def main():
basepath = str(Path(__file__).parent.absolute())
IO_PARAMS = {
'problem_type':
'flow0d', # solid, fluid, flow0d, solid_flow0d, fluid_flow0d
'write_results_every': -999,
'output_path': '' + basepath + '/tmp',
'simname': 'test'
}
SOLVER_PARAMS = {'tol_res': 1.0e-8, 'tol_inc': 1.0e-8}
TIME_PARAMS = {
'maxtime': 10 * 1.0,
'numstep': 10 * 100,
'timint': 'ost', # ost
'theta_ost': 0.5,
'initial_conditions': init(),
'eps_periodic': 0.03,
'periodic_checktype': 'pQvar'
}
MODEL_PARAMS = {
'modeltype': 'syspulcap',
'parameters': param(),
'chamber_models': {
'lv': {
'type': '0D_elast',
'activation_curve': 2
},
'rv': {
'type': '0D_elast',
'activation_curve': 2
},
'la': {
'type': '0D_elast',
'activation_curve': 1
},
'ra': {
'type': '0D_elast',
'activation_curve': 1
}
}
}
# define your time curves here (syntax: tcX refers to curve X)
class time_curves():
def tc1(self, t): # atrial activation
act_dur = 2. * param()['t_ed']
t0 = 0.
if t >= t0 and t <= t0 + act_dur:
return 0.5 * (1. - np.cos(2. * np.pi * (t - t0) / act_dur))
else:
return 0.0
def tc2(self, t): # ventricular activation
act_dur = 1.8 * (param()['t_es'] - param()['t_ed'])
t0 = param()['t_ed']
if t >= t0 and t <= t0 + act_dur:
return 0.5 * (1. - np.cos(2. * np.pi * (t - t0) / act_dur))
else:
return 0.0
# problem setup
problem = ambit.Ambit(IO_PARAMS,
TIME_PARAMS,
SOLVER_PARAMS,
constitutive_params=MODEL_PARAMS,
time_curves=time_curves())
# solve time-dependent problem
problem.solve_problem()
# --- results check
tol = 1.0e-6
s_corr = np.zeros(problem.mp.cardvasc0D.numdof)
# correct results
s_corr[0] = 2.9433926104934122E+04
s_corr[1] = 7.0386144010472729E-01
s_corr[2] = 4.2678334743198088E-01
s_corr[3] = 6.7442751399979128E-01
s_corr[4] = 7.8447355051941843E+00
s_corr[5] = 4.6065595569000950E+04
s_corr[6] = 7.5426962510972304E+00
s_corr[7] = -1.1478898357265389E+04
s_corr[8] = -1.0718237002034781E+04
s_corr[9] = -8.4007390955961782E+03
s_corr[10] = -5.7419312828933507E+03
s_corr[11] = -1.9132875426215376E+03
s_corr[12] = 2.1087309064812008E+00
s_corr[13] = 1.9898868996888057E+04
s_corr[14] = 2.0751857916695799E+00
s_corr[15] = 1.7186285836733463E+04
s_corr[16] = 2.0732040949606132E+00
s_corr[17] = 1.3479806604615822E+04
s_corr[18] = 2.0782222891608901E+00
s_corr[19] = 9.2042331302840139E+03
s_corr[20] = 2.0766705496498501E+00
s_corr[21] = 3.0595541185596117E+03
s_corr[22] = 1.7839813644519802E+00
s_corr[23] = -4.6650427627891768E+04
s_corr[24] = 3.4387975523172128E+04
s_corr[25] = 5.3317892047428794E-01
s_corr[26] = 8.9862420216417258E-02
s_corr[27] = 4.9879094495111614E-01
s_corr[28] = 1.8877949970498080E+00
s_corr[29] = 1.2785936834889279E+04
s_corr[30] = 1.7919004707881436E+00
s_corr[31] = -8.4133350499779073E+04
s_corr[32] = 1.6151509560740245E+00
s_corr[33] = -5.9085660502758556E+03
check1 = results_check.results_check_vec(problem.mp.s,
s_corr,
problem.mp.comm,
tol=tol)
success = results_check.success_check([check1], problem.mp.comm)
return success
def main():
basepath = str(Path(__file__).parent.absolute())
IO_PARAMS = {'problem_type' : 'solid_flow0d_multiscale_gandr',
'mesh_domain' : ''+basepath+'/input/heart3Dcoarse_domain.xdmf',
'mesh_boundary' : ''+basepath+'/input/heart3Dcoarse_boundary.xdmf',
'fiber_data' : {'nodal' : [''+basepath+'/input/fib_fiber_coords_nodal_3Dcoarse.txt',''+basepath+'/input/fib_sheet_coords_nodal_3Dcoarse.txt']},
'write_results_every' : 1,
'output_path' : ''+basepath+'/tmp',
'results_to_write' : ['displacement','theta','phi_remod','fiberstretch_e'],
'simname' : 'multiscale_eccentric_mr'}
SOLVER_PARAMS_SOLID = {'solve_type' : 'direct', # direct, iterative
'tol_res' : 1.0e-8,
'tol_inc' : 1.0e-8,
'divergence_continue' : 'PTC',
'k_ptc_initial' : 10.0,
'print_local_iter' : False,
'tol_res_local' : 1.0e-10,
'tol_inc_local' : 1.0e-10}
SOLVER_PARAMS_FLOW0D = {'tol_res' : 1.0e-6,
'tol_inc' : 1.0e-6}
TIME_PARAMS_SOLID_SMALL = {'maxtime' : 1.0*100,
'numstep' : 50*100,
'timint' : 'genalpha',
'theta_ost' : 1.0,
'rho_inf_genalpha' : 0.8}
TIME_PARAMS_SOLID_LARGE = {'maxtime' : 2592000.0, # 1 month: 30*24*60*60 s
'numstep' : 1000,
'timint' : 'static'}
TIME_PARAMS_FLOW0D = {'timint' : 'ost', # ost
'theta_ost' : 0.5,
'eps_periodic' : 999,
'periodic_checktype' : 'pQvar',
'initial_file' : ''+basepath+'/input/initial_syspulcap_multiscale.txt'}
MODEL_PARAMS_FLOW0D = {'modeltype' : 'syspulcap',
'parameters' : param(),
'chamber_models' : {'lv' : {'type' : '3D_solid'}, 'rv' : {'type' : '3D_solid'}, 'la' : {'type' : '0D_elast', 'activation_curve' : 2}, 'ra' : {'type' : '0D_elast', 'activation_curve' : 2}},
'perturb_type' : ['mr',1.0e-6],
'perturb_after_cylce' : 1}
FEM_PARAMS = {'order_disp' : 1,
'order_pres' : 1,
'quad_degree' : 1,
'incompressible_2field' : False,
'prestress_initial' : True,
'lin_remodeling_full' : False}
COUPLING_PARAMS = {'surface_ids' : [[1],[2]],
'coupling_quantity' : ['volume','volume'],
'coupling_type' : 'monolithic_direct'}
MULTISCALE_GR_PARAMS = {'gandr_trigger_phase' : 'end_diastole', # end_diastole, end_systole
'numcycles' : 10,
'tol_small' : 0.08, # cycle error tolerance: overrides eps_periodic from TIME_PARAMS_FLOW0D
'tol_large' : 5.0e-3, # growth rate tolerance [mm^3/s]
'tol_outer' : 3.0e-3,
'write_checkpoints' : True,
'restart_cycle' : 0,
'restart_from_small' : False}
MATERIALS = {'MAT1' : {'guccione_dev' : {'c_0' : 1.662, 'b_f' : 14.31, 'b_t' : 4.49, 'b_fs' : 10.},
'sussmanbathe_vol' : {'kappa' : 1.0e3},
'active_fiber' : {'sigma0' : 150., 'alpha_max' : 10.0, 'alpha_min' : -30.0, 'activation_curve' : 1, 'frankstarling' : True, 'amp_min' : 1., 'amp_max' : 1.5, 'lam_threslo' : 1.01, 'lam_maxlo' : 1.15, 'lam_threshi' : 999., 'lam_maxhi' : 9999.},
'inertia' : {'rho0' : 1.0e-6},
'growth' : {'growth_dir' : 'fiber',
'growth_trig' : 'fibstretch',
'trigger_reduction' : 0.99,
'growth_thres' : 1.05,
'thres_tol' : 1.0e-3,
'thetamax' : 3.0,
'thetamin' : 1.0,
'tau_gr' : 2.0e4,
'gamma_gr' : 2.0,
'tau_gr_rev' : 4.0e4,
'gamma_gr_rev' : 2.0,
'remodeling_mat' : {'guccione_dev' : {'c_0' : 1.662, 'b_f' : 14.31, 'b_t' : 4.49, 'b_fs' : 10.},
'sussmanbathe_vol' : {'kappa' : 1.0e3}}}}}
# define your load curves here (syntax: tcX refers to curve X, to be used in BC_DICT key 'curve' : [X,0,0], or 'curve' : X)
class time_curves():
def tc1(self, t):
K = 5.
