Robustness classification of materials, assemblies and buildings
- 4 July 2013
- journal article
- research article
- Published by SAGE Publications in Journal of Building Physics
- Vol. 37 (3), 213-245
- https://doi.org/10.1177/1744259113489809
Abstract
Reliable methods are needed for classifying the robustness of buildings and building materials for many reasons, including ensuring that constructions can withstand the climate conditions resulting from global warming, which might be more severe than was assumed in an existing building’s design. Evaluating the robustness of buildings is also important for reducing process-induced building defects. We describe and demonstrate a flexible framework for classifying the robustness of building materials, building assemblies, and whole buildings that incorporates climate and service life considerations.Keywords
This publication has 17 references indexed in Scilit:
- Accelerated climate ageing of building materials, components and structures in the laboratoryJournal of Materials Science, 2012
- Development of a model for radon concentration in indoor airScience of The Total Environment, 2012
- Accelerated climate aging of building materials and their characterization by Fourier transform infrared radiation analysisJournal of Building Physics, 2011
- Traditional, state-of-the-art and future thermal building insulation materials and solutions – Properties, requirements and possibilitiesEnergy and Buildings, 2011
- Hot box investigations and theoretical assessments of miscellaneous vacuum insulation panel configurations in building envelopesJournal of Building Physics, 2010
- The path to the high performance thermal building insulation materials and solutions of tomorrowJournal of Building Physics, 2010
- Implementation of radon barriers, model development and calculation of radon concentration in indoor airJournal of Building Physics, 2010
- Vacuum insulation panels for building applications: A review and beyondEnergy and Buildings, 2010
- Decay-influencing factors: A basis for service life prediction of wood and wood-based productsWood Material Science & Engineering, 2006
- Interpretation of criteria weights in multicriteria decision makingComputers & Industrial Engineering, 1999