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Pool boiling in porous media has been applied in various thermal management systems by using latent heat and increasing the heat transfer area and thermal conduction path to improve the heat transfer performance. In mechanical equipment, vibration is an inevitable problem due to reasons such as engine operation and high-speed relative motion between transmission system components, which causes the system components to be affected by vibration forces or vibration accelerations. This study focuses on a review of published articles about the effects of mechanical vibration on the characteristics of boiling process in porous media by two aspects: heat transfer performance and bubble dynamics. Heat transfer coefficient (HTC) and critical heat flux are two main parameters used to measure the boiling heat transfer characteristics of porous media. For bubble dynamics investigations, properties such as migration, fragment, coalescence, departure diameter and frequency are the focus of research attention. Different mechanical vibration parameters, i.e., direction, frequency, and amplitude, will have different effects on the above characteristics. It is worth mentioning that the greatest influence occurs under resonance conditions, and this has been verified through experimental and simulation calculations. This review highlights the importance of considering mechanical vibrations in the design and optimization of porous media systems for efficient heat transfer applications. Further research is warranted to explore the detailed mechanisms and optimize the vibration parameters for enhanced heat transfer performance in thermal management systems using porous media.

The accelerator-driven sub-critical system is driven by external neutron sources, which are generated by the spallation reaction and maintain the stable operation of the sub-critical core, while the external neutron source increases the complexity of reactor neutron kinetic processes. This article focuses on simulation analysis of neutron space–time kinetics with a dynamic analysis code, which is developed based on the improved quasi-static approximation and Monte Carlo neutron transport method. The amplitude function and shape functions are solved to achieve the dynamics simulation process. Then, the transient responses of beam interruptions and reactivity insertions are calculated and analyzed for an experimental facility. To further verify the correctness and reliability of dynamic behavior, the simulation results are compared with experimental values, and the results show that the normalized neutron fluxes varying with time are in good agreement with the corresponding values. It can be concluded that the improved quasi-static coupled probability theory method can be used to solve the neutron space–time kinetic problem of the experimental facility, and the results are reliable.

The insulation performance of oil-immersed paper bushings is prone to deteriorate, primarily due to moisture intrusion and thermal aging. The frequency domain spectroscopy (FDS) method is commonly employed to assess the insulation condition of the bushing. However, identifying and extracting relaxation polarization information from the low-frequency region of the FDS curve can be challenging, and there is little research about the condition evaluation under the combined effects of aging states and moisture content. To address this issue, this article uses the Taylor formula mathematical model to extract characteristic parameters from the dielectric modulus curve of OIP bushings and uses the KNN algorithm to achieve the evaluation of aging and moisture status. Then, the effectiveness and accuracy of the proposed method are validated on three field OIP bushings. The results demonstrate that the evaluation accuracy of the proposed method exceeds 83%, which has significant advantages compared to other classification algorithms. The innovation of this article lies in extracting new feature parameters and combining them with intelligent classification algorithms to evaluate the moisture and aging state of the bushing.

Metal–organic frameworks (MOFs) have been widely used in various fields, including gas storage, separation, sensors, and catalysis, owing to their excellent performance. In this study, a zinc-based MOF [MIL-125(Zn)] was successfully synthesized using the solvothermal method, and Ag-doped ZnO (Ag/ZnO) was prepared by pyrolyzing Ag/MIL-125(Zn). The fabricated Ag/ZnO was used as a photocatalyst for rhodamine (RhB) degradation. Results showed that the MIL-125(Zn) derived from Ag/ZnO exhibits superior photocatalytic activity. It can degrade 99.4% of RhB under 20-min ultraviolet (UV) light irradiation, higher than those achieved using ZnO (73.2%) and MIL-125(ZnO) (19.6%). Furthermore, Ag/ZnO shows excellent stability. After four photocatalytic degradation cycles, the photocatalytic activity of Ag/ZnO reduces by only 3.6%. The excellent photocatalytic performance of Ag/ZnO may be attributed to the synergistic effect of Ag nanoparticles and ZnO. The possible photocatalytic mechanism of RhB degradation on the Ag/ZnO photocatalyst under UV light irradiation was proposed.

With the acceleration of energy reform, photovoltaic, energy storage, electric vehicles, and other new loads in low-voltage distribution networks have been rapidly developed. However, the distribution network with distributed power supply has some problems, such as imprecise power flow modeling and difficult coordination between various energy sources and loads, which bring challenges to the online optimization of the distribution network load curve. In this study, a multi-time scale online load optimal operation scheme of the distribution network is proposed by using the Bayesian online learning method. This scheme transforms the online power optimization of the distribution network into a Markov decision process. The output time of different energy sources is different, and the load with different user load characteristics is optimized. The scheme can track the state of the distribution network in real time and make the optimization scheme of multi-energy output online. Finally, an example is given to verify the effectiveness of the proposed method, which has theoretical significance for promoting the diversified development of low-voltage user-side load.

With the development of power grid technology, a large number of constant power loads (CPL) are introduced into the power grid system. The negative damping characteristic of CPL poses a great challenge to the stability of power grid under the condition of large signal disturbance. This paper focuses on the large signal stability and dynamic response characteristics of DC microgrid with CPL. The mixed potential function (MPF) method is adopted to model the large signal characterstic of load converter controlled by the traditional PI control strategy and the new virtual DC motor (VDM) control strategy. The large signal stability criteria and the asymptotic stability region of the DC microgrid system under the two control strategies are derived. The dynamic response characteristics of the DC microgrid are compared under three large signal operation conditions of the load step, load linear change and the load fault. The results show that VDM control strategy can effectively improve dynamic response characteristics of the DC microgrid system compared with those of PI control, and enhance the stability and anti-interference ability of the DC microgrid system.

The kinetic energy stored in the doubly-fed induction generators (DFIG)-based wind farm can be utilized to sustain the dynamic system frequency. However, difficulties arise in determining the control gain to effectively improve the frequency nadir and smoothly return to the maximum power point tracking (MPPT) operation. This paper addresses a two-phase short-term frequency response (STFR) scheme to boost the frequency nadir and minimize the second drop in the system frequency based on a piecewise control gain. To achieve the first goal, a constant control coefficient, which is determined according to the initial operating conditions of the DFIG-based wind farm, is employed until the frequency nadir produces. To achieve the second goal, the control coefficient, which changes with time, facilitates to smoothly return to the MPPT operation. The effectiveness of the proposed two-phase STFR scheme is verified under various wind power penetration levels, wind speeds, and disturbances. The results reveal that the frequency nadir is improved, and simultaneously, it smoothly returns to the MPPT operation and minimizes the second drop in the system frequency.