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Calculate Mould Growth Index (VTT model)

Source: R/calcMould_VTT.R
calcMould_VTT.Rd

This function calculates the mould growth index on wooden materials based on temperature, relative humidity, and other factors. It implements the mathematical model developed by Hukka and Viitanen, which predicts mould growth under varying environmental conditions.

Usage

calcMould_VTT(
  Temp,
  RH,
  M_prev = 0,
  sensitivity = "very",
  wood = 0,
  surface = 0
)

Arguments

Temp

Temperature (°Celsius)

RH

Relative Humidity (0-100%)

M_prev

The previous mould index value (default is 0).

sensitivity

The sensitivity level of the material to mould growth. Options are 'very', 'sensitive', 'medium', or 'resistant'. Default is 'very'.

wood

The wood species; 0 for pine and 1 for spruce. Default is 0.

surface

The surface quality; 0 for resawn kiln dried timber and 1 for timber dried under normal kiln drying process. Default is 0 (worst case).

Value

M Mould growth index

  • 0 = No mould growth

  • 1 = Small amounts of mould growth on surface visible under microscope

  • 2 = Several local mould growth colonies on surface visible under microscope

  • 3 = Visual findings of mould on surface <10% coverage or 50% coverage under microsocpe

  • 4 = Visual findings of mould on surface 10-50% coverage or >50% coverage under microscope

  • 5 = Plenty of growth on surface >50% visual coverage

  • 6 = Heavy and tight growth, coverage almost 100%

Details

Senstivity is related to the material surface, mould will grow on. Options in function avaiable are:

  • 'very' sensitive materials include pine and sapwood.

  • 'sensitive' materials include glued wooden boards, PUR with paper surface, spruce

  • 'medium' resistant materials include concrete, glass wool, polyester wool

  • 'resistant' materials include PUR polished surface

References

Hukka, A., Viitanen, H. A mathematical model of mould growth on wooden material. Wood Science and Technology 33, 475–485 (1999). https://doi.org/10.1007/s002260050131

Viitanen, Hannu, and Tuomo Ojanen. "Improved model to predict mold growth in building materials." Thermal Performance of the Exterior Envelopes of Whole Buildings X–Proceedings CD (2007): 2-7.

Examples

calcMould_VTT(Temp = 25, RH = 85)
#> [1] 0.01838254

calcMould_VTT(Temp = 18, RH = 70, M_prev = 2, sensitivity = "medium", wood = 1, surface = 1)
#> [1] 2.001801

head(mydata) |>
   dplyr::mutate(
      MouldIndex = calcMould_VTT(Temp, RH),
      MouldIndex_sensitve = calcMould_VTT(Temp, RH, sensitivity = "sensitive")
   )
#> # A tibble: 6 × 7
#>   Site   Sensor Date                 Temp    RH MouldIndex MouldIndex_sensitve
#>   <chr>  <chr>  <dttm>              <dbl> <dbl>      <dbl>               <dbl>
#> 1 London Room 1 2024-01-01 00:00:00  21.8  36.8          0                   0
#> 2 London Room 1 2024-01-01 00:15:00  21.8  36.7          0                   0
#> 3 London Room 1 2024-01-01 00:29:59  21.8  36.6          0                   0
#> 4 London Room 1 2024-01-01 00:44:59  21.7  36.6          0                   0
#> 5 London Room 1 2024-01-01 00:59:59  21.7  36.5          0                   0
#> 6 London Room 1 2024-01-01 01:14:59  21.7  36.2          0                   0