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军用危险品进箱基本条件研究

Study on stuffing environmental conditions of military dangerous products
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摘要 为了保证进藏军用危险品安全开展集装箱运输 ,在青藏线的格尔木和川藏线的成都地区对集装箱内部环境条件温、湿度进行了测试 ,并建立了数学模型 ,意在找出其内部环境条件变化规律 ,为军用危险品安全进箱提供理论依据和技术支持。 The present author has made the climate environmental experiment on the inner temperature, humidity of the containers and their influence on the surrounding air temperature, solar radiation and wind speed in Geermu and Chengdu areas with particular climatic and weather conditions. As is known, military dangerous products or materials, such as ammunition and dynamite, are particular with their demands for environmental conditions. When such products or materials are transported into Tibet, a great attention should be paid to the road conditions, the climatic environmental conditions on the container's inner temperature, humidity and the other affecting factors, including air temperature, solar radiation and wind speed not only in Tibet, but also in Geermu and Chengdu areas, the primary transferred depots on the line. To ensure the full safety of the containers in the transportation, the author has done a series of experiments and collected abundant first-hand data and information (up to 7 000 items in all) from our tests during the recent three years. Through meticulous analysis of the data collected, particularly on the difference between the container's internal temperature, the surrounding atmospheric temperature and the sun radiation, we have formulated and established a set of non-linear mathematical models by means of statistic analysis for predicating and forecasting the most hazardous temperature scope -70 ℃ inside the containers in the two areas. And consequently, an academic basis has been provided for military dangerous materials safely entering containers. The author has put forward, in turn, a few suggestions on attentive questions for containers transportation entering Tibet.
出处 《安全与环境学报》 CAS CSCD 2004年第2期43-46,共4页 Journal of Safety and Environment
关键词 安全工程 危险品 集装箱 环境条件 预测模型 safety engineering dangerous goods container environmental conditions model forecasting
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