Home

Context Navigation

source: palm/trunk/SOURCE/lpm_droplet_collision.f90 @ 1878

Last change on this file since 1878 was 1861, checked in by hoffmann, 9 years ago
last commit documented
Property svn:keywords set to `Id`
File size: 22.6 KB

Rev	Line
[1682]	1	!> @file lpm_droplet_collision.f90
[1036]	2	!--------------------------------------------------------------------------------!
	3	! This file is part of PALM.
	4	!
	5	! PALM is free software: you can redistribute it and/or modify it under the terms
	6	! of the GNU General Public License as published by the Free Software Foundation,
	7	! either version 3 of the License, or (at your option) any later version.
	8	!
	9	! PALM is distributed in the hope that it will be useful, but WITHOUT ANY
	10	! WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
	11	! A PARTICULAR PURPOSE. See the GNU General Public License for more details.
	12	!
	13	! You should have received a copy of the GNU General Public License along with
	14	! PALM. If not, see <http://www.gnu.org/licenses/>.
	15	!
[1818]	16	! Copyright 1997-2016 Leibniz Universitaet Hannover
[1036]	17	!--------------------------------------------------------------------------------!
	18	!
[849]	19	! Current revisions:
	20	! ------------------
[1823]	21	!
[1861]	22	!
[1321]	23	! Former revisions:
	24	! -----------------
	25	! $Id: lpm_droplet_collision.f90 1861 2016-04-13 13:22:08Z hellstea $
	26	!
[1861]	27	! 1860 2016-04-13 13:21:28Z hoffmann
	28	! Interpolation of dissipation rate adjusted to more reasonable values.
	29	!
[1823]	30	! 1822 2016-04-07 07:49:42Z hoffmann
	31	! Integration of a new collision algortithm based on Shima et al. (2009) and
	32	! Soelch and Kaercher (2010) called all_or_nothing. The previous implemented
	33	! collision algorithm is called average_impact. Moreover, both algorithms are
	34	! now positive definit due to their construction, i.e., no negative weighting
	35	! factors should occur.
	36	!
[1683]	37	! 1682 2015-10-07 23:56:08Z knoop
	38	! Code annotations made doxygen readable
	39	!
[1360]	40	! 1359 2014-04-11 17:15:14Z hoffmann
	41	! New particle structure integrated.
	42	! Kind definition added to all floating point numbers.
	43	!
[1323]	44	! 1322 2014-03-20 16:38:49Z raasch
	45	! REAL constants defined as wp_kind
	46	!
[1321]	47	! 1320 2014-03-20 08:40:49Z raasch
[1320]	48	! ONLY-attribute added to USE-statements,
	49	! kind-parameters added to all INTEGER and REAL declaration statements,
	50	! kinds are defined in new module kinds,
	51	! revision history before 2012 removed,
	52	! comment fields (!:) to be used for variable explanations added to
	53	! all variable declaration statements
[1072]	54	!
[1093]	55	! 1092 2013-02-02 11:24:22Z raasch
	56	! unused variables removed
	57	!
[1072]	58	! 1071 2012-11-29 16:54:55Z franke
[1071]	59	! Calculation of Hall and Wang kernel now uses collision-coalescence formulation
	60	! proposed by Wang instead of the continuous collection equation (for more
	61	! information about new method see PALM documentation)
	62	! Bugfix: message identifiers added
[849]	63	!
[1037]	64	! 1036 2012-10-22 13:43:42Z raasch
	65	! code put under GPL (PALM 3.9)
	66	!
[850]	67	! 849 2012-03-15 10:35:09Z raasch
	68	! initial revision (former part of advec_particles)
[849]	69	!
[850]	70	!
[849]	71	! Description:
	72	! ------------
[1682]	73	!> Calculates change in droplet radius by collision. Droplet collision is
	74	!> calculated for each grid box seperately. Collision is parameterized by
[1822]	75	!> using collision kernels. Two different kernels are available:
[1682]	76	!> Hall kernel: Kernel from Hall (1980, J. Atmos. Sci., 2486-2507), which
	77	!> considers collision due to pure gravitational effects.
	78	!> Wang kernel: Beside gravitational effects (treated with the Hall-kernel) also
	79	!> the effects of turbulence on the collision are considered using
	80	!> parameterizations of Ayala et al. (2008, New J. Phys., 10,
	81	!> 075015) and Wang and Grabowski (2009, Atmos. Sci. Lett., 10,
	82	!> 1-8). This kernel includes three possible effects of turbulence:
	83	!> the modification of the relative velocity between the droplets,
	84	!> the effect of preferential concentration, and the enhancement of
	85	!> collision efficiencies.
[849]	86	!------------------------------------------------------------------------------!
[1682]	87	SUBROUTINE lpm_droplet_collision (i,j,k)
	88
[849]	89
[1359]	90
[1320]	91	USE arrays_3d, &
[1822]	92	ONLY: diss, ql_v, ql_vp
[849]	93
[1320]	94	USE cloud_parameters, &
[1822]	95	ONLY: rho_l
[1320]	96
	97	USE constants, &
	98	ONLY: pi
	99
	100	USE control_parameters, &
[1822]	101	ONLY: dt_3d, message_string, dz
[1320]	102
	103	USE cpulog, &
	104	ONLY: cpu_log, log_point_s
	105
	106	USE grid_variables, &
[1822]	107	ONLY: dx, dy
[1320]	108
	109	USE kinds
	110
	111	USE lpm_collision_kernels_mod, &
[1822]	112	ONLY: ckernel, recalculate_kernel
[1320]	113
	114	USE particle_attributes, &
[1822]	115	ONLY: all_or_nothing, average_impact, dissipation_classes, &
	116	hall_kernel, iran_part, number_of_particles, particles, &
	117	particle_type, prt_count, use_kernel_tables, wang_kernel
[1320]	118
[1822]	119	USE random_function_mod, &
	120	ONLY: random_function
	121
[1359]	122	USE pegrid
	123
[849]	124	IMPLICIT NONE
	125
[1682]	126	INTEGER(iwp) :: eclass !<
	127	INTEGER(iwp) :: i !<
	128	INTEGER(iwp) :: j !<
	129	INTEGER(iwp) :: k !<
	130	INTEGER(iwp) :: n !<
[1822]	131	INTEGER(iwp) :: m !<
[1682]	132	INTEGER(iwp) :: rclass_l !<
	133	INTEGER(iwp) :: rclass_s !<
[849]	134
[1822]	135	REAL(wp) :: collection_probability !< probability for collection
	136	REAL(wp) :: ddV !< inverse grid box volume
	137	REAL(wp) :: epsilon !< dissipation rate
	138	REAL(wp) :: factor_volume_to_mass !< 4.0 / 3.0 * pi * rho_l
	139	REAL(wp) :: xm !< mean mass of droplet m
	140	REAL(wp) :: xn !< mean mass of droplet n
[1359]	141
[1822]	142	REAL(wp), DIMENSION(:), ALLOCATABLE :: weight !< weighting factor
	143	REAL(wp), DIMENSION(:), ALLOCATABLE :: mass !< total mass of super droplet
[1359]	144
[849]	145	CALL cpu_log( log_point_s(43), 'lpm_droplet_coll', 'start' )
	146
[1822]	147	number_of_particles = prt_count(k,j,i)
	148	factor_volume_to_mass = 4.0_wp / 3.0_wp * pi * rho_l
	149	ddV = 1 / ( dx * dy * dz )
[849]	150	!
[1822]	151	!-- Collision requires at least one super droplet inside the box
	152	IF ( number_of_particles > 0 ) THEN
[849]	153
	154	!
[1359]	155	!-- Now apply the different kernels
[1822]	156	IF ( use_kernel_tables ) THEN
[849]	157	!
[1822]	158	!-- Fast method with pre-calculated collection kernels for
[1359]	159	!-- discrete radius- and dissipation-classes.
	160	!--
	161	!-- Determine dissipation class index of this gridbox
	162	IF ( wang_kernel ) THEN
[1860]	163	eclass = INT( diss(k,j,i) * 1.0E4_wp / 600.0_wp * &
[1359]	164	dissipation_classes ) + 1
	165	epsilon = diss(k,j,i)
	166	ELSE
	167	epsilon = 0.0_wp
	168	ENDIF
	169	IF ( hall_kernel .OR. epsilon * 1.0E4_wp < 0.001_wp ) THEN
	170	eclass = 0 ! Hall kernel is used
	171	ELSE
	172	eclass = MIN( dissipation_classes, eclass )
	173	ENDIF
	174
[849]	175	!
[1359]	176	!-- Droplet collision are calculated using collision-coalescence
	177	!-- formulation proposed by Wang (see PALM documentation)
[1822]	178	!-- Temporary fields for total mass of super-droplet and weighting factors
	179	!-- are allocated.
	180	ALLOCATE(mass(1:number_of_particles), weight(1:number_of_particles))
[849]	181
[1822]	182	mass(1:number_of_particles) = particles(1:number_of_particles)%weight_factor * &
	183	particles(1:number_of_particles)%radius*3 &
	184	factor_volume_to_mass
	185	weight(1:number_of_particles) = particles(1:number_of_particles)%weight_factor
[849]	186
[1822]	187	IF ( average_impact ) THEN ! select collision algorithm
[1071]	188
[1822]	189	DO n = 1, number_of_particles
[1071]	190
[1822]	191	rclass_l = particles(n)%class
	192	xn = mass(n) / weight(n)
[849]	193
[1822]	194	DO m = n, number_of_particles
[849]	195
[1822]	196	rclass_s = particles(m)%class
	197	xm = mass(m) / weight(m)
[849]	198
[1822]	199	IF ( xm .LT. xn ) THEN
	200
	201	!
	202	!-- Particle n collects smaller particle m
	203	collection_probability = ckernel(rclass_l,rclass_s,eclass) * &
	204	weight(n) * ddV * dt_3d
[849]	205
[1822]	206	mass(n) = mass(n) + mass(m) * collection_probability
	207	weight(m) = weight(m) - weight(m) * collection_probability
	208	mass(m) = mass(m) - mass(m) * collection_probability
	209	ELSEIF ( xm .GT. xn ) THEN
[849]	210	!
[1822]	211	!-- Particle m collects smaller particle n
	212	collection_probability = ckernel(rclass_l,rclass_s,eclass) * &
	213	weight(m) * ddV * dt_3d
[849]	214
[1822]	215	mass(m) = mass(m) + mass(n) * collection_probability
	216	weight(n) = weight(n) - weight(n) * collection_probability
	217	mass(n) = mass(n) - mass(n) * collection_probability
	218	ELSE
[1071]	219	!
[1822]	220	!-- Same-size collections. If n = m, weight is reduced by the
	221	!-- number of possible same-size collections; the total mass
	222	!-- is not changed during same-size collection.
	223	!-- Same-size collections of different
	224	!-- particles ( n /= m ) are treated as same-size collections
	225	!-- of ONE partilce with weight = weight(n) + weight(m) and
	226	!-- mass = mass(n) + mass(m).
	227	!-- Accordingly, each particle loses the same number of
	228	!-- droplets to the other particle, but this has no effect on
	229	!-- total mass mass, since the exchanged droplets have the
	230	!-- same radius.
[849]	231
[1822]	232	!-- Note: For m = n this equation is an approximation only
	233	!-- valid for weight >> 1 (which is usually the case). The
	234	!-- approximation is weight(n)-1 = weight(n).
	235	weight(n) = weight(n) - 0.5_wp * weight(n) * &
	236	ckernel(rclass_l,rclass_s,eclass) * &
	237	weight(m) * ddV * dt_3d
	238	IF ( n .NE. m ) THEN
	239	weight(m) = weight(m) - 0.5_wp * weight(m) * &
	240	ckernel(rclass_l,rclass_s,eclass) * &
	241	weight(n) * ddV * dt_3d
	242	ENDIF
	243	ENDIF
[1071]	244
[1822]	245	ENDDO
[1071]	246
[1822]	247	ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass
	248
[1359]	249	ENDDO
[849]	250
[1822]	251	ELSEIF ( all_or_nothing ) THEN ! select collision algorithm
[849]	252
[1822]	253	DO n = 1, number_of_particles
[849]	254
[1822]	255	rclass_l = particles(n)%class
	256	xn = mass(n) / weight(n) ! mean mass of droplet n
[849]	257
[1822]	258	DO m = n, number_of_particles
[849]	259
[1822]	260	rclass_s = particles(m)%class
	261	xm = mass(m) / weight(m) ! mean mass of droplet m
[849]	262
[1822]	263	IF ( weight(n) .LT. weight(m) ) THEN
	264	!
	265	!-- Particle n collects weight(n) droplets of particle m
	266	collection_probability = ckernel(rclass_l,rclass_s,eclass) * &
	267	weight(m) * ddV * dt_3d
[1071]	268
[1822]	269	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
	270	mass(n) = mass(n) + weight(n) * xm
	271	weight(m) = weight(m) - weight(n)
	272	mass(m) = mass(m) - weight(n) * xm
	273	ENDIF
	274
	275	ELSEIF ( weight(m) .LT. weight(n) ) THEN
[849]	276	!
[1822]	277	!-- Particle m collects weight(m) droplets of particle n
	278	collection_probability = ckernel(rclass_l,rclass_s,eclass) * &
	279	weight(n) * ddV * dt_3d
	280
	281	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
	282	mass(m) = mass(m) + weight(m) * xn
	283	weight(n) = weight(n) - weight(m)
	284	mass(n) = mass(n) - weight(m) * xn
	285	ENDIF
	286	ELSE
[849]	287	!
[1822]	288	!-- Collisions of particles of the same weighting factor.
	289	!-- Particle n collects 1/2 weight(n) droplets of particle m,
	290	!-- particle m collects 1/2 weight(m) droplets of particle n.
	291	!-- The total mass mass changes accordingly.
	292	!-- If n = m, the first half of the droplets coalesces with the
	293	!-- second half of the droplets; mass is unchanged because
	294	!-- xm = xn for n = m.
[849]	295
[1822]	296	!-- Note: For m = n this equation is an approximation only
	297	!-- valid for weight >> 1 (which is usually the case). The
	298	!-- approximation is weight(n)-1 = weight(n).
	299	collection_probability = ckernel(rclass_l,rclass_s,eclass) * &
	300	weight(n) * ddV * dt_3d
[849]	301
[1822]	302	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
	303	mass(n) = mass(n) + 0.5_wp * weight(n) * ( xm - xn )
	304	mass(m) = mass(m) + 0.5_wp * weight(m) * ( xn - xm )
	305	weight(n) = weight(n) - 0.5_wp * weight(m)
	306	weight(m) = weight(n)
	307	ENDIF
	308	ENDIF
[849]	309
[1822]	310	ENDDO
[849]	311
[1822]	312	ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass
[849]	313
[1822]	314	ENDDO
[849]	315
[1822]	316	ENDIF
[849]	317
	318
	319
	320
[1822]	321	IF ( ANY(weight < 0.0_wp) ) THEN
	322	WRITE( message_string, * ) 'negative weighting'
	323	CALL message( 'lpm_droplet_collision', 'PA0028', &
	324	2, 2, -1, 6, 1 )
	325	ENDIF
[849]	326
[1822]	327	particles(1:number_of_particles)%radius = ( mass(1:number_of_particles) / &
	328	( weight(1:number_of_particles) &
	329	* factor_volume_to_mass &
	330	) &
	331	)**0.33333333333333_wp
[849]	332
[1822]	333	particles(1:number_of_particles)%weight_factor = weight(1:number_of_particles)
[849]	334
[1822]	335	DEALLOCATE(weight, mass)
[849]	336
[1822]	337	ELSEIF ( .NOT. use_kernel_tables ) THEN
	338	!
	339	!-- Collection kernels are calculated for every new
	340	!-- grid box. First, allocate memory for kernel table.
	341	!-- Third dimension is 1, because table is re-calculated for
	342	!-- every new dissipation value.
	343	ALLOCATE( ckernel(1:number_of_particles,1:number_of_particles,1:1) )
	344	!
	345	!-- Now calculate collection kernel for this box. Note that
	346	!-- the kernel is based on the previous time step
	347	CALL recalculate_kernel( i, j, k )
	348	!
	349	!-- Droplet collision are calculated using collision-coalescence
	350	!-- formulation proposed by Wang (see PALM documentation)
	351	!-- Temporary fields for total mass of super-droplet and weighting factors
	352	!-- are allocated.
	353	ALLOCATE(mass(1:number_of_particles), weight(1:number_of_particles))
[849]	354
[1822]	355	mass(1:number_of_particles) = particles(1:number_of_particles)%weight_factor * &
	356	particles(1:number_of_particles)%radius*3 &
	357	factor_volume_to_mass
[849]	358
[1822]	359	weight(1:number_of_particles) = particles(1:number_of_particles)%weight_factor
[849]	360
[1822]	361	IF ( average_impact ) THEN ! select collision algorithm
[849]	362
[1822]	363	DO n = 1, number_of_particles
[849]	364
[1822]	365	xn = mass(n) / weight(n) ! mean mass of droplet n
[849]	366
[1822]	367	DO m = n, number_of_particles
[849]	368
[1822]	369	xm = mass(m) / weight(m) !mean mass of droplet m
[849]	370
[1822]	371	IF ( xm .LT. xn ) THEN
[849]	372	!
[1822]	373	!-- Particle n collects smaller particle m
	374	collection_probability = ckernel(n,m,1) * weight(n) * &
	375	ddV * dt_3d
	376
	377	mass(n) = mass(n) + mass(m) * collection_probability
	378	weight(m) = weight(m) - weight(m) * collection_probability
	379	mass(m) = mass(m) - mass(m) * collection_probability
	380	ELSEIF ( xm .GT. xn ) THEN
[849]	381	!
[1822]	382	!-- Particle m collects smaller particle n
	383	collection_probability = ckernel(n,m,1) * weight(m) * &
	384	ddV * dt_3d
[849]	385
[1822]	386	mass(m) = mass(m) + mass(n) * collection_probability
	387	weight(n) = weight(n) - weight(n) * collection_probability
	388	mass(n) = mass(n) - mass(n) * collection_probability
	389	ELSE
[849]	390	!
[1822]	391	!-- Same-size collections. If n = m, weight is reduced by the
	392	!-- number of possible same-size collections; the total mass
	393	!-- mass is not changed during same-size collection.
	394	!-- Same-size collections of different
	395	!-- particles ( n /= m ) are treated as same-size collections
	396	!-- of ONE partilce with weight = weight(n) + weight(m) and
	397	!-- mass = mass(n) + mass(m).
	398	!-- Accordingly, each particle loses the same number of
	399	!-- droplets to the other particle, but this has no effect on
	400	!-- total mass mass, since the exchanged droplets have the
	401	!-- same radius.
	402	!--
	403	!-- Note: For m = n this equation is an approximation only
	404	!-- valid for weight >> 1 (which is usually the case). The
	405	!-- approximation is weight(n)-1 = weight(n).
	406	weight(n) = weight(n) - 0.5_wp * weight(n) * &
	407	ckernel(n,m,1) * weight(m) * &
	408	ddV * dt_3d
	409	IF ( n .NE. m ) THEN
	410	weight(m) = weight(m) - 0.5_wp * weight(m) * &
	411	ckernel(n,m,1) * weight(n) * &
	412	ddV * dt_3d
	413	ENDIF
	414	ENDIF
[849]	415
	416
[1359]	417	ENDDO
[849]	418
[1822]	419	ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass
[849]	420
[1822]	421	ENDDO
[849]	422
[1822]	423	ELSEIF ( all_or_nothing ) THEN ! select collision algorithm
[849]	424
[1822]	425	DO n = 1, number_of_particles
[849]	426
[1822]	427	xn = mass(n) / weight(n) ! mean mass of droplet n
[849]	428
[1822]	429	DO m = n, number_of_particles
[849]	430
[1822]	431	xm = mass(m) / weight(m) !mean mass of droplet m
[849]	432
[1822]	433	IF ( weight(n) .LT. weight(m) ) THEN
	434	!
	435	!-- Particle n collects smaller particle m
	436	collection_probability = ckernel(n,m,1) * weight(m) * &
	437	ddV * dt_3d
[1071]	438
[1822]	439	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
	440	mass(n) = mass(n) + weight(n) * xm
	441	weight(m) = weight(m) - weight(n)
	442	mass(m) = mass(m) - weight(n) * xm
	443	ENDIF
[1359]	444
[1822]	445	ELSEIF ( weight(m) .LT. weight(n) ) THEN
[1071]	446	!
[1822]	447	!-- Particle m collects smaller particle n
	448	collection_probability = ckernel(n,m,1) * weight(n) * &
	449	ddV * dt_3d
[1071]	450
[1822]	451	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
	452	mass(m) = mass(m) + weight(m) * xn
	453	weight(n) = weight(n) - weight(m)
	454	mass(n) = mass(n) - weight(m) * xn
	455	ENDIF
	456	ELSE
	457	!
	458	!-- Collisions of particles of the same weighting factor.
	459	!-- Particle n collects 1/2 weight(n) droplets of particle m,
	460	!-- particle m collects 1/2 weight(m) droplets of particle n.
	461	!-- The total mass mass changes accordingly.
	462	!-- If n = m, the first half of the droplets coalesces with the
	463	!-- second half of the droplets; mass is unchanged because
	464	!-- xm = xn for n = m.
	465	!--
	466	!-- Note: For m = n this equation is an approximation only
	467	!-- valid for weight >> 1 (which is usually the case). The
	468	!-- approximation is weight(n)-1 = weight(n).
	469	collection_probability = ckernel(n,m,1) * weight(n) * &
	470	ddV * dt_3d
[1071]	471
[1822]	472	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
	473	mass(n) = mass(n) + 0.5_wp * weight(n) * ( xm - xn )
	474	mass(m) = mass(m) + 0.5_wp * weight(m) * ( xn - xm )
	475	weight(n) = weight(n) - 0.5_wp * weight(m)
	476	weight(m) = weight(n)
	477	ENDIF
	478	ENDIF
[1071]	479
	480
[1822]	481	ENDDO
[1071]	482
[1822]	483	ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass
[1071]	484
[1822]	485	ENDDO
[1071]	486
[1822]	487	ENDIF
[1071]	488
[1822]	489	IF ( ANY(weight < 0.0_wp) ) THEN
	490	WRITE( message_string, * ) 'negative weighting'
	491	CALL message( 'lpm_droplet_collision', 'PA0028', &
	492	2, 2, -1, 6, 1 )
	493	ENDIF
	494
	495	particles(1:number_of_particles)%radius = ( mass(1:number_of_particles) / &
	496	( weight(1:number_of_particles) &
	497	* factor_volume_to_mass &
	498	) &
	499	)**0.33333333333333_wp
	500
	501	particles(1:number_of_particles)%weight_factor = weight(1:number_of_particles)
	502
	503	DEALLOCATE( weight, mass, ckernel )
	504
	505	ENDIF
	506
[1359]	507	ENDIF
[1822]	508
[849]	509
	510	!
[1822]	511	!-- Check if LWC is conserved during collision process
[1359]	512	IF ( ql_v(k,j,i) /= 0.0_wp ) THEN
[1822]	513	IF ( ql_vp(k,j,i) / ql_v(k,j,i) >= 1.0001_wp .OR. &
[1359]	514	ql_vp(k,j,i) / ql_v(k,j,i) <= 0.9999_wp ) THEN
[1822]	515	WRITE( message_string, * ) ' LWC is not conserved during', &
	516	' collision! ', &
	517	' LWC after condensation: ', ql_v(k,j,i), &
	518	' LWC after collision: ', ql_vp(k,j,i)
	519	CALL message( 'lpm_droplet_collision', 'PA0040', 2, 2, -1, 6, 1 )
[1359]	520	ENDIF
	521	ENDIF
[849]	522
	523	CALL cpu_log( log_point_s(43), 'lpm_droplet_coll', 'stop' )
	524
[1359]	525	END SUBROUTINE lpm_droplet_collision

Note: See TracBrowser for help on using the repository browser.

Download in other formats:

| Impressum | ©Leibniz Universität Hannover |