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0c2597d97f
feat: implement data clustering using PHT feat: implement interpolation refactor: use named vector for DHT species definition and significant digits data: remove unusable input scripts data: move Phreeqc database to benchmark dir refactor: rename dolomite benchmark directory refactor: remove DHT prop type from input script
172 lines
3.8 KiB
R
172 lines
3.8 KiB
R
## Time-stamp: "Last modified 2023-08-01 18:34:47 mluebke"
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database <- normalizePath("../share/poet/bench/dolo/phreeqc_kin.dat")
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input_script <- normalizePath("../share/poet/bench/dolo/dolo_inner.pqi")
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#################################################################
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## Section 1 ##
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## Grid initialization ##
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#################################################################
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n <- 400
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m <- 200
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types <- c("scratch", "phreeqc", "rds")
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init_cell <- list(
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"H" = 110.683,
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"O" = 55.3413,
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"Charge" = -5.0822e-19,
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"C" = 1.2279E-4,
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"Ca" = 1.2279E-4,
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"Cl" = 0,
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"Mg" = 0,
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"O2g" = 0.499957,
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"Calcite" = 2.07e-4,
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"Dolomite" = 0
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)
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grid <- list(
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n_cells = c(n, m),
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s_cells = c(5, 2.5),
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type = types[1],
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init_cell = as.data.frame(init_cell, check.names = FALSE),
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props = names(init_cell),
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database = database,
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input_script = input_script
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)
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##################################################################
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## Section 2 ##
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## Diffusion parameters and boundary conditions ##
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##################################################################
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## initial conditions
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init_diffu <- list(
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"H" = 1.110124E+02,
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"O" = 5.550833E+01,
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"Charge" = -1.216307659761E-09,
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"C(4)" = 1.230067028174E-04,
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"Ca" = 1.230067028174E-04,
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"Cl" = 0,
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"Mg" = 0
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)
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## diffusion coefficients
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alpha_diffu <- c(
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"H" = 1E-6,
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"O" = 1E-6,
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"Charge" = 1E-6,
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"C(4)" = 1E-6,
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"Ca" = 1E-6,
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"Cl" = 1E-6,
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"Mg" = 1E-6
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)
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## list of boundary conditions/inner nodes
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vecinj_diffu <- list(
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list(
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"H" = 1.110124E+02,
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"O" = 5.550796E+01,
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"Charge" = -3.230390327801E-08,
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"C(4)" = 0,
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"Ca" = 0,
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"Cl" = 0.002,
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"Mg" = 0.001
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),
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list(
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"H" = 110.683,
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"O" = 55.3413,
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"Charge" = 1.90431e-16,
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"C(4)" = 0,
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"Ca" = 0.0,
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"Cl" = 0.004,
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"Mg" = 0.002
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),
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init_diffu
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)
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vecinj_inner <- list(
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l1 = c(1, floor(n / 2), floor(m / 2))
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# l2 = c(2,1400,800),
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# l3 = c(2,1600,800)
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)
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boundary <- list(
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# "N" = c(1, rep(0, n-1)),
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"N" = rep(3, n),
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"E" = rep(3, m),
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"S" = rep(3, n),
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"W" = rep(3, m)
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)
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diffu_list <- names(alpha_diffu)
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vecinj <- do.call(rbind.data.frame, vecinj_diffu)
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names(vecinj) <- names(init_diffu)
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diffusion <- list(
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init = as.data.frame(init_diffu, check.names = FALSE),
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vecinj = vecinj,
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vecinj_inner = vecinj_inner,
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vecinj_index = boundary,
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alpha = alpha_diffu
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)
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#################################################################
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## Section 3 ##
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## Chemistry module (Phreeqc) ##
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#################################################################
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## # optional when using DHT
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dht_species <- c(
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"H" = 3,
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"O" = 3,
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"Charge" = 3,
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"C(4)" = 6,
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"Ca" = 6,
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"Cl" = 3,
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"Mg" = 5,
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"Calcite" = 4,
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"Dolomite" = 4
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)
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## # Optional when using Interpolation (example with less key species and custom
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## # significant digits)
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#pht_species <- c(
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# "C(4)" = 3,
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# "Ca" = 3,
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# "Mg" = 2,
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# "Calcite" = 2,
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# "Dolomite" = 2
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#)
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chemistry <- list(
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database = database,
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input_script = input_script,
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dht_species = dht_species
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# pht_species = pht_species
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)
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#################################################################
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## Section 4 ##
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## Putting all those things together ##
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#################################################################
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iterations <- 20000
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dt <- 200
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setup <- list(
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grid = grid,
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diffusion = diffusion,
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chemistry = chemistry,
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iterations = iterations,
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timesteps = rep(dt, iterations),
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store_result = TRUE,
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out_save = c(1, seq(50, iterations, by = 50))
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)
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