crm_opt2 | R Documentation |
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)
crm_opt2( d_y, flux_factor, avg_prob_coll, mth_prop_oper, avoidance_rate, lac_factor )
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. |
A numeric vector, the expected number of collisions per month based on model Option 2.
get_fhd_rotor()
, get_flux_factor()
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)
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