case. This paper describes a new method of combining the Duncan-Chang model calculations of dam settlement with the Karhunen-Loeve decomposition, through extending the interval field finite element method from the linear elastic model to a nonlinear model. In this method, the variability of tangential modulus is described using a spatial dependence function in the form of square exponents; the Galerkin method with the Legendre polynomial basic functions is used to calculate the eigenvalues and eigenfunctions of variable modulus characteristics. We have coded an Abaqus user subroutine UMAT to implement the interval Duncan-Chang model, and adopted a Python script to calculate the response interval of dam settlement stress to the variations in modulus parameters, with the settlement interval so calculated being compared with the traditional vertex method. Analysis of engineering cases shows that our new method can effectively calculate the dam’s settlement interval that covers the vertex interval, and that the cost of finite element calculations is reduced from exponential to polynomial. The method can be further extended to the analysis of long-term dam deformation.
		2024 Vol. 43 (5): 103-114 [Abstract] ( 45 ) PDF (1911 KB) ( 211 )

	115	Deterioration of alkali-fly ash-added concrete under freezing-salt coupling effect
		SHAO Shanqing, GONG Aimin, QU Baoli, WANG Fulai, LUO Jiahui, YONG Kang, JIN Zhuo
		DOI: 10.11660/slfdxb.20240511
		To study the deterioration of alkali-excited fly ash concrete under sulfate environment, this paper studies the variations in mass loss, ultrasonic wave velocity loss, and compressive strength loss of fly ash concrete, by examining the specimens of different alkali admixtures (0%, 5%, 8%, and 10%) under the coupling of freeze-thaw cycling and different sulfate contents. We determine deterioration patterns through experimental tests using electron microscopy, EDS energy spectroscopy, and XRD diffraction, and develop an artificial neural network prediction model of deterioration patterns based on the test data. The results show adding alkaline exciters improves the durability of fly ash concrete significantly at the optimal alkali admixture of 8%. The deterioration of the specimens shows a linear positive correlation with the number of freeze-thaw cycles. In terms of mass loss, the specimens with different dosages show two stages, smooth declining and accelerated declining; the latter stage appears earlier for the specimens without the alkali exciter. In terms of the loss of ultrasonic wave velocity and the loss of compressive strength, the specimens doped with alkali exciters show only a steady declining stage. Microscopic analysis reveals that the intensified deterioration of alkali-excited fly ash concrete is caused by gradual generation of gypsum and calcovanadate, and our artificial neural network prediction model has high accuracy.
		2024 Vol. 43 (5): 115-122 [Abstract] ( 56 ) PDF (2717 KB) ( 150 )