Journal of Hydroelectric Engineering

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水力发电学报

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2025 Vol. 44, No. 8 Published: 2025-08-25

	1	Review of forecast informed reservoir operation ^Hot!
		LIU Pan, YE Hao, ZHANG Xiaojing, XU Huan
		DOI: 10.11660/slfdxb.20250801
		As key water resource projects, reservoirs and their efficient operation are crucial to the society. However, most reservoirs, domestic or international, have been formulating the operating rules based on historical statistical data, and the static rules for planning and design limit their capability of proactive responding to floods and droughts. Recent advancements in meteorological and hydrological forecasting have made forecast informed reservoir operation (FIRO) a research hotspot. This paper discusses the main factors that impact the accuracy of numerical weather forecasts, commonly used hydrological models, and rapidly developing artificial intelligence forecasting techniques. The review also covers the FIRO methods and their applications. Finally, we suggest the comprehensive use of various meteorological and hydrological forecasting products to achieve efficient water resource utilization－including global navigation satellite system (GNSS)-based precipitable water vapor, the development of FIRO methods focusing on the vapor-precipitation-runoff three lines of defense, and the construction of deep reinforcement learning operation models that account for the multi-blocking effects of cascade reservoirs.
		2025 Vol. 44 (8): 1-10 [Abstract] ( 83 ) PDF (536 KB) ( 104 )

	11	Mathematical model of random motion of elliptical water droplets
		ZHANG Hua, ZHOU Yiheng, XU Zehui
		DOI: 10.11660/slfdxb.20250802
		Aiming at the issue of the random motion characteristics of water droplets in a wind field, we formulate a hypothesis that the steady-state deformation of water droplets is ellipsoidal, and uses white noise to describe the randomness of the windward area caused by changes in relative wind speed and water droplet motion posture. A stochastic differential equation is worked out for the motion of ellipsoidal water droplets; their motion shape and drift distance are tested to verify the correctness of this new model. We apply it to calculations of the dispersion coefficients of water droplets under different conditions. The results show that for ellipsoidal droplets in motion, their random effects－produced by the random forces of a large number of air molecules and the changes in their windward area－are directly proportional to their Froude number.
		2025 Vol. 44 (8): 11-19 [Abstract] ( 74 ) PDF (2489 KB) ( 77 )

	20	Vibration predictions of pumped storage units based on adaptive feature and optimized KELM
		FU Wenlong, ZHU Xinfeng, XIONG Haowei, XIANG Ying, SHAO Mengxin, KONG Zehao, SUN Zheng
		DOI: 10.11660/slfdxb.20250803
		This paper presents a vibration prediction method of pumped storage units based on adaptive features and an optimized kernel extreme learning machine (KELM) to reduce the impact of the nonlinear, non-stationary characteristics of vibration signals on the accuracy of vibration predictions. First, we use improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) to decompose a vibration signal and generate the intrinsic mode components of different frequencies. And, an autoencoder is used to extract the features of these components adaptively and capture their key features dynamically. Then, a KELM prediction model is developed to predict each component separately, using a modified DEIHHO algorithm to optimize its regularization parameter and kernel parameter. Finally, the final prediction result of unit vibration is obtained by superadding the predictions of all the components. Comparison with previous experimental data shows our new method is better in vibration prediction of pumped storage units and improves the accuracy effectively.
		2025 Vol. 44 (8): 20-30 [Abstract] ( 52 ) PDF (1109 KB) ( 56 )

