77 resultados para self-energy


Relevância:

20.00% 20.00%

Publicador:

Resumo:

Cryocoolers have been progressively replacing the use of the stored cryogens in cryogenic chains used for detector cooling, thanks to their higher and higher reliability. However, the mechanical vibrations, the electromagnetic interferences and the temperature fluctuations inherent to their functioning could reduce the sensor’s sensitivity. In order to minimize this problem, compact thermal energy storage units (ESU) are studied, devices able to store thermal energy without significant temperature increase. These devices can be used as a temporary cold source making it possible to turn the cryocooler OFF providing a proper environment for the sensor. A heat switch is responsible for the thermal decoupling of the ESU from the cryocooler’s temperature that increases when turned OFF. In this work, several prototypes working around 40 K were designed, built and characterized. They consist in a low temperature cell that contains the liquid neon connected to an expansion volume at room temperature for gas storage during the liquid evaporation phase. To turn this system insensitive to the gravity direction, the liquid is retained in the low temperature cell by capillary effect in a porous material. Thanks to pressure regulation of the liquid neon bath, 900 J were stored at 40K. The higher latent heat of the liquid and the inexistence of triple point transitions at 40 K turn the pressure control during the evaporation a versatile and compact alternative to an ESU working at the triple point transitions. A quite compact second prototype ESU directly connected to the cryocooler cold finger was tested as a temperature stabilizer. This device was able to stabilize the cryocooler temperature ((≈ 40K ±1 K) despite sudden heat bursts corresponding to twice the cooling power of the cryocooler. This thesis describes the construction of these devices as well as the tests performed. It is also shown that the thermal model developed to predict the thermal behaviour of these devices, implemented as a software,describes quite well the experimental results. Solutions to improve these devices are also proposed.

Relevância:

20.00% 20.00%

Publicador:

Resumo:

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.