t_contr, t_relax = 0.2, 0.53
alpha_max = MATERIALS['MAT1']['active_fiber']['alpha_max']
alpha_min = MATERIALS['MAT1']['active_fiber']['alpha_min']
c1 = t_contr + alpha_max/(K*(alpha_max-alpha_min))
c2 = t_relax - alpha_max/(K*(alpha_max-alpha_min))
# Diss Hirschvogel eq. 2.101
return (K*(t-c1)+1.)*((K*(t-c1)+1.)>0.) - K*(t-c1)*((K*(t-c1))>0.) - K*(t-c2)*((K*(t-c2))>0.) + (K*(t-c2)-1.)*((K*(t-c2)-1.)>0.)
def tc2(self, t): # atrial activation
act_dur = 2.*param()['t_ed']
t0 = 0.
if t >= t0 and t <= t0 + act_dur:
return 0.5*(1.-np.cos(2.*np.pi*(t-t0)/act_dur))
else:
return 0.0
BC_DICT = { 'robin' : [{'type' : 'spring', 'id' : [3], 'dir' : 'normal', 'stiff' : 0.075},
{'type' : 'dashpot', 'id' : [3], 'dir' : 'normal', 'visc' : 0.005},
{'type' : 'spring', 'id' : [4], 'dir' : 'normal', 'stiff' : 10.0}, # 2.5, 1.25
{'type' : 'dashpot', 'id' : [4], 'dir' : 'normal', 'visc' : 0.0005},
{'type' : 'spring', 'id' : [4], 'dir' : 'xyz', 'stiff' : 0.25},
{'type' : 'dashpot', 'id' : [4], 'dir' : 'xyz', 'visc' : 0.0005}] }
# problem setup
problem = ambit.Ambit(IO_PARAMS, [TIME_PARAMS_SOLID_SMALL, TIME_PARAMS_SOLID_LARGE, TIME_PARAMS_FLOW0D], [SOLVER_PARAMS_SOLID, SOLVER_PARAMS_FLOW0D], FEM_PARAMS, [MATERIALS, MODEL_PARAMS_FLOW0D], BC_DICT, time_curves=time_curves(), coupling_params=COUPLING_PARAMS, multiscale_params=MULTISCALE_GR_PARAMS)
# solve time-dependent problem
problem.solve_problem()
# --- results check
tol = 1.0e-6
s_corr = np.zeros(problem.mp.pbsmall.pbf.cardvasc0D.numdof)
# correct 0D results
s_corr[0] = 9.8218127134072438E+03
s_corr[1] = 1.6830389591312851E+00
s_corr[2] = 6.9122581694220819E-01
s_corr[3] = 1.6732171464178778E+00
s_corr[4] = 6.1991003628749271E+00
s_corr[5] = 3.4679811145201791E+04
s_corr[6] = 5.9629754596187894E+00
s_corr[7] = -1.5127985585647235E+04
s_corr[8] = -1.4071745452471156E+04
s_corr[9] = -1.1030984515776136E+04
s_corr[10] = -7.5370923441673440E+03
s_corr[11] = -2.5111069127516153E+03
s_corr[12] = 1.9079271968625631E+00
s_corr[13] = 1.8611601990631785E+04
s_corr[14] = 1.8421266816160995E+00
s_corr[15] = 1.4042777929688003E+04
s_corr[16] = 1.8404635461013050E+00
s_corr[17] = 1.1012196762017255E+04
s_corr[18] = 1.8450877129650409E+00
s_corr[19] = 7.5357188622862641E+03
s_corr[20] = 1.8422585559378539E+00
s_corr[21] = 2.4886342151947470E+03
s_corr[22] = 1.6041858523754655E+00
s_corr[23] = -5.3410330934638907E+04
s_corr[24] = 1.4955139915285741E+04
s_corr[25] = 4.8317355188752570E-01
s_corr[26] = -4.2450391200662768E-02
s_corr[27] = 4.6821841197224007E-01
s_corr[28] = 3.1803505880679763E+00
s_corr[29] = 1.4570153064883158E+04
s_corr[30] = 3.0710744400813530E+00
s_corr[31] = -8.0065756622318950E+04
s_corr[32] = 2.8638179712861844E+00
s_corr[33] = 1.2057400362096410E+04
check1 = results_check.results_check_vec(problem.mp.pbsmall.pbf.s, s_corr, problem.mp.comm, tol=tol)
success = results_check.success_check([check1], problem.mp.comm)
return success
def main():
basepath = str(Path(__file__).parent.absolute())
IO_PARAMS = {
'problem_type':
'solid_flow0d', # solid, fluid, flow0d, solid_flow0d, fluid_flow0d
'mesh_domain': '' + basepath + '/input/chamber_domain.xdmf',
'mesh_boundary': '' + basepath + '/input/chamber_boundary.xdmf',
'write_results_every': -999,
'output_path': '' + basepath + '/tmp/',
'results_to_write': [''],
'simname': 'test'
}
SOLVER_PARAMS_SOLID = {
'solve_type': 'direct', # direct, iterative
'tol_res': 1.0e-8,
'tol_inc': 1.0e-8
}
SOLVER_PARAMS_FLOW0D = {'tol_res': 1.0e-8, 'tol_inc': 1.0e-8}
TIME_PARAMS_SOLID = {
'maxtime': 1.0,
'numstep': 20,
'numstep_stop': 10,
'timint': 'genalpha', # genalpha, ost, static
'theta_ost': 1.0,
'rho_inf_genalpha': 0.8
}
TIME_PARAMS_FLOW0D = {
'timint': 'ost', # ost
'theta_ost': 0.5,
'initial_conditions': {
'p_0': 0.0,
'q_0': 0.0,
's_0': 0.0
}
}
MODEL_PARAMS_FLOW0D = {
'modeltype': '4elwindkesselLsZ',
'parameters': {
'R': 1.0e3,
'C': 0.0,
'Z': 10.0,
'L': 5.0,
'p_ref': 0.0
}
}
FEM_PARAMS = {
'order_disp': 1,
'order_pres': 1,
'quad_degree': 1,
'incompressible_2field': False
} # True, False
COUPLING_PARAMS = {
'surface_ids': [[3]],
'coupling_quantity': 'volume',
'coupling_type': 'monolithic_direct'
}
MATERIALS = {
'MAT1': {
'neohooke_dev': {
'mu': 100.
