Estimate Aerosol Particle Collection Through Sample Lines

Description

This package provides a method to estimate sampling efficiency of sampling systems drawing aerosol particles through tubing.

Details

Functions were developed consistent with the approach described in Hogue, Mark; Thompson, Martha; Farfan, Eduardo; Hadlock, Dennis, (2014), "Hand Calculations for Transport of Radioactive Aerosols through Sampling Systems" Health Phys 106, 5, S78-S87, <doi:10.1097/HP.0000000000000092>.

To learn how to use AeroSampleR, start with the vignette: 'browseVignettes(package = "AeroSampleR")'

bend efficiency

Description

In order to run this function, first produce a particle distribution with the 'particle_dist' function, then produce a parameter set with the 'set_params' function. Both of these results must be stored as per examples described in the help set with each.

Usage

bend_eff(df, params, method, bend_angle, bend_radius, elnum)

Arguments

Value

data frame containing original particle distribution with added data for this element

References

A. R. McFarland, H. Gong, A. Muyshondt, W. B. Wente, and N. K. Anand Environmental Science & Technology 1997 31 (12), 3371-3377 <doi:10.1021/es960975c>

Pusheng Zhang, Randy M. Roberts, André Bénard, Computational guidelines and an empirical model for particle deposition in curved pipes using an Eulerian-Lagrangian approach, Journal of Aerosol Science, Volume 53, 2012, Pages 1-20,ISSN 0021-8502, <doi:10.1016/j.jaerosci.2012.05.007>

David Y. H. Pui, Francisco Romay-Novas & Benjamin Y. H. Liu (1987) Experimental Study of Particle Deposition in Bends of Circular Cross Section, Aerosol Science and Technology, 7:3, 301-315, <doi:10.1080/02786828708959166>

Examples

df <- particle_dist() # set up particle distribution
params <- set_params_1("D_tube" = 2.54, "Q_lpm" = 100,
"T_C" = 25, "P_kPa" = 101.325) #example system parameters
df <- set_params_2(df, params) #particle size-dependent parameters
df <- probe_eff(df, params, orient = 'h') #probe orientation - horizontal
df <- bend_eff(df, params, method='Zhang', bend_angle=90,
bend_radius=0.1, elnum=3)
head(df)

Data from readme file for use in plot examples

Description

This data was created by running the readme script. It is needed for simple plot examples.

Usage

dat_for_plots

Format

A data.frame

D_p

particle diameter in micrometers

dens

probability density

dist

either log_norm or discrete

C_c

Cunningham slip correction factor

v_ts

particle terminal velocity

Re_p

Reynold's number for particle

Stk

Stokes' number for particle

eff_probe

aspiration efficiency for probe

eff_bend_2

transport efficiency for the second component, a bend

eff_tube_3

transport efficiency for the third component, a straight tube

Create a particle distribution

Description

Needed as a first step in estimating system efficiency. Make the data frame that will be used to estimate efficiency of variously sized aerosol particles' transport through the sampling system. To create your data, save this data to the global environment as shown in the examples.

Usage

particle_dist(
  AMAD = 5,
  log_norm_sd = 2.5,
  log_norm_min = 5e-04,
  log_norm_max = 100,
  discrete_vals = c(1, 5, 10)
)

Arguments

Details

All inputs are in micron AMAD, meaning: the aerodynamic diameter of a particle is the diameter of a standard density (1000 kg/m3) sphere that has the same gravitational settling velocity as the particle in question.

Value

a data frame containing a lognormally distributed set of particles and discrete particle sizes

Examples

df <- particle_dist() # default
df <- particle_dist(AMAD = 4.4,
                    log_norm_sd = 1.8)
head(df)

Probe efficiency

Description

In order to run this function, first produce a particle distribution with the 'particle_dist' function, then produce a parameter set with the 'set_params' function. Both of these results must be stored as per examples described in the help set with each.

Usage

probe_eff(df, params, orient = "u", method = "blunt pipe")

Arguments

Value

data frame containing original particle distribution with added data for this element

Examples

df <- particle_dist() # set up particle distribution
params <- set_params_1("D_tube" = 2.54, "Q_lpm" = 100,
"T_C" = 25, "P_kPa" = 101.325) #example system parameters
df <- set_params_2(df, params) #particle size-dependent parameters
df <- probe_eff(df, params, orient = 'u') #probe orientation - draws upward
head(df)

report on transport efficiency

Description

In order to run a report, first produce a model of each individual element. Start with producing a particle distribution with the 'particle_dist' function, then produce a parameter set with the 'set_params' function. Both of these results must be stored as per examples described in the help set with each. Next, add elements in the sample system until all are complete.

Usage

report_basic(df, params, dist)

Arguments

Value

report of system efficiency

Examples

df <- particle_dist() # set up particle distribution
params <- set_params_1("D_tube" = 2.54, "Q_lpm" = 100,
"T_C" = 25, "P_kPa" = 101.325) #example system parameters
df <- set_params_2(df, params) #particle size-dependent parameters
df <- probe_eff(df, params, orient = 'h') #probe orientation - horizontal
df <- bend_eff(df, params, method='Zhang', bend_angle=90,
bend_radius=0.1, elnum=3)
df <- tube_eff(df, params, L = 100,
angle_to_horiz = 90, elnum = 3)
report_basic(df, params, dist = 'discrete')

report on cumulative transport system efficiency (discrete particle sizes only)

Description

In order to run a report, first produce a model of each individual element. Start with producing a particle distribution with the 'particle_dist' function, then produce a parameter set with the 'set_params' function. Both of these results must be stored as per examples described in the help set with each. Next, add elements in the sample system until all are complete.

