To improve the accuracy of calculating the aluminum electrolysis pre-close wind volume, this study focused on optimizing the two main factors that influence its magnitude: the aluminum output speed and the pre-close wind volume coefficient. First, the Unscented Kalman Filter (UKF) algorithm was used to estimate the aluminum output speed, and its application in real production was verified through simulation experiments. The results demonstrate that UKF provides more accurate speed estimates when handling the non-linear dynamic system of aluminum electrolysis. When there was a sudden change in speed, the UKF achieved a relative error of only 0.0373%, significantly lower than the 2.52% error of the traditional Kalman Filter (KF). At the same time, the UKF exhibited a shorter runtime in the simulation. Additionally, this research introduces a self-correction mechanism for the pre-close wind volume coefficient for the first time. By dynamically adjusting the parameter based on aluminum output deviations and applying the Average Filter (AF) to improve the compensation accuracy, the pre-close wind volume coefficient can be precisely calculated. The combination of these methods significantly enhances the accuracy and robustness of pre-close wind volume calculations, providing solid theoretical foundations and the technical support needed to achieve high-precision aluminum output control.

Addressing the issue of leakage in practical scenarios involving hose pumps, this paper conducts an analysis on hose pumps with existing compression gaps. The model is simplified to represent the two-dimensional Newtonian fluid pulsating flow of a single-sided sine wave passing through the tube. The study derives the axial flow velocity distribution within the tube while establishing correlations between the leakage volume, tube clearance, pressure differential, deformed cross-sectional length of the tube, rotor speed (which exhibits a negative correlation), the deformation length of the tube in the x-direction, and the fluid's dynamic viscosity (demonstrating a positive correlation). Utilizing a bidirectional fluid-structure coupling method, this analysis investigates hose pumps with compression gaps. Specifically, it examines the flow field pressure, velocity, and vortex intensity of two Newtonian fluids with Reynolds numbers of 10–30 and 6000–15 000, respectively, within a 180° bend tube with a curvature-to-inner-diameter ratio of 4.6. This analysis is conducted under inlet velocities of 0.32 and 0.6 m/s, and outlet pressures of 0 and 0.1 MPa. The study identifies the positions of extreme leakage rates, elucidating the flow field characteristics and their impact on leakage. Furthermore, it investigates the causes of secondary flows within the tube, concluding that the fluid inside the tube exhibits symmetric helical motion. This research establishes the periodic variations in flow field vortex intensity and secondary flow intensity, along with the conclusion that leakage rates are positively correlated with axial vortex intensity and negatively correlated with secondary flow intensity.

Hose pumps, renowned for their ability to efficiently transport highly viscous and corrosive fluids, hold an irreplaceable position in numerous engineering domains. With a wide range of fluid types being transported by hose pumps, the study of pressure variations during the conveyance of different fluid states is of paramount importance, as it positively contributes to optimizing hose pump structures, reducing noise, and enhancing hose pump longevity. To investigate pressure variations in hose pumps during the conveyance of varying fluid states, this paper employs a bidirectional fluid–structure coupling method and utilizes commercial finite element software, ANSYS. The research validates the causes of variations in hose pumps during fluid conveyance and examines the overall pressure distribution within the fluid domain of hose pumps conveying different fluid states at varying rotor speeds. The results indicate that when the fluid within the hose pump is in a turbulent state, pressure variations exhibit multiple minor amplitude oscillations, whereas in a laminar state, pressure variations display fewer oscillations but with more significant amplitudes. Moreover, higher rotor speeds exacerbate pressure variations. Recommendations include optimizing the shape of the squeezing roller and enhancing pressure variation control through shell angle optimization.

Predicting and optimizing the mechanical performance of the helically wound nylon-reinforced rubber fertilizer hose (HWNR hose) is crucial for enhancing the performance of hose pumps. This study aims to enhance the service life of HWNR hoses and the efficiency of liquid fertilizer transport. First, a finite element simulation model and a mathematical model were established to analyze the influence of fiber layer arrangement on the maximum shear strain on the coaxial surface (MSS) and the reaction force on the extrusion roller (RF). For the first time, the Crested Porcupine Optimizer algorithm was used to improve the Generalized Regression Neural Network (CPO-GRNN) method to establish a surrogate model for predicting the mechanical properties of HWNR hoses, and it was compared with Response Surface Methodology (RSM). Results showed CPO-GRNN's superiority in handling complex nonlinear problems. Finally, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was employed for optimization design. Compared to the original HWNR hose with an MSS of 0.906 and an RF of 30,376N, the optimized design reduced the MSS by 7.99% and increased the RF by 2.46%, significantly enhancing their service life and liquid fertilizer transport capacity. However, further research on fatigue damage is needed.