Journal of Hydroelectric Engineering

水力发电学报

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2026 Vol. 45, No. 2 Published: 2026-02-25

	1	Displacement prediction model for arch dams with cracks integrating feature selection and feature extraction
		JIANG Chengyang, SU Huaizhi, XU Bo
		DOI: 10.11660/slfdxb.20260201
		Previous prediction models were limited by their inadequate consideration of temperature hysteresis effects and crack influences of an arch dam, and suffer from overly complex, redundant displacement factors and low prediction accuracy. To achieve accurate predictions of displacement in the arch dams with significant cracks, this paper develops a novel predictive method. First, we construct a displacement monitoring model for the dams, accounting for temperature hysteresis effect and crack influences. Then, a gradient boosting regression tree (GBRT) is used for feature selection among influencing factors, eliminating irrelevant variables; Kernel principal component analysis (KPCA) is applied to extract features from the retained temperature hysteresis and crack factors, so as to construct a displacement prediction dataset. Finally, we construct a displacement prediction model by integrating the salp swarm algorithm with the kernel extreme learning machine (SSA-KELM). Engineering case results demonstrate feature selection and feature extraction effectively mitigate the interference of irrelevant variables and reduce data dimensions, thereby improving prediction accuracy significantly. Compared with other benchmark models, SSA-KELM that presents the highest prediction accuracy and stability is a new viable approach for predicting displacement in arch dams with cracks.
		2026 Vol. 45 (2): 1-14 [Abstract] ( 76 ) PDF (1463 KB) ( 74 )

	15	Stacking-based deep ensemble model for concrete strength prediction considering aggregate gradation and derived features
		CAI Zhijian, WANG Xiaoling, ZHANG Jun, WANG Dong, WU Binping, YU Hongling
		DOI: 10.11660/slfdxb.20260202
		Accurate prediction of concrete compressive strength plays a significant role in quality control during construction. Previous predictive models largely focused on the influence of initial mix proportions, but neglected the impact of aggregate gradation, derived features, and its interpretability. This study develops a stacking-based deep ensemble model for predicting compressive strength, which holistically considers these two factors to improve predictive accuracy and interpretability. This novel model uses three widely used ensemble learning algorithms and a Convolutional Neural Network (CNN) as heterogeneous base learners to leverage diversity and heterogeneity among these algorithms. To improve the tree-based models that are usually too sensitive to hyperparameters and limited by their capacity for high-dimensional feature extraction, we integrate CNN with a channel attention mechanism, thereby enhancing its feature representation capability. A Multi-Layer Perceptron (MLP) incorporating an attention mechanism is adopted as a robust meta-learner to mitigate overfitting risks. Leveraging the SHAP (Shapley Additive explanation) framework, we examine systematically the critical features of concrete strength prediction and their interactive effects. Experimental results show our new model, through considering aggregate gradation and derived features comprehensively, achieves a 27.53% improvement in the accuracy of compressive strength predictions. Using a SHAP analysis, we have identified the dominant drivers of the model－water-to-binder ratio, water content, fly-ash-to-water ratio, cement content, and the mass fraction of aggregates in the size range of 31.5-40 mm. This study improves predictive accuracy and sheds light on the understanding of core parameters governing concrete strength through interpretable analysis, helping intelligent concrete management.
		2026 Vol. 45 (2): 15-30 [Abstract] ( 71 ) PDF (6912 KB) ( 34 )

