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To address the need for the accurate parameterization of radiative absorption by gasses (for predicting atmospheric warming), Chou et al. developed a new k-distribution method. In this study, we compared the improved k-distribution method (hereinafter referred to as the NEW method) with the New Goddard radiation schemes (hereinafter referred to as the OLD method) for the WRF (the weather research and forecasting) model. The results of radiative flux calculations by the NEW and OLD methods of k-distribution using the New Goddard Radiation Scheme were compared with the results of the line-by-line (LBL) method, and the results showed that the radiative flux calculated by the NEW was accurate to within 1.00 Wm−2 with respect to the LBL, while the OLD showed large differences at altitudes above the upper troposphere and near the surface. Therefore, in this study, we selected clear-sky and cloudy-day conditions and compared the weather elements prediction results of WRF using the NEW and OLD methods. For the clear-sky days, the downward shortwave radiation at the surface and the temperature at 2 m above the surface (hereinafter referred to as T2) over land and ocean were reversed in sign due to the highly sensitive absorption coefficients of gasses. For cloudy days, the absorption effect by gasses harmonized with the scattering effect induced by cloud droplets; the differences in the shortwave and longwave radiations and radiative heating rate between the NEW and OLD methods were obvious. Thus, it was analyzed that the proposed NEW method could lead to significant improvements in forecasting weather elements. [ABSTRACT FROM AUTHOR]

In this paper, a quantitative analysis is performed focusing on the read-after-write latency (RWL) phenomenon in HfOX-based ferroelectric field-effect transistors with a metal-ferroelectric-insulator-semiconductor structure. RWL is scrutinized by modifying two variables: the pulse width (tp) for the "write 1" operation and the operating temperature (T); the response of the charge component is found to follow an emission mechanism. Additionally, we identified a notable change in charge behavior at a specific temperature (Tb), where capture and emission are in balance. Experimental investigations have demonstrated that the activation energy (EA) for these charge components is situated between 0.2 and 0.5 eV, and the Tb is ∼50 °C. By elucidating the relationship between T, tp, remnant polarization (Pr), and Tb, we offer insights into the importance of optimizing tp and Pr on the transient response of the balanced charge and the related RWL phenomenon. [ABSTRACT FROM AUTHOR]

In this paper, we propose a battery management algorithm to optimize the lifetimes of retired lithium batteries with heterogeneous states of health in a battery energy storage system under dynamic power demand. A battery energy storage system allows for the use of retired lithium batteries for applications such as backup power in homes, data centers, etc. In a battery energy storage system, a battery pack consists of several retired batteries connected in parallel or in series to fulfill the required power demand. Owing to the retired batteries' different capacity levels, i.e., states of health, a scheduling strategy is required to turn battery cells inside the battery pack on and off such that the secondary lifetimes of the retired batteries are extended. To establish the optimal scheduling policy, it is necessary to determine the correct states of each battery cell, including the state of charge and the state of health. To that end, the proposed algorithm first estimates the state of charge and state of health for all cells based on data measured using an extended Kalman filter. Then, a deep reinforcement learning scheduling algorithm is implemented to connect/disconnect the battery cells to/from the battery pack based on their states. Via simulation, we show that the proposed algorithm estimates the state of charge and state of health of each battery cell with low error and extends the lifetime of battery packs by 20.6%, compared to methods proposed in previous works. [ABSTRACT FROM AUTHOR]