[1682] | 1 | !> @file lpm_droplet_collision.f90 |
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[1036] | 2 | !--------------------------------------------------------------------------------! |
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| 3 | ! This file is part of PALM. |
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| 4 | ! |
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| 5 | ! PALM is free software: you can redistribute it and/or modify it under the terms |
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| 6 | ! of the GNU General Public License as published by the Free Software Foundation, |
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| 7 | ! either version 3 of the License, or (at your option) any later version. |
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| 8 | ! |
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| 9 | ! PALM is distributed in the hope that it will be useful, but WITHOUT ANY |
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| 10 | ! WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR |
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| 11 | ! A PARTICULAR PURPOSE. See the GNU General Public License for more details. |
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| 12 | ! |
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| 13 | ! You should have received a copy of the GNU General Public License along with |
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| 14 | ! PALM. If not, see <http://www.gnu.org/licenses/>. |
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| 15 | ! |
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[1818] | 16 | ! Copyright 1997-2016 Leibniz Universitaet Hannover |
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[1036] | 17 | !--------------------------------------------------------------------------------! |
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| 18 | ! |
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[849] | 19 | ! Current revisions: |
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| 20 | ! ------------------ |
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[1823] | 21 | ! |
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| 22 | ! |
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[1321] | 23 | ! Former revisions: |
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| 24 | ! ----------------- |
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| 25 | ! $Id: lpm_droplet_collision.f90 1823 2016-04-07 08:57:52Z maronga $ |
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| 26 | ! |
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[1823] | 27 | ! 1822 2016-04-07 07:49:42Z hoffmann |
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| 28 | ! Integration of a new collision algortithm based on Shima et al. (2009) and |
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| 29 | ! Soelch and Kaercher (2010) called all_or_nothing. The previous implemented |
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| 30 | ! collision algorithm is called average_impact. Moreover, both algorithms are |
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| 31 | ! now positive definit due to their construction, i.e., no negative weighting |
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| 32 | ! factors should occur. |
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| 33 | ! |
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[1683] | 34 | ! 1682 2015-10-07 23:56:08Z knoop |
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| 35 | ! Code annotations made doxygen readable |
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| 36 | ! |
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[1360] | 37 | ! 1359 2014-04-11 17:15:14Z hoffmann |
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| 38 | ! New particle structure integrated. |
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| 39 | ! Kind definition added to all floating point numbers. |
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| 40 | ! |
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[1323] | 41 | ! 1322 2014-03-20 16:38:49Z raasch |
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| 42 | ! REAL constants defined as wp_kind |
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| 43 | ! |
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[1321] | 44 | ! 1320 2014-03-20 08:40:49Z raasch |
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[1320] | 45 | ! ONLY-attribute added to USE-statements, |
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| 46 | ! kind-parameters added to all INTEGER and REAL declaration statements, |
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| 47 | ! kinds are defined in new module kinds, |
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| 48 | ! revision history before 2012 removed, |
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| 49 | ! comment fields (!:) to be used for variable explanations added to |
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| 50 | ! all variable declaration statements |
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[1072] | 51 | ! |
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[1093] | 52 | ! 1092 2013-02-02 11:24:22Z raasch |
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| 53 | ! unused variables removed |
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| 54 | ! |
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[1072] | 55 | ! 1071 2012-11-29 16:54:55Z franke |
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[1071] | 56 | ! Calculation of Hall and Wang kernel now uses collision-coalescence formulation |
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| 57 | ! proposed by Wang instead of the continuous collection equation (for more |
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| 58 | ! information about new method see PALM documentation) |
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| 59 | ! Bugfix: message identifiers added |
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[849] | 60 | ! |
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[1037] | 61 | ! 1036 2012-10-22 13:43:42Z raasch |
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| 62 | ! code put under GPL (PALM 3.9) |
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| 63 | ! |
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[850] | 64 | ! 849 2012-03-15 10:35:09Z raasch |
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| 65 | ! initial revision (former part of advec_particles) |
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[849] | 66 | ! |
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[850] | 67 | ! |
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[849] | 68 | ! Description: |
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| 69 | ! ------------ |
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[1682] | 70 | !> Calculates change in droplet radius by collision. Droplet collision is |
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| 71 | !> calculated for each grid box seperately. Collision is parameterized by |