	31	Study on predictive reconstruction and numerical simulations of fluid-structure interaction fields in large-scale sluice chambers
		GONG Chengyong, WENG Weitao, WANG Yinying, CHEN Shiming, GUO Xinyu
		DOI: 10.11660/slfdxb.20260203
		To examine the interaction mechanism between flood discharge and a sluice chamber, a novel method is developed coupling fluid-structure interaction (FSI) Finite Element analysis with a Back Propagation Neural Network, based on stress-strain characteristics, and applied to the Datengxia water control hub project. This method facilitates the development of a digital twin based on numerical simulation data. We construct a finite element model of COMSOL for flood discharge and sluice chamber structure, and simulate five flood discharge scenarios of 23400 m3/s, 30600 m3/s, 39000 m3/s, 42300 m3/s, and 66200 m3/s. Then, we examine the FSI process of the sluice chamber and its corresponding load patterns. A total of 1250 monitoring points are arranged throughout the sluice chamber and the flow domain. The time-sequence data for four hydraulic parameters are extracted at a 15-second interval－flow velocity ( ), pressure ( ), turbulence intensity ( ), and vorticity ( ). And, stress and displacement data are simultaneously collected from the sluice chamber, so that training datasets for the BP Neural Network (BPNN) can be constructed. Finally, we develop a BPNN model for predictions of the sluice chamber’s stress and displacement, using spatial coordinates and hydraulic parameters as inputs, and train and validate it. Results show a high predictive accuracy of this FSI collaborative BPNN method－the coefficient of determination (R2) reaches up to 0.975 for stress and 0.987 for displacement. Specifically, 96.0% of the stress predictions have an error below 10% with the maximum absolute error of 0.097 MPa; 99.1% of the predicted displacements have an error below 10% with the maximum absolute error of 0.395 mm, or significantly below the allowable deformation threshold of 0.45 mm for chamber joints. This study verifies the feasibility of our new method, the reliability of BPNN in predicting stress and displacement in the sluice chamber, and the advantage of methodology.
		2026 Vol. 45 (2): 31-45 [Abstract] ( 125 ) PDF (8941 KB) ( 72 )

	46	Application of physics-encoded data-driven constitutive modeling in stress-deformation analysis of rockfill dams
		HE Zhihan, MA Gang, ZHOU Wei, WANG Jingzhou, LI Yanlong, HU Jinfang
		DOI: 10.11660/slfdxb.20260204
		In recent years, efforts have been made to apply the Artificial Intelligence for Science (AI4S) paradigm in various fields of hydraulic and hydropower engineering, e.g. the data-driven techniques used in the constitutive modeling of engineering materials. However, data-driven constitutive models often suffer from limited generalizability and robustness; most of the previous studies remained confined to simple numerical examples, leaving applicability to complex engineering problems in need of further verification. This study adopts a Generalized Plasticity Model-Physics-encoded Neural Network (GPM-PeNN), developed by our team, to simulate the stress and deformation of a rockfill dam. This model is trained using a synthetic dataset of rockfill materials from the Lawa high concrete-faced rockfill dam, and it is embedded into the general-purpose finite element code ABAQUS via a user-defined material module (UMAT). It is used to simulate the stress and deformation responses during dam-filling. Compared with finite element analyses based on traditional constitutive models, our simulations－based on the physics-encoded neural network constitutive model－align with general mechanical behaviors, and exhibit high accuracy and good convergence, thereby validating the feasibility of applying data-driven constitutive models in practical engineering applications.
		2026 Vol. 45 (2): 46-57 [Abstract] ( 58 ) PDF (4937 KB) ( 33 )

	58	Optimal configuration of multi-energy complementary energy storage in Qinghai accounting for hydropower characteristics
		HE Pinkun, MA Jun, LIU Chulei, LIU Tingxiang, LI Zhengxi, PENG Yang, XIAO Feng
		DOI: 10.11660/slfdxb.20260205
		To address the combined challenges of wind-solar power fluctuations and seasonal hydropower disparities in the Qinghai grid under high renewable energy penetration, this paper presents a bi-level optimization model for energy storage capacity planning. The model explicitly considers the patterns of hydropower output and its complementarity with renewable energy by incorporating time-dependent operational constraints that quantify these characteristics. For a typical year, the optimized storage configuration in the scenario under certain time-segmented hydropower constraints is 526 MW/1578 MWh with a 3-hour duration, achieving a 91% renewable energy utilization rate. This rate is higher than the ones of 84%, 88%, and 86% achieved by the hydropower operations under no constraint, annual wide-constraint, and annual narrow-constraint, respectively. It verifies that our novel method that represents the hydropower features using quantified constraints enhances its rationality and applicability in practical applications of the storage configuration, thereby supporting higher renewable energy integration.
		2026 Vol. 45 (2): 58-67 [Abstract] ( 68 ) PDF (2102 KB) ( 29 )

