Radiation Safety

Provides functions for radiation safety, also known as "radiation protection" and "radiological control". The science of radiation protection is called "health physics" and its engineering functions are called "radiological engineering". Functions in this package cover many of the computations needed by radiation safety professionals. Examples include: obtaining updated calibration and source check values for radiation monitors to account for radioactive decay in a reference source, simulating instrument readings to better understand measurement uncertainty, correcting instrument readings for geometry and ambient atmospheric conditions. Many of these functions are described in Johnson and Kirby (2011, ISBN-13: 978-1609134198). Utilities are also included for developing inputs and processing outputs with radiation transport codes, such as MCNP, a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron, or coupled neutron/photon/electron transport (Werner et. al. (2018) ).

The goal of radsafer is to provide functions that are useful for radiation safety professionals.

Installation

You can install the released version of radsafer from CRAN with:

install.packages("radsafer")

Or install the development version from GitHub:

# install.packages("devtools")
devtools::install_github("markhogue/radsafer")

Oveview

To start using the installed package:

library(radsafer)

radsafer families of functions

• Related functions are identified as members of families:
  • rad measurements
  • mcnp tools
  • decay corrections
  • radionuclides

Decay Correction Functions

Radsafer includes several functions to manage radioactive decay corrections:

dk_cf provides a correction factor. Revise a calibration or source check value to today’s date (the default) or a date and time of your choosing.

dk_cf(half_life = 5.27, date1 = "2010-12-01", date2 = "2018-12-01", time_unit = "y")
#> [1] 0.3491632

Use this function to correct for the value needed today. Say, a disk source originally had a target count rate of 3000 cpm:

3000 * dk_cf(half_life = 5.27, date1 = "2010-12-01", date2 = "2018-12-01", time_unit = "y")
#> [1] 1047.49

Other decay functions answer the following questions: * What is the decayed activity? dk_activity, Given a percentage reduction in activity, how many half-lives have passed.dk_pct_to_num_half_life

• How long will it take to reach the target radioactivity? dk_time

• Given the radioactivity at one time, what was the radioactivity at an earlier time? dk_reverse

• Given two data points, estimate the half-life: half_life_2pt

rad measurements functions

air_dens_cf Correct vented ion chamber readings based on difference in air pressure (readings in degrees Celsius and mm Hg):

air_dens_cf(T.actual = 30, P.actual = 760, T.ref = 20, P.ref = 760)
#> [1] 1.034112

Let’s try it out combined with the instrument reading:

rdg <- 100
(rdg_corrected <- rdg * air_dens_cf(T.actual = 30, P.actual = 760, T.ref = 20, P.ref = 760))
#> [1] 103.4112

neutron_geom_cf

Correct for geometry when reading a close neutron source. Example: neutron rem detector with a radius of 11 cm and source near surface:

neutron_geom_cf(11.1, 11)
#> [1] 0.7236467

disk_to_disk_solid_angle

Correct for a mismatch between the source calibration of a counting system and the item being measured. A significant factor in the counting efficiency is the solid angle from the source to the detector. You can also check for the impact of an item not being centered with the detector.

Example: You are counting an air sample with an active collection diameter of 45 mm, your detector has a radius of 25 mm and there is a gap between the two of 5 mm. (The function is based on radius, not diameter so be sure to divide the diameter by two.) The relative solid angle is:

(as_rel_solid_angle <- as.numeric(disk_to_disk_solid_angle(r.source = 45/2, gap = 20, r.detector = 12.5, runs = 1e4, plot.opt = "n")))
#>    mean_eff         SEM
#>  0.04806641 0.002132889
#> [1] 0.048066408 0.002132889

An optional plot is available in 2D or 3D:

(as_rel_solid_angle <- as.numeric(disk_to_disk_solid_angle(r.source = 45/2, gap = 20, r.detector = 12.5, runs = 1e4, plot.opt = "3d")))

#>    mean_eff        SEM
#>  0.04965531 0.00217145
#> [1] 0.04965531 0.00217145

Continuing the example: the only calibration source you had available with the appropriate isotope has an active diameter of 20 mm. Is this a big deal? Let’s estimate the relative solid angle of the calibration, then take a ratio of the two.