	31	Seismic analysis of gravel columns-reinforced high CFRD with thick layered alluvial deposit
		WANG Zhao, WANG Rui, WANG Rongxin, WANG Ke, LIU Chao, WU Mingxin, YAO Yu, ZHANG Jianmin
		DOI: 10.11660/slfdxb.20250804
		he seismic design of a high concrete face rockfill dam (CFRD) sitting on thick layered alluvial deposit poses a significant challenge. This study focuses on seismic responses of both its deep alluvial deposit and its structure, using a plasticity constitutive model for large post-liquefaction deformation of sand (CycLiq) and a high-performance GEOSX platform for solid-fluid coupled analysis. The findings reveal the seismic responses are notably stronger in areas adjacent to the banks, where the alluvial deposit is thinner. This underscores the limited reinforcement effect of gravel columns if located on the floor of the valley where alluvial deposit is deep. This study suggests an optimized treatment scheme, emphasizing the reinforcement of alluvial deposit near both banks. Our analysis shows that for these areas, the scheme of adopting a large area replacement ratio of gravel columns can yield a significant improvement on the reinforcement, an 80% decrease in gravel column treating work, and up to 26% reduction of joint deformation.
		2025 Vol. 44 (8): 31-43 [Abstract] ( 50 ) PDF (3275 KB) ( 56 )

	44	Experimental study on mechanical properties of carbon fiber-reinforced hydraulic asphalt concrete
		KOU Jialiang, REN Yuting, LI Bao, LIU Yunhe
		DOI: 10.11660/slfdxb.20250805
		Trabecular bending and uniaxial compression tests of carbon fiber-reinforced asphalt concrete are carried out under different temperatures and different loading rates to study their effects on the mechanical properties, focusing on the stress-strain behavior of trabecular bending and uniaxial compression under different environmental conditions. The test results show that at a temperature as low as -20 °C and a loading rate of 1.67 mm/min, flexural tensile strength varies between 1.30 and 11.10 MPa; at the rate of 1 mm/min, compressive strength increases from 2.41 to 31.10 MPa. We have observed that at the same loading rate, temperature has a great influence on flexural tensile strength and compressive strength. When the temperature is fixed at 20 °C, flexural tensile strength increases from 1.03 to 2.50 MPa as the loading rate increases from 1.67 to 16.7 mm/min, and compressive strength increases from 2.41 to 3.81 MPa as the rate increases from 1 to 10 mm/min. Analysis on the test data of carbon fiber asphalt concrete gives its relationship between flexural tensile strength and compressive strength in the condition of the same temperature and same loading rate.
		2025 Vol. 44 (8): 44-56 [Abstract] ( 47 ) PDF (2109 KB) ( 24 )

	57	Intelligent traceability of mine water inrush and intervention analysis of mining strategy in Pingshuo mining area
		LI Weihong, WANG Mingyang, WANG Congcong, WANG Enzhi, ZHOU Ting, LIU Zhankui, GU Hongbiao, JIA Zili, HU Guoxin
		DOI: 10.11660/slfdxb.20250806
		Mining activities significantly affect ion concentration in groundwater, and changes in mining strategies exhibit notable heterogeneity in their impact on different aquifer lithologies. Traditional methods lack reliability in identifying water sources, since they are based on empirical groundwater chemical characteristics. This study adopts causal inference models to describe the evolution and heterogeneity of water chemical characteristics, and presents a groundwater traceability inference model based on Random Forest (RF) and Generalized Random Forest (GRF). Using nearly 20 years of groundwater chemical data from the Pingshuo mining area, and combining the RF model with data augmentation techniques, we have achieved intelligent traceability of aquifer lithologies with an accuracy of exceeding 97%. The results indicate adjustments in mining strategies have a significant impact on aquifer lithologies, particularly on the water quality from mining voids and sandstone, which exhibits strong heterogeneity in ion concentrations. The heterogeneity further affects the traceability model's classification ability. This study reveals the mechanisms of how certain mining strategy intervention influences the variations in water chemical characteristics in different aquifer lithologies, and helps optimize groundwater resource management in mining areas.
		2025 Vol. 44 (8): 57-70 [Abstract] ( 47 ) PDF (5016 KB) ( 24 )

