Thermal Bridge Modeling and a Dynamic Analysis Method Using the Analogy of a Steady-State Thermal Bridge Analysis and System Identification Process for Building Energy Simulation: Methodology and Validation
It is challenging to apply heat flow through a thermal bridge, which requires the analysis of 2D or 3D heat transfer to building energy simulation (BES). Research on the dynamic analysis of thermal bridges has been underway for many years, but their utilization remains low in BESs. This paper propos...
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MDPI AG
2020-08-01
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Series: | Energies |
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Online Access: | https://www.mdpi.com/1996-1073/13/17/4422 |
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author | Heegang Kim Myoungsouk Yeo |
author_facet | Heegang Kim Myoungsouk Yeo |
author_sort | Heegang Kim |
collection | DOAJ |
description | It is challenging to apply heat flow through a thermal bridge, which requires the analysis of 2D or 3D heat transfer to building energy simulation (BES). Research on the dynamic analysis of thermal bridges has been underway for many years, but their utilization remains low in BESs. This paper proposes a thermal bridge modeling and a dynamic analysis method that can be easily applied to BESs. The main idea begins with an analogy of the steady-state analysis of thermal bridges. As with steady-state analysis, the proposed method first divides the thermal bridge into a clear wall, where the heat flow is uniform, and the sections that are not the clear wall (the thermal bridge part). For the clear wall part, the method used in existing BESs is applied and analyzed. The thermal bridge part (TB part) is modeled with the linear time-invariant system (LTI system) and the system identification process is performed to find the transfer function. Then, the heat flow is obtained via a linear combination of the two parts. This method is validated by comparing the step, sinusoidal and annual outdoor temperature response of the finite differential method (FDM) simulation. When the thermal bridge was modeled as a third-order model, the root mean square error (RMSE) of annual heat flow with the FDM solution of heat flow through the entire wall was about 0.1 W. |
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id | doaj.art-4c8f9ae128434e23a6c99b65124370d9 |
institution | Directory Open Access Journal |
issn | 1996-1073 |
language | English |
last_indexed | 2024-03-10T16:46:48Z |
publishDate | 2020-08-01 |
publisher | MDPI AG |
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series | Energies |
spelling | doaj.art-4c8f9ae128434e23a6c99b65124370d92023-11-20T11:31:47ZengMDPI AGEnergies1996-10732020-08-011317442210.3390/en13174422Thermal Bridge Modeling and a Dynamic Analysis Method Using the Analogy of a Steady-State Thermal Bridge Analysis and System Identification Process for Building Energy Simulation: Methodology and ValidationHeegang Kim0Myoungsouk Yeo1Department of Architecture and Architectural Engineering, Seoul National University, Seoul 08826, KoreaDepartment of Architecture and Architectural Engineering, Seoul National University, Seoul 08826, KoreaIt is challenging to apply heat flow through a thermal bridge, which requires the analysis of 2D or 3D heat transfer to building energy simulation (BES). Research on the dynamic analysis of thermal bridges has been underway for many years, but their utilization remains low in BESs. This paper proposes a thermal bridge modeling and a dynamic analysis method that can be easily applied to BESs. The main idea begins with an analogy of the steady-state analysis of thermal bridges. As with steady-state analysis, the proposed method first divides the thermal bridge into a clear wall, where the heat flow is uniform, and the sections that are not the clear wall (the thermal bridge part). For the clear wall part, the method used in existing BESs is applied and analyzed. The thermal bridge part (TB part) is modeled with the linear time-invariant system (LTI system) and the system identification process is performed to find the transfer function. Then, the heat flow is obtained via a linear combination of the two parts. This method is validated by comparing the step, sinusoidal and annual outdoor temperature response of the finite differential method (FDM) simulation. When the thermal bridge was modeled as a third-order model, the root mean square error (RMSE) of annual heat flow with the FDM solution of heat flow through the entire wall was about 0.1 W.https://www.mdpi.com/1996-1073/13/17/4422thermal bridgemodeling and dynamic analysissystem identification |
spellingShingle | Heegang Kim Myoungsouk Yeo Thermal Bridge Modeling and a Dynamic Analysis Method Using the Analogy of a Steady-State Thermal Bridge Analysis and System Identification Process for Building Energy Simulation: Methodology and Validation Energies thermal bridge modeling and dynamic analysis system identification |
title | Thermal Bridge Modeling and a Dynamic Analysis Method Using the Analogy of a Steady-State Thermal Bridge Analysis and System Identification Process for Building Energy Simulation: Methodology and Validation |
title_full | Thermal Bridge Modeling and a Dynamic Analysis Method Using the Analogy of a Steady-State Thermal Bridge Analysis and System Identification Process for Building Energy Simulation: Methodology and Validation |
title_fullStr | Thermal Bridge Modeling and a Dynamic Analysis Method Using the Analogy of a Steady-State Thermal Bridge Analysis and System Identification Process for Building Energy Simulation: Methodology and Validation |
title_full_unstemmed | Thermal Bridge Modeling and a Dynamic Analysis Method Using the Analogy of a Steady-State Thermal Bridge Analysis and System Identification Process for Building Energy Simulation: Methodology and Validation |
title_short | Thermal Bridge Modeling and a Dynamic Analysis Method Using the Analogy of a Steady-State Thermal Bridge Analysis and System Identification Process for Building Energy Simulation: Methodology and Validation |
title_sort | thermal bridge modeling and a dynamic analysis method using the analogy of a steady state thermal bridge analysis and system identification process for building energy simulation methodology and validation |
topic | thermal bridge modeling and dynamic analysis system identification |
url | https://www.mdpi.com/1996-1073/13/17/4422 |
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