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[1822] | 72 | !> using collision kernels. Two different kernels are available: |
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[1682] | 73 | !> Hall kernel: Kernel from Hall (1980, J. Atmos. Sci., 2486-2507), which |
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| 74 | !> considers collision due to pure gravitational effects. |
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| 75 | !> Wang kernel: Beside gravitational effects (treated with the Hall-kernel) also |
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| 76 | !> the effects of turbulence on the collision are considered using |
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| 77 | !> parameterizations of Ayala et al. (2008, New J. Phys., 10, |
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| 78 | !> 075015) and Wang and Grabowski (2009, Atmos. Sci. Lett., 10, |
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| 79 | !> 1-8). This kernel includes three possible effects of turbulence: |
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| 80 | !> the modification of the relative velocity between the droplets, |
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| 81 | !> the effect of preferential concentration, and the enhancement of |
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| 82 | !> collision efficiencies. |
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[849] | 83 | !------------------------------------------------------------------------------! |
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[1682] | 84 | SUBROUTINE lpm_droplet_collision (i,j,k) |
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| 85 | |
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[849] | 86 | |
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[1359] | 87 | |
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[1320] | 88 | USE arrays_3d, & |
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[1822] | 89 | ONLY: diss, ql_v, ql_vp |
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[849] | 90 | |
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[1320] | 91 | USE cloud_parameters, & |
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[1822] | 92 | ONLY: rho_l |
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[1320] | 93 | |
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| 94 | USE constants, & |
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| 95 | ONLY: pi |
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| 96 | |
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| 97 | USE control_parameters, & |
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[1822] | 98 | ONLY: dt_3d, message_string, dz |
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[1320] | 99 | |
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| 100 | USE cpulog, & |
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| 101 | ONLY: cpu_log, log_point_s |
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| 102 | |
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| 103 | USE grid_variables, & |
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[1822] | 104 | ONLY: dx, dy |
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[1320] | 105 | |
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| 106 | USE kinds |
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| 107 | |
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| 108 | USE lpm_collision_kernels_mod, & |
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[1822] | 109 | ONLY: ckernel, recalculate_kernel |
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[1320] | 110 | |
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| 111 | USE particle_attributes, & |
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[1822] | 112 | ONLY: all_or_nothing, average_impact, dissipation_classes, & |
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| 113 | hall_kernel, iran_part, number_of_particles, particles, & |
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| 114 | particle_type, prt_count, use_kernel_tables, wang_kernel |
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[1320] | 115 | |
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[1822] | 116 | USE random_function_mod, & |
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| 117 | ONLY: random_function |
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| 118 | |
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[1359] | 119 | USE pegrid |
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| 120 | |
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[849] | 121 | IMPLICIT NONE |
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| 122 | |
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[1682] | 123 | INTEGER(iwp) :: eclass !< |
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| 124 | INTEGER(iwp) :: i !< |
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| 125 | INTEGER(iwp) :: j !< |
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| 126 | INTEGER(iwp) :: k !< |
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| 127 | INTEGER(iwp) :: n !< |
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[1822] | 128 | INTEGER(iwp) :: m !< |
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[1682] | 129 | INTEGER(iwp) :: rclass_l !< |
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| 130 | INTEGER(iwp) :: rclass_s !< |
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[849] | 131 | |
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[1822] | 132 | REAL(wp) :: collection_probability !< probability for collection |
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| 133 | REAL(wp) :: ddV !< inverse grid box volume |
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| 134 | REAL(wp) :: epsilon !< dissipation rate |
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| 135 | REAL(wp) :: factor_volume_to_mass !< 4.0 / 3.0 * pi * rho_l |
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| 136 | REAL(wp) :: xm !< mean mass of droplet m |
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| 137 | REAL(wp) :: xn !< mean mass of droplet n |
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[1359] | 138 | |
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[1822] | 139 | REAL(wp), DIMENSION(:), ALLOCATABLE :: weight !< weighting factor |
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| 140 | REAL(wp), DIMENSION(:), ALLOCATABLE :: mass !< total mass of super droplet |
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[1359] | 141 | |
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[849] | 142 | CALL cpu_log( log_point_s(43), 'lpm_droplet_coll', 'start' ) |
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| 143 | |
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[1822] | 144 | number_of_particles = prt_count(k,j,i) |
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| 145 | factor_volume_to_mass = 4.0_wp / 3.0_wp * pi * rho_l |
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| 146 | ddV = 1 / ( dx * dy * dz ) |