},
'ogden_vol': {
'kappa': 100. / (1. - 2. * 0.49)
},
'inertia': {
'rho0': 1.0e-6
}
}
}
# define your load curves here (syntax: tcX refers to curve X, to be used in BC_DICT key 'curve' : [X,0,0], or 'curve' : X)
class time_curves():
def tc1(self, t):
pmax = -10.
return pmax * t / TIME_PARAMS_SOLID['maxtime']
BC_DICT = {
'dirichlet': [{
'id': [1],
'dir': 'x',
'val': 0.
}, {
'id': [3],
'dir': 'y',
'val': 0.
}, {
'id': [3],
'dir': 'z',
'val': 0.
}],
'neumann': [{
'type': 'true',
'id': [2],
'dir': 'normal',
'curve': 1
}]
}
# problem setup
problem = ambit.Ambit(IO_PARAMS, [TIME_PARAMS_SOLID, TIME_PARAMS_FLOW0D],
[SOLVER_PARAMS_SOLID, SOLVER_PARAMS_FLOW0D],
FEM_PARAMS, [MATERIALS, MODEL_PARAMS_FLOW0D],
BC_DICT,
time_curves=time_curves(),
coupling_params=COUPLING_PARAMS)
# solve time-dependent problem
problem.solve_problem()
# --- results check
tol = 1.0e-7
s_corr = np.zeros(problem.mp.pbf.cardvasc0D.numdof)
# correct 0D results
s_corr[0] = 9.2733644380642666E+00
s_corr[1] = -9.1004836216937203E-03
s_corr[2] = -1.6375196030721982E-02
check1 = results_check.results_check_vec(problem.mp.pbf.s,
s_corr,
problem.mp.comm,
tol=tol)
success = results_check.success_check([check1], problem.mp.comm)
return success
def main():
basepath = str(Path(__file__).parent.absolute())
# all possible input parameters
IO_PARAMS = {
'problem_type':
'solid_flow0d', # solid, fluid, flow0d, solid_flow0d, fluid_flow0d
'mesh_domain': '' + basepath + '/input/heart3Dcoarse_domain.xdmf',
'mesh_boundary': '' + basepath + '/input/heart3Dcoarse_boundary.xdmf',
'write_results_every': -999,
'output_path': '' + basepath + '/tmp/',
'results_to_write':
['displacement', 'pressure'], # see io_routines.py for what to write
'simname': 'test'
} # how to name the output
SOLVER_PARAMS_SOLID = {
'solve_type': 'iterative', # direct, iterative
'tol_res': 1.0e-8,
'tol_inc': 1.0e-8,
'tol_lin': 1.0e-7,
'print_liniter_every': 50,
'divergence_continue':
None, # what to apply when Newton diverges: None, PTC ('ptc' can stay False)
'ptc':
False, # if you want to use PTC straight away (independent of divergence_continue)
'k_ptc_initial': 0.1
} # initial PTC value that adapts during nonlinear iteration
SOLVER_PARAMS_FLOW0D = {'tol_res': 1.0e-6, 'tol_inc': 1.0e-6}
TIME_PARAMS_SOLID = {
'maxtime': 1.0,
'numstep': 100,
'numstep_stop': 1,
'timint': 'ost',
'theta_ost': 0.5
}
TIME_PARAMS_FLOW0D = {
'timint': 'ost',
'theta_ost': 0.5,
'initial_conditions': init(), # a dictionary
'eps_periodic': 1.0e-3, # cardiac cycle periodicity tolerance
'periodic_checktype': None
} # None, 'allvar', 'pQvar'
MODEL_PARAMS_FLOW0D = {
'modeltype': 'syspulcap',
'parameters': param(),
'chamber_models': {
'lv': {
'type': '3D_solid'
},
'rv': {
'type': '3D_solid'
},
'la': {
'type': '0D_elast',
'activation_curve': 1
},
'ra': {
'type': '0D_elast',
'activation_curve': 1
}
}
}
FEM_PARAMS = {
'order_disp':
2, # order of displacement interpolation (solid mechanics)
'order_pres':
1, # order of pressure interpolation (solid, fluid mechanics)
'quad_degree': 5, # quadrature degree
'incompressible_2field': True
} # if we want to use a 2-field functional for pressure dofs (always applies for fluid mechanics, optional for solid)
COUPLING_PARAMS = {
'surface_ids': [
[1], [2]
], # for syspul* models: order is lv, rv, la, ra (has to be consistent with chamber_models dict)
'surface_p_ids': [[1], [2]],
'coupling_quantity': [
'flux', 'flux'
], # volume, flux, pressure (former need 'monolithic_direct', latter needs 'monolithic_lagrange' as coupling_type)
'coupling_type': 'monolithic_direct'
} # monolithic_direct, monolithic_lagrange
# see solid_material.py or fluid_material.py for material laws available (and their parameters)
MATERIALS = {
'MAT1': {
'neohooke_dev': {
'mu': 10.
},
'inertia': {
'rho0': 1.0e-6
},
'rayleigh_damping': {
'eta_m': 0.0,
'eta_k': 0.0001
}
}
}
# define your load curves here (syntax: tcX refers to curve X, to be used in BC_DICT key 'curve' : [X,0,0], or 'curve' : X)
# some examples... up to 9 possible (tc1 until tc9 - feel free to implement more in timeintegration.py --> timecurves function if needed...)
class time_curves():
def tc1(self, t): # atrial activation
act_dur = 2. * param()['t_ed']
t0 = 0.
