การพัฒนาแบบจำลองทางคณิตศาสตร์สำหรับการคาดการณ์ความเข้มข้นฝุ่นละอองภายในอาคาร
In this study, wind speed, wind direction, air exchange rate (AER) and indoor and outdoor concentrations were measured and published literatures were included to developed indoor particulate matter prediction model. The result found that wind speed, wind direction, number of windows, window directio...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | |
| التنسيق: | Theses and Dissertations |
| اللغة: | Thai |
| منشور في: |
จุฬาลงกรณ์มหาวิทยาลัย
2005
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://digiverse.chula.ac.th/Info/item/dc:57547 |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
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| المؤسسة: | Chulalongkorn University |
| اللغة: | Thai |
| الملخص: | In this study, wind speed, wind direction, air exchange rate (AER) and indoor and outdoor concentrations were measured and published literatures were included to developed indoor particulate matter prediction model. The result found that wind speed, wind direction, number of windows, window direction and screen on window effected on AER. From these factor,prediction ventilation equation was developed by multiple regression analysis. The result from Factor of Two analysis showed that the equation can predict AER at 62.30% and was well used when open window one side of wall or two side but not opposite side. Indoor-Outdoor ratio (I/O) of TSP PM10 and PM2.5 were 3.32, 2.26 and 1.35 respectively. PM10 concentration model was developed from box model and prediction ventilation equation. This model predicted well when using measurement PM10 and AER (94.83%). The model performed less well when using measurement PM10 and prediction AER (91.38%), prediction PM10 (I/O) and measurement AER (31.04%) and prediction PM and AER (31.04%). The result suggest that the particle penetration from indoor to outdoor and I/O in many place should be studied to increase the efficiency of model. |
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