Usage

report_cum_plots(df, micron)

Arguments

Value

A plot of cumulative transport efficiencies is generated in a plot window

Examples

report_cum_plots(dat_for_plots, micron = 10)

report relative masses by particle of a log-normal distribution

Description

This function shows the entire table of results by particle diameter.

Usage

report_log_mass(df)

Arguments

Value

data frame containing mass-based particle fractions in ambient location and in distribution delivered through the system.

Examples

df <- particle_dist() # set up particle distribution
params <- set_params_1("D_tube" = 2.54, "Q_lpm" = 100,
"T_C" = 25, "P_kPa" = 101.325) #example system parameters
df <- set_params_2(df, params) #particle size-dependent parameters
df <- probe_eff(df, params, orient = 'h') #probe orientation - horizontal
df <- bend_eff(df, params, method='Zhang', bend_angle=90,
bend_radius=0.1, elnum=3)
df <- tube_eff(df, params, L = 100,
angle_to_horiz = 90, elnum = 3)
report_log_mass(df)

plots of individual on transport system elements

Description

In order to run a report, first produce a model of each individual element. Start with producing a particle distribution with the 'particle_dist' function, then produce a parameter set with the 'set_params' function. Both of these results must be stored as per examples described in the help set with each. Next, add elements in the sample system until all are complete.

Usage

report_plots(df, dist)

Arguments

Value

A plot of transport efficiencies is generated in a plot window

Examples

report_plots(dat_for_plots, dist = 'discrete')

Set parameters (not particle size specific)

Description

Make a set of parameters that will be used throughout this package. 'set_params_1' sets all single parameters. 'set_params_2' adds particle-size-dependent parameters to the particle distribution

Usage

set_params_1(D_tube_cm, Q_lpm, T_C = 20, P_kPa = 101.325)

Arguments

Details

All parameters are to be in MKS units, except as noted.

Value

a data frame with singular parameters

examples params <- set_params_1("D_tube" = 2.54, "Q_lpm" = 100, "T_C" = 25, "P_kPa" = 101.325) t(params)

Make a set of particle-size-dependent parameters

Description

This set of parameters will be used for evaluation of transport efficiency for particle-size-dependent parameters.

Usage

set_params_2(df, params)

Arguments

Details

No user-selected arguments are needed. Parameters are used in efficiency functions. For each particle diameter, an entry is made in the data frame for the Cunningham slip correction factor, the particle terminal velocity, the particle Reynold's number, and the Stokes factor.

'set_params_1' sets all single parameters. 'set_params_2' adds particle size-dependent parameters to the particle distribution

Value

a data frame starting with the submitted particle distribution with additional columns for particle-size-dependent parameters

Examples

df <- particle_dist()
params <- set_params_1("D_tube" = 2.54, "Q_lpm" = 100,
"T_C" = 25, "P_kPa" = 101.325)
df <- set_params_2(df, params)
head(df)

Tube efficiency

Description

Computation is consistent with the approach described in Hogue, Mark; Thompson, Martha; Farfan, Eduardo; Hadlock, Dennis, (2014), "Hand Calculations for Transport of Radioactive Aerosols through Sampling Systems" Health Phys 106, 5, S78-S87, <doi:10.1097/HP.0000000000000092>, with the exception that the diffusion deposition mechanism is included.

Usage

tube_eff(df, params, L_cm, angle_to_horiz, elnum)

Arguments

Details

In order to run this function, first produce a particle distribution with the 'particle_dist' function, then produce a parameter set with the 'set_params' function. Both of these results must be stored as per examples described in the help set with each.

Value

data frame containing original particle distribution with added data for this element

Examples

# Example output is a sample of the full particle data set.

# laminar flow (Reynolds number < 2100)

df <- particle_dist() #  distribution
params <- set_params_1("D_tube" = 2.54, "Q_lpm" = 20,
"T_C" = 25, "P_kPa" = 101.325) #example system parameters
df <- set_params_2(df, params) #particle size-dependent parameters
df <- probe_eff(df, params, orient = 'h') #probe orientation - horizontal
df <- tube_eff(df, params, L_cm = 100,
angle_to_horiz = 90, elnum = 2)
(df[sort(sample(1:1000, 10)), ])
# turbulent flow (Reynolds number > 4000)

df <- particle_dist() #  distribution
params <- set_params_1("D_tube" = 2.54, "Q_lpm" = 100,
"T_C" = 25, "P_kPa" = 101.325) #example system parameters
df <- set_params_2(df, params) #particle size-dependent parameters
df <- probe_eff(df, params, orient = 'h') #probe orientation - horizontal
df <- tube_eff(df, params, L_cm = 100,
angle_to_horiz = 90, elnum = 2)
(df[sort(sample(1:1000, 10)), ])

# midrange flow (Reynolds number > 2100 and < 4000)

df <- particle_dist() #  distribution
params <- set_params_1("D_tube" = 2.54, "Q_lpm" = 60,
"T_C" = 25, "P_kPa" = 101.325) #example system parameters
df <- set_params_2(df, params) #particle size-dependent parameters
df <- probe_eff(df, params, orient = 'h') #probe orientation - horizontal
df <- tube_eff(df, params, L_cm = 100,
angle_to_horiz = 90, elnum = 2)
(df[sort(sample(1:1000, 10)), ])