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[849] | 147 | ! |
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[1822] | 148 | !-- Collision requires at least one super droplet inside the box |
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| 149 | IF ( number_of_particles > 0 ) THEN |
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[849] | 150 | |
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| 151 | ! |
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[1359] | 152 | !-- Now apply the different kernels |
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[1822] | 153 | IF ( use_kernel_tables ) THEN |
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[849] | 154 | ! |
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[1822] | 155 | !-- Fast method with pre-calculated collection kernels for |
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[1359] | 156 | !-- discrete radius- and dissipation-classes. |
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| 157 | !-- |
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| 158 | !-- Determine dissipation class index of this gridbox |
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| 159 | IF ( wang_kernel ) THEN |
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| 160 | eclass = INT( diss(k,j,i) * 1.0E4_wp / 1000.0_wp * & |
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| 161 | dissipation_classes ) + 1 |
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| 162 | epsilon = diss(k,j,i) |
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| 163 | ELSE |
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| 164 | epsilon = 0.0_wp |
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| 165 | ENDIF |
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| 166 | IF ( hall_kernel .OR. epsilon * 1.0E4_wp < 0.001_wp ) THEN |
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| 167 | eclass = 0 ! Hall kernel is used |
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| 168 | ELSE |
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| 169 | eclass = MIN( dissipation_classes, eclass ) |
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| 170 | ENDIF |
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| 171 | |
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[849] | 172 | ! |
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[1359] | 173 | !-- Droplet collision are calculated using collision-coalescence |
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| 174 | !-- formulation proposed by Wang (see PALM documentation) |
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[1822] | 175 | !-- Temporary fields for total mass of super-droplet and weighting factors |
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| 176 | !-- are allocated. |
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| 177 | ALLOCATE(mass(1:number_of_particles), weight(1:number_of_particles)) |
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[849] | 178 | |
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[1822] | 179 | mass(1:number_of_particles) = particles(1:number_of_particles)%weight_factor * & |
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| 180 | particles(1:number_of_particles)%radius**3 * & |
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| 181 | factor_volume_to_mass |
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| 182 | weight(1:number_of_particles) = particles(1:number_of_particles)%weight_factor |
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[849] | 183 | |
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[1822] | 184 | IF ( average_impact ) THEN ! select collision algorithm |
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[1071] | 185 | |
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[1822] | 186 | DO n = 1, number_of_particles |
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[1071] | 187 | |
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[1822] | 188 | rclass_l = particles(n)%class |
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| 189 | xn = mass(n) / weight(n) |
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[849] | 190 | |
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[1822] | 191 | DO m = n, number_of_particles |
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[849] | 192 | |
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[1822] | 193 | rclass_s = particles(m)%class |
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| 194 | xm = mass(m) / weight(m) |
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[849] | 195 | |
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[1822] | 196 | IF ( xm .LT. xn ) THEN |
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| 197 | |
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| 198 | ! |
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| 199 | !-- Particle n collects smaller particle m |
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| 200 | collection_probability = ckernel(rclass_l,rclass_s,eclass) * & |
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| 201 | weight(n) * ddV * dt_3d |
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[849] | 202 | |
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[1822] | 203 | mass(n) = mass(n) + mass(m) * collection_probability |
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| 204 | weight(m) = weight(m) - weight(m) * collection_probability |
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| 205 | mass(m) = mass(m) - mass(m) * collection_probability |
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| 206 | ELSEIF ( xm .GT. xn ) THEN |
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[849] | 207 | ! |
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[1822] | 208 | !-- Particle m collects smaller particle n |
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| 209 | collection_probability = ckernel(rclass_l,rclass_s,eclass) * & |
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| 210 | weight(m) * ddV * dt_3d |
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[849] | 211 | |
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[1822] | 212 | mass(m) = mass(m) + mass(n) * collection_probability |
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| 213 | weight(n) = weight(n) - weight(n) * collection_probability |
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| 214 | mass(n) = mass(n) - mass(n) * collection_probability |
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| 215 | ELSE |
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[1071] | 216 | ! |
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[1822] | 217 | !-- Same-size collections. If n = m, weight is reduced by the |
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| 218 | !-- number of possible same-size collections; the total mass |
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| 219 | !-- is not changed during same-size collection. |
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| 220 | !-- Same-size collections of different |
