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Proposed existing building diagnosis framework for energy efficiency improvement
Cost-effective strategies and quantitative evidence of impact are essential for remodeling. Therefore, the first step is to define the remodeling scheme, conduct case studies and collect data according to established methodologies. Problems are then identified and improvement plans proposed, while s...
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Published in: | Case studies in thermal engineering 2023-09, Vol.49, p.103232, Article 103232 |
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description | Cost-effective strategies and quantitative evidence of impact are essential for remodeling. Therefore, the first step is to define the remodeling scheme, conduct case studies and collect data according to established methodologies. Problems are then identified and improvement plans proposed, while simplifying the diagnostic process. In this study, a framework for retrofitting an existing building was presented and a case study focusing on the proposed methodology was carried out. Comparisons of the measured value with the design value of the insulation performance from the case study showed that the error rate was 79.2%–112.8% for walls and 20.4%–27.6% for windows. In addition, energy savings analysis through calibration simulation showed that the error between design and measured values was 33.7%. By accumulating the case study results, the cause of the difference in savings can be analysed and similar data can be inferred without field diagnosis. |
doi_str_mv | 10.1016/j.csite.2023.103232 |
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Therefore, the first step is to define the remodeling scheme, conduct case studies and collect data according to established methodologies. Problems are then identified and improvement plans proposed, while simplifying the diagnostic process. In this study, a framework for retrofitting an existing building was presented and a case study focusing on the proposed methodology was carried out. Comparisons of the measured value with the design value of the insulation performance from the case study showed that the error rate was 79.2%–112.8% for walls and 20.4%–27.6% for windows. In addition, energy savings analysis through calibration simulation showed that the error between design and measured values was 33.7%. 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subjects | 3D scanning Energy performance Existing building In-situ diagnostics Remodeling framework |
title | Proposed existing building diagnosis framework for energy efficiency improvement |
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