Thermal Bridge Modeling According to Time-Varying Indoor Temperature for Dynamic Building Energy Simulation Using System Identification
It is not easy to dynamically analyze thermal bridges that require multi-dimensional analysis in building energy simulations, which are mostly one-dimensional platforms. To solve this problem, many studies have been conducted and, recently, a study was conducted to model a thermal bridge based on th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/12/12/2178 |
| _version_ | 1797461064632238080 |
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| author | Heegang Kim Jihye Kim Myoungsouk Yeo |
| author_facet | Heegang Kim Jihye Kim Myoungsouk Yeo |
| author_sort | Heegang Kim |
| collection | DOAJ |
| description | It is not easy to dynamically analyze thermal bridges that require multi-dimensional analysis in building energy simulations, which are mostly one-dimensional platforms. To solve this problem, many studies have been conducted and, recently, a study was conducted to model a thermal bridge based on the data obtained by approaching this in a similar way to steady-state analysis, showing high accuracy. This was an early-stage study, which is only applicable when the indoor temperature is constant. By extending the study, a thermal bridge model that can be applied even when the indoor temperature changes over time in building energy simulations is proposed and validated. Since the governing equation, the heat diffusion equation, is linear, the key idea is to create and apply two thermal bridge transfer function models by expressing the heat flow that enters the room as a linear combination of the transfer function for indoor temperature and the transfer function for outdoor temperature. For the proposed thermal bridge model, the NRMSE of the model itself showed a high accuracy of 0.001, and in the verification through annual simulation using the model, the NRMSE showed an accuracy of 0.1. |
| first_indexed | 2024-03-09T17:15:03Z |
| format | Article |
| id | doaj.art-2b544ab7b2ee492ca5052f939b1c9335 |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-09T17:15:03Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-2b544ab7b2ee492ca5052f939b1c93352023-11-24T13:43:09ZengMDPI AGBuildings2075-53092022-12-011212217810.3390/buildings12122178Thermal Bridge Modeling According to Time-Varying Indoor Temperature for Dynamic Building Energy Simulation Using System IdentificationHeegang Kim0Jihye Kim1Myoungsouk Yeo2Institute of Construction and Environmental Engineering, Seoul National University, Seoul 08826, Republic of KoreaDepartment of Architectural Engineering, College of Engineering, Kwangwoon University, Seoul 01897, Republic of KoreaInstitute of Construction and Environmental Engineering, Seoul National University, Seoul 08826, Republic of KoreaIt is not easy to dynamically analyze thermal bridges that require multi-dimensional analysis in building energy simulations, which are mostly one-dimensional platforms. To solve this problem, many studies have been conducted and, recently, a study was conducted to model a thermal bridge based on the data obtained by approaching this in a similar way to steady-state analysis, showing high accuracy. This was an early-stage study, which is only applicable when the indoor temperature is constant. By extending the study, a thermal bridge model that can be applied even when the indoor temperature changes over time in building energy simulations is proposed and validated. Since the governing equation, the heat diffusion equation, is linear, the key idea is to create and apply two thermal bridge transfer function models by expressing the heat flow that enters the room as a linear combination of the transfer function for indoor temperature and the transfer function for outdoor temperature. For the proposed thermal bridge model, the NRMSE of the model itself showed a high accuracy of 0.001, and in the verification through annual simulation using the model, the NRMSE showed an accuracy of 0.1.https://www.mdpi.com/2075-5309/12/12/2178thermal bridgedata-driven system modelingsystem identificationtime-varying indoor temperaturedynamic analysisbuilding energy simulation |
| spellingShingle | Heegang Kim Jihye Kim Myoungsouk Yeo Thermal Bridge Modeling According to Time-Varying Indoor Temperature for Dynamic Building Energy Simulation Using System Identification Buildings thermal bridge data-driven system modeling system identification time-varying indoor temperature dynamic analysis building energy simulation |
| title | Thermal Bridge Modeling According to Time-Varying Indoor Temperature for Dynamic Building Energy Simulation Using System Identification |
| title_full | Thermal Bridge Modeling According to Time-Varying Indoor Temperature for Dynamic Building Energy Simulation Using System Identification |
| title_fullStr | Thermal Bridge Modeling According to Time-Varying Indoor Temperature for Dynamic Building Energy Simulation Using System Identification |
| title_full_unstemmed | Thermal Bridge Modeling According to Time-Varying Indoor Temperature for Dynamic Building Energy Simulation Using System Identification |
| title_short | Thermal Bridge Modeling According to Time-Varying Indoor Temperature for Dynamic Building Energy Simulation Using System Identification |
| title_sort | thermal bridge modeling according to time varying indoor temperature for dynamic building energy simulation using system identification |
| topic | thermal bridge data-driven system modeling system identification time-varying indoor temperature dynamic analysis building energy simulation |
| url | https://www.mdpi.com/2075-5309/12/12/2178 |
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