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| 221 | !-- particles ( n /= m ) are treated as same-size collections |
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| 222 | !-- of ONE partilce with weight = weight(n) + weight(m) and |
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| 223 | !-- mass = mass(n) + mass(m). |
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| 224 | !-- Accordingly, each particle loses the same number of |
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| 225 | !-- droplets to the other particle, but this has no effect on |
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| 226 | !-- total mass mass, since the exchanged droplets have the |
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| 227 | !-- same radius. |
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[849] | 228 | |
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[1822] | 229 | !-- Note: For m = n this equation is an approximation only |
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| 230 | !-- valid for weight >> 1 (which is usually the case). The |
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| 231 | !-- approximation is weight(n)-1 = weight(n). |
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| 232 | weight(n) = weight(n) - 0.5_wp * weight(n) * & |
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| 233 | ckernel(rclass_l,rclass_s,eclass) * & |
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| 234 | weight(m) * ddV * dt_3d |
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| 235 | IF ( n .NE. m ) THEN |
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| 236 | weight(m) = weight(m) - 0.5_wp * weight(m) * & |
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| 237 | ckernel(rclass_l,rclass_s,eclass) * & |
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| 238 | weight(n) * ddV * dt_3d |
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| 239 | ENDIF |
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| 240 | ENDIF |
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[1071] | 241 | |
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[1822] | 242 | ENDDO |
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[1071] | 243 | |
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[1822] | 244 | ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass |
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| 245 | |
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[1359] | 246 | ENDDO |
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[849] | 247 | |
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[1822] | 248 | ELSEIF ( all_or_nothing ) THEN ! select collision algorithm |
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[849] | 249 | |
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[1822] | 250 | DO n = 1, number_of_particles |
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[849] | 251 | |
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[1822] | 252 | rclass_l = particles(n)%class |
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| 253 | xn = mass(n) / weight(n) ! mean mass of droplet n |
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[849] | 254 | |
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[1822] | 255 | DO m = n, number_of_particles |
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[849] | 256 | |
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[1822] | 257 | rclass_s = particles(m)%class |
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| 258 | xm = mass(m) / weight(m) ! mean mass of droplet m |
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[849] | 259 | |
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[1822] | 260 | IF ( weight(n) .LT. weight(m) ) THEN |
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| 261 | ! |
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| 262 | !-- Particle n collects weight(n) droplets of particle m |
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| 263 | collection_probability = ckernel(rclass_l,rclass_s,eclass) * & |
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| 264 | weight(m) * ddV * dt_3d |
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[1071] | 265 | |
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[1822] | 266 | IF ( collection_probability .GT. random_function( iran_part ) ) THEN |
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| 267 | mass(n) = mass(n) + weight(n) * xm |
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| 268 | weight(m) = weight(m) - weight(n) |
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| 269 | mass(m) = mass(m) - weight(n) * xm |
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| 270 | ENDIF |
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| 271 | |
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| 272 | ELSEIF ( weight(m) .LT. weight(n) ) THEN |
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[849] | 273 | ! |
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[1822] | 274 | !-- Particle m collects weight(m) droplets of particle n |
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| 275 | collection_probability = ckernel(rclass_l,rclass_s,eclass) * & |
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| 276 | weight(n) * ddV * dt_3d |
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| 277 | |
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| 278 | IF ( collection_probability .GT. random_function( iran_part ) ) THEN |
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| 279 | mass(m) = mass(m) + weight(m) * xn |
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| 280 | weight(n) = weight(n) - weight(m) |
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| 281 | mass(n) = mass(n) - weight(m) * xn |
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| 282 | ENDIF |
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| 283 | ELSE |
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[849] | 284 | ! |
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[1822] | 285 | !-- Collisions of particles of the same weighting factor. |
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| 286 | !-- Particle n collects 1/2 weight(n) droplets of particle m, |
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| 287 | !-- particle m collects 1/2 weight(m) droplets of particle n. |
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| 288 | !-- The total mass mass changes accordingly. |
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| 289 | !-- If n = m, the first half of the droplets coalesces with the |
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| 290 | !-- second half of the droplets; mass is unchanged because |
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| 291 | !-- xm = xn for n = m. |
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[849] | 292 | |
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[1822] | 293 | !-- Note: For m = n this equation is an approximation only |
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| 294 | !-- valid for weight >> 1 (which is usually the case). The |
