AtmosphericModels
Installation
Download Julia 1.6 or later, if you haven't already. You can add AtmosphericModels from Julia's package manager, by typing
using Pkg
pkg"add AtmosphericModels"
at the Julia prompt.
Exported types
AtmosphericModel
@enum ProfileLaw EXP=1 LOG=2 EXPLOG=3 FAST_EXP=4 FAST_LOG=5 FAST_EXPLOG=6
Exported functions
clear(s::AM)
calc_rho(s::AM, height)
calc_wind_factor(am::AM, height, profile_law::Int64=am.set.profile_law)
Wind profile
The EXPLOG profile law is the fitted linear combination of the exponentional and the log law.
Usage
using AtmosphericModels
am = AtmosphericModel()
const profile_law = Int(EXPLOG)
height = 100.0
wf = calc_wind_factor(am, height, profile_law)
The result is the factor with which the ground wind speed needs to be mulitplied to get the wind speed at the given height.
Plot a wind profile
using AtmosphericModels, Plots
am = AtmosphericModel()
heights = 6:1000
wf = [calc_wind_factor(am, height, Int(EXPLOG)) for height in heights]
plot(heights, wf, legend=false, xlabel="height [m]", ylabel="wind factor")
Benchmark
using AtmosphericModels, BenchmarkTools
am = AtmosphericModel()
@benchmark calc_wind_factor(am, height, Int(EXPLOG)) setup=(height=Float64((6.0+rand()*500.0)))
Profile law | time [ns] |
---|---|
EXP | 12 |
LOG | 16 |
EXPLOG | 33 |
FAST_EXP | 6.6 |
FAST_LOG | 6.6 |
FAST_EXPLOG | 6.6 |
The FAST versions are an approximations with an error of less than and are correct only for the default values of h_ref, z0 and alpha.
Air density
using AtmosphericModels, BenchmarkTools
am = AtmosphericModel()
@benchmark calc_rho(am, height) setup=(height=Float64((6.0+rand()*500.0)))
This gives 4.85 ns as result. Plot the air density:
heights = 6:1000
rhos = [calc_rho(am, height) for height in heights]
plot(heights, rhos, legend=false, xlabel="height [m]", ylabel="air density [kg/m³]")
Running the test scripts
First, add TestEnv to your global environment.
julia
using Pkg
Pkg.add("TestEnv")
exit()
Then you can run Julia using this project and run the tests:
julia --project
using TestEnv
TestEnv.activate()
include("test/bench.jl")
include("calc_approximations.jl")
include("runtests.jl")
Further reading
These models are described in detail in Dynamic Model of a Pumping Kite Power System.
See also
- Research Fechner
- The application KiteViewer
- the package KiteUtils
- the packages KiteModels and WinchModels and KitePodModels
- the packages KiteControllers and KiteViewers