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Predictive method for fires in CLT and glulam structures – A priori modelling versus real scale compartment fire tests & an improved method
- Publication Year :
- 2021
-
Abstract
- Predictive modelling of the fire duration, fire temperatures, heat release rates and the structural capacity during building fires can be used to show compliance with performance-based building code requirements. The predictive models presented in this report focusses on the post flashover fire including the decay phase and extinction of flaming combustion for mass timber structures. A priori predictions of five recent compartment fire tests have been set against experimental results and compared. After the tests, the model has been updated, mostly for increased ease of use and increased accuracy for the decay phase. The model consists of a single-zone model which uses an energy equilibrium approach to obtain gas temperatures and surface temperatures of compartment boundaries. The energy contribution of charring mass timber is included using through-depth temperature calculations of the structure and experimental relationships to determine the combustion rate. The through-depth temperatures of mass timber members also serve to provide information for structural calculations using temperature dependent reduced material properties. However, the structural calculations are out of the scope of the current report. The radiation conditions (and total thermal exposure to walls ceilings and floors) predicted by the updated model were accurately described the of recent full-scale experiments within the variations between and within the tests. The comparisons with experiments showed that the total heat is, however, underestimated in some cases and surface temperatures were underestimated in the decay phase. Local effects caused by a radiative feedback loop between surfaces that show significant char oxidation, which occurred in a part of the test, is not included in the model.
Details
- Database :
- OAIster
- Notes :
- application/pdf, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1321866136
- Document Type :
- Electronic Resource