chemdose_chlordecay_once function

Apply chemdose_chlordecayfunction within a data frame and output a data frame

This function allows chemdose_chlordecay to be added to a piped data frame. Its output is a data frame containing columns for free_chlorine or combined_chlorine (depending on chlorine type).

chemdose_chlordecay_once(
  df,
  input_water = "defined_water",
  cl2_dose = 0,
  time = 0,
  treatment = "raw",
  cl_type = "chlorine"
)

Arguments

• df: a data frame containing a water class column, which has already been computed using define_water_once. The df may include a column named for the applied chlorine dose (cl2), and a column for time in hours.
• input_water: name of the column of water class data to be used as the input for this function. Default is "defined_water".
• cl2_dose: Applied chlorine or chloramine dose (mg/L as cl2). Model results are valid for doses between 0.995 and 41.7 mg/L for raw water, and for doses between 1.11 and 24.7 mg/L for coagulated water.
• time: Reaction time (hours). Chlorine decay model results are valid for reaction times between 0.25 and 120 hours. Chloramine decay model does not have specified boundary conditions.
• treatment: Type of treatment applied to the water. Options include "raw" for no treatment (default), "coag" for water that has been coagulated or softened.
• cl_type: Type of chlorination applied, either "chlorine" (default) or "chloramine".

Returns

A data frame with updated chlorine residuals.

Details

The data input comes from a water class column, as initialized in define_water_chain.

If the input data frame has a chlorine dose column (cl2) or time column (time), the function will use those columns. Note: The function can only take cl2 and time inputs as EITHER a column or as function arguments, not both.

tidywater functions cannot be added after this function because they require a water class input.

For large datasets, using fn_once or fn_chain may take many minutes to run. These types of functions use the furrr package for the option to use parallel processing and speed things up. To initialize parallel processing, use plan(multisession) or plan(multicore) (depending on your operating system) prior to your piped code with the fn_once or fn_chain functions. Note, parallel processing is best used when your code block takes more than a minute to run, shorter run times will not benefit from parallel processing.

Examples

library(purrr)
library(furrr)
library(tidyr)
library(dplyr)

example_df <- water_df %>%
  mutate(br = 50) %>%
  define_water_chain() %>%
  balance_ions_chain() %>%
  chemdose_chlordecay_once(input_water = "balanced_water", cl2_dose = 4, time = 8)

example_df <- water_df %>%
  mutate(br = 50) %>%
  define_water_chain() %>%
  balance_ions_chain() %>%
  mutate(
    cl2_dose = seq(2, 24, 2),
    time = 30
  ) %>%
  chemdose_chlordecay_once(input_water = "balanced_water")

example_df <- water_df %>%
  mutate(br = 80) %>%
  define_water_chain() %>%
  balance_ions_chain() %>%
  mutate(time = 8) %>%
  chemdose_chlordecay_once(
    input_water = "balanced_water", cl2_dose = 6, treatment = "coag",
    cl_type = "chloramine"
  )

# Initialize parallel processing
plan(multisession, workers = 2) # Remove the workers argument to use all available compute
example_df <- water_df %>%
  mutate(br = 50) %>%
  define_water_chain() %>%
  balance_ions_chain() %>%
  chemdose_chlordecay_once(input_water = "balanced_water", cl2_dose = 4, time = 8)

# Optional: explicitly close multisession processing
plan(sequential)

See Also

chemdose_chlordecay