if t >= t0 and t <= t0 + act_dur:
return 0.5 * (1. - np.cos(2. * np.pi * (t - t0) / act_dur))
else:
return 0.0
BC_DICT = {
'robin': [{
'type': 'spring',
'id': [3],
'dir': 'normal',
'stiff': 0.075
}, {
'type': 'dashpot',
'id': [3],
'dir': 'normal',
'visc': 0.005
}, {
'type': 'spring',
'id': [4],
'dir': 'normal',
'stiff': 2.5
}, {
'type': 'dashpot',
'id': [4],
'dir': 'normal',
'visc': 0.0005
}, {
'type': 'spring',
'id': [4],
'dir': 'xyz',
'stiff': 0.25
}, {
'type': 'dashpot',
'id': [4],
'dir': 'xyz',
'visc': 0.0005
}]
}
# problem setup
problem = ambit.Ambit(IO_PARAMS, [TIME_PARAMS_SOLID, TIME_PARAMS_FLOW0D],
[SOLVER_PARAMS_SOLID, SOLVER_PARAMS_FLOW0D],
FEM_PARAMS, [MATERIALS, MODEL_PARAMS_FLOW0D],
BC_DICT,
time_curves=time_curves(),
coupling_params=COUPLING_PARAMS)
# problem solve
problem.solve_problem()
# --- results check
tol = 1.0e-6
s_corr = np.zeros(problem.mp.pbf.cardvasc0D.numdof)
# correct 0D results
s_corr[0] = 1.5095864743040130E+06
s_corr[1] = 1.2844204058649662E+00
s_corr[2] = -2.2965082274795714E+00
s_corr[3] = -2.2516606843904677E-01
s_corr[4] = 1.2035047944220826E+01
s_corr[5] = 7.9266376779754364E+03
s_corr[6] = 1.0920576465746846E+01
s_corr[7] = 4.8757248185773104E+04
s_corr[8] = 4.5874998121783552E+04
s_corr[9] = 3.5972406593836102E+04
s_corr[10] = 2.4558826877860327E+04
s_corr[11] = 8.1860969826562832E+03
s_corr[12] = 2.2677989771675335E+00
s_corr[13] = 8.3769499009227275E+02
s_corr[14] = 2.2702566758390823E+00
s_corr[15] = 9.5189334925959599E+02
s_corr[16] = 2.2702868360248418E+00
s_corr[17] = 7.5312458499319700E+02
s_corr[18] = 2.2701207039868367E+00
s_corr[19] = 5.0027868673701960E+02
s_corr[20] = 2.2705227157170751E+00
s_corr[21] = 1.7138025576859900E+02
s_corr[22] = 2.2541277949292278E+00
s_corr[23] = 2.0733856020336604E+05
s_corr[24] = 9.9000307744360238E+04
s_corr[25] = 2.7306345247149444E-01
s_corr[26] = -4.3686268354670260E-01
s_corr[27] = 1.7406314472713416E-01
s_corr[28] = 2.4017163277669913E+00
s_corr[29] = 1.1803816043509409E+04
s_corr[30] = 2.3131877074406706E+00
s_corr[31] = 2.0066530960234333E+05
s_corr[32] = 1.6159475288856615E+00
s_corr[33] = 3.9878128320907672E+04
check1 = results_check.results_check_vec(problem.mp.pbf.s,
s_corr,
problem.mp.comm,
tol=tol)
success = results_check.success_check([check1], problem.mp.comm)
return success
def main():
basepath = str(Path(__file__).parent.absolute())
IO_PARAMS = {
'problem_type':
'flow0d', # solid, fluid, flow0d, solid_flow0d, fluid_flow0d
'write_results_every': -999,
'output_path': '' + basepath + '/tmp/',
'simname': 'test'
}
SOLVER_PARAMS = {
'solve_type': 'direct', # direct
'tol_res': 1.0e-8,
'tol_inc': 1.0e-8
}
TIME_PARAMS = {
'maxtime': 1.0,
'numstep': 100,
'numstep_stop': 100,
'timint': 'ost', # ost
'theta_ost': 0.5,
'initial_conditions': init()
}
MODEL_PARAMS = {
'modeltype': '4elwindkesselLsZ',
'parameters': param(),
'excitation_curve': 1
}
# define your time curves here (syntax: tcX refers to curve X)
class time_curves():
def tc1(self, t):
return 0.5 * (1. - np.cos(2. * np.pi * (t) / 0.1)) + 1.0
# problem setup
problem = ambit.Ambit(IO_PARAMS,
TIME_PARAMS,
SOLVER_PARAMS,
constitutive_params=MODEL_PARAMS,
time_curves=time_curves())
# solve time-dependent problem
problem.solve_problem()
# --- results check
tol = 1.0e-7
s_corr = np.zeros(problem.mp.cardvasc0D.numdof)
# correct results
s_corr[0] = 1.0608252198133588E+00
s_corr[1] = 0.0
s_corr[2] = 0.0
check1 = results_check.results_check_vec(problem.mp.s,
s_corr,
problem.mp.comm,
tol=tol)
success = results_check.success_check([check1], problem.mp.comm)
return success
def main():
basepath = str(Path(__file__).parent.absolute())
# reads in restart step from the command line
try: restart_step = int(sys.argv[1])
except: restart_step = 0
IO_PARAMS = {'problem_type' : 'solid_flow0d', # solid, fluid, flow0d, solid_flow0d, fluid_flow0d
'mesh_domain' : ''+basepath+'/input/heart2D_domain.xdmf',
'mesh_boundary' : ''+basepath+'/input/heart2D_boundary.xdmf',
'fiber_data' : {'nodal' : [''+basepath+'/input/fib_fiber_coords_nodal_2D.txt',''+basepath+'/input/fib_sheet_coords_nodal_2D.txt']},
'write_results_every' : 1,
'output_path' : ''+basepath+'/tmp/',
'results_to_write' : ['displacement'],
'simname' : 'solid_flow0d_2Dheart',
'write_restart_every' : 1,
'restart_step' : restart_step}
SOLVER_PARAMS_SOLID = {'solve_type' : 'direct', # direct, iterative
'tol_res' : 1.0e-8,
'tol_inc' : 1.0e-8}
SOLVER_PARAMS_FLOW0D = {'tol_res' : 1.0e-6,
'tol_inc' : 1.0e-6}
TIME_PARAMS_SOLID = {'maxtime' : 1.0,
'numstep' : 500,
'numstep_stop' : 5,
'timint' : 'genalpha', # genalpha, ost, static
'theta_ost' : 1.0,
'rho_inf_genalpha' : 0.8}
TIME_PARAMS_FLOW0D = {'timint' : 'ost', # ost
'theta_ost' : 0.5,
'initial_conditions' : init()}
MODEL_PARAMS_FLOW0D = {'modeltype' : 'syspul',
'parameters' : param(),
'chamber_models' : {'lv' : {'type' : '3D_fem', 'interfaces' : 1}, 'rv' : {'type' : '3D_fem', 'interfaces' : 1}, 'la' : {'type' : '0D_elast', 'activation_curve' : 2}, 'ra' : {'type' : '0D_elast', 'activation_curve' : 2}}}
FEM_PARAMS = {'order_disp' : 1,
'order_pres' : 1,
'quad_degree' : 1,
'incompressible_2field' : False,
'prestress_initial' : True}
COUPLING_PARAMS = {'surface_ids' : [[1],[2]],
'cq_factor' : [80.,80.],
'coupling_quantity' : 'volume',
'coupling_type' : 'monolithic_direct'}
MATERIALS = {'MAT1' : {'holzapfelogden_dev' : {'a_0' : 0.059, 'b_0' : 8.023, 'a_f' : 18.472, 'b_f' : 16.026, 'a_s' : 2.481, 'b_s' : 11.120, 'a_fs' : 0.216, 'b_fs' : 11.436},
'sussmanbathe_vol' : {'kappa' : 1.0e3},
'active_fiber' : {'sigma0' : 50.0, 'alpha_max' : 15.0, 'alpha_min' : -20.0, 'activation_curve' : 1},
'inertia' : {'rho0' : 1.0e-6}}}
# define your load curves here (syntax: tcX refers to curve X, to be used in BC_DICT key 'curve' : [X,0,0], or 'curve' : X)
class time_curves():
def tc1(self, t):
K = 5.
