Simulate paired soil-profile realizations for a material pool

Draws NS synthetic columns with sampleSoilLayers(), evaluates each with evaluateSoilLayers() and characterizes it with characterizeProfile(). Every realization is kept with its layers, so the profile quantities stay paired: the Go, mo, VSo, VS30 and TrRayleigh of one row belong to the same column. summarizeProfiles() reduces this population to marginal statistics; propagateSitePeriod() and propagateBeamPeriod() solve the fundamental periods of the soil profile and truncated shear beam on each row before any reduction.

Usage

simulateSoilProfiles(Hs, USCS, NS, h, water, POP, Vref, m1 = HardinExponent)

Arguments

Hs: One positive height in metres.
USCS: Character vector of USCS codes forming the material pool.
NS: Number of realizations, a positive integer.
h: One positive layer thickness in metres.
water: Water-table height as a fraction of Hs.
POP: Preconsolidation pressure in kPa.
Vref: One positive reference velocity in m/s, see estimateVS30().
m1: Nodes of the plasticity exponent, see evaluateSoilLayers(), whose published table is also the default here.

Value

A data.table with one row per realization: realization, Hs, Hw (water-table height, m), POP, Vref, the columns of characterizeProfile() and layers, a list column holding the evaluated layer table of the row. The rows are the population generated by the pool under the caller's random stream.

Examples

set.seed(20260915)
simulateSoilProfiles(Hs = 10, USCS = c("ML", "MH"), NS = 3, h = 1,
                     water = 0, POP = 100, Vref = 760)
#>    realization    Hs    Hw   POP  Vref    NL       Go        mo      VSo
#>          <int> <num> <num> <num> <num> <int>    <num>     <num>    <num>
#> 1:           1    10     0   100   760    10 59.62915 0.2980117 178.0648
#> 2:           2    10     0   100   760    10 76.30413 0.5459589 195.3620
#> 3:           3    10     0   100   760    10 69.44542 0.5433113 186.2848
#>        VS30    SID TrRayleigh Gravels Sands Fines Clays Silts Organic   USCS
#>       <num> <char>      <num>   <num> <num> <num> <num> <num>   <num> <char>
#> 1: 322.7362     CD  0.2411996       0     0   100     0   100       0  MH.ML
#> 2: 317.2137     CD  0.2354715       0     0   100     0   100       0  MH.ML
#> 3: 306.6465     CD  0.2414145       0     0   100     0   100       0  MH.ML
#>     fitSigma fitLayers              layers
#>        <num>     <int>              <list>
#> 1: 0.3309554        10 <data.table[10x19]>
#> 2: 0.4070521        10 <data.table[10x19]>
#> 3: 0.3098340        10 <data.table[10x19]>