Intelligent Roof Truss Digitalization of the building Process

Abstract

Sweden has a big market for different wood and timber products, but the raw material usage still can be improved and optimized to its full strength and potential. The modern building and construction industry uses wood according to its specified property values in the different strength classes. However, it is well known that wood has a considerable natural variability in its properties. In the grading process, the fifth percentile value, also called the characteristic value, is used to declare and specify the properties in the respective class of the structural wood member. This means that in a batch of wood members from a strength class, 95% of all the members have a strength value above the specified characteristic value. This aspect and uncertainty of the actual strength of an individual timber member is considered in the calibration of safety factors in the design standards, which aim at a certain target reliability. In this thesis the potential of using the knowledge of the updated and actual material properties of the individual wood members in the design and assembly process of structures in order to increase safety and enhance resource efficiency is studied. So far truss builders don't use the results and knowledge from the grading process they determined for each single piece of wood. Instead, they only use the characteristic values from the strength class. Instead, in the design and assembly process of structures, the members can be allocated in the structure according to their actual properties, which can be used to increase the safety. In places with more demands in terms of strength the wood members with the highest actual strength values can be used, and in places with lower demands wood with lower actual strength is used. In this thesis, this process is simulated in models in the software MATLAB and RFEM and the probability of failure is determined. The results show that the probability of failure can be reduced by using the updated knowledge of the individual property values of each wood member instead of the characteristic value only. The raw material saving potential for a more recourse efficient construction is evaluated.