	71	Influence of maximum particle size of aggregate on performance of impermeable layer asphalt concrete
		LI Yanlong, KUDERETI Rehaman, DONG Jing, LIU Yunhe, CHEN Junhao
		DOI: 10.11660/slfdxb.20250807
		Applicability of larger particle size aggregate in asphalt concrete used as impervious panel material helps reduce material costs while improving its mechanical properties. This paper presents a method that increases the maximum particle size Dmax of its concrete aggregate from 16 mm to 26.5 mm and 31.5 mm. Optimal mix parameters are obtained through mix proportion tests for three sets of asphalt concrete with different maximum particle sizes; Their splitting, uniaxial compression, tensile, and slope flow tests are conducted. The performances are compared and the influence of aggregate size on mechanical properties is examined. The results demonstrate the maximum particle size has a significant impact on both its mix proportion parameters and properties. With the maximum particle size increasing, the gradation index increases, while the specific surface area of aggregate and the asphalt-aggregate ratio both decreases (from 7.0% to 6.2%), reducing material costs effectively. Appropriate increase in the maximum particle size helps improve splitting strength (an increase of 4.02%) and compressive strength (an increase of 14.07%) of asphalt concrete, and reduce the slope flow value. However, when the maximum particle size is too large, tensile strength decreases (a reduction of 5.78%), brittle failure dominates the failure mode, and toughness and deformation adaptability are weakened. This study would lay a theoretical basis for further research on large particle size aggregates used in impermeable layer asphalt concrete to build pumped storage power station panels.
		2025 Vol. 44 (8): 71-80 [Abstract] ( 54 ) PDF (2034 KB) ( 24 )

	81	Stress analysis and rapid crack assessment of spherical particles: From mono-particle to multi-particle systems
		JIANG Hui, YUAN Yaoyun, ZHOU Yuande, WANG Jinting, ZHANG Xianke, DU Xiuli
		DOI: 10.11660/slfdxb.20250808
		Granular materials are widely used in engineering applications, where their internal stress distribution and fracture behavior greatly influence the stability and safety of structures such as rockfill dams and roadbeds. This study investigates the internal stress distributions and crack initiation mechanisms of spherical particles under uniaxial compression based on two analytical solutions: the Hiramatsu-Oka (HO) solution, and the Dean-Sneddon-Parsons (DSP) solution. The results indicate loading range significantly influences internal stress distribution and crack initiation location. Stress distributions obtained from both solutions are highly consistent, while the DSP solution offers superior extensibility. We further extend the DSP solution to multi-point loading conditions, and develop a rapid evaluation framework for stress distribution and crack initiation in granular assemblies based on an approach of coupling the scaled boundary finite element method (SBFEM) and DSP. This framework efficiently determines contact force distributions in granular assemblies using SBFEM, and applies the stress superposition principle of the DSP solution to achieve a rapid assessment of stress fields and crack initiation zones. The findings lay a theoretical foundation for understanding stress distribution and fracture mechanism in granular materials, and they could be further applied to rapid evaluation of the deformation and potential breakage rates in granular assemblies.
		2025 Vol. 44 (8): 81-92 [Abstract] ( 50 ) PDF (3328 KB) ( 36 )

