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A comprehensive framework to select climate data for hygrothermal simulations : application on solid masonry walls in Brussels
- Source :
- Central European Symposium on Building Physics, 5th, Proceedings
- Publication Year :
- 2022
-
Abstract
- Moisture is a major agent of material degradation in building facades. The long-term degradation risks of building components are often evaluated by means of hygrothermal simulations for both new constructions as well as renovation. Due to the high computation load of these simulations, a Moisture Reference Year (MRY) (i.e. one year representing the moisture stress on the façade) is often used instead of simulating the long-term climate itself. In the past, a number of methods were developed to select MRYs, but they do not perform equally well for different wall types, materials, damage mechanisms etc. Today, a guideline to select an MRY method that is suitable for a specific study does not exist. Therefore, we developed a framework to select proper climate data for hygrothermal simulations. This paper presents the 5 levels of the framework, and its application on solid masonry walls in Brussels. The 5 levels account for the available resources, but result in a different level of detail. The optimal approach, yet computationally expensive, remains to simulate the long-term climate. Second best, an MRY is selected from one long-term simulation of a reference case, and that MRY is used in the remaining simulations. On the other hand, the ‘one-fits-all’ MRY needs the lowest computational requirements, but it is uncertain whether the ‘one-fits-all’ MRY actually represents the long-term moisture stress on the building. To conclude, the framework was successfully tested on solid masonry walls with and without interior insulation in Brussels.
- Subjects :
- Technology and Engineering
Arts and Architecture
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Central European Symposium on Building Physics, 5th, Proceedings
- Accession number :
- edsair.od.......330..59e73c32fd65c852a0316dc90502e788