Search

Phase change materials (PCM) with their high latent heat capacity have a great ability to store energy during their phase change process. The PCM are renowned for their applications in solar and thermal energy storage systems for the purpose of heating and cooling. However, one of the major drawbacks of PCM is their low thermal conductivity due to which their charging and discharging time reduces along with the reduction in energy storage capacity. This reduction in the energy storage capacity of PCM can be improved by producing organic-inorganic hybrid form-stable PCM, with the combination of two or more PCM together to increase their energy storage capacity. Nanoparticles that possess high thermal conductivity are also doped with these hybrid PCM (HPCM)to improve the effectiveness of thermal conductivity. This paper presents a short review on the applications of HPCM in energy storage and building application. Apart from this a short section of applications of composite PCM (CPCM) is also reviewed with discussions made at the end of each section. Results from the past literature depicted that the application of these HPCM and CPCM enhanced the energy storage capacity and thermal conductivity of the base PCM and selection of a proper hybrid material plays an essential role in their stability. It is presumed that this study will provide a sagacity, to the readers, to investigate their thermophysical properties and other essential applications. [ABSTRACT FROM AUTHOR]

Rotating machinery plays a significant role in industrial applications and covers a wide range of mechanical equipment. A vibration analysis using signal processing techniques is generally conducted for condition monitoring of rotary machinery and engineering structures in order to prevent failure, reduce maintenance cost and to enhance the reliability of the system. Empirical mode decomposition (EMD) is amongst the most substantial non-linear and non-stationary signal processing techniques and it has been widely utilized for fault detection in rotary machinery. This paper presents the EMD, time waveform and power spectrum density (PSD) analysis for localized spur gear fault detection. Initially, the test model was developed for the vibration analysis of single tooth breakage of spur gear at different RPMs and then specific fault was introduced in driven gear under different damage conditions. The data, recorded by means of a wireless tri-axial accelerometer, was then analyzed using EMD and PSD techniques and the results were plotted. The results depicted that EMD algorithms are found to be more functional than the ordinarily used PSD and time waveform techniques. [ABSTRACT FROM AUTHOR]