This paper performed a numerical study into the dynamic stress improvement of an axial-flow pump and validated the simulation results with a prototype test. To further analyze the dynamic stress characteristics of impeller blades of axial-flow pumps, a bidirectional fluid–structure interaction (FSI) was applied to numerical simulations of the unsteady three-dimensional (3-D) flow field of the whole flow system of an axial-flow pump, and the gravity effect was also taken into account. In addition, real-structure-based single-blade finite element model was established. By using the finite element method, a calculation of the blade’s dynamic characteristics was conducted, and its dynamic stress distribution was determined based on the fourth strength theory. The numerical results were consistent with the prototype tests. In a rotation cycle, the dynamic stress of the blade showed a tendency of first increasing, and then decreasing, where the maximum value appeared in the third quadrant and the minimum appeared in the first quadrant in view of the gravity effect. A method for reducing the stress concentration near the root of impeller blades was presented, which would effectively alleviate the possibility of cracking in the unreliable region of blades. Simultaneously, an experimental method for the underwater measurement of the dynamic stress of prototypical hydraulic machinery was put forward, which could realize the underwater sealing of data acquisition instruments on rotating machinery and the offline collection of measured data, finally effectively measuring the stress of underwater moving objects.

An optimization model for the complementary operation of a photovoltaic-wind-pumped storage system is built to make full use of solar and wind energy. Apart from ensuring the maximum economic benefit which is normally used as the only objective, the stable objectives of minimizing the output fluctuation and variation of load and output difference are added to form the multiobjective problems because of lack of study on access capacity of photovoltaic and wind power. The model aims to increase the power benefit and reduce the output fluctuation and variation of load and output difference under the constraints of station, output balance, and transmission limitation. In a case study, four schemes including single-objective independent operation, single-objective complementary operation, and multiobjective complementary operation are compared to discuss the effect of pumped storage station on economic objective and stable objectives. Furthermore, the opposite trend of the two objectives is proved and a compromise optimal solution is given. The results indicate that the pumped storage station can effectively increase power benefit and access capacity of photovoltaic and wind power. The study can provide references to the complementary optimization of the pumped storage station and the intermittent renewable energy.

Preliminary design of a new installation concept of a drag-driven vertical axis hydrokinetic turbine is presented. The device consists of a three-bladed, wheel-shaped, turbine partially embedded in relatively shallow channel streambanks. It is envisioned to be installed along the outer banks of meandering rivers, where the flow velocity is increased, to maximize energy extraction. To test its applicability in natural streams, flume experiments were conducted to measure velocity around the turbine and power performance using Acoustic Doppler Velocimetry and a controlled motor drive coupled with a torque transducer. The experiment results comprise the power coefficient, the spatial evolution of the mean velocity deficit, and a description of the flow structures generated by the turbine and responsible for the unsteadiness of the wake flow. Applying a triple decomposition on the Reynolds stresses, we identify the dominant contribution to such unsteadiness to be strongly associated with the blade passing frequency.

This paper proposes a novel parametric output-only modal identification method, termed parametric complexity pursuit (PCP), for accurate identification of modal parameters in civil engineering structures. The proposed method extends the complexity pursuit (CP) algorithm through a system representation. Unlike the standard CP approach, which extracts modes individually, the PCP algorithm transforms CP into a parametric formulation that enables global identification of all modal parameters of interest. This parametric framework provides a rigorous theoretical foundation aligned with structural dynamics and explicitly accounts for mutual influences among different modes, thereby enhancing both accuracy and robustness. Numerical experiments on a simulated 3-DOF system under various damping conditions and closely spaced modes demonstrate that PCP maintains consistent identification accuracy across all damping levels, exhibiting true damping-independent performance. In contrast, conventional CP suffers from marked accuracy degradation as damping increases and fails to properly identify the closely spaced modes. Application to the HCT building further confirms the practical effectiveness of PCP, with comparative analysis demonstrating its superiority over existing output-only techniques in modal separation capability and identification accuracy. The proposed PCP method offers a robust and theoretically grounded framework for output-only modal identification, particularly advantageous in challenging scenarios involving high damping and closely spaced modes.

Forecasting the deformation and movement of cumulus clouds provides an important basis for ultra-short-term solar irradiance nowcasting in photovoltaic (PV) power generation. Existing methods mainly use two-dimensional (2D) ground-based sky images for forecasting, which have limited ability to represent the three-dimensional (3D) spatial structure of cumulus clouds and the influence of wind on cloud motion. In this study, we propose a wind-aware ultra-short-term spatiotemporal forecasting model for 3D cumulus clouds, termed three-dimensional Cloud Long Short-Term Memory with Wind Gate Recurrent Unit (3dCLSTM + WindGRU). The model uses 3dCLSTM to learn the spatial structure and temporal evolution of 3D voxel cumulus cloud sequences, and embeds a WindGRU unit between 3dCLSTM layers to introduce wind speed and wind direction information for wind-driven transient motion modeling. Experiments were conducted on 1-min and 10-min 3D cumulus cloud datasets reconstructed from ground-based sky image datasets collected at sites in California and Colorado, USA. All voxel sequences were resampled to 64 × 64 × 64, with five-step prediction for the 1-min dataset and three-step prediction for the 10-min dataset. The results show that 3dCLSTM achieved a structural similarity index measure (SSIM) of 0.7913 on the 1-min dataset, while 3dCLSTM + WindGRU achieved the best performance on the 10-min dataset, with an SSIM of 0.3512 and a peak signal-to-noise ratio (PSNR) of 18.3625. Compared with 3dCLSTM, introducing WindGRU improved the SSIM by 4.8% on the 10-min dataset, with a more evident improvement under relatively high wind-speed conditions. These results indicate that wind-aware volumetric spatiotemporal modeling can support ultra-short-term 3D cumulus cloud forecasting and provide a useful technical basis for solar irradiance nowcasting.