t_contr, t_relax = 0.0, 0.53
alpha_max = MATERIALS['MAT1']['active_fiber']['alpha_max']
alpha_min = MATERIALS['MAT1']['active_fiber']['alpha_min']
c1 = t_contr + alpha_max/(K*(alpha_max-alpha_min))
c2 = t_relax - alpha_max/(K*(alpha_max-alpha_min))
# Diss Hirschvogel eq. 2.101
return (K*(t-c1)+1.)*((K*(t-c1)+1.)>0.) - K*(t-c1)*((K*(t-c1))>0.) - K*(t-c2)*((K*(t-c2))>0.) + (K*(t-c2)-1.)*((K*(t-c2)-1.)>0.)
def tc2(self, t): # atrial activation
act_dur = 2.*param()['t_ed']
t0 = 0.
if t >= t0 and t <= t0 + act_dur:
return 0.5*(1.-np.cos(2.*np.pi*(t-t0)/act_dur))
else:
return 0.0
BC_DICT = { 'dirichlet' : [{'dir' : '2dimZ', 'val' : 0.}],
'robin' : [{'type' : 'spring', 'id' : [3], 'dir' : 'normal', 'stiff' : 0.075},
{'type' : 'dashpot', 'id' : [3], 'dir' : 'normal', 'visc' : 0.005}] }
# problem setup
problem = ambit.Ambit(IO_PARAMS, [TIME_PARAMS_SOLID, TIME_PARAMS_FLOW0D], [SOLVER_PARAMS_SOLID, SOLVER_PARAMS_FLOW0D], FEM_PARAMS, [MATERIALS, MODEL_PARAMS_FLOW0D], BC_DICT, time_curves=time_curves(), coupling_params=COUPLING_PARAMS)
# solve time-dependent problem
problem.solve_problem()
# --- results check
tol = 1.0e-6
s_corr = np.zeros(problem.mp.pbf.cardvasc0D.numdof)
# correct 0D results
s_corr[0] = -2.0114350666760171E-02
s_corr[1] = 3.9868184096752618E-01
s_corr[2] = -1.0274818383992834E+00
s_corr[3] = 5.9982534828086920E-01
s_corr[4] = 1.0874643732273704E+01
s_corr[5] = 7.1802465982943570E+04
s_corr[6] = 2.2872622295989982E+00
s_corr[7] = 8.4716159930435591E+04
s_corr[8] = -1.2619948195877369E-02
s_corr[9] = 2.5407439126854764E-01
s_corr[10] = -1.8318777040206888E-01
s_corr[11] = 3.8027387249972561E-01
s_corr[12] = 2.2121515765204145E+00
s_corr[13] = 3.5710868582746974E+04
s_corr[14] = 1.6764885477792106E+00
s_corr[15] = 8.5187113787445720E+04
check1 = results_check.results_check_vec(problem.mp.pbf.s, s_corr, problem.mp.comm, tol=tol)
success = results_check.success_check([check1], problem.mp.comm)
return success
def main():
basepath = str(Path(__file__).parent.absolute())
IO_PARAMS = {
'problem_type':
'solid_flow0d_multiscale_gandr',
'mesh_domain':
'' + basepath + '/input/heart3Dcoarse_domain.xdmf',
'mesh_boundary':
'' + basepath + '/input/heart3Dcoarse_boundary.xdmf',
'fiber_data': {
'nodal': [
'' + basepath + '/input/fib_fiber_coords_nodal_3Dcoarse.txt',
'' + basepath + '/input/fib_sheet_coords_nodal_3Dcoarse.txt'
]
},
'write_results_every':
1,
'output_path':
'' + basepath + '/tmp',
'results_to_write':
['displacement', 'theta', 'phi_remod', 'trmandelstress_e'],
'simname':
'multiscale_concentric_as'
}
SOLVER_PARAMS_SOLID = {
'solve_type': 'direct', # direct, iterative
'tol_res': 1.0e-8,
'tol_inc': 1.0e-8,
'divergence_continue': 'PTC',
'k_ptc_initial': 10.0,
'print_local_iter': False,
'tol_res_local': 1.0e-10,
'tol_inc_local': 1.0e-10
}
SOLVER_PARAMS_FLOW0D = {'tol_res': 1.0e-6, 'tol_inc': 1.0e-6}
TIME_PARAMS_SOLID_SMALL = {
'maxtime': 1.0 * 100,
'numstep': 50 * 100,
'timint': 'genalpha',
'theta_ost': 1.0,
'rho_inf_genalpha': 0.8
}
TIME_PARAMS_SOLID_LARGE = {
'maxtime': 2592000.0, # 1 month: 30*24*60*60 s
'numstep': 1000,
'timint': 'static'
}
TIME_PARAMS_FLOW0D = {
'timint': 'ost', # ost
'theta_ost': 0.5,
'eps_periodic': 999,
'periodic_checktype': 'pQvar',
'initial_file':
'' + basepath + '/input/initial_syspulcap_multiscale.txt'
}
MODEL_PARAMS_FLOW0D = {
'modeltype': 'syspulcap',
'parameters': param(),
'chamber_models': {
'lv': {
'type': '3D_fem',
'interfaces': 1
},
'rv': {
'type': '3D_fem',
'interfaces': 1
},
'la': {
'type': '0D_elast',
'activation_curve': 2
},
'ra': {
'type': '0D_elast',
'activation_curve': 2
}
},
'perturb_type': ['as', 50.],
'perturb_after_cylce': 1
}
FEM_PARAMS = {
'order_disp': 1,
'order_pres': 1,
'quad_degree': 1,
'incompressible_2field': False,
'prestress_initial': True,
'lin_remodeling_full': False
}
COUPLING_PARAMS = {
'surface_ids': [[1], [2]],
'coupling_quantity': 'volume',
'coupling_type': 'monolithic_direct'
}
MULTISCALE_GR_PARAMS = {
'gandr_trigger_phase': 'end_systole', # end_diastole, end_systole
'numcycles': 10,
'tol_small':
0.08, # cycle error tolerance: overrides eps_periodic from TIME_PARAMS_FLOW0D
'tol_large': 5.0e-3, # growth rate tolerance [mm^3/s]
'tol_outer': 3.0e-3,
'write_checkpoints': True,
'restart_cycle': 0,
'restart_from_small': False
}
MATERIALS = {
'MAT1': {
'guccione_dev': {
'c_0': 1.662,
'b_f': 14.31,
'b_t': 4.49,
'b_fs': 10.
