Flat-histogram method comparison on the two-dimensional Ising model

Optimized Dynamic Collision Avoidance Algorithm for USV Path Planning

Ship collision avoidance is a complex process that is influenced by numerous factors. In this study, we propose a novel method called the Optimal Collision Avoidance Point (OCAP) for unmanned surface vehicles (USVs) to determine when to take appropriate actions to avoid collisions. The approach combines a model that accounts for the two degrees of freedom in USV dynamics with a velocity obstacle method for obstacle detection and avoidance. The method calculates the change in the USV's navigation state based on the critical condition of collision avoidance. First, the coordinates of the optimal collision avoidance point in the current ship encounter state are calculated based on the relative velocities and kinematic parameters of the USV and obstacles. Then, the increments of the vessel's linear velocity and heading angle that can reach the optimal collision avoidance point are set as a constraint for dynamic window sampling. Finally, the algorithm evaluates the probabilities of collision hazards for trajectories that satisfy the critical condition and uses the resulting collision avoidance probability value as a criterion for course assessment. The resulting collision avoidance algorithm is optimized for USV maneuverability and is capable of handling multiple moving obstacles in real-time. Experimental results show that the OCAP algorithm has higher and more robust path-finding efficiency than the other two algorithms when the dynamic obstacle density is higher.

Understanding the Solid-State Electrode-Electrolyte Interface of a Model System Using First-Principles Statistical Mechanics and Thin-Film X-ray Characterization

Intermixing of atomic species at the electrode-electrolyte boundaries can impact the properties of the interfaces in solid-state batteries. Herein, this work uses first-principles statistical mechanics along with experimental characterization to understand intermixing at the electrode-electrolyte interface. For the model presented in this work, lithium manganese oxide (LiMn₂O₄, LMO) and lithium lanthanum titanate (Li_3xLa_2/3-xTiO₃, LLTO) are employed as the cathode and electrolyte, respectively. The results of the computational work show that Ti-Mn intermixing at the interface is significant at synthesis temperatures. The experimental results in this work find that, at some critical temperatures between 600 and 700 °C for material preparation, the interface of LLTO-LMO becomes blurred. Calculations predict that the interface is unstable with regard to Ti-Mn intermixing starting at 0 K, suggesting that the critical temperature found in the experiment is related to kinetics. The work overall suggests that, in designing a solid-state battery, the fundamental reactions such as intermixing need to be considered.