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Wrapper function to run CRM calculations under option 1:

  • Basic model, i.e. flights across collision risk height are uniformly distributed.

  • Proportion at collision risk height derived from site survey.

Usage

crm_opt1(
  flux_factor,
  prop_crh_surv,
  avg_prob_coll,
  mth_prop_oper,
  avoidance_rate,
  lac_factor
)

Arguments

flux_factor

a vector containing the flux factor for each month

prop_crh_surv

The proportion of flights at collision risk height derived from site survey (\(Q_2R\)). Only required for model Option 1.

avg_prob_coll

A numeric value, the average probability of collision for a single bird transit through a rotor, assuming no avoidance action (\(p_{average}\)).

mth_prop_oper

A numeric vector, the proportion of time during which turbines are operational per month.

avoidance_rate

A numeric value within the interval \([0, 1]\). The avoidance rate, expressing the probability that a bird flying on a collision course with a turbine will take evading action to avoid collision.

lac_factor

A numerical value, the large array correction factor. Defaults to 1, meaning large array correction is not applicable.

Value

A numeric vector, the expected number of collisions per month based on model option 1

See also

get_flux_factor() for calculating the flux factor

Examples


 flux_fct <- get_flux_factor(
      n_turbines = 100,
      rotor_radius = 120,
      flight_speed = 13.1,
      bird_dens = c(1.19,0.85,1.05,1.45,1.41,1.45,1.12,1.45,0.93,0.902,1.06,1.23),
      daynight_hrs = Day_Length(52),
      noct_activity = 0.5
      )

turb_oper <- data.frame(
   month = month.abb,
   prop_oper = runif(12,0.5,0.8)
   )
turb_oper_month <- turb_oper$prop_oper

crm_opt1(
 flux_factor = flux_fct,
 prop_crh_surv = 0.13,
 avg_prob_coll = 0.1494609,
 mth_prop_oper = turb_oper_month,
 avoidance_rate = 0.989,
 lac_factor = 0.9998287)
#>  [1]  78.86228  40.14027  74.74202  81.46317  97.97719  85.37349  78.57620
#>  [8] 111.10758  61.99363  56.93208  66.58078  85.62335