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Number of collisions under model option 2

Source: R/crm_opt2.R
crm_opt2.Rd

Wrapper function to run CRM calculations under option 2, i.e.:

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

  • Proportion at collision risk height derived from a flight height distribution (\(Q'_2R\))

Usage

crm_opt2(
  d_y,
  flux_factor,
  avg_prob_coll,
  mth_prop_oper,
  avoidance_rate,
  lac_factor
)

Arguments

d_y

a vector with the proportion of bird flights at height bands within the rotor disc

flux_factor

a vector containing the flux factor for each month

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 2.

See also

get_fhd_rotor(), get_flux_factor()

Examples


avg_collision_risk <-
 get_avg_prob_collision(
   flight_speed = 13.1,
   body_lt = 0.85,
   wing_span = 1.01,
   prop_upwind = 0.5,
   flap_glide = 1,
   rotor_speed = 15,
   rotor_radius = 120,
   blade_width = 5,
   blade_pitch = 15,
   n_blades = 3,
   chord_prof = chord_prof_5MW
 )


 gen_fhd_dat <- Johnston_Flight_heights_SOSS %>%
      dplyr::filter(variable=="Gannet.est") %>%
      dplyr::select(height,prop)

 gen_fhd <- gen_fhd_dat$prop

 gen_fhd_at_rotor <-
    get_fhd_rotor(
      hub_height = 150,
      fhd = gen_fhd,
      rotor_radius = 120,
      tidal_offset = 2.5,
      yinc = 0.05)


 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_opt2(
    flux_factor = flux_fct,
    d_y = gen_fhd_at_rotor,
    avg_prob_coll = avg_collision_risk,
    mth_prop_oper = turb_oper_month,
    avoidance_rate = 0.989,
   lac_factor = 0.9998299)
#>  [1] 15.43130 15.57042 15.86670 20.69549 25.44495 26.24387 22.79381 22.49253
#>  [9] 14.88926 13.32071 16.94002 17.84437