A Quantitative Analysis on Key Factors Affecting the Thermal Performance of the Hybrid Air-Based BIPV/T System
Air-based BIPV/T is of significant research interest in reducing energy load and improving indoor comfort. As many factors related to meteorology, geometry and operation contribute to the thermal performance of BIPV/T, especially for one kind of hybrid air-based BIPV/T (HAB-BIPV/T), quantifying the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/12/8/1135 |
| _version_ | 1797439083713134592 |
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| author | Juanli Guo Yongyun Jin Zhenyu Li Meiling Li |
| author_facet | Juanli Guo Yongyun Jin Zhenyu Li Meiling Li |
| author_sort | Juanli Guo |
| collection | DOAJ |
| description | Air-based BIPV/T is of significant research interest in reducing energy load and improving indoor comfort. As many factors related to meteorology, geometry and operation contribute to the thermal performance of BIPV/T, especially for one kind of hybrid air-based BIPV/T (HAB-BIPV/T), quantifying the effects of such uncertain parties is essential. In this paper, a numerical analysis was conducted regarding 13 parameters of one HAB-BIPV/T prototype. For each quantity of interest, the kernel density estimate was regarded as an approximation to the probability density function to assess uncertainty propagation. A sequential sensitivity analysis was used to quickly screen (by Morris) and exactly quantify (by Sobol’) the effects of significant variables. The surrogate model based on a back propagation neural network was employed to dramatically reduce the computational cost of Monte Carlo analysis. The results show that the uncertain inputs discussed can induce considerable fluctuations in the three quantities of interest. The most significant parameters on AUI include air inlet height, cavity thickness, air inlet velocity and number of air inlets. The outcomes of this study provide insights into the correlation between various factors and the thermal efficiency of the HAB-BIPV/T as a reference for similar design works. |
| first_indexed | 2024-03-09T11:47:38Z |
| format | Article |
| id | doaj.art-866d16c0ad13417f81285dcf5a43256c |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-09T11:47:38Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-866d16c0ad13417f81285dcf5a43256c2023-11-30T23:19:47ZengMDPI AGBuildings2075-53092022-08-01128113510.3390/buildings12081135A Quantitative Analysis on Key Factors Affecting the Thermal Performance of the Hybrid Air-Based BIPV/T SystemJuanli Guo0Yongyun Jin1Zhenyu Li2Meiling Li3School of Architecture, Tianjin University, Tianjin 300072, ChinaTianjin International Engineering Institute, Tianjin University, Tianjin 300072, ChinaSchool of Civil Engineering, Tianjin University, Tianjin 300072, ChinaSchool of Architecture, Tianjin University, Tianjin 300072, ChinaAir-based BIPV/T is of significant research interest in reducing energy load and improving indoor comfort. As many factors related to meteorology, geometry and operation contribute to the thermal performance of BIPV/T, especially for one kind of hybrid air-based BIPV/T (HAB-BIPV/T), quantifying the effects of such uncertain parties is essential. In this paper, a numerical analysis was conducted regarding 13 parameters of one HAB-BIPV/T prototype. For each quantity of interest, the kernel density estimate was regarded as an approximation to the probability density function to assess uncertainty propagation. A sequential sensitivity analysis was used to quickly screen (by Morris) and exactly quantify (by Sobol’) the effects of significant variables. The surrogate model based on a back propagation neural network was employed to dramatically reduce the computational cost of Monte Carlo analysis. The results show that the uncertain inputs discussed can induce considerable fluctuations in the three quantities of interest. The most significant parameters on AUI include air inlet height, cavity thickness, air inlet velocity and number of air inlets. The outcomes of this study provide insights into the correlation between various factors and the thermal efficiency of the HAB-BIPV/T as a reference for similar design works.https://www.mdpi.com/2075-5309/12/8/1135hybrid air-based BIPV/Tuncertainty quantificationsensitivity analysisuncertainty propagationair utilization index |
| spellingShingle | Juanli Guo Yongyun Jin Zhenyu Li Meiling Li A Quantitative Analysis on Key Factors Affecting the Thermal Performance of the Hybrid Air-Based BIPV/T System Buildings hybrid air-based BIPV/T uncertainty quantification sensitivity analysis uncertainty propagation air utilization index |
| title | A Quantitative Analysis on Key Factors Affecting the Thermal Performance of the Hybrid Air-Based BIPV/T System |
| title_full | A Quantitative Analysis on Key Factors Affecting the Thermal Performance of the Hybrid Air-Based BIPV/T System |
| title_fullStr | A Quantitative Analysis on Key Factors Affecting the Thermal Performance of the Hybrid Air-Based BIPV/T System |
| title_full_unstemmed | A Quantitative Analysis on Key Factors Affecting the Thermal Performance of the Hybrid Air-Based BIPV/T System |
| title_short | A Quantitative Analysis on Key Factors Affecting the Thermal Performance of the Hybrid Air-Based BIPV/T System |
| title_sort | quantitative analysis on key factors affecting the thermal performance of the hybrid air based bipv t system |
| topic | hybrid air-based BIPV/T uncertainty quantification sensitivity analysis uncertainty propagation air utilization index |
| url | https://www.mdpi.com/2075-5309/12/8/1135 |
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