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| 295 | !-- approximation is weight(n)-1 = weight(n). |
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| 296 | collection_probability = ckernel(rclass_l,rclass_s,eclass) * & |
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| 297 | weight(n) * ddV * dt_3d |
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[849] | 298 | |
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[1822] | 299 | IF ( collection_probability .GT. random_function( iran_part ) ) THEN |
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| 300 | mass(n) = mass(n) + 0.5_wp * weight(n) * ( xm - xn ) |
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| 301 | mass(m) = mass(m) + 0.5_wp * weight(m) * ( xn - xm ) |
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| 302 | weight(n) = weight(n) - 0.5_wp * weight(m) |
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| 303 | weight(m) = weight(n) |
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| 304 | ENDIF |
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| 305 | ENDIF |
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[849] | 306 | |
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[1822] | 307 | ENDDO |
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[849] | 308 | |
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[1822] | 309 | ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass |
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[849] | 310 | |
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[1822] | 311 | ENDDO |
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[849] | 312 | |
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[1822] | 313 | ENDIF |
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[849] | 314 | |
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| 315 | |
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| 316 | |
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| 317 | |
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[1822] | 318 | IF ( ANY(weight < 0.0_wp) ) THEN |
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| 319 | WRITE( message_string, * ) 'negative weighting' |
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| 320 | CALL message( 'lpm_droplet_collision', 'PA0028', & |
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| 321 | 2, 2, -1, 6, 1 ) |
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| 322 | ENDIF |
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[849] | 323 | |
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[1822] | 324 | particles(1:number_of_particles)%radius = ( mass(1:number_of_particles) / & |
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| 325 | ( weight(1:number_of_particles) & |
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| 326 | * factor_volume_to_mass & |
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| 327 | ) & |
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| 328 | )**0.33333333333333_wp |
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[849] | 329 | |
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[1822] | 330 | particles(1:number_of_particles)%weight_factor = weight(1:number_of_particles) |
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[849] | 331 | |
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[1822] | 332 | DEALLOCATE(weight, mass) |
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[849] | 333 | |
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[1822] | 334 | ELSEIF ( .NOT. use_kernel_tables ) THEN |
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| 335 | ! |
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| 336 | !-- Collection kernels are calculated for every new |
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| 337 | !-- grid box. First, allocate memory for kernel table. |
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| 338 | !-- Third dimension is 1, because table is re-calculated for |
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| 339 | !-- every new dissipation value. |
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| 340 | ALLOCATE( ckernel(1:number_of_particles,1:number_of_particles,1:1) ) |
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| 341 | ! |
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| 342 | !-- Now calculate collection kernel for this box. Note that |
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| 343 | !-- the kernel is based on the previous time step |
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| 344 | CALL recalculate_kernel( i, j, k ) |
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| 345 | ! |
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| 346 | !-- Droplet collision are calculated using collision-coalescence |
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| 347 | !-- formulation proposed by Wang (see PALM documentation) |
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| 348 | !-- Temporary fields for total mass of super-droplet and weighting factors |
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| 349 | !-- are allocated. |
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| 350 | ALLOCATE(mass(1:number_of_particles), weight(1:number_of_particles)) |
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[849] | 351 | |
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[1822] | 352 | mass(1:number_of_particles) = particles(1:number_of_particles)%weight_factor * & |
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| 353 | particles(1:number_of_particles)%radius**3 * & |
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| 354 | factor_volume_to_mass |
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[849] | 355 | |
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[1822] | 356 | weight(1:number_of_particles) = particles(1:number_of_particles)%weight_factor |
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[849] | 357 | |
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[1822] | 358 | IF ( average_impact ) THEN ! select collision algorithm |
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[849] | 359 | |
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[1822] | 360 | DO n = 1, number_of_particles |
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[849] | 361 | |
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[1822] | 362 | xn = mass(n) / weight(n) ! mean mass of droplet n |
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[849] | 363 | |
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[1822] | 364 | DO m = n, number_of_particles |
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[849] | 365 | |
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[1822] | 366 | xm = mass(m) / weight(m) !mean mass of droplet m |
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[849] | 367 | |
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[1822] | 368 | IF ( xm .LT. xn ) THEN |
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[849] | 369 | ! |
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[1822] | 370 | !-- Particle n collects smaller particle m |