},
'sussmanbathe_vol': {
'kappa': 1.0e3
},
'active_fiber': {
'sigma0': 150.,
'alpha_max': 10.0,
'alpha_min': -30.0,
'activation_curve': 1,
'frankstarling': True,
'amp_min': 1.,
'amp_max': 1.5,
'lam_threslo': 1.01,
'lam_maxlo': 1.15,
'lam_threshi': 999.,
'lam_maxhi': 9999.
},
'inertia': {
'rho0': 1.0e-6
},
'growth': {
'growth_dir': 'crossfiber',
'growth_trig': 'volstress',
'trigger_reduction': 0.99,
'growth_thres': 1.05,
'thres_tol': 1.0e-3,
'thetamax': 3.0,
'thetamin': 1.0,
'tau_gr': 32.0e4,
'gamma_gr': 2.0,
'tau_gr_rev': 64.0e4,
'gamma_gr_rev': 2.0,
'remodeling_mat': {
'guccione_dev': {
'c_0': 10 * 1.662,
'b_f': 14.31,
'b_t': 4.49,
'b_fs': 10.
},
'sussmanbathe_vol': {
'kappa': 1.0e3
},
'active_fiber': {
'sigma0': 150.,
'alpha_max': 10.0,
'alpha_min': -30.0,
'activation_curve': 1,
'frankstarling': True,
'amp_min': 1.,
'amp_max': 1.5,
'lam_threslo': 1.01,
'lam_maxlo': 1.15,
'lam_threshi': 999.,
'lam_maxhi': 9999.
}
}
}
}
}
# define your load curves here (syntax: tcX refers to curve X, to be used in BC_DICT key 'curve' : [X,0,0], or 'curve' : X)
class time_curves():
def tc1(self, t):
K = 5.
t_contr, t_relax = 0.2, 0.53
alpha_max = MATERIALS['MAT1']['active_fiber']['alpha_max']
alpha_min = MATERIALS['MAT1']['active_fiber']['alpha_min']
c1 = t_contr + alpha_max / (K * (alpha_max - alpha_min))
c2 = t_relax - alpha_max / (K * (alpha_max - alpha_min))
# Diss Hirschvogel eq. 2.101
return (K * (t - c1) + 1.) * (
(K * (t - c1) + 1.) > 0.) - K * (t - c1) * (
(K * (t - c1)) > 0.) - K * (t - c2) * (
(K * (t - c2)) > 0.) + (K * (t - c2) - 1.) * (
(K * (t - c2) - 1.) > 0.)
def tc2(self, t): # atrial activation
act_dur = 2. * param()['t_ed']
t0 = 0.
if t >= t0 and t <= t0 + act_dur:
return 0.5 * (1. - np.cos(2. * np.pi * (t - t0) / act_dur))
else:
return 0.0
BC_DICT = {
'robin': [
{
'type': 'spring',
'id': [3],
'dir': 'normal',
'stiff': 0.075
},
{
'type': 'dashpot',
'id': [3],
'dir': 'normal',
'visc': 0.005
},
{
'type': 'spring',
'id': [4],
'dir': 'normal',
'stiff': 10.0
}, # 2.5, 1.25
{
'type': 'dashpot',
'id': [4],
'dir': 'normal',
'visc': 0.0005
},
{
'type': 'spring',
'id': [4],
'dir': 'xyz',
'stiff': 0.25
},
{
'type': 'dashpot',
'id': [4],
'dir': 'xyz',
'visc': 0.0005
}
]
}
# problem setup
problem = ambit.Ambit(
IO_PARAMS,
[TIME_PARAMS_SOLID_SMALL, TIME_PARAMS_SOLID_LARGE, TIME_PARAMS_FLOW0D],
[SOLVER_PARAMS_SOLID, SOLVER_PARAMS_FLOW0D],
FEM_PARAMS, [MATERIALS, MODEL_PARAMS_FLOW0D],
BC_DICT,
time_curves=time_curves(),
coupling_params=COUPLING_PARAMS,
multiscale_params=MULTISCALE_GR_PARAMS)
# solve time-dependent problem
problem.solve_problem()
# --- results check
tol = 1.0e-6
s_corr = np.zeros(problem.mp.pbf.cardvasc0D.numdof)
# correct 0D results
s_corr[0] = 1.5095864743040130E+06
s_corr[1] = 1.2844204058649662E+00
s_corr[2] = -2.2965082274795714E+00
s_corr[3] = -2.2516606843904677E-01
s_corr[4] = 1.2035047944220826E+01
s_corr[5] = 7.9266376779754364E+03
s_corr[6] = 1.0920576465746846E+01
s_corr[7] = 4.8757248185773104E+04
s_corr[8] = 4.5874998121783552E+04
s_corr[9] = 3.5972406593836102E+04
s_corr[10] = 2.4558826877860327E+04
s_corr[11] = 8.1860969826562832E+03
s_corr[12] = 2.2677989771675335E+00
s_corr[13] = 8.3769499009227275E+02
s_corr[14] = 2.2702566758390823E+00
s_corr[15] = 9.5189334925959599E+02
s_corr[16] = 2.2702868360248418E+00
s_corr[17] = 7.5312458499319700E+02
s_corr[18] = 2.2701207039868367E+00
s_corr[19] = 5.0027868673701960E+02
s_corr[20] = 2.2705227157170751E+00
s_corr[21] = 1.7138025576859900E+02
s_corr[22] = 2.2541277949292278E+00
s_corr[23] = 2.0733856020336604E+05
s_corr[24] = 9.9000307744360238E+04
s_corr[25] = 2.7306345247149444E-01
s_corr[26] = -4.3686268354670260E-01
s_corr[27] = 1.7406314472713416E-01
s_corr[28] = 2.4017163277669913E+00
s_corr[29] = 1.1803816043509409E+04
s_corr[30] = 2.3131877074406706E+00
s_corr[31] = 2.0066530960234333E+05
s_corr[32] = 1.6159475288856615E+00
s_corr[33] = 3.9878128320907672E+04
check1 = results_check.results_check_vec(problem.mp.pbf.s,
s_corr,
problem.mp.comm,
tol=tol)
success = results_check.success_check([check1], problem.mp.comm)
return success
def main():
basepath = str(Path(__file__).parent.absolute())
IO_PARAMS = {
'problem_type':
'flow0d', # solid, fluid, flow0d, solid_flow0d, fluid_flow0d
'write_results_every': -999,
'output_path': '' + basepath + '/tmp',
'simname': 'test'
}
SOLVER_PARAMS = {'tol_res': 1.0e-8, 'tol_inc': 1.0e-8}
TIME_PARAMS = {
'maxtime': 10 * 1.0,
'numstep': 10 * 100,
'timint': 'ost', # ost
'theta_ost': 0.5,
'initial_conditions': init(),
'eps_periodic': 0.03,
'periodic_checktype': 'pQvar'
}
MODEL_PARAMS = {
'modeltype': 'syspul',
'parameters': param(),
'chamber_models': {
'lv': {
'type': '0D_elast',
'activation_curve': 2
},
'rv': {
'type': '0D_elast',
'activation_curve': 2
},
'la': {
'type': '0D_elast',
'activation_curve': 1
},
'ra': {
'type': '0D_elast',
'activation_curve': 1
}
}
}
# define your time curves here (syntax: tcX refers to curve X)
class time_curves():
def tc1(self, t): # atrial activation
act_dur = 2. * param()['t_ed']
t0 = 0.
