Harvesting electrical energy from rain by SPMS - Special pipe and micro-generator system
This paper presents a methodology to find optimal height for pipe of special pipe and micro generator system - SPMS for harvesting electrical energy from potential energy of precipitations in form of rain. Theoretical calculations in order to obtain theoretical amount of energy for two-storey house in western slope of Vidzeme upland of Latvia are presented as well as calculations to obtain real amount of obtainable energy based on experimental data are presented. Virtual model of SPMS developed according experimental data in simulation program Lab VIEW 7.1 is described.
Harvesting raindrop energy: experimental study
At present, the energy autonomy of a microsystem is limited by the lifespan of the battery. Hence the development of the energy harvesting concept, whereby the energy needed to power the sensor is taken from the operating environment. However, there is no single solution suitable for all types of environment. In this paper, we look at a still unexploited source of energy: rain. Our system scavenges the vibration energy from a piezoelectric flexible structure impacted by a water drop. We present an experimental device that validates the aforementioned theoretical results.
Effect of superficial gas velocity on the particle temperature distribution in a fluidized bed with heat production
The heat transfer behavior of particles and gas in an olefin polymerization fluidized bed was numerically analyzed using an in-house developed 3-D computational fluid dynamics discrete element model (CFD-DEM). First the implementation of the model was verified by comparing simulation results with analytical results. A constant volumetric heat production rate was implemented in the particle energy equation to mimic the heat production due to the polymerization reaction. It was found that the probability density function (PDF) of the particle temperature becomes more homogeneous with increasing superficial gas velocity. Furthermore, instantaneous snapshots of the thermal driving force (the difference between the single particle temperature and bed-average gas temperature, Tp− ) for different heat production rates provide detailed insight in the particle temperature distribution inside the fluidized bed. The time- and bed-averaged particle convective heat transfer coefficient, which was calculated by Gunn׳s correlation, was found to be independent of the superficial gas velocity. This is explained by the fact that the relative velocity of gas and particles in the emulsion phase, where most of the particles and gas interact, is hardly influenced when increasing the gas superficial velocity. From the spatial distribution of Nusselt number, it becomes apparent that the high heat transfer regions are found in the wake of rising bubbles, whereas low heat transfer rates are found in the clouds of the bubbles.