Changeset 3839
- Timestamp:
- 05/19/10 09:57:00 (15 years ago)
- Location:
- issm/trunk/src/m/solutions/jpl
- Files:
-
- 26 edited
Legend:
- Unmodified
- Added
- Removed
-
issm/trunk/src/m/solutions/jpl/ControlInitialization.m
r3799 r3839 1 function [inputs models]=ControlInitialization(models,inputs);1 function models=ControlInitialization(models); 2 2 3 3 %recover models … … 55 55 % get pressure (reconditionned) and create 4d u_g 56 56 displaystring(verbose,'\n%s',['computing pressure according to Pattyn...']); 57 p_g=ComputePressure(m_dh.elements,m_dh.nodes,mdh.vertices,m_dh.loads,m_dh.materials,m_dh.parameters, inputs,DiagnosticAnalysisEnum(),HorizAnalysisEnum());57 p_g=ComputePressure(m_dh.elements,m_dh.nodes,mdh.vertices,m_dh.loads,m_dh.materials,m_dh.parameters,DiagnosticAnalysisEnum(),HorizAnalysisEnum()); 58 58 p_g=p_g/m_ds.parameters.stokesreconditioning; 59 59 u_g_stokes=zeros(m_ds.nodesets.gsize,1); -
issm/trunk/src/m/solutions/jpl/SpawnCore.m
r3796 r3839 1 function responses=SpawnCore(models, inputs,variables,variabledescriptors,analysis_type,sub_analysis_type,counter);1 function responses=SpawnCore(models,variables,variabledescriptors,analysis_type,sub_analysis_type,counter); 2 2 %SPAWNCORE - for Qmu analysis, using Dakota. Spawn the core solution. 3 3 % 4 4 % Usage: 5 % responses=SpawnCore(models, inputs,variables,variabledescriptors)5 % responses=SpawnCore(models,variables,variabledescriptors) 6 6 % 7 7 … … 47 47 if analysis_type==DiagnosticAnalysisEnum(), 48 48 49 results=diagnostic_core(models ,inputs);49 results=diagnostic_core(models); 50 50 51 51 else -
issm/trunk/src/m/solutions/jpl/balancedthickness.m
r3796 r3839 25 25 26 26 displaystring(md.verbose,'\n%s',['call computational core:']); 27 results=balancedthickness_core(models, inputs,BalancedthicknessAnalysisEnum(),NoneAnalysisEnum());27 results=balancedthickness_core(models,BalancedthicknessAnalysisEnum(),NoneAnalysisEnum()); 28 28 29 29 displaystring(md.verbose,'\n%s',['load results...']); -
issm/trunk/src/m/solutions/jpl/balancedthickness2.m
r3796 r3839 28 28 29 29 displaystring(md.verbose,'\n%s',['call computational core:']); 30 results=balancedthickness2_core(models, inputs,Balancedthickness2AnalysisEnum(),NoneAnalysisEnum());30 results=balancedthickness2_core(models,Balancedthickness2AnalysisEnum(),NoneAnalysisEnum()); 31 31 32 32 displaystring(md.verbose,'\n%s',['load results...']); -
issm/trunk/src/m/solutions/jpl/balancedthickness2_core.m
r3799 r3839 1 function results=balancedthickness2_core(models, inputs,analysis_type,sub_analysis_type)1 function results=balancedthickness2_core(models,analysis_type,sub_analysis_type) 2 2 %BALANCEDTHICKNESS_CORE - linear solution sequence 3 3 % 4 4 % Usage: 5 % h_g=balancedthickness2_core(m, inputs,analysis_type,sub_analysis_type)5 % h_g=balancedthickness2_core(m,analysis_type,sub_analysis_type) 6 6 7 7 %get FE model -
issm/trunk/src/m/solutions/jpl/balancedthickness_core.m
r3799 r3839 1 function results=balancedthickness_core(models, inputs,analysis_type,sub_analysis_type)1 function results=balancedthickness_core(models,analysis_type,sub_analysis_type) 2 2 %BALANCEDTHICKNESS_CORE - linear solution sequence 3 3 % 4 4 % Usage: 5 % h_g=balancedthickness_core(m, inputs,analysis_type,sub_analysis_type)5 % h_g=balancedthickness_core(m,analysis_type,sub_analysis_type) 6 6 7 7 %get FE model -
issm/trunk/src/m/solutions/jpl/balancedvelocities.m
