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| Environmental Characteristics of Dry Heat and Dry Cold in Dunhuang Area |
| Received:May 18, 2020 Revised:June 27, 2020 |
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| DOI：10.7643/issn.1672-9242.2020.12.013 |
| KeyWord:Dunhuang dry heat time dry cooling time critical condition environmental characteristics environmental adaptability |
| Author | Institution |
| TANG Qi-huan |
Southwest Technology and Engineering Research Institute, Chongqing , China;National Observation & Research Station on Materials Corrosion in Atmospheric Environment in Jiangjin, Chongqing, Chongqing , China |
| ZHANG Xian-yong |
Southwest Technology and Engineering Research Institute, Chongqing , China |
| ZHANG Yan |
Southwest Technology and Engineering Research Institute, Chongqing , China |
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| Abstract: |
| The work aims to establish a characterization method for the characteristics of dry heat and dry cold environments in atmospheric environment, so as to quantitatively characterize the harshness of dry heat and dry cold in atmospheric environment, and to provide reference for the aging test and evaluation of polymer materials and products in this area. The combination of temperature and relative humidity was set as a critical value. The time of temperature above critical temperature and relative humidity below critical relative humidity was defined as dry-heat time; the time of temperature below critical temperature and relative humidity below critical relative humidity was defined as dry-cooling time. And the dry-heat and dry-cooling environment characteristics were characterized by dry-heat time, dry-cooling time as a percentage of total time in a given period. With 25 ℃ RH 40 % and 5 ℃ RH 40 % as the critical condition, the monthly and annual percentages of dry-heat time and dry-cooling time can counted to characterize the characteristics of dry-heat and dry-cooling in atmospheric environment. June and July of Dunhuang were dry-heat severe month, the monthly dry-heat time percentage was more than 40%, January and February were dry-cold severe months, and the monthly dry-cooling time percentage can exceed 70%. The critical temperature, critical relative humidity, statistical year, data interval time, etc. have great influence on the statistical results. |
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