(cal_rel_solid_angle <- disk_to_disk_solid_angle(r.source = 20, gap = 20, r.detector = 12.5, runs = 1e4, plot.opt = "n"))
#>    mean_eff         SEM
#>  0.05137294 0.002206029
#>     mean_eff         SEM
#> 1 0.05137294 0.002206029

Correct for the mismatch:

(cf <- cal_rel_solid_angle / as_rel_solid_angle)
#>   mean_eff      SEM
#> 1 1.034591 1.015924

This makes sense - the air sample has particles originating outside the source radius, so more of them will be lost, thus an adjustment is needed for the activity measurement.

scaler_sim

Scaler counts: obtain quick distributions for parameters of interest:

scaler_sim(true_bkg = 50, true_samp = 10, ct_time = 20, trials = 1e5)

rate_meter_sim

Rate meters: In the ratemeter simulation, readings are plotted once per second for a default time of 600 seconds. The meter starts with a reading of zero and builds up based on the time constant. Resolution uncertainty is established to express the uncertainty from reading an analog scale, including the instability of its readings. Many standard references identify the precision or resolution uncertainty of analog readings as half of the smallest increment. This should be considered the single coverage uncertainty for a very stable reading. When a reading is not very stable, evaluation of the reading fluctuation is evaluated in terms of numbers of scale increments covered by meter indication over a reasonable evaluation period. Example with default time constant:

rate_meter_sim(cpm_equilibrium = 270, meter_scale_increments = seq(100, 1000, 20))

To estimate time constant, use tau.estimate

Stay-time computation

Given a dose rate, dose allowed, and a safety margin (default = 20%), calculate stay time with: stay_time

stay_time(dose_rate = 120, dose_allowed = 100, margin =  20)
#> [1] "Time allowed is 40 minutes"
#> [1] 40

mcnp tools functions

If you create MCNP inputs, these functions may be helpful:

mcnp_si_sp_RD Obtain emission data from the RadData package and write to a file for use with the radiation transport code, MCNP.

mcnp_si_hist and mcnp_sp_hist

• Create an energy distribution from histogram data with: si_hist and sp_hist (Load the data into R first using copy and paste with scan or reading from an external table with, for example, read.table.)

mcnp_matrix_rotations

• Determine the entries needed for MCNP coordinate transformation rotation

mcnp_cone_angle

• Quickly obtain the cone angle entry

mcnp_plot_out_spec

For MCNP outputs, plot the results of a tally with energy bins. Either first save your data to a text file, or copy and paste it using mcnp_scan2spec.df. Then plot it using your favorite method, or do a quick plot with mcnp_plot_out_spec:

mcnp_plot_out_spec(photons_cs137_hist, 'example Cs-137 well irradiator')

radionuclides

Search by alpha, beta, photon or use the general screen option.

search_phot_by_E allows screening based on energy, half-life, and minimum probability. Also available are search_alpha_by_E, search_beta_by_E, and bin_screen_phot. bin_screen_phot allows limiting searhes to radionuclides with emissions in an energy bin of interest with additional filters for not having photons in other specified energy bins. Results for all these search functions may be plotted with RN_plt.

Here’s a search for photon energy between 0.99 and 1.01 MeV, half-life between 13 and 15 minutes, and probability at least 1e-4

search_results <- search_phot_by_E(0.99, 1.01, 13 * 60, 15 * 60, 1e-4)

RN_plt(spec_0.1_0.3)

The RN_index_screen function helps find a radionuclide of interest based on decay mode, half-life, and total emission energy.

In this example, we search for radionuclides decaying by spontaneous fission with half-lives between 6 months and 2 years.

RNs_selected <- RN_index_screen(dk_mode = "SF", min_half_life_seconds = 0.5 * 3.153e7, max_half_life_seconds = 2 * 3.153e7)

Other radionuclides family functions provide specific activity and short tables of decay data.