In the present study, Mo was added to Cu–15Ni–8Sn alloy as the fourth element to solve the limitation of service performance of the alloy by composition design. The phase composition, microstructure transformation and mechanical properties of Cu–15Ni–8Sn–xMo (x = 0.3, 0.9, 1.5 wt.%) alloy were systematically studied by simulation calculation and experimental characterization. The results show that the addition of Mo can improve the as-cast structure of Cu–15Ni–8Sn alloy and reduce segregation and Cu–Mo phase precipitates on the surface with the increase in Mo contents. During solution treatment, Mo can partially dissolve into the matrix, which may be the key to improving the properties of the alloy. Furthermore, the discontinuous precipitation of Sn can be effectively inhibited by adding the appropriate amount of Mo to Cu–15Ni–8Sn alloy, and the hardness of alloy does not decrease greatly after a long-time aging treatment. When Mo content is 0.9 wt.%, the alloy reaches the peak hardness of 384 HV at 4 h of aging. These results provide new ideas for composition optimization of Cu–15Ni–8Sn alloy.

In the present study, a Cu–6Ni–6Sn–0.6Si alloy is fabricated through frequency induction melting, then subjected to solution treatment, rolling, and annealing. The phase composition, microstructure evolution, and transition mechanism of the Cu–6Ni–6Sn–0.6Si alloy are researched systematically through simulation calculation and experimental characterization. The ultimate as-annealed sample simultaneously performs with high strength and good ductility according to the uniaxial tensile test results at room temperature. There are amounts of precipitates generated, which are identified as belonging to the DO22 and L12 phases through the transmission electron microscope (TEM) analysis. The DO22 and L12 phase precipitates have a significant strengthening effect. Meanwhile, the generation of the common discontinuous precipitation of the γ phase, which is harmful to the mechanical properties of the copper–nickel–tin alloy, is inhibited mightily during the annealing process, possibly due to the existence of the Ni5Si2 primary phase. Therefore, the as-annealed sample of the Cu–6Ni–6Sn–0.6Si alloy possesses high tensile strength and elongation, which are 967 MPa and 12%, respectively.

In this paper, a phase-scheduled-command filtered-x least mean square (FXLMS) algorithm with a phase error between the disturbance and command signal is analyzed in detail. The influence of the phase error on the control effort, convergence time constant and performance of convergence is explained for both stationary and nonstationary disturbance signal cases. An estimation ratio, in both stationary and nonstationary disturbance cases, of the pseudo-error MSE convergence performance is also developed and discussed. Simulation results were collected to verify the analysis. The results show that, for both stationary and nonstationary disturbance, the phase error may heavily increase the distance of the optimum vector from the initial value, leading to a large control effort, a large convergence time constant and poor convergence performance. The estimation ratio also has a satisfactory performance for estimating the influence of the phase error.

In this paper, the Phase-Scheduled-Command FXLMS algorithm with the phase error between the disturbance and command signal is analyzed in detail. The influence of the phase error on the convergence time constant, convergence rate, and performance of convergence is explained for both stationary and nonstationary disturbance signals case. For stationary disturbance, the phase error slightly increases the convergence rate but heavily increases the distance of the optimum vector from the initial value, leading to poor convergence time constant performance. For nonstationary disturbance, the existence of phase error leads to poor convergence performance in every step, resulting in poor sound profiling performance. And the estimation of the phase error influence is developed in the closed form. Simulations are performed to demonstrate the validity of the analysis results.

To explore the dynamic mechanical performance of metal rubber (MR) under high-speed impact loading, cylindrical solid MR specimens with spring coil outer diameters of 2–4 mm and relative densities of 0.2–0.35 have been prepared, and dynamic compression tests have been carried out utilizing the split Hopkinson pressure bar (SHPB) device at strain rates of 400–1000 s⁻¹. The dynamic stress–strain response of MR has been systematically analyzed, and the influences of strain rate, spring coil outer diameter, and relative density on its dynamic elastic modulus and energy absorption properties have also been quantitatively investigated. The results reveal that the dynamic stress–strain relationship of MR under high-speed impact presents significant nonlinearity and distinct strain rate effect. MR specimens with higher relative density, smaller spring coil outer diameter, or higher strain rate exhibit a larger dynamic elastic modulus, while those with higher relative density, larger spring coil outer diameter, or lower strain rate achieve higher energy absorption efficiency. A modified dynamic constitutive model for MR based on the Sherwood-Frost model has been developed by incorporating strain rate, relative density, and spring coil outer diameter as key influencing variables. The results show that the maximum mean relative error between the predicted and experimental data is less than 20%, indicating a favorable accuracy and reliability of the constitutive model. The proposed model can effectively characterize and predict the dynamic mechanical behavior of MR under high-speed impact loading conditions, providing a reliable theoretical basis for the engineering application of MR in impact-resistant structures.