	93	Mechanical characteristics of fiber-reinforced abrasion-resistant fly ash concrete under uniaxial compression
		QIN Yuan, YUAN Xudong, WU Jiangjiang, ZHAO Yingcheng, ZHAO Jingwei, DUAN Minghan
		DOI: 10.11660/slfdxb.20250809
		This study selects polypropylene fibers (PP) and polyacrylonitrile fibers (PAN) as reinforcing contents of high-strength wear-resistant fly ash concrete (HF concrete) to improve its brittle damage characteristics. Combining digital image correlation technology (DIC) and ultrasonic detection (UT), we conduct experimental tests and examine the stress-strain characteristic parameters of this fiber-reinforced HF concrete under the condition of compression damage. The results show its damage and failure process can be divided into five stages－elasticity, plasticity, sudden damage, accelerated damage, and residual damage. PP inhibits the initiation of microcracks in elastoplastic stage, and PAN inhibits the propagation of microcracks in abrupt damage stage. With a PP content of 0.6 kg/m3 and PAN of 0.6 kg/m3, the concrete enjoys the best hybrid effect and a peak stress increase of 8.35% or 4.47% in comparison with that of the single PP or PAN respectively, and it manifests an increase of 23.74% or 9.87% respectively in its compressive toughness index. Finally, a stress-strain full curve model is developed for such fiber-reinforced HF concrete based on the CEB-FIP model and Guo Zhenhai model, and it is optimized using an improved differential evolution algorithm. It gives optimized stress-strain full curves in good agreement with the experimental curves. Our findings help engineering application of fiber-reinforced HF concrete and lay a basis for follow-up research.
		2025 Vol. 44 (8): 93-104 [Abstract] ( 51 ) PDF (1282 KB) ( 48 )

	105	Adaptive identification of concrete dam deformation outliers based on optimized statistical model
		XIAO Sheng, YANG Jie, CHENG Lin, MA Chunhui, XU Xiaoyan
		DOI: 10.11660/slfdxb.20250810
		The development of a safety monitoring model utilizing dam deformation monitoring data is a crucial method for the quantitative analysis of deformation patterns, but previous deformation monitoring models often suffer from severe shortcomings in the selection of influencing factors and resisting outlier interference. This study develops an adaptive identification method for deformation outliers in concrete dams based on optimized statistical models. This method not only identifies outliers during regression modeling, but also prevents the monitoring model from distortion caused by erroneous data cleansing. First, we use a Bayesian model selection technique to reduce redundancy among the deformation’s influencing factors, helping identify significant explanatory variables in the statistical modeling phase. Then, we use the least trimmed squares estimation for robust regression analysis of the deformation monitoring data, and construct a monitoring model that adaptively identifies various types of anomalies in the deformation data series. Finally, we design and implement a visualization strategy for different types of anomalies to generate an intuitive representation of their locations and potential impacts. A case study demonstrates that this new method identifies key deformation factors effectively, and adaptively reduces the interference of different anomaly types to regression analysis. It leads to improvement on the significance of regression results and the goodness of fit and prediction accuracy, manifesting satisfactory applicability for detecting anomalies in monitoring data and conducting quantitative analyses of dam safety behaviors.
		2025 Vol. 44 (8): 105-118 [Abstract] ( 50 ) PDF (3169 KB) ( 70 )

	119	Automatic identification method of safety hazards in hydropower construction based on dual attention mechanism
		XU Renle, TIAN Dan, SHAO Bo, ZHONG Xinning, WANG Qiushi
		DOI: 10.11660/slfdxb.20250811
		To accurately identify the safety hazards at hydropower construction sites in real time, this paper combines the channel attention mechanism and spatial attention mechanism, improves and applies the YOLOv8 algorithm, and develops an automatic identification method of safety hazards in hydropower construction based on the dual attention mechanism. First, based on the YOLOv8 network framework, we construct a channel attention mechanism to highlight key features adaptively, strengthen dynamically the expression of image features of hidden danger areas, and suppress the influence of background noise. Then, a spatial attention mechanism is built that helps weight important regions, reduce background interference, and optimize feature fusion. It allows to adjust attention adaptively, enhance local detail capture and the positioning accuracy, improve the multi-scale target detection ability, and enhance the spatial feature representation ability of the model. Finally, we verify the accuracy and reliability of the model through a case study of an ongoing construction project. The results show that the proposed method identifies the hazards effectively against the interference in the construction site through the attention mechanism, and achieves an accuracy rate of up to 86.2%, better than previous identification models, thereby improving the dynamic management, prevention and control of hydropower construction safety hazards.
		2025 Vol. 44 (8): 119-128 [Abstract] ( 66 ) PDF (2717 KB) ( 57 )