if t >= t0 and t <= t0 + act_dur:
return 0.5 * (1. - np.cos(2. * np.pi * (t - t0) / act_dur))
else:
return 0.0
def tc2(self, t): # ventricular activation
act_dur = 1.8 * (param()['t_es'] - param()['t_ed'])
t0 = param()['t_ed']
if t >= t0 and t <= t0 + act_dur:
return 0.5 * (1. - np.cos(2. * np.pi * (t - t0) / act_dur))
else:
return 0.0
# problem setup
problem = ambit.Ambit(IO_PARAMS,
TIME_PARAMS,
SOLVER_PARAMS,
constitutive_params=MODEL_PARAMS,
time_curves=time_curves())
# solve time-dependent problem
problem.solve_problem()
# --- results check
tol = 1.0e-6
s_corr = np.zeros(problem.mp.cardvasc0D.numdof)
# correct results
s_corr[0] = 2.7156831671111686E+04
s_corr[1] = 6.5014832315152615E-01
s_corr[2] = 2.3863884814303105E-01
s_corr[3] = 6.2299149148041377E-01
s_corr[4] = 7.3204325568836603E+00
s_corr[5] = 4.4855244723865435E+04
s_corr[6] = 1.9666233818994407E+00
s_corr[7] = -2.3737219188883661E+04
s_corr[8] = 3.2279121521802968E+04
s_corr[9] = 4.9648390872022957E-01
s_corr[10] = 1.6997499381247427E-01
s_corr[11] = 4.6420478719842723E-01
s_corr[12] = 1.8990559860434069E+00
s_corr[13] = -8.1705347914691476E+04
s_corr[14] = 1.4965782216339247E+00
s_corr[15] = -1.0232540549572852E+04
check1 = results_check.results_check_vec(problem.mp.s,
s_corr,
problem.mp.comm,
tol=tol)
success = results_check.success_check([check1], problem.mp.comm)
return success
def main():
basepath = str(Path(__file__).parent.absolute())
IO_PARAMS = {'problem_type' : 'flow0d',
'write_results_every' : -999,
'output_path' : ''+basepath+'/tmp/',
'simname' : 'test'}
SOLVER_PARAMS = {'tol_res' : 1.0e-7,
'tol_inc' : 1.0e-7}
TIME_PARAMS = {'maxtime' : 5.0,
'numstep' : 500,
'timint' : 'ost',
'theta_ost' : 1.0,
'initial_conditions' : init(),
'eps_periodic' : 0.05,
'periodic_checktype' : 'pvar'}
MODEL_PARAMS = {'modeltype' : 'syspulcaprespir',
'parameters' : param(),
'chamber_models' : {'lv' : {'type' : '0D_elast_prescr', 'elastance_curve' : 1}, 'rv' : {'type' : '0D_elast_prescr', 'elastance_curve' : 2}, 'la' : {'type' : '0D_elast_prescr', 'elastance_curve' : 3}, 'ra' : {'type' : '0D_elast_prescr', 'elastance_curve' : 4}}}
# define your time curves here (syntax: tcX refers to curve X)
class time_curves():
def tc1(self, t):
elastinterp = np.loadtxt(''+str(basepath)+'/input/elastances_lv.txt', skiprows=0)
equidist_time_array = np.zeros(len(elastinterp))
for i in range(len(equidist_time_array)):
equidist_time_array[i] = (i+1)/len(equidist_time_array)
return np.interp(t, equidist_time_array, elastinterp)
def tc2(self, t):
elastinterp = np.loadtxt(''+str(basepath)+'/input/elastances_rv.txt', skiprows=0)
equidist_time_array = np.zeros(len(elastinterp))
for i in range(len(equidist_time_array)):
equidist_time_array[i] = (i+1)/len(equidist_time_array)
return np.interp(t, equidist_time_array, elastinterp)
def tc3(self, t):
elastinterp = np.loadtxt(''+str(basepath)+'/input/elastances_la.txt', skiprows=0)
equidist_time_array = np.zeros(len(elastinterp))
for i in range(len(equidist_time_array)):
equidist_time_array[i] = (i+1)/len(equidist_time_array)
return np.interp(t, equidist_time_array, elastinterp)
def tc4(self, t):
elastinterp = np.loadtxt(''+str(basepath)+'/input/elastances_ra.txt', skiprows=0)
equidist_time_array = np.zeros(len(elastinterp))
for i in range(len(equidist_time_array)):
equidist_time_array[i] = (i+1)/len(equidist_time_array)
return np.interp(t, equidist_time_array, elastinterp)
# problem setup
problem = ambit.Ambit(IO_PARAMS, TIME_PARAMS, SOLVER_PARAMS, constitutive_params=MODEL_PARAMS, time_curves=time_curves())
# solve time-dependent problem
problem.solve_problem()
# --- results check
tol = 1.0e-6
s_corr = np.zeros(problem.mp.cardvasc0D.numdof)