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| 371 | collection_probability = ckernel(n,m,1) * weight(n) * & |
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| 372 | ddV * dt_3d |
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| 373 | |
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| 374 | mass(n) = mass(n) + mass(m) * collection_probability |
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| 375 | weight(m) = weight(m) - weight(m) * collection_probability |
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| 376 | mass(m) = mass(m) - mass(m) * collection_probability |
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| 377 | ELSEIF ( xm .GT. xn ) THEN |
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[849] | 378 | ! |
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[1822] | 379 | !-- Particle m collects smaller particle n |
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| 380 | collection_probability = ckernel(n,m,1) * weight(m) * & |
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| 381 | ddV * dt_3d |
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[849] | 382 | |
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[1822] | 383 | mass(m) = mass(m) + mass(n) * collection_probability |
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| 384 | weight(n) = weight(n) - weight(n) * collection_probability |
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| 385 | mass(n) = mass(n) - mass(n) * collection_probability |
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| 386 | ELSE |
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[849] | 387 | ! |
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[1822] | 388 | !-- Same-size collections. If n = m, weight is reduced by the |
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| 389 | !-- number of possible same-size collections; the total mass |
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| 390 | !-- mass is not changed during same-size collection. |
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| 391 | !-- Same-size collections of different |
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| 392 | !-- particles ( n /= m ) are treated as same-size collections |
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| 393 | !-- of ONE partilce with weight = weight(n) + weight(m) and |
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| 394 | !-- mass = mass(n) + mass(m). |
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| 395 | !-- Accordingly, each particle loses the same number of |
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| 396 | !-- droplets to the other particle, but this has no effect on |
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| 397 | !-- total mass mass, since the exchanged droplets have the |
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| 398 | !-- same radius. |
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| 399 | !-- |
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| 400 | !-- Note: For m = n this equation is an approximation only |
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| 401 | !-- valid for weight >> 1 (which is usually the case). The |
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| 402 | !-- approximation is weight(n)-1 = weight(n). |
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| 403 | weight(n) = weight(n) - 0.5_wp * weight(n) * & |
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| 404 | ckernel(n,m,1) * weight(m) * & |
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| 405 | ddV * dt_3d |
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| 406 | IF ( n .NE. m ) THEN |
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| 407 | weight(m) = weight(m) - 0.5_wp * weight(m) * & |
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| 408 | ckernel(n,m,1) * weight(n) * & |
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| 409 | ddV * dt_3d |
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| 410 | ENDIF |
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| 411 | ENDIF |
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[849] | 412 | |
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| 413 | |
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[1359] | 414 | ENDDO |
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[849] | 415 | |
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[1822] | 416 | ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass |
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[849] | 417 | |
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[1822] | 418 | ENDDO |
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[849] | 419 | |
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[1822] | 420 | ELSEIF ( all_or_nothing ) THEN ! select collision algorithm |
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[849] | 421 | |
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[1822] | 422 | DO n = 1, number_of_particles |
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[849] | 423 | |
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[1822] | 424 | xn = mass(n) / weight(n) ! mean mass of droplet n |
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[849] | 425 | |
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[1822] | 426 | DO m = n, number_of_particles |
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[849] | 427 | |
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[1822] | 428 | xm = mass(m) / weight(m) !mean mass of droplet m |
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[849] | 429 | |
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[1822] | 430 | IF ( weight(n) .LT. weight(m) ) THEN |
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| 431 | ! |
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| 432 | !-- Particle n collects smaller particle m |
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| 433 | collection_probability = ckernel(n,m,1) * weight(m) * & |
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| 434 | ddV * dt_3d |
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[1071] | 435 | |
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[1822] | 436 | IF ( collection_probability .GT. random_function( iran_part ) ) THEN |
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| 437 | mass(n) = mass(n) + weight(n) * xm |
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| 438 | weight(m) = weight(m) - weight(n) |
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| 439 | mass(m) = mass(m) - weight(n) * xm |
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| 440 | ENDIF |
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[1359] | 441 | |
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[1822] | 442 | ELSEIF ( weight(m) .LT. weight(n) ) THEN |
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[1071] | 443 | ! |
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[1822] | 444 | !-- Particle m collects smaller particle n |
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| 445 | collection_probability = ckernel(n,m,1) * weight(n) * & |
