Quantum dense coding over Bloch channels

Dynamics of coded information over Bloch channels is investigated for different values of the channel's parameters. We show that, the suppressing of the travelling coded information over Bloch channel can be increased by decreasing the equilibrium absolute value of information carrier and consequently decreasing the distilled information by eavesdropper. The amount of decoded information can be improved by increasing the equilibrium values of the two qubits and decreasing the ratio between longitudinal and transverse relaxation times. The robustness of coded information in maximum and partial entangled states is discussed. It is shown that the maximum entangled states are more robust than the partial entangled state over this type of channels

Thermal modeling of cylindrical LiFePO4 batteries

Thermal management of Li-ion batteries is important because of the high energy content and the risk of rapid temperature development in the high current range. Reliable and safe operation of these batteries is seriously endangered by high temperatures. It is important to have a simple but accurate model to evaluate the thermal behavior of batteries under a variety of operating conditions and be able to predict the internal temperature as well. To achieve this goal, a radial-axial model is developed to investigate the evolution of the temperature distribution in cylindrical Li-ion cells. Experimental data on LiFePO4 cylindrical Li-ion batteries are used to determine the overpotentials and to estimate the State-of-Charge-dependent entropies from the previously developed adaptive thermal model [1]. The heat evolution is assumed to be uniform inside the battery. Heat exchange from the battery surfaces with the ambient is non-uniform, i.e. depends on the temperature of a particular point at the surface of the cell. Furthermore, the model was adapted for implementation in battery management systems. It is shown that the model can accurately predict the temperature distribution inside the cell in a wide range of operating conditions. Good agreement with the measured temperature development has been achieved. Decreasing the heat conductivity coefficient during cell manufacturing and increasing the heat transfer coefficient during battery operation suppresses the temperature evolution. This modified model can be used for the scale-up of large size batteries and battery packs

DePAint: A Decentralized Safe Multi-Agent Reinforcement Learning Algorithm considering Peak and Average Constraints

The field of safe multi-agent reinforcement learning, despite its potential applications in various domains such as drone delivery and vehicle automation, remains relatively unexplored. Training agents to learn optimal policies that maximize rewards while considering specific constraints can be challenging, particularly in scenarios where having a central controller to coordinate the agents during the training process is not feasible. In this paper, we address the problem of multi-agent policy optimization in a decentralized setting, where agents communicate with their neighbors to maximize the sum of their cumulative rewards while also satisfying each agent's safety constraints. We consider both peak and average constraints. In this scenario, there is no central controller coordinating the agents and both the rewards and constraints are only known to each agent locally/privately. We formulate the problem as a decentralized constrained multi-agent Markov Decision Problem and propose a momentum-based decentralized policy gradient method, DePAint, to solve it. To the best of our knowledge, this is the first privacy-preserving fully decentralized multi-agent reinforcement learning algorithm that considers both peak and average constraints. We also provide theoretical analysis and empirical evaluation of our algorithm in various scenarios and compare its performance to centralized algorithms that consider similar constraints

Understanding Hydrogen Adsorption in MIL-47-M (M = V and Fe) through Density Functional Theory

The present paper aims to investigate the role of open metal site metal-organic frameworks (MOFs) on hydrogen adsorptivity using periodic boundary condition (PBC) density functional theory (DFT). Hence, MIL-47-M (M = V and Fe) were selected and one hydrogen molecule adsorptivity was calculated in different orientations on them. Four different chemical sites were identified in every cluster section of these MOFs, and molecular hydrogen adsorption was studied in these sites. In these MOFs, V has fewer electrons than Fe in its valence layer. Results demonstrated that when dihedral angle of M-O-H-H is 0, the binding energy of hydrogen adsorption is higher than that in other orientations in both MILs (-26.16 and -19

Drag Reduction And Heating

Paper presented at 2018 Canadian Society of Mechanical Engineers International Congress, 27-30 May 2018.An external force is required to maintain the relative movement of horizontal plates. It is shown that this force is reduced when the plates are subject to a spatially distributed heating. The largest reduction occurs for heating wavelengths of the order of distance between the plates with its magnitude increasing proportionally to the second power of the relevant Rayleigh number. It is shown that a sufficiently strong heating eliminates the need for the driving force altogether. The effect is active only in small Reynolds number flows