Valve-controlled hydraulic systems are widely used in various hydraulic equipment, but their asymmetric characteristics are the most critical factor restricting further improvements in system performance. This paper takes large asymmetric complex hydraulic equipment as the industrial background, and proposes a state feedback-based symmetric switching control method to address the complex control strategy and difficult control accuracy caused by input–output asymmetry and the inconsistent response of asymmetric valve-controlled hydraulic systems. A system state space model is established, and the parameterized expression that satisfies the state space switching-based symmetric control law is solved. Feedback and feedforward links based on state space symmetric switching are designed to transform the asymmetric system into a state space symmetric system. And the research results will be applied to the experimental setup of the 300 MN forging hydraulic press control system. Through simulation verification, under asymmetric PID control conditions, due to the influence of the asymmetric characteristics of the system structure, load, and their coupling relationship, the forward response time is shorter than the unloaded response time, and the overshoot is larger than the unloaded response time. The reverse response time is longer than the unloaded response time, and the overshoot is smaller than the unloaded response time. After symmetric control, the forward and reverse dynamic system characteristic curves completely overlap, proving that the system has achieved symmetric transformation; through experimental verification, under asymmetric PID control conditions, when the proportional valve opening remains constant, changes in the load pressure will cause changes in the load speed. For every 1 MPa increase in the load pressure, the load speed will slow down by about 0.0033 m/s. The load speed of the system after symmetrical control replacement will be much less affected by changes in the load pressure. The simulation and experimental results have shown that this method is expected to solve the key problem of inconsistent dynamic characteristics of complex equipment hydraulic systems in both the forward and reverse directions due to asymmetry, and the inability to ensure control accuracy in both directions using symmetric control strategies. This paper has developed a set of control theories and methods applicable to hydraulic systems with complex asymmetry.

Chemical short-range order (CSRO) is associated with heterogeneous lattice distortion in refractory multi-principal-element alloys, but its relationship with cyclic dislocation organization remains unresolved. Hybrid Monte Carlo and molecular dynamics simulations were combined with statistical field reconstruction and three-dimensional discrete dislocation dynamics to examine cyclic deformation in HfNbTa. Structure–function analysis of the atomistic strain fields provided the descriptors used to reconstruct heterogeneous strain fields for the as-cast and annealed samples. These reconstructed fields served as the direct inputs to the DDD simulations. Under the simulated loading conditions, the as-cast sample exhibited wider hysteresis loops and approximately four times the final dislocation density of the annealed sample. In the examined network realization, the annealed sample developed a lower-density network with a narrower diagonal concentration of dislocations. Projected band width characterized the transverse extent of this feature. Additional comparisons showed comparable macroscopic stress responses across the tested initial dislocation arrangements and field phases. These results distinguish dislocation storage from spatial organization under the two sample-specific CSRO-associated reconstructed fields; the diagonal morphology is an observation within the examined realizations.

The outstanding mechanical properties of nickel-based alloys are predominantly governed by the characteristics of their nano-precipitation. Traditional optimization approaches, however, have focused almost exclusively on average precipitation size, neglecting the non-uniform size distribution induced by the temperature gradient during the actual preparation process. This oversight leads to inaccurate optimization parameters, hindering the reliable design and broader engineering application of these alloys. This study investigates the coupling effect of average size and deviation on the mechanical behavior of nickel-based superalloys by experiment and simulation. The characterization of prepared nickel-based alloys confirms the spatial non-uniform distribution of the precipitation size and calibrates dislocation dynamics (DD) simulation inputs. When the precipitation size exhibits no deviation, conventional strengthening models align with simulation results, confirming the accuracy of the simulations. Under high size deviation, however, significant discrepancies arise between traditional models and simulation outcomes, indicating that conventional models fail to account for the effect of size deviation. This is because size deviation leads to spatial heterogeneity in precipitate distribution, which is difficult to describe using a unified theoretical framework. Machine learning (ML)-augmented analysis of the extensive DD dataset reveals a previously unrecognized synergistic effect governed by precipitation size heterogeneity. Surprisingly, contrary to the conventional preference for a uniform size distribution, we find that an appropriate size deviation increases the number of precipitates that effectively pin dislocations in three-dimensional space, thereby enhancing strength at a constant volume fraction. Our combined experimentally calibrated DD/ML approach identifies an optimal range of size variation that maximizes strengthening potential. These results provide a new strategy and an effective pathway for performance optimization of nickel-based alloys.