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| 446 | ddV * dt_3d |
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[1071] | 447 | |
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[1822] | 448 | IF ( collection_probability .GT. random_function( iran_part ) ) THEN |
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| 449 | mass(m) = mass(m) + weight(m) * xn |
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| 450 | weight(n) = weight(n) - weight(m) |
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| 451 | mass(n) = mass(n) - weight(m) * xn |
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| 452 | ENDIF |
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| 453 | ELSE |
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| 454 | ! |
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| 455 | !-- Collisions of particles of the same weighting factor. |
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| 456 | !-- Particle n collects 1/2 weight(n) droplets of particle m, |
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| 457 | !-- particle m collects 1/2 weight(m) droplets of particle n. |
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| 458 | !-- The total mass mass changes accordingly. |
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| 459 | !-- If n = m, the first half of the droplets coalesces with the |
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| 460 | !-- second half of the droplets; mass is unchanged because |
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| 461 | !-- xm = xn for n = m. |
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| 462 | !-- |
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| 463 | !-- Note: For m = n this equation is an approximation only |
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| 464 | !-- valid for weight >> 1 (which is usually the case). The |
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| 465 | !-- approximation is weight(n)-1 = weight(n). |
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| 466 | collection_probability = ckernel(n,m,1) * weight(n) * & |
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| 467 | ddV * dt_3d |
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[1071] | 468 | |
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[1822] | 469 | IF ( collection_probability .GT. random_function( iran_part ) ) THEN |
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| 470 | mass(n) = mass(n) + 0.5_wp * weight(n) * ( xm - xn ) |
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| 471 | mass(m) = mass(m) + 0.5_wp * weight(m) * ( xn - xm ) |
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| 472 | weight(n) = weight(n) - 0.5_wp * weight(m) |
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| 473 | weight(m) = weight(n) |
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| 474 | ENDIF |
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| 475 | ENDIF |
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[1071] | 476 | |
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| 477 | |
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[1822] | 478 | ENDDO |
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[1071] | 479 | |
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[1822] | 480 | ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass |
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[1071] | 481 | |
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[1822] | 482 | ENDDO |
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[1071] | 483 | |
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[1822] | 484 | ENDIF |
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[1071] | 485 | |
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[1822] | 486 | IF ( ANY(weight < 0.0_wp) ) THEN |
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| 487 | WRITE( message_string, * ) 'negative weighting' |
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| 488 | CALL message( 'lpm_droplet_collision', 'PA0028', & |
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| 489 | 2, 2, -1, 6, 1 ) |
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| 490 | ENDIF |
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| 491 | |
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| 492 | particles(1:number_of_particles)%radius = ( mass(1:number_of_particles) / & |
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| 493 | ( weight(1:number_of_particles) & |
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| 494 | * factor_volume_to_mass & |
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| 495 | ) & |
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| 496 | )**0.33333333333333_wp |
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| 497 | |
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| 498 | particles(1:number_of_particles)%weight_factor = weight(1:number_of_particles) |
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| 499 | |
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| 500 | DEALLOCATE( weight, mass, ckernel ) |
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| 501 | |
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| 502 | ENDIF |
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| 503 | |
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[1359] | 504 | ENDIF |
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[1822] | 505 | |
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[849] | 506 | |
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| 507 | ! |
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[1822] | 508 | !-- Check if LWC is conserved during collision process |
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[1359] | 509 | IF ( ql_v(k,j,i) /= 0.0_wp ) THEN |
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[1822] | 510 | IF ( ql_vp(k,j,i) / ql_v(k,j,i) >= 1.0001_wp .OR. & |
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[1359] | 511 | ql_vp(k,j,i) / ql_v(k,j,i) <= 0.9999_wp ) THEN |
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[1822] | 512 | WRITE( message_string, * ) ' LWC is not conserved during', & |
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| 513 | ' collision! ', & |
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| 514 | ' LWC after condensation: ', ql_v(k,j,i), & |
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| 515 | ' LWC after collision: ', ql_vp(k,j,i) |
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| 516 | CALL message( 'lpm_droplet_collision', 'PA0040', 2, 2, -1, 6, 1 ) |
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[1359] | 517 | ENDIF |
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| 518 | ENDIF |
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[849] | 519 | |
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| 520 | CALL cpu_log( log_point_s(43), 'lpm_droplet_coll', 'stop' ) |
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| 521 | |
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[1359] | 522 | END SUBROUTINE lpm_droplet_collision |
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