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Study On The Energy-saving Of Air- Conditioning & Ventilation In Subway

Posted on:2005-03-05Degree:MasterType:Thesis
Country:ChinaCandidate:D X YangFull Text:PDF
GTID:2132360125462964Subject:Heating, Gas Supply, Ventilation and Air Conditioning Engineering
Abstract/Summary:PDF Full Text Request
With the rapid development of Chinese economy and the expansion of city population, the traffic is more and more crowded. As a result, subway is becoming more and more important. Subway is a modern traffic system with large transportation and high speed. All of these characteristics make it produce a lot of heat in the subway, affects the subway environment directly. If we cannot improve subway ventilation effectively, the temperature in the subway will ascend to the degree that passengers are not able to tolerant. It is important to establish a better subway ventilation system that can not only provide safe and comfortable environment for passengers, cut down the energy consummation, but also reduce initial investment and running cost of subway construct system.With the reference of the actual situation of the No.1 line of Tianjin subway, this article introduces the factors which affect the environment's control of subway such as train movement, passenger number, light, working way of ventilation and air conditioning etc. With the help of Neural Network, this article put forward a new way to realize frequency conversion control in term of heat load in different status. Based on satisfying load need, we receive a required air flux and then alter the fan transducer's frequency to realize a soft Subway environment control. By comparing and analyzing CFD's simulated data and experimental data, this article also tests the relatively high performance of a new fan. By adopting intelligent control and organizing ventilation and air conditioning operation mode effectively, we can control temperature rise in a much better way. The energy saving and environment protection effect is also very obvious.
Keywords/Search Tags:Subway environment control, Neural Network, CFD, Air conditioning & ventilation mode, Frequency conversion control
PDF Full Text Request
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