The paper presents a new approach for analyzing mold growth risk in buildings, based on a mixed simulation approach with consideration of uncertainties in relevant building parameters. The approach is capable to predict and explain unexpected mold growth occurrences that would typically not show up in standard deterministic simulation. This study simulates the local environmental conditions at material surfaces in buildings by using a mix of standard simulation tools. By introducing uncertainties in relevant input parameters, this approach generates a statistical distribution of time aggregated mold growth conditions at a number of "trouble spots"in a specific building case. This distribution is then translated into an overall mold risk indicator. In addition, our method identifies those parameters whose uncertainty range has a dominant effect on an increase in mold risk. By thus identifying the critical influence of building components, building operation and maintenance factors on the increase in risk, appropriate actions during the building design and procurement process can be set up to address these risks.

• Godfried Augenbroe(College of Architecture, Georgia Institute of Technology)
• Moon, Hyeun-Jun(Dankook University) Corresponding author