Evaluation of hygrothermal models for mold growth avoidance prediction

The  most  dominant  moisture-related  problem  in building materials is probably mold growth. It occurs as a result of relatively high moisture concentrations. Although recent research has established the causal, physical-biological relationship between moisture content, temperature, material type, and mold growth, we do not have an established set of causal relationships between certain building parameters (such as envelope characteristics) and the risk  of mold growth. This indicates a need for  a “performance indicator” (PI) that expresses the mold growth risk in existing buildings as the causal effect of certain building parameters. Such a performance indicator should express the relationships between mold growth occurrence and the physical descriptors of building components, HVAC systems and layout, maintenance and cleaning operation, and so  forth. This paper will deal with the first stage of research that focuses on the construction of such a PI. In this stage, we will deal with the accurate prediction of mold growth based on the availability of detailed information of the physical state (i.e., temperature and moisture content) of the materials in the building over time. Based on the accurate simulation of these states, these states can be aggregated into a PI value that is meaningful to the actual risk that mold growth will  indeed  occur  under  these circumstances.  A method for the latter will be presented.