AT.D.RDD.Gy {libamtrack} | R Documentation |
Returns local dose as a function of distance r_m for a given radial dose distribution model
AT.D.RDD.Gy(r.m, E.MeV.u, particle.no, material.no, rdd.model, rdd.parameter, er.model, stopping.power.source.no)
r.m |
distance [m] (array of size n). |
E.MeV.u |
particle (ion) energy per nucleon [MeV/u] (single number, no
mixed fields) (see also |
particle.no |
particle code number (single number, no mixed fields)
(see also |
material.no |
material code number (single number, no mixed fields)
(see also |
rdd.model |
radial dose distribution model index (see also
|
rdd.parameter |
radial dose distribution model parameters (array of size 4). |
er.model |
electron range / track with model index (see also
|
stopping.power.source.no |
TODO (see also
|
D.RDD.Gy |
dose [Gy] (array of size n) |
status |
status |
View the C source code here: http://sourceforge.net/apps/trac/libamtrack/browser/trunk/src/AT_RDD.c#L485
# Compute dose in several distances of an 100 MeV/u neon ion in water # according to 'Site' parametrization AT.D.RDD.Gy( r.m = 10^(-9:-4), E.MeV.u = 100, particle.no = 10020, material.no = 1, rdd.model = 4, rdd.parameter = c(5e-8, 1e-10), er.model = 2, stopping.power.source.no = 2) # Compare the Geiss parametrization of RDD for protons and Carbon ions at # different energies: df <- expand.grid( E.MeV.u = 10^seq(0, 3, length.out = 4), # from 1 to 1000 MeV/u in 4 steps particle.no = c(1001,6012), # protons and carbons r.m = 10^seq(-9, -2, length.out = 100), # from 1 nm to 1 cm in 100 steps material.no = 2, # Aluminium Oxide rdd.model = 3, # Geiss parametrization rdd.parameter = 5e-8, # Fixed core size of 50 nm er.model = 4, # Geiss track width parametrization D.Gy = 0) # For later use ii <- df$particle.no == 1001 # Add particle names df$particle.name <- "Carbon-12" df$particle.name[ii] <- "Protons" for (i in 1:nrow(df)){ # Loop through particles/energies df$D.Gy[i] <- AT.D.RDD.Gy( r.m = df$r.m[i], E.MeV.u = df$E.MeV.u[i], particle.no = df$particle.no[i], material.no = df$material.no[i], rdd.model = df$rdd.model[i], rdd.parameter = df$rdd.parameter[i], er.model = df$er.model[i], stopping.power.source.no = 2)$D.RDD.Gy }