Water jet technology is widely used in various fields, in which the nozzle is an important element to form the jet. To solve the problem of low water jet operation efficiency of square nozzles, the internal flow channel structure of the nozzle of the key jet device is studied. Through the combination of computational fluid dynamics (CFD) and particle image velocimetry (PIV) experiments, the influence of main structural parameters such as the contraction angle and length-to-diameter ratio of the inner flow channel on the velocity and length of the constant-velocity core region is explored. Since the jet flow structure is a symmetrical structure along the axial direction, the model of the jet flow structure was built half of the model along the axial direction. The results show that a smaller length-to-diameter ratio and a smaller contraction angle of the nozzle result in better jet cohesion and lower dynamic pressure in the constant-velocity core area, which is more suitable for long-distance, low-pressure water jet operations.

Accurate load identification serves as a fundamental requirement for achieving lightweight and efficient structural designs. This paper presents a dynamic load identification method for structures with parameter uncertainties, integrating the ellipsoidal model with shape functions. The approach explicitly accounts for correlations among uncertain structural parameters, leading to improved identification accuracy and more compact load bounds. The method first establishes an ellipsoidal model for the uncertain parameters, representing their feasible domain as a compact ellipsoidal set. This model is then incorporated into the dynamic load identification framework. Convex optimization theory and the Lagrangian multiplier method are employed to derive analytical expressions for the load bounds. Shape functions are utilized to describe the temporal variation of the load, reducing the ill-posedness of the inverse problem, while central finite difference approximations are applied to compute load sensitivities with respect to the uncertain parameters. The efficacy of the proposed method is validated through a numerical example involving a 21-bar truss structure, demonstrating its advantages in both identification accuracy and boundary compactness compared to conventional interval methods.