A pump is one of the most important machines in the processes and flow systems. The operation of multistage centrifugal pumps could generate pressure fluctuations and instabilities that may be detrimental to the performance and integrity of the pump. In this paper, a numerical study of the influence of pressure fluctuations and unsteady flow patterns was undertaken in the pump flow channel of three configurations with different diffuser vane numbers. It was found that the amplitude of pressure fluctuation in the diffuser was increased gradually with the increase in number of diffuser vanes. The lower number of diffuser vanes was beneficial to obtain a weaker pressure fluctuation intensity. With the static pressure gradually increasing, the effects of impeller blade passing frequency attenuated gradually, and the effect of diffuser vanes was increased gradually.

An impeller blade with a slot structure can affect the velocity distribution in the impeller flow passage of the centrifugal pump, thus affecting the pump’s performance. Various slot structure geometric parameter combinations were tested in this study to explore this relationship: slot position p, slot width b₁, slot deflection angle β, and slot depth h with (3–4) levels were selected for each factor on an L₁₆ orthogonal test table. The results show that b₁ and h are the major factors influencing pump performance under low and rated flow conditions, while p is the major influencing factor under the large flow condition. The slot structure close to the front edge of the impeller blade can change the low-pressure region of the suction inlet of the impeller flow passage, thus improving the fluid velocity distribution in the impeller. Optimal slot parameter combinations according to the actual machining precision may include a small slot width b₁, slot depth h of ¼ b, slot deflection angle β of 45°–60°, and slot position p close to the front edge of the blade at 20–40%.

The impeller vane exit placement angle has a critical role in the flow characteristics of the fluid inside the lobe, thus having a profound effect on the overall pump performance. The purpose of this study is to investigate the effect of the impeller exit angle on the operating characteristics of a high-speed well submersible pump, and the numerical calculation results of the original model are in good agreement with the experimental results. In this paper, five different impeller vane exit angles, namely 10°, 15°, 20°, 25° and 30°, are selected for numerical analysis based on the original model, and the flow conditions of 0.6 Q, 1.0 Q and 1.4 Q are analyzed for each angle. The results show that the impeller vane exit placement angle not only affects the static pressure distribution, velocity distribution and streamline distribution within the impeller and guide vane, but also has a significant effect on the head curve, power curve and efficiency curve of the well submersible pump. As the flow slip inside the impeller of high-speed well submersible pumps intensifies, the large impeller outlet angle will cause the power of the impeller to increase linearly with the flow rate, thus reducing the pump efficiency. In the low-flow and high-flow conditions, a small outlet angle of 10° will make the efficiency of high-speed submersible pumps higher than in other conditions, and these findings can provide some reference for the optimal design of high-speed submersible pumps.

The fluidized bed is a critical reactor in the energy and chemical industries, where the mixing and agglomeration behaviors of binary particles significantly influence both the efficiency of reaction processes and the uniformity of final products. However, the selection of appropriate drag force models remains a subject of debate due to the variability in particle properties and operating conditions. In this study, we investigated the fluidization behavior of binary mixtures composed of two different sizes of Geldart-D particles within a fluidized bed, evaluating nine distinct drag force models, including Wen and Yu; Schiller and Naumann; Ergun; Gidaspow, Bezburuah, and Ding; Huilin and Gidaspow; De Felice; Syamlal and O’Brien; and Hill, Koch, and Ladd. We focused on four key parameters: particle mixing degree, migration characteristics, temperature variation, and mean pressure drop. Simulation results revealed that the choice of drag model markedly affected mixing behavior, migration dynamics, and temperature distribution. Notably, the Ergun; Gidaspow, Bezburuah, and Ding; and Hill, Koch, and Ladd models exhibited superior particle mixing uniformity. While the drag model had a relatively minor impact on particle temperature changes, its selection became critical in simulations requiring high-temperature precision. Regarding pressure drop, the Huilin and Gidaspow and Gidaspow, Bezburuah, and Ding models demonstrated smaller and more stable pressure drop fluctuations. These findings offer valuable theoretical insights into gas–solid two-phase flow under binary particle mixing and provide practical guidance for the design and operation of fluidized bed reactors.

The flexible operation of coal-fired boilers poses significant challenges to thermal safety, particularly due to delayed responses in wall temperature under variable load conditions, which may lead to overheating risks and reduced equipment lifespan. To address this issue, we propose a PLO-KAN framework for high-precision prediction of high-temperature superheater wall temperatures. The framework integrates a Kolmogorov–Arnold Network (KAN) with learnable B-spline activation functions to enhance interpretability, a sliding-window strategy to capture temporal dependencies, and Polar Lights Optimization (PLO) for automated hyperparameter tuning, balancing local exploitation and global exploration. The method is validated using 10,000 operational samples from a 1000 MW ultra-supercritical once-through boiler, with 68 key features selected from 106 candidates. Results show that the proposed model achieves high accuracy and robustness in both single-step and multi-step forecasting, maintaining reliable performance within a five-minute prediction horizon. The proposed method provides an efficient and interpretable solution for real-time wall temperature prediction, supporting proactive thermal management and enhancing operational safety in coal-fired power plants.