r3796 r3839 27 27 28 28 displaystring(md.verbose,'\n%s',['call computational core:']); 29 results=balancedvelocities_core(models, inputs,BalancedvelocitiesAnalysisEnum(),NoneAnalysisEnum());29 results=balancedvelocities_core(models,BalancedvelocitiesAnalysisEnum(),NoneAnalysisEnum()); 30 30 31 31 displaystring(md.verbose,'\n%s',['load results...']); -
issm/trunk/src/m/solutions/jpl/balancedvelocities_core.m
r3799 r3839 1 function results=balancedvelocities_core(models, inputs,analysis_type,sub_analysis_type)1 function results=balancedvelocities_core(models,analysis_type,sub_analysis_type) 2 2 %BALANCEDVELOCITIES_CORE - linear solution sequence 3 3 % 4 4 % Usage: 5 % v_g=balancedvelocities_core(m, inputs,analysis_type,sub_analysis_type)5 % v_g=balancedvelocities_core(m,analysis_type,sub_analysis_type) 6 6 7 7 %get FE model -
issm/trunk/src/m/solutions/jpl/control_core.m
r3796 r3839 1 function results=control_core(models ,inputs)1 function results=control_core(models) 2 2 %CONTROL_CORE - compute the core inversion 3 3 % 4 4 % Usage: 5 % results=control_core(models ,inputs);5 % results=control_core(models); 6 6 % 7 7 8 8 %Preprocess models 9 [inputs models]=ControlInitialization(models,inputs);9 models=ControlInitialization(models); 10 10 11 11 %recover active model. … … 37 37 %In case we are running a steady state control method, compute new temperature field using new parameter distribution: 38 38 if model.parameters.ControlSteady; 39 steadystate_results=steadystate_core(models ,inputs); t_g=steadystate_results.t_g;39 steadystate_results=steadystate_core(models); t_g=steadystate_results.t_g; 40 40 inputs=add(inputs,'temperature',t_g,'doublevec',1,model.parameters.NumberOfNodes); 41 41 end … … 46 46 47 47 %Update inputs in datasets 48 [model.elements,model.nodes,model.vertices,model.loads,model.materials,model.parameters]=UpdateFromInputs(model.elements,model.nodes,model.vertices,model.loads,model.materials,model.parameters ,inputs);48 [model.elements,model.nodes,model.vertices,model.loads,model.materials,model.parameters]=UpdateFromInputs(model.elements,model.nodes,model.vertices,model.loads,model.materials,model.parameters); 49 49 50 50 displaystring(verbose,'\n%s',[' computing gradJ...']); 51 results_grad=gradjcompute_core(models ,inputs);51 results_grad=gradjcompute_core(models); 52 52 u_g=results_grad.u_g; c(n).grad_g=results_grad.grad_g; 53 53 if dim==3, … … 78 78 79 79 displaystring(verbose,'\n%s',[' optimizing along gradient direction...']); 80 [search_scalar c(n).J]=ControlOptimization('objectivefunctionC',0,1,options,models, inputs,param_g,c(n).grad_g,n,model.parameters);80 [search_scalar c(n).J]=ControlOptimization('objectivefunctionC',0,1,options,models,param_g,c(n).grad_g,n,model.parameters); 81 81 82 82 displaystring(verbose,'\n%s',[' updating parameter using optimized search scalar...']); … … 119 119 if model.parameters.ControlSteady; 120 120 inputs=add(inputs,model.parameters.ControlType,param_g,'doublevec',1,model.parameters.NumberOfNodes); 121 steadystate_results=steadystate_core(models ,inputs); t_g=steadystate_results.t_g;121 steadystate_results=steadystate_core(models); t_g=steadystate_results.t_g; 122 122 u_g=steadystate_results.u_g; 123 123 t_g=steadystate_results.t_g; … … 125 125 else 126 126 inputs=add(inputs,model.parameters.ControlType,param_g,'doublevec',1,model.parameters.NumberOfNodes); 127 results_diag=diagnostic_core(models ,inputs);127 results_diag=diagnostic_core(models); 128 128 u_g=results_diag.u_g; 129 129 end -
issm/trunk/src/m/solutions/jpl/diagnostic_core_linear.m
r3838 r3839 9 9 10 10 %Update inputs in datasets 11 [m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters]=UpdateFromInputs(m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters ,inputs);11 [m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters]=UpdateFromInputs(m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters); 12 12 13 13 %system matrices 14 [K_gg, p_g]=SystemMatrices(m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);15 [K_gg, p_g,kmax]=PenaltySystemMatrices(K_gg,p_g,m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);14 [K_gg, p_g]=SystemMatrices(m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters,analysis_type,sub_analysis_type); 15 [K_gg, p_g,kmax]=PenaltySystemMatrices(K_gg,p_g,m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters,analysis_type,sub_analysis_type); 16 16 17 17 %Reduce tangent matrix from g size to f size -
issm/trunk/src/m/solutions/jpl/diagnostic_core_nonlinear.m
r3837 r3839 34 34 35 35 %penalties 36 [K_gg , p_g, kmax]=PenaltySystemMatrices(K_gg_nopenalty,p_g_nopenalty,m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);36 [K_gg , p_g, kmax]=PenaltySystemMatrices(K_gg_nopenalty,p_g_nopenalty,m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters,analysis_type,sub_analysis_type); 37 37 38 38 %Reduce tangent matrix from g size to f size … … 58 58 59 59 %penalty constraints 60 [loads,constraints_converged,num_unstable_constraints] =PenaltyConstraints( m.elements,m.nodes,m.vertices,loads, m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);60 [loads,constraints_converged,num_unstable_constraints] =PenaltyConstraints( m.elements,m.nodes,m.vertices,loads, m.materials,m.parameters,analysis_type,sub_analysis_type); 61 61 error; 62 62 … … 66 66 converged=convergence(K_ff,p_f,soln(count).u_f,soln(count-1).u_f,m.parameters); 67 67 68 %add convergence status into inputs68 %add convergence status into 69 69 inputs=add(inputs,'converged',converged,'double'); 70 70 … … 85 85 inputs=add(inputs,'velocity',u_g,'doublevec',m.parameters.NumberOfDofsPerNode,m.parameters.NumberOfNodes); 86 86 m.parameters.Kflag=1; m.parameters.Pflag=0; 87 [K_gg, p_g]=SystemMatrices(m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);87 [K_gg, p_g]=SystemMatrices(m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters,analysis_type,sub_analysis_type); 88 88 [K_ff, K_fs] = Reducematrixfromgtof( K_gg, m.Gmn, m.nodesets); 89 89 varargout(1)={K_ff}; -
issm/trunk/src/m/solutions/jpl/gradjcompute_core.m
r3799 r3839 1 function results=gradjcompute_core(models ,inputs);1 function results=gradjcompute_core(models); 2 2 3 3 %recover active models … … 21 21 %Buid Du, difference between observed velocity and model velocity. 22 22 displaystring(verbose,'%s',' computing Du...'); 23 [Du_g]=Du(m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);23 [Du_g]=Du(m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters,analysis_type,sub_analysis_type); 24 24 25 25 %Reduce adjoint load from g-set to f-set … … 35 35 36 36 %Compute gradJ 37 grad_g=Gradj(m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);37 grad_g=Gradj(m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters,analysis_type,sub_analysis_type); 38 38 if (dim==3 & extrude_param), 39 39 displaystring(verbose,'%s',' extruding gradient...'); … … 44 44 %compute initial velocity from diagnostic_core (horiz+vertical) 45 45 displaystring(verbose,'%s',' compute 3d initial velocity...'); 46 results_diag=diagnostic_core(models ,inputs);46 results_diag=diagnostic_core(models); 47 47 u_g=results_diag.u_g; 48 48 end -
issm/trunk/src/m/solutions/jpl/objectivefunctionC.m
r3799 r3839 1 function J =objectivefunctionC(search_scalar,models, inputs,p_g,grad_g,n,analysis_type,sub_analysis_type);1 function J =objectivefunctionC(search_scalar,models,p_g,grad_g,n,analysis_type,sub_analysis_type); 2 2 3 3 %recover active model. … … 23 23 24 24 %Compute misfit for this velocity field. 25 J=CostFunction(m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);25 J=CostFunction(m.elements,m.nodes,m.vertices,m.loads,m.materials,m.parameters,analysis_type,sub_analysis_type); -
issm/trunk/src/m/solutions/jpl/prognostic.m
r3796 r3839 27 27 28 28 displaystring(md.verbose,'\n%s',['call computational core:']); 29 results=prognostic_core(models, inputs,PrognosticAnalysisEnum(),NoneAnalysisEnum());29 results=prognostic_core(models,PrognosticAnalysisEnum(),NoneAnalysisEnum()); 30 30 31 31 displaystring(md.verbose,'\n%s',['load results...']); -
issm/trunk/src/m/solutions/jpl/prognostic2.m
r3534 r3839 28 28 29 29 displaystring(md.verbose,'\n%s',['call computational core:']); 30 results=prognostic2_core(models, inputs,Prognostic2AnalysisEnum(),NoneAnalysisEnum());30 results=prognostic2_core(models,Prognostic2AnalysisEnum(),NoneAnalysisEnum()); 31 31 32 32 displaystring(md.verbose,'\n%s',['load results...']); -
issm/trunk/src/m/solutions/jpl/prognostic2_core.m
r3799 r3839 1 function results=prognostic2_core(models, inputs,analysis_type,sub_analysis_type)1 function results=prognostic2_core(models,analysis_type,sub_analysis_type) 2 2 %PROGNOSTIC2_CORE - linear solution sequence 3 3 % 4 4 % Usage: 5 % h_g=prognostic2_core(m, inputs,analysis_type,sub_analysis_type)5 % h_g=prognostic2_core(m,analysis_type,sub_analysis_type) 6 6 7 7 %get FE model -
issm/trunk/src/m/solutions/jpl/prognostic_core.m
r3799 r3839 1 function results=prognostic_core(models, inputs,analysis_type,sub_analysis_type)1 function results=prognostic_core(models,analysis_type,sub_analysis_type) 2 2 %PROGNOSTIC_CORE - linear solution sequence 3 3 % 4 4 % Usage: 5 % h_g=prognostic_core(m, inputs,analysis_type,sub_analysis_type)5 % h_g=prognostic_core(m,analysis_type,sub_analysis_type) 6 6 7 7 %get FE model -
issm/trunk/src/m/solutions/jpl/slopecompute.m
r3552 r3839 17 17 md.dof=modelsize(models); 18 18 19 %initialize inputs20 inputs=inputlist;21 22 19 %compute solution 23 20 displaystring(md.verbose,'\n%s',['call computational core:']); 24 results=slopecompute_core(models, inputs,SlopecomputeAnalysisEnum(),NoneAnalysisEnum());21 results=slopecompute_core(models,SlopecomputeAnalysisEnum(),NoneAnalysisEnum()); 25 22 26 23 displaystring(md.verbose,'\n%s',['load results...']); -
issm/trunk/src/m/solutions/jpl/slopecompute_core.m
r3799 r3839 1 function results=slopecompute_core(models, inputs,analysis_type,sub_analysis_type)1 function results=slopecompute_core(models,analysis_type,sub_analysis_type) 2 2 %SLOPECOMPUTE_CORE - linear solution sequence 3 3 % 4 4 % Usage: 5 % [sx_g sy_g]=slopecompute_core(m, inputs,analysis_type,sub_analysis_type)5 % [sx_g sy_g]=slopecompute_core(m,analysis_type,sub_analysis_type) 6 6 7 7 %get FE model -
issm/trunk/src/m/solutions/jpl/steadystate.m
r3796 r3839 55 55 models.ds.parameters.ControlSteady=1; 56 56 %launch core of control solution. 57 results=control_core(models ,inputs);57 results=control_core(models); 58 58 59 59 %process results … … 62 62 else, 63 63 %launch core of steadystate solution. 64 results=steadystate_core(models ,inputs);64 results=steadystate_core(models); 65 65 66 66 %process results … … 70 70 else 71 71 %launch dakota driver for steadystate core solution 72 Qmu(models, inputs,models.dh.parameters);72 Qmu(models,models.dh.parameters); 73 73 end 74 74 -
issm/trunk/src/m/solutions/jpl/steadystate_core.m
r3796 r3839 1 function results=steadystate_core(models ,inputs);1 function results=steadystate_core(models); 2 2 %STEADYSTATE_CORE - compute the core temperature and velocity field at thermal steady state. 3 3 % 4 4 % Usage: 5 % results=steadystate_core(models ,inputs);5 % results=steadystate_core(models); 6 6 % 7 7 … … 42 42 inputs=add(inputs,'velocity',results_diagnostic.u_g,'doublevec',ndof,m_t.parameters.NumberOfNodes); 43 43 end 44 results_thermal=thermal_core(models ,inputs);44 results_thermal=thermal_core(models); 45 45 46 46 %add temperature to inputs. … … 51 51 52 52 %now compute diagnostic velocity using the steady state temperature. 53 results_diagnostic=diagnostic_core(models ,inputs);53 results_diagnostic=diagnostic_core(models); 54 54 55 55 %convergence? -
issm/trunk/src/m/solutions/jpl/thermal.m
r3796 r3839 30 30 if ~models.t.parameters.QmuAnalysis, 31 31 %launch core of diagnostic solution. 32 results=thermal_core(models ,inputs);32 results=thermal_core(models); 33 33 34 34 %process results … … 37 37 else 38 38 %launch dakota driver for diagnostic core solution 39 Qmu(models, inputs,models.t.parameters);39 Qmu(models,models.t.parameters); 40 40 end 41 41 -
issm/trunk/src/m/solutions/jpl/thermal_core.m
r3799 r3839 1 function results=thermal_core(models ,inputs)1 function results=thermal_core(models) 2 2 %THERMAL_CORE - core of thermal solution 3 3 % 4 4 % Usage: 5 % solution=thermal_core(models ,inputs)5 % solution=thermal_core(models) 6 6 7 7 %get FE model … … 15 15 16 16 displaystring(m_t.parameters.Verbose,'\n%s',['computing temperatures...']); 17 [results.t_g m_t.loads melting_offset]=thermal_core_nonlinear(m_t, inputs,ThermalAnalysisEnum(),NoneAnalysisEnum());17 [results.t_g m_t.loads melting_offset]=thermal_core_nonlinear(m_t,,ThermalAnalysisEnum(),NoneAnalysisEnum()); 18 18 19 19 displaystring(m_t.parameters.Verbose,'\n%s',['computing melting...']); … … 43 43 displaystring(m_t.parameters.Verbose,'\n%s',[' computing temperatures...']); 44 44 inputs=add(inputs,'temperature',results(n).t_g,'doublevec',1,m_t.parameters.NumberOfNodes); 45 [results(n+1).t_g m_t.loads melting_offset]=thermal_core_nonlinear(m_t, inputs,ThermalAnalysisEnum(),NoneAnalysisEnum());45 [results(n+1).t_g m_t.loads melting_offset]=thermal_core_nonlinear(m_t,ThermalAnalysisEnum(),NoneAnalysisEnum()); 46 46 47 47 displaystring(m_t.parameters.Verbose,'\n%s',[' computing melting...']); -
issm/trunk/src/m/solutions/jpl/thermal_core_nonlinear.m
r3838 r3839 1 function [t_g ,loads, melting_offset]=thermal_core_nonlinear(m, inputs,analysis_type,sub_analysis_type)1 function [t_g ,loads, melting_offset]=thermal_core_nonlinear(m,analysis_type,sub_analysis_type) 2 2 %THERMAL_CORE_NONLINEAR - core of thermal solution sequence. 3 3 % model is return together with temperature 4 4 % 5 5 % Usage: 6 % [t_g ,loads, melting_offset]=thermal_core_nonlinear(m, inputs,analysis_type,sub_analysis_type);6 % [t_g ,loads, melting_offset]=thermal_core_nonlinear(m,analysis_type,sub_analysis_type); 7 7 8 8 count=1; … … 20 20 21 21 %Update inputs in datasets 22 [m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters]=UpdateFromInputs(m.elements,m.nodes,m.vertices, loads,m.materials,m.parameters ,inputs);22 [m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters]=UpdateFromInputs(m.elements,m.nodes,m.vertices, loads,m.materials,m.parameters); 23 23 24 24 %system matrices … … 26 26 if count==1 27 27 displaystring(m.parameters.Verbose,'%s',[' system matrices']); 28 [K_gg_nopenalty, p_g_nopenalty]=SystemMatrices(m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);28 [K_gg_nopenalty, p_g_nopenalty]=SystemMatrices(m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters,analysis_type,sub_analysis_type); 29 29 end 30 30 displaystring(m.parameters.Verbose,'%s',[' penalty system matrices']); 31 [K_gg , p_g, melting_offset]=PenaltySystemMatrices(K_gg_nopenalty,p_g_nopenalty,m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);31 [K_gg , p_g, melting_offset]=PenaltySystemMatrices(K_gg_nopenalty,p_g_nopenalty,m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters,analysis_type,sub_analysis_type); 32 32 else 33 33 displaystring(m.parameters.Verbose,'%s',[' system matrices']); 34 [K_gg , p_g]=SystemMatrices(m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);34 [K_gg , p_g]=SystemMatrices(m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters,analysis_type,sub_analysis_type); 35 35 displaystring(m.parameters.Verbose,'%s',[' penalty system matrices']); 36 [K_gg , p_g, melting_offset]=PenaltySystemMatrices(K_gg,p_g,m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);36 [K_gg , p_g, melting_offset]=PenaltySystemMatrices(K_gg,p_g,m.elements,m.nodes,m.vertices,loads,m.materials,m.parameters,analysis_type,sub_analysis_type); 37 37 end 38 38 … … 54 54 inputs=add(inputs,'temperature',t_g,'doublevec',m.parameters.NumberOfDofsPerNode,m.parameters.NumberOfNodes); 55 55 displaystring(m.parameters.Verbose,'%s',[' update inputs']); 56 [m.elements,m.nodes,m.vertices, loads,m.materials,m.parameters]=UpdateFromInputs(m.elements,m.nodes,m.vertices, loads,m.materials,m.parameters ,inputs);56 [m.elements,m.nodes,m.vertices, loads,m.materials,m.parameters]=UpdateFromInputs(m.elements,m.nodes,m.vertices, loads,m.materials,m.parameters); 57 57 58 58 %penalty constraints 59 59 displaystring(m.parameters.Verbose,'%s',[' penalty constraints']); 60 [loads,constraints_converged,num_unstable_constraints] =PenaltyConstraints(m.elements,m.nodes,m.vertices,loads, m.materials,m.parameters, inputs,analysis_type,sub_analysis_type);60 [loads,constraints_converged,num_unstable_constraints] =PenaltyConstraints(m.elements,m.nodes,m.vertices,loads, m.materials,m.parameters,analysis_type,sub_analysis_type); 61 61 62 62 if ~converged, -
issm/trunk/src/m/solutions/jpl/transient2d.m
r3796 r3839 71 71 72 72 %Get horizontal solution. 73 rawresults=diagnostic_core(models ,inputs);73 rawresults=diagnostic_core(models); 74 74 solution(n+1).u_g=rawresults.u_g; solution(n+1).p_g=rawresults.p_g; 75 75 … … 77 77 disp(sprintf('%s',' computing new thickness...')); 78 78 inputs=add(inputs,'velocity',solution(n+1).u_g,'doublevec',2,models.p.parameters.NumberOfNