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source: palm/trunk/SOURCE/lpm_droplet_collision.f90 @ 2000

Last change on this file since 2000 was 2000, checked in by knoop, 8 years ago
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1	!> @file lpm_droplet_collision.f90
2	!------------------------------------------------------------------------------!
3	! This file is part of PALM.
4	!
5	! PALM is free software: you can redistribute it and/or modify it under the
6	! terms of the GNU General Public License as published by the Free Software
7	! Foundation, either version 3 of the License, or (at your option) any later
8	! version.
9	!
10	! PALM is distributed in the hope that it will be useful, but WITHOUT ANY
11	! WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
12	! A PARTICULAR PURPOSE. See the GNU General Public License for more details.
13	!
14	! You should have received a copy of the GNU General Public License along with
15	! PALM. If not, see <http://www.gnu.org/licenses/>.
16	!
17	! Copyright 1997-2016 Leibniz Universitaet Hannover
18	!------------------------------------------------------------------------------!
19	!
20	! Current revisions:
21	! ------------------
22	! Forced header and separation lines into 80 columns
23	!
24	! Former revisions:
25	! -----------------
26	! $Id: lpm_droplet_collision.f90 2000 2016-08-20 18:09:15Z knoop $
27	!
28	! 1884 2016-04-21 11:11:40Z hoffmann
29	! Conservation of mass should only be checked if collisions took place.
30	!
31	! 1860 2016-04-13 13:21:28Z hoffmann
32	! Interpolation of dissipation rate adjusted to more reasonable values.
33	!
34	! 1822 2016-04-07 07:49:42Z hoffmann
35	! Integration of a new collision algortithm based on Shima et al. (2009) and
36	! Soelch and Kaercher (2010) called all_or_nothing. The previous implemented
37	! collision algorithm is called average_impact. Moreover, both algorithms are
38	! now positive definit due to their construction, i.e., no negative weighting
39	! factors should occur.
40	!
41	! 1682 2015-10-07 23:56:08Z knoop
42	! Code annotations made doxygen readable
43	!
44	! 1359 2014-04-11 17:15:14Z hoffmann
45	! New particle structure integrated.
46	! Kind definition added to all floating point numbers.
47	!
48	! 1322 2014-03-20 16:38:49Z raasch
49	! REAL constants defined as wp_kind
50	!
51	! 1320 2014-03-20 08:40:49Z raasch
52	! ONLY-attribute added to USE-statements,
53	! kind-parameters added to all INTEGER and REAL declaration statements,
54	! kinds are defined in new module kinds,
55	! revision history before 2012 removed,
56	! comment fields (!:) to be used for variable explanations added to
57	! all variable declaration statements
58	!
59	! 1092 2013-02-02 11:24:22Z raasch
60	! unused variables removed
61	!
62	! 1071 2012-11-29 16:54:55Z franke
63	! Calculation of Hall and Wang kernel now uses collision-coalescence formulation
64	! proposed by Wang instead of the continuous collection equation (for more
65	! information about new method see PALM documentation)
66	! Bugfix: message identifiers added
67	!
68	! 1036 2012-10-22 13:43:42Z raasch
69	! code put under GPL (PALM 3.9)
70	!
71	! 849 2012-03-15 10:35:09Z raasch
72	! initial revision (former part of advec_particles)
73	!
74	!
75	! Description:
76	! ------------
77	!> Calculates change in droplet radius by collision. Droplet collision is
78	!> calculated for each grid box seperately. Collision is parameterized by
79	!> using collision kernels. Two different kernels are available:
80	!> Hall kernel: Kernel from Hall (1980, J. Atmos. Sci., 2486-2507), which
81	!> considers collision due to pure gravitational effects.
82	!> Wang kernel: Beside gravitational effects (treated with the Hall-kernel) also
83	!> the effects of turbulence on the collision are considered using
84	!> parameterizations of Ayala et al. (2008, New J. Phys., 10,
85	!> 075015) and Wang and Grabowski (2009, Atmos. Sci. Lett., 10,
86	!> 1-8). This kernel includes three possible effects of turbulence:
87	!> the modification of the relative velocity between the droplets,
88	!> the effect of preferential concentration, and the enhancement of
89	!> collision efficiencies.
90	!------------------------------------------------------------------------------!
91	SUBROUTINE lpm_droplet_collision (i,j,k)
92
93
94
95	USE arrays_3d, &
96	ONLY: diss, ql_v, ql_vp
97
98	USE cloud_parameters, &
99	ONLY: rho_l
100
101	USE constants, &
102	ONLY: pi
103
104	USE control_parameters, &
105	ONLY: dt_3d, message_string, dz
106
107	USE cpulog, &
108	ONLY: cpu_log, log_point_s
109
110	USE grid_variables, &
111	ONLY: dx, dy
112
113	USE kinds
114
115	USE lpm_collision_kernels_mod, &
116	ONLY: ckernel, recalculate_kernel
117
118	USE particle_attributes, &
119	ONLY: all_or_nothing, average_impact, dissipation_classes, &
120	hall_kernel, iran_part, number_of_particles, particles, &
121	particle_type, prt_count, use_kernel_tables, wang_kernel
122
123	USE random_function_mod, &
124	ONLY: random_function
125
126	USE pegrid
127
128	IMPLICIT NONE
129
130	INTEGER(iwp) :: eclass !<
131	INTEGER(iwp) :: i !<
132	INTEGER(iwp) :: j !<
133	INTEGER(iwp) :: k !<
134	INTEGER(iwp) :: n !<
135	INTEGER(iwp) :: m !<
136	INTEGER(iwp) :: rclass_l !<
137	INTEGER(iwp) :: rclass_s !<
138
139	REAL(wp) :: collection_probability !< probability for collection
140	REAL(wp) :: ddV !< inverse grid box volume
141	REAL(wp) :: epsilon !< dissipation rate
142	REAL(wp) :: factor_volume_to_mass !< 4.0 / 3.0 * pi * rho_l
143	REAL(wp) :: xm !< mean mass of droplet m
144	REAL(wp) :: xn !< mean mass of droplet n
145
146	REAL(wp), DIMENSION(:), ALLOCATABLE :: weight !< weighting factor
147	REAL(wp), DIMENSION(:), ALLOCATABLE :: mass !< total mass of super droplet
148
149	CALL cpu_log( log_point_s(43), 'lpm_droplet_coll', 'start' )
150
151	number_of_particles = prt_count(k,j,i)
152	factor_volume_to_mass = 4.0_wp / 3.0_wp * pi * rho_l
153	ddV = 1 / ( dx * dy * dz )
154	!
155	!-- Collision requires at least one super droplet inside the box
156	IF ( number_of_particles > 0 ) THEN
157
158	!
159	!-- Now apply the different kernels
160	IF ( use_kernel_tables ) THEN
161	!
162	!-- Fast method with pre-calculated collection kernels for
163	!-- discrete radius- and dissipation-classes.
164	!--
165	!-- Determine dissipation class index of this gridbox
166	IF ( wang_kernel ) THEN
167	eclass = INT( diss(k,j,i) * 1.0E4_wp / 600.0_wp * &
168	dissipation_classes ) + 1
169	epsilon = diss(k,j,i)
170	ELSE
171	epsilon = 0.0_wp
172	ENDIF
173	IF ( hall_kernel .OR. epsilon * 1.0E4_wp < 0.001_wp ) THEN
174	eclass = 0 ! Hall kernel is used
175	ELSE
176	eclass = MIN( dissipation_classes, eclass )
177	ENDIF
178
179	!
180	!-- Droplet collision are calculated using collision-coalescence
181	!-- formulation proposed by Wang (see PALM documentation)
182	!-- Temporary fields for total mass of super-droplet and weighting factors
183	!-- are allocated.
184	ALLOCATE(mass(1:number_of_particles), weight(1:number_of_particles))
185
186	mass(1:number_of_particles) = particles(1:number_of_particles)%weight_factor * &
187	particles(1:number_of_particles)%radius*3 &
188	factor_volume_to_mass
189	weight(1:number_of_particles) = particles(1:number_of_particles)%weight_factor
190
191	IF ( average_impact ) THEN ! select collision algorithm
192
193	DO n = 1, number_of_particles
194
195	rclass_l = particles(n)%class
196	xn = mass(n) / weight(n)
197
198	DO m = n, number_of_particles
199
200	rclass_s = particles(m)%class
201	xm = mass(m) / weight(m)
202
203	IF ( xm .LT. xn ) THEN
204
205	!
206	!-- Particle n collects smaller particle m
207	collection_probability = ckernel(rclass_l,rclass_s,eclass) * &
208	weight(n) * ddV * dt_3d
209
210	mass(n) = mass(n) + mass(m) * collection_probability
211	weight(m) = weight(m) - weight(m) * collection_probability
212	mass(m) = mass(m) - mass(m) * collection_probability
213	ELSEIF ( xm .GT. xn ) THEN
214	!
215	!-- Particle m collects smaller particle n
216	collection_probability = ckernel(rclass_l,rclass_s,eclass) * &
217	weight(m) * ddV * dt_3d
218
219	mass(m) = mass(m) + mass(n) * collection_probability
220	weight(n) = weight(n) - weight(n) * collection_probability
221	mass(n) = mass(n) - mass(n) * collection_probability
222	ELSE
223	!
224	!-- Same-size collections. If n = m, weight is reduced by the
225	!-- number of possible same-size collections; the total mass
226	!-- is not changed during same-size collection.
227	!-- Same-size collections of different
228	!-- particles ( n /= m ) are treated as same-size collections
229	!-- of ONE partilce with weight = weight(n) + weight(m) and
230	!-- mass = mass(n) + mass(m).
231	!-- Accordingly, each particle loses the same number of
232	!-- droplets to the other particle, but this has no effect on
233	!-- total mass mass, since the exchanged droplets have the
234	!-- same radius.
235
236	!-- Note: For m = n this equation is an approximation only
237	!-- valid for weight >> 1 (which is usually the case). The
238	!-- approximation is weight(n)-1 = weight(n).
239	weight(n) = weight(n) - 0.5_wp * weight(n) * &
240	ckernel(rclass_l,rclass_s,eclass) * &
241	weight(m) * ddV * dt_3d
242	IF ( n .NE. m ) THEN
243	weight(m) = weight(m) - 0.5_wp * weight(m) * &
244	ckernel(rclass_l,rclass_s,eclass) * &
245	weight(n) * ddV * dt_3d
246	ENDIF
247	ENDIF
248
249	ENDDO
250
251	ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass
252
253	ENDDO
254
255	ELSEIF ( all_or_nothing ) THEN ! select collision algorithm
256
257	DO n = 1, number_of_particles
258
259	rclass_l = particles(n)%class
260	xn = mass(n) / weight(n) ! mean mass of droplet n
261
262	DO m = n, number_of_particles
263
264	rclass_s = particles(m)%class
265	xm = mass(m) / weight(m) ! mean mass of droplet m
266
267	IF ( weight(n) .LT. weight(m) ) THEN
268	!
269	!-- Particle n collects weight(n) droplets of particle m
270	collection_probability = ckernel(rclass_l,rclass_s,eclass) * &
271	weight(m) * ddV * dt_3d
272
273	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
274	mass(n) = mass(n) + weight(n) * xm
275	weight(m) = weight(m) - weight(n)
276	mass(m) = mass(m) - weight(n) * xm
277	ENDIF
278
279	ELSEIF ( weight(m) .LT. weight(n) ) THEN
280	!
281	!-- Particle m collects weight(m) droplets of particle n
282	collection_probability = ckernel(rclass_l,rclass_s,eclass) * &
283	weight(n) * ddV * dt_3d
284
285	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
286	mass(m) = mass(m) + weight(m) * xn
287	weight(n) = weight(n) - weight(m)
288	mass(n) = mass(n) - weight(m) * xn
289	ENDIF
290	ELSE
291	!
292	!-- Collisions of particles of the same weighting factor.
293	!-- Particle n collects 1/2 weight(n) droplets of particle m,
294	!-- particle m collects 1/2 weight(m) droplets of particle n.
295	!-- The total mass mass changes accordingly.
296	!-- If n = m, the first half of the droplets coalesces with the
297	!-- second half of the droplets; mass is unchanged because
298	!-- xm = xn for n = m.
299
300	!-- Note: For m = n this equation is an approximation only
301	!-- valid for weight >> 1 (which is usually the case). The
302	!-- approximation is weight(n)-1 = weight(n).
303	collection_probability = ckernel(rclass_l,rclass_s,eclass) * &
304	weight(n) * ddV * dt_3d
305
306	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
307	mass(n) = mass(n) + 0.5_wp * weight(n) * ( xm - xn )
308	mass(m) = mass(m) + 0.5_wp * weight(m) * ( xn - xm )
309	weight(n) = weight(n) - 0.5_wp * weight(m)
310	weight(m) = weight(n)
311	ENDIF
312	ENDIF
313
314	ENDDO
315
316	ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass
317
318	ENDDO
319
320	ENDIF
321
322
323
324
325	IF ( ANY(weight < 0.0_wp) ) THEN
326	WRITE( message_string, * ) 'negative weighting'
327	CALL message( 'lpm_droplet_collision', 'PA0028', &
328	2, 2, -1, 6, 1 )
329	ENDIF
330
331	particles(1:number_of_particles)%radius = ( mass(1:number_of_particles) / &
332	( weight(1:number_of_particles) &
333	* factor_volume_to_mass &
334	) &
335	)**0.33333333333333_wp
336
337	particles(1:number_of_particles)%weight_factor = weight(1:number_of_particles)
338
339	DEALLOCATE(weight, mass)
340
341	ELSEIF ( .NOT. use_kernel_tables ) THEN
342	!
343	!-- Collection kernels are calculated for every new
344	!-- grid box. First, allocate memory for kernel table.
345	!-- Third dimension is 1, because table is re-calculated for
346	!-- every new dissipation value.
347	ALLOCATE( ckernel(1:number_of_particles,1:number_of_particles,1:1) )
348	!
349	!-- Now calculate collection kernel for this box. Note that
350	!-- the kernel is based on the previous time step
351	CALL recalculate_kernel( i, j, k )
352	!
353	!-- Droplet collision are calculated using collision-coalescence
354	!-- formulation proposed by Wang (see PALM documentation)
355	!-- Temporary fields for total mass of super-droplet and weighting factors
356	!-- are allocated.
357	ALLOCATE(mass(1:number_of_particles), weight(1:number_of_particles))
358
359	mass(1:number_of_particles) = particles(1:number_of_particles)%weight_factor * &
360	particles(1:number_of_particles)%radius*3 &
361	factor_volume_to_mass
362
363	weight(1:number_of_particles) = particles(1:number_of_particles)%weight_factor
364
365	IF ( average_impact ) THEN ! select collision algorithm
366
367	DO n = 1, number_of_particles
368
369	xn = mass(n) / weight(n) ! mean mass of droplet n
370
371	DO m = n, number_of_particles
372
373	xm = mass(m) / weight(m) !mean mass of droplet m
374
375	IF ( xm .LT. xn ) THEN
376	!
377	!-- Particle n collects smaller particle m
378	collection_probability = ckernel(n,m,1) * weight(n) * &
379	ddV * dt_3d
380
381	mass(n) = mass(n) + mass(m) * collection_probability
382	weight(m) = weight(m) - weight(m) * collection_probability
383	mass(m) = mass(m) - mass(m) * collection_probability
384	ELSEIF ( xm .GT. xn ) THEN
385	!
386	!-- Particle m collects smaller particle n
387	collection_probability = ckernel(n,m,1) * weight(m) * &
388	ddV * dt_3d
389
390	mass(m) = mass(m) + mass(n) * collection_probability
391	weight(n) = weight(n) - weight(n) * collection_probability
392	mass(n) = mass(n) - mass(n) * collection_probability
393	ELSE
394	!
395	!-- Same-size collections. If n = m, weight is reduced by the
396	!-- number of possible same-size collections; the total mass
397	!-- mass is not changed during same-size collection.
398	!-- Same-size collections of different
399	!-- particles ( n /= m ) are treated as same-size collections
400	!-- of ONE partilce with weight = weight(n) + weight(m) and
401	!-- mass = mass(n) + mass(m).
402	!-- Accordingly, each particle loses the same number of
403	!-- droplets to the other particle, but this has no effect on
404	!-- total mass mass, since the exchanged droplets have the
405	!-- same radius.
406	!--
407	!-- Note: For m = n this equation is an approximation only
408	!-- valid for weight >> 1 (which is usually the case). The
409	!-- approximation is weight(n)-1 = weight(n).
410	weight(n) = weight(n) - 0.5_wp * weight(n) * &
411	ckernel(n,m,1) * weight(m) * &
412	ddV * dt_3d
413	IF ( n .NE. m ) THEN
414	weight(m) = weight(m) - 0.5_wp * weight(m) * &
415	ckernel(n,m,1) * weight(n) * &
416	ddV * dt_3d
417	ENDIF
418	ENDIF
419
420
421	ENDDO
422
423	ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass
424
425	ENDDO
426
427	ELSEIF ( all_or_nothing ) THEN ! select collision algorithm
428
429	DO n = 1, number_of_particles
430
431	xn = mass(n) / weight(n) ! mean mass of droplet n
432
433	DO m = n, number_of_particles
434
435	xm = mass(m) / weight(m) !mean mass of droplet m
436
437	IF ( weight(n) .LT. weight(m) ) THEN
438	!
439	!-- Particle n collects smaller particle m
440	collection_probability = ckernel(n,m,1) * weight(m) * &
441	ddV * dt_3d
442
443	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
444	mass(n) = mass(n) + weight(n) * xm
445	weight(m) = weight(m) - weight(n)
446	mass(m) = mass(m) - weight(n) * xm
447	ENDIF
448
449	ELSEIF ( weight(m) .LT. weight(n) ) THEN
450	!
451	!-- Particle m collects smaller particle n
452	collection_probability = ckernel(n,m,1) * weight(n) * &
453	ddV * dt_3d
454
455	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
456	mass(m) = mass(m) + weight(m) * xn
457	weight(n) = weight(n) - weight(m)
458	mass(n) = mass(n) - weight(m) * xn
459	ENDIF
460	ELSE
461	!
462	!-- Collisions of particles of the same weighting factor.
463	!-- Particle n collects 1/2 weight(n) droplets of particle m,
464	!-- particle m collects 1/2 weight(m) droplets of particle n.
465	!-- The total mass mass changes accordingly.
466	!-- If n = m, the first half of the droplets coalesces with the
467	!-- second half of the droplets; mass is unchanged because
468	!-- xm = xn for n = m.
469	!--
470	!-- Note: For m = n this equation is an approximation only
471	!-- valid for weight >> 1 (which is usually the case). The
472	!-- approximation is weight(n)-1 = weight(n).
473	collection_probability = ckernel(n,m,1) * weight(n) * &
474	ddV * dt_3d
475
476	IF ( collection_probability .GT. random_function( iran_part ) ) THEN
477	mass(n) = mass(n) + 0.5_wp * weight(n) * ( xm - xn )
478	mass(m) = mass(m) + 0.5_wp * weight(m) * ( xn - xm )
479	weight(n) = weight(n) - 0.5_wp * weight(m)
480	weight(m) = weight(n)
481	ENDIF
482	ENDIF
483
484
485	ENDDO
486
487	ql_vp(k,j,i) = ql_vp(k,j,i) + mass(n) / factor_volume_to_mass
488
489	ENDDO
490
491	ENDIF
492
493	IF ( ANY(weight < 0.0_wp) ) THEN
494	WRITE( message_string, * ) 'negative weighting'
495	CALL message( 'lpm_droplet_collision', 'PA0028', &
496	2, 2, -1, 6, 1 )
497	ENDIF
498
499	particles(1:number_of_particles)%radius = ( mass(1:number_of_particles) / &
500	( weight(1:number_of_particles) &
501	* factor_volume_to_mass &
502	) &
503	)**0.33333333333333_wp
504
505	particles(1:number_of_particles)%weight_factor = weight(1:number_of_particles)
506
507	DEALLOCATE( weight, mass, ckernel )
508
509	ENDIF
510
511	!
512	!-- Check if LWC is conserved during collision process
513	IF ( ql_v(k,j,i) /= 0.0_wp ) THEN
514	IF ( ql_vp(k,j,i) / ql_v(k,j,i) >= 1.0001_wp .OR. &
515	ql_vp(k,j,i) / ql_v(k,j,i) <= 0.9999_wp ) THEN
516	WRITE( message_string, * ) ' LWC is not conserved during', &
517	' collision! ', &
518	' LWC after condensation: ', ql_v(k,j,i), &
519	' LWC after collision: ', ql_vp(k,j,i)
520	CALL message( 'lpm_droplet_collision', 'PA0040', 2, 2, -1, 6, 1 )
521	ENDIF
522	ENDIF
523
524	ENDIF
525
526	CALL cpu_log( log_point_s(43), 'lpm_droplet_coll', 'stop' )
527
528	END SUBROUTINE lpm_droplet_collision

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