## correct results - from former testcase (5 cycles with each 1.0 s, theta = 1.0)
## currently CANNOT be reproduced with the prescribed elastance model here (even though we're not too far off...)
## TODO: Check why this is the case!
#s_corr[0] = 7.71781462654294883e+04
#s_corr[1] = 4.82455285374715770e-01
#s_corr[2] = -9.32089188108091160e-01
#s_corr[3] = 4.05277139109286311e-01
#s_corr[4] = 9.72616902019019669e+00
#s_corr[5] = 5.83726080022352398e+04
#s_corr[6] = 9.32931790589786658e+00
#s_corr[7] = 1.83084886403833043e+04
#s_corr[8] = 1.72154627598280422e+04
#s_corr[9] = 1.35034073594659403e+04
#s_corr[10] = 9.21242124362669529e+03
#s_corr[11] = 3.07080126056907102e+03
#s_corr[12] = 2.41090621846982422e+00
#s_corr[13] = 2.27052534769887789e+04
#s_corr[14] = 2.41613895635923948e+00
#s_corr[15] = 2.21779080874570500e+04
#s_corr[16] = 2.41406095622704475e+00
#s_corr[17] = 1.74172480658872846e+04
#s_corr[18] = 2.41889648262861146e+00
#s_corr[19] = 1.18412162444708483e+04
#s_corr[20] = 2.41890958116365296e+00
#s_corr[21] = 3.95711134217977497e+03
#s_corr[22] = 2.04035648172536721e+00
#s_corr[23] = 9.42308665820743918e+04
#s_corr[24] = 7.15400334964196954e+04
#s_corr[25] = 2.31123843349538866e-01
#s_corr[26] = -2.39084978137291376e-01
#s_corr[27] = 1.59583809853119180e-01
#s_corr[28] = 2.55043359122603297e+00
#s_corr[29] = 2.05678359828922803e+04
#s_corr[30] = 2.39617482135434079e+00
#s_corr[31] = 3.90560782940216595e+04
#s_corr[32] = 2.10325423414917845e+00
#s_corr[33] = 1.08053263251630851e+05
#s_corr[34] = 4.77138986718484014e+06
#s_corr[35] = 2.66700289957665256e+05
#s_corr[36] = 9.99650347866085411e+01
#s_corr[37] = 3.27022324023728411e-02
#s_corr[38] = 1.48960517556904676e-01
#s_corr[39] = 1.67086022107776043e+04
#s_corr[40] = 1.66918635646860639e+04
#s_corr[41] = 1.30961635410208564e+04
#s_corr[42] = 8.89244395770556184e+03
#s_corr[43] = 2.98353472804512467e+03
#s_corr[44] = 1.59148286724528916e+01
#s_corr[45] = 5.05719330574661186e+00
#s_corr[46] = 1.59054445599070569e+01
#s_corr[47] = 5.05719330574661186e+00
#s_corr[48] = 1.58961192182105986e+01
#s_corr[49] = 5.06015201758573507e+00
#s_corr[50] = 3.46365073559847225e+00
#s_corr[51] = 1.34592586031045460e+01
#s_corr[52] = 4.11463113554487236e+00
#s_corr[53] = 1.20061143012695695e+01
#s_corr[54] = 4.12264630043372993e+00
#s_corr[55] = 1.19870456277740534e+01
#s_corr[56] = 4.12650550117093129e+00
#s_corr[57] = 1.19774295132249193e+01
#s_corr[58] = 4.13959751959834321e+00
#s_corr[59] = 1.19526966777885217e+01
#s_corr[60] = 8.15516536353003829e+00
#s_corr[61] = 6.85478506275626120e+00
#s_corr[62] = 4.42228745397937040e+00
#s_corr[63] = 1.11168107086389227e+01
#s_corr[64] = 4.87983353032786340e+01
#s_corr[65] = 1.47121161937896550e+00
#s_corr[66] = 7.33259028428000548e+00
#s_corr[67] = 7.35917863339734968e+00
#s_corr[68] = 6.40038489593068594e+00
#s_corr[69] = 8.09752757832401571e+00
#s_corr[70] = 8.15548041504590238e+00
#s_corr[71] = 6.85197645062970562e+00
#s_corr[72] = 4.42194570246950125e+00
#s_corr[73] = 1.11159168023280195e+01
#s_corr[74] = 4.87944514855986995e+01
#s_corr[75] = 1.46148783974661067e+00
#s_corr[76] = 7.33353820491393904e+00
#s_corr[77] = 7.35448022540421764e+00
#s_corr[78] = 6.40121826107596270e+00
#s_corr[79] = 8.09305239721075331e+00
#s_corr[80] = 1.59169639733867108e+01
#s_corr[81] = 5.05686647907035258e+00
# "new" "correct" results after 1 cycle
s_corr[0] = 7.8772984062558084E+04
s_corr[1] = 4.8659486302195032E-01
s_corr[2] = -9.3610058358450243E-01
s_corr[3] = 4.0782187895939220E-01
s_corr[4] = 9.7688277148044182E+00
s_corr[5] = 5.8808488437678505E+04
s_corr[6] = 9.3690308416361692E+00
s_corr[7] = 1.8467820872202938E+04
s_corr[8] = 1.7334898156421506E+04
s_corr[9] = 1.3597017271886743E+04
s_corr[10] = 9.2764846741601486E+03
s_corr[11] = 3.0920607948138941E+03
s_corr[12] = 2.3904106904481224E+00
s_corr[13] = 2.1963539583972666E+04
s_corr[14] = 2.4078904587582968E+00
s_corr[15] = 2.2186303961320122E+04
s_corr[16] = 2.4058351324957048E+00
s_corr[17] = 1.7424935125746462E+04
s_corr[18] = 2.4105541578551586E+00
s_corr[19] = 1.1842731275571505E+04
s_corr[20] = 2.4107809114187750E+00
s_corr[21] = 3.9598510095865377E+03
s_corr[22] = 2.0319657244376885E+00
s_corr[23] = 9.3711973674203065E+04
s_corr[24] = 7.0539636117053349E+04
s_corr[25] = 2.3269582989298973E-01
s_corr[26] = -2.4254777064876870E-01
s_corr[27] = 1.6215619377593637E-01
s_corr[28] = 2.5876339002636235E+00
s_corr[29] = 2.1024862315696508E+04
s_corr[30] = 2.4299474328958999E+00
s_corr[31] = 3.9854755419966961E+04
s_corr[32] = 2.1310367672461474E+00
s_corr[33] = 1.0962946028161315E+05
s_corr[34] = 4.9359151070363959E+06
s_corr[35] = 1.2176999298415647E+06
s_corr[36] = 9.9835478479934423E+01
s_corr[37] = 1.1874877807660576E-02
s_corr[38] = 1.8905022661610985E-01
s_corr[39] = 1.6856052226168646E+04
s_corr[40] = 1.6807410235902895E+04
s_corr[41] = 1.3186748889259841E+04
s_corr[42] = 8.9541309449532910E+03
s_corr[43] = 3.0041461413938432E+03
s_corr[44] = 1.5868870030490044E+01
s_corr[45] = 5.0645312522587602E+00
s_corr[46] = 1.5853909749529379E+01
s_corr[47] = 5.0669389175553903E+00
s_corr[48] = 1.5849765885394156E+01
s_corr[49] = 5.0676025646993645E+00
s_corr[50] = 1.6195682913639453E+00
s_corr[51] = 1.7179751665615537E+01
s_corr[52] = 3.8185082152968373E+00
s_corr[53] = 1.2477049172174398E+01
s_corr[54] = 3.9607746097186181E+00
s_corr[55] = 1.2246871673462810E+01
s_corr[56] = 4.0976635194540458E+00
s_corr[57] = 1.2021904244523247E+01
s_corr[58] = 4.1363317713754935E+00
s_corr[59] = 1.1959313574705780E+01
s_corr[60] = 8.1560564804157494E+00
s_corr[61] = 6.8543786891326901E+00
s_corr[62] = 4.4220064405023898E+00
s_corr[63] = 1.1117637256132248E+01
s_corr[64] = 4.8799048063729643E+01
s_corr[65] = 1.4670011536083674E+00
s_corr[66] = 7.3334628304288074E+00
s_corr[67] = 7.3581916462645314E+00
s_corr[68] = 6.4011225251472208E+00
s_corr[69] = 8.0967303185253847E+00
s_corr[70] = 8.1554715871500623E+00
s_corr[71] = 6.8518898508557946E+00
s_corr[72] = 4.4219094292144900E+00
s_corr[73] = 1.1115847759264300E+01
s_corr[74] = 4.8793936123173694E+01
s_corr[75] = 1.4608640562779471E+00
s_corr[76] = 7.3335746032859470E+00
s_corr[77] = 7.3541764115858905E+00
s_corr[78] = 6.4012488006615680E+00
s_corr[79] = 8.0927561433097157E+00
s_corr[80] = 1.5885890375194892E+01
s_corr[81] = 5.0617824505327755E+00
check1 = results_check.results_check_vec(problem.mp.s, s_corr, problem.mp.comm, tol=tol)
success = results_check.success_check([check1], problem.mp.comm)
return success