	68	Spatiotemporal evolution and driving factors of carbon storage in reservoir rim regions of hydropower projects
		MA Fangping, PENG Fang, FENG Xingguo, HU Jing, WANG Haoran, HE Wenyan, ZHANG Hong
		DOI: 10.11660/slfdxb.20260206
		This study aims to verify the low-carbon attributes of hydropower projects. Focusing on the Pubugou hydropower project commissioned in late 2010 on the mainstream of the middle Dadu River, we examine the spatiotemporal evolution and driving mechanisms of carbon storage in the reservoir rim region using the InVEST model and Geodetector, based on its 1990-2023 land use data. The results indicate the region’s land use underwent three distinct stages in the study period－natural succession, engineering disturbance, and ecological adjustment. Forest land consistently remained dominant in land cover type, with its proportion gradually increasing up to 70.2%. Spatially, carbon storage featured a pattern of being enriched at higher elevations and sparse at lower elevations; Temporally, it grew at an average annual rate of 0.11%, verifying carbon sequestration has been enhanced in the region since the completion of this project. Forest land acted as the core contributor to carbon sequestration. We also find that natural factors were dominant in the spatial differentiation, while socioeconomic factors imposed relatively weak influences. The interaction of dual factors further enhanced this spatial differentiation. These findings provide a novel perspective for assessing the low-carbon benefits of hydropower projects in alpine valley regions, and lay a basis for ecological management of reservoir rims.
		2026 Vol. 45 (2): 68-83 [Abstract] ( 60 ) PDF (2828 KB) ( 30 )

	84	Shifting of scour-silting inflection points in Longmen-Sanmenxia reach and their impacts on Tongguan riverbed elevation
		WEN Zhichao, HUANG Zhe, XIAO Yong, LU Jun, GAO Xing
		DOI: 10.11660/slfdxb.20260207
		The Tongguan section serves as a crucial node for water and sediment transport in the joint operation of reservoir groups in the middle Yellow River. Based on the data measured in the Sanmenxia reservoir since implementing its operation of storing clear water and discharging sediment, this study examines the spatiotemporal distribution characteristics of scour and silting in the Longmen-Sanmenxia reach and the evolution of the Tongguan riverbed elevation. The results show that this reach’s upper section (Longmen-Tongguan) experiences scour in non-flood season and silting in flood season, whereas opposite is the pattern of scour and silting in its lower section (Tongguan-Sanmenxia). Specifically in the study reach, an inflection point occurs for transition between scour and silting. In the non-flood seasons of 2010-2021, the reach’s scour-to-silting inflection points were concentrated in the tail of Longmen-Tonguan upstream of the Tongguan station. Their locations were mainly related to flow energy at the Longmen station－they shifted downstream by roughly 19.45 km for every 1×106 J/m increase in flow energy. In contrast, in the flood seasons, the silting-to-scour inflection points were concentrated in the reservoir tail of Tongguan-Sanmenxia downstream of Tongguan; they shifted upstream by 32.10 km for every 1×106 J/m increase in flow energy. Within the same hydrological year, the non-flood season and flood season inflection points serve as the endpoint of along-channel scour in the wandering river reach and the starting point of scour in the reservoir, respectively. Between these two points, slight scour or slight silting occurs. Tongguan is located exactly right between them, and its bed elevation is proportional to the distance between them. A larger distance indicates a wider range of the river reach that stays in the state of slight scour and slight silting, which means it is more difficult to effectively lower the Tongguan riverbed elevation. To overcome the difficulty, an effective measure should be to enhance flow energy in the study reach through optimizing the water-sediment relationship in the middle Yellow River.
		2026 Vol. 45 (2): 84-95 [Abstract] ( 59 ) PDF (2174 KB) ( 34 )

	96	Study on pressure pulsation characteristics and tracing in vaneless section of pumped storage units under turbine mode
		WANG Chenxu, GUANG Weilong, XIAO Ruofu, YAO Zhifeng, TAO Ran, LIANG Quanwei, JIN Faye
		DOI: 10.11660/slfdxb.20260208
		Wide-load operation in the turbine mode is increasingly required for pump turbines in pumped storage plants, yet the pressure pulsations in the turbine intensify notably under small-opening, low-load conditions, posing a potential threat to unit safety and stability. Using the pulsation tracing network (PTN) method, this study examines a pump-turbine with a five-long and five-short blade runner, focusing on analysis of the pressure pulsation characteristics in its vaneless section under different heads, different guide vane openings, and different loads in the turbine mode. The results reveal complicated pressure pulsation components in the vaneless section, including typical frequencies such as 0.33fn, 1fn, 3fn, 5fn , and 10fn (fn for one tenth of the blade passing frequency), and the ones of 10fn and 5 fn exert the most significant influence. The phase characteristic analysis further indicates the dominant frequency pulsations propagate upstream and downstream, affecting flow stability throughout the full passage. These findings provide valuable insights for optimizing pump-turbine runner design to enhance wide-load operational performance.
		2026 Vol. 45 (2): 96-105 [Abstract] ( 72 ) PDF (4984 KB) ( 49 )

	106	Study on flow characteristics of different labyrinth seal structures of reversible runners
		ZHENG Yingxia, WU Daoke, SHU Lingfeng, CHEN Yong, FU Xiaolong, GONG Ruzhi, WANG Hongjie
		DOI: 10.11660/slfdxb.20260209
		This study addresses unclear energy dissipation mechanisms in complicated flows in the runner labyrinth ring section of a pump-turbine under the runaway condition, and examines how these flows affect the unit’s overall hydraulic performance. We compare three seal types of crown labyrinth rings: ladder, serrated, and inclined-tooth, using a combined method of the high-resolution three-dimensional (3D) computational fluid dynamics (CFD) and the entropy production theory. The results indicate that of the three types, the inclined-tooth seal, through inducing a circumferential swirl, manifests the highest total entropy production and superior sealing performance. The serrated seal suppresses the leakage flows effectively and reduces the axial hydraulic thrust significantly, whereas the inclined-tooth seal tends to increase radial forces and cause pronounced fluctuations in the axial thrust. The performance of the ladder seal falls between the two. We have observed the labyrinth structure indirectly affects entropy production and vortex development in the runner and guide vane sections. The design of the upper crown labyrinth seal should balance local dissipation and overall stability－ since the serrated type is suitable for controlling axial thrust, while the inclined-tooth type is ideal for applications requiring high sealing performance. This study lays a theoretical basis for optimizing the labyrinth seal design in pump-turbine runners.
		2026 Vol. 45 (2): 106-114 [Abstract] ( 62 ) PDF (4268 KB) ( 45 )

	115	Hydrodynamic performance and parameter optimization of novel fin-ring horizontal axis hydrokinetic turbine
		SONG Ke, HUAN Huiting, WEI Liuchuang, WANG Yongli
		DOI: 10.11660/slfdxb.20260210
		Tidal current turbines represent core equipment in the development and utilization of ocean energy. To broaden the application of such turbines, the computational fluid dynamics (CFD) method is carried out to investigate three-dimensional numerical simulations of a novel fin-ring horizontal-axis hydrokinetic turbine. This turbine features an unconventional structural design, consisting of a central hub, 7 concentric rings and 88 fin plates. First, it tends to evaluate the hydrodynamic performance of the original design through numerical simulations, and verify the reliability of the numerical model against previously existing experimental measurements in literature. Then, a parametric analysis is focused on the two key design parameters of the fin plates (camber and angle of attack) to systematically examine the turbine's hydrodynamic performance with different combinations of these parameters and determine the optimal design. The results illustrate the combination of a camber of 10 mm and an angle of attack at 20°achieves the best balance between guiding efficiency and resistance loss, thereby significantly enhancing turbine performance. This optimal combination peaks with the power coefficient of 0.42 and a corresponding tip-speed ratio of 1.8. It is also demonstrated that the fin-ring turbine’s certain advantages in energy capture efficiency and eco-friendliness, compared to traditional horizontal-axis and vertical-axis turbines. This study elucidates the hydrodynamic characteristics of this turbine laying a quantitative basis for parameter matching, offering new insights for innovative tidal turbine designs.
		2026 Vol. 45 (2): 115-124 [Abstract] ( 51 ) PDF (1890 KB) ( 30 )