A comprehensive numerical study was conducted to investigate heat transfer enhancement during the melting process in a 2D square cavity through dispersion of nanoparticles.A paraffin-based nanofluid containing various...A comprehensive numerical study was conducted to investigate heat transfer enhancement during the melting process in a 2D square cavity through dispersion of nanoparticles.A paraffin-based nanofluid containing various volume fractions of Cu was applied.The governing equations were solved on a non-uniform mesh using a pressure-based finite volume method with an enthalpy porosity technique to trace the solid-liquid interface.The effects of nanoparticle dispersion in a pure fluid and of some significant parameters,namely nanoparticle volume fraction,cavity size and hot wall temperature,on the fluid flow,heat transfer features and melting time were studied.The results are presented in terms of temperature and velocity profiles,streamlines,isotherms,moving interface position,solid fraction and dimensionless heat flux.The suspended nanoparticles caused an increase in thermal conductivity of nano-enhanced phase change material(NEPCM)compared to conventional PCM,resulting in heat transfer enhancement and a higher melting rate.In addition,the nanofluid heat transfer rate increased and the melting time decreased as the volume fraction of nanoparticles increased.The higher temperature difference between the melting temperature and the hot wall temperature expedited the melting process of NEPCM.展开更多
Power swing is an undesirable variation in power flow. This can be caused by large disturbances in demand load, switching, disconnection or reclosing lines. This phenomenon may enter the zones of distance relays and c...Power swing is an undesirable variation in power flow. This can be caused by large disturbances in demand load, switching, disconnection or reclosing lines. This phenomenon may enter the zones of distance relays and cause relay malfunction leading to the disconnection of healthy lines and undermining network reliability. Accordingly, this paper presents a new power swing detection method based on the prediction of current signal with a GMDH (Group Method of Data Handling) artificial neural network. The main advantage of the proposed method over its counterparts is the immunity to noise effect in signals. In addition, the proposed method can detect stable, unstable, and multi-mode power swings and is capable of distinguishing them from the variety of permanent faults occurring simultaneously. The method is tested for different types of power swings and simultaneous faults using DIgSILENT and MATLAB, and compared with some latest power swing detection methods. The results demonstrate the superiority of the proposed method in terms of response time, the ability to detect power swings of different varieties, and the ability to detect different faults that may occur simultaneously with power swings.展开更多
文摘A comprehensive numerical study was conducted to investigate heat transfer enhancement during the melting process in a 2D square cavity through dispersion of nanoparticles.A paraffin-based nanofluid containing various volume fractions of Cu was applied.The governing equations were solved on a non-uniform mesh using a pressure-based finite volume method with an enthalpy porosity technique to trace the solid-liquid interface.The effects of nanoparticle dispersion in a pure fluid and of some significant parameters,namely nanoparticle volume fraction,cavity size and hot wall temperature,on the fluid flow,heat transfer features and melting time were studied.The results are presented in terms of temperature and velocity profiles,streamlines,isotherms,moving interface position,solid fraction and dimensionless heat flux.The suspended nanoparticles caused an increase in thermal conductivity of nano-enhanced phase change material(NEPCM)compared to conventional PCM,resulting in heat transfer enhancement and a higher melting rate.In addition,the nanofluid heat transfer rate increased and the melting time decreased as the volume fraction of nanoparticles increased.The higher temperature difference between the melting temperature and the hot wall temperature expedited the melting process of NEPCM.
文摘Power swing is an undesirable variation in power flow. This can be caused by large disturbances in demand load, switching, disconnection or reclosing lines. This phenomenon may enter the zones of distance relays and cause relay malfunction leading to the disconnection of healthy lines and undermining network reliability. Accordingly, this paper presents a new power swing detection method based on the prediction of current signal with a GMDH (Group Method of Data Handling) artificial neural network. The main advantage of the proposed method over its counterparts is the immunity to noise effect in signals. In addition, the proposed method can detect stable, unstable, and multi-mode power swings and is capable of distinguishing them from the variety of permanent faults occurring simultaneously. The method is tested for different types of power swings and simultaneous faults using DIgSILENT and MATLAB, and compared with some latest power swing detection methods. The results demonstrate the superiority of the proposed method in terms of response time, the ability to detect power swings of different varieties, and the ability to detect different faults that may occur simultaneously with power swings.