Assessing Mold Risks in Buildings under Uncertainty

In many cases, microbial growth in buildings
involves local, situational, and sometimes
idiosyncratic aspects of a building during its
operation. These unexpected behaviors cannot be
captured by current deterministic performance
evaluation methods. Hence, a new probabilistic
performance indicator for mold growth risk is
developed by treating mold as a risk and a limit
state phenomenon.
This new approach requires a reliable aggregation
method to arrive at quantified mold growth risk and
the extension of standard simulation capacity to
account for additional mechanisms of the mold
phenomenon. It also implicates uncertainty in
building parameters, including natural variation of
hygrothermal properties in building materials,
deviation between as-designed values, and the
actual in-use values of the parameters.
This new approach is capable of explaining
unexpected and non-deterministic mold growth
occurrences. Moreover, it identifies the parameters
that have dominant effects on the increase in mold
risk.

Autorentext

Prof. Hyeun Jun Moon is currently teaching in the Department of Architectural Engineering at Dankook University in Korea. He received his Ph.D. in the College of Architecture at Georgia Institute of Technology. He served as a scientific committee member in the Building Simulation conferences since 2003.

Klappentext

In many cases, microbial growth in buildings involves local, situational, and sometimes idiosyncratic aspects of a building during its operation. These unexpected behaviors cannot be captured by current deterministic performance evaluation methods. Hence, a new probabilistic performance indicator for mold growth risk is developed by treating mold as a risk and a limit state phenomenon. This new approach requires a reliable aggregation method to arrive at quantified mold growth risk and the extension of standard simulation capacity to account for additional mechanisms of the mold phenomenon. It also implicates uncertainty in building parameters, including natural variation of hygrothermal properties in building materials, deviation between "as-designed" values, and the actual "in-use" values of the parameters. This new approach is capable of explaining unexpected and non-deterministic mold growth occurrences. Moreover, it identifies the parameters that have dominant effects on the increase in mold risk.