کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6697205 | 1428354 | 2018 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Optimal design of an indoor environment by the CFD-based adjoint method with area-constrained topology and cluster analysis
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Optimal design of an indoor environment by the CFD-based adjoint method with area-constrained topology and cluster analysis Optimal design of an indoor environment by the CFD-based adjoint method with area-constrained topology and cluster analysis](/preview/png/6697205.png)
چکیده انگلیسی
An indoor environment should be designed to provide occupants with a desirable level of thermal comfort and air quality. The optimal design of an indoor environment can be achieved by using the computational fluid dynamics (CFD)-based adjoint method to determine the size, locations, and shape of air supply inlets, and the air supply parameters (i.e., velocity, temperature, and angle). However, the optimal design may involve a large number of air supply inlets, which would be impractical to implement. This investigation developed an area-constrained topology and cluster analysis to consolidate multiple air supply inlets into a limited number and to determine their size and locations. The desired indoor environment can be maintained by further optimizing the air supply inlet shape and parameters. This investigation demonstrated the method's capability by applying it to a two-person office and a single-aisle, fully-occupied aircraft cabin. The optimal thermal comfort conditions around the occupants can be achieved with a limited number of air supply inlets at appropriate locations.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Building and Environment - Volume 138, 15 June 2018, Pages 171-180
Journal: Building and Environment - Volume 138, 15 June 2018, Pages 171-180
نویسندگان
Xingwang Zhao, Wei Liu, Dayi Lai, Qingyan Chen,