Current hygrothermal tools mainly execute deterministic
simulation due to the fact that each parameter uses a specific value.
Thus, the corresponding output will be a predictably determined
value or function. However, the simulation inputs in the real world,
e.g., occupants' activities [1] and [2], material properties [3] and [4],
and climatic data [5], will not always follow the way defined in the
simulation. Standardized material data in the building code cannot
sufficiently represent real on-site material property, due to the
influence caused by aging, temperature, and moisture content
variation [6]. Climatic data used in the simulation is either the
measured data of past years or synthetic data, which does not
represent what the climate will be in the future. There exist
considerable uncertainties in hygrothermal material properties,
depending on the structure of the material, the type of measurement,
measurement procedure, etc. [7e11]. The stochastic nature of
the inputs will lead to variations in the simulation outputs.
A simulation using deterministic inputs cannot adequately take
into account the variable conditions and unexpected scenarios
Current hygrothermal tools mainly execute deterministic
simulation due to the fact that each parameter uses a specific value.
Thus, the corresponding output will be a predictably determined
value or function. However, the simulation inputs in the real world,
e.g., occupants' activities [1] and [2], material properties [3] and [4],
and climatic data [5], will not always follow the way defined in the
simulation. Standardized material data in the building code cannot
sufficiently represent real on-site material property, due to the
influence caused by aging, temperature, and moisture content
variation [6]. Climatic data used in the simulation is either the
measured data of past years or synthetic data, which does not
represent what the climate will be in the future. There exist
considerable uncertainties in hygrothermal material properties,
depending on the structure of the material, the type of measurement,
measurement procedure, etc. [7e11]. The stochastic nature of
the inputs will lead to variations in the simulation outputs.
A simulation using deterministic inputs cannot adequately take
into account the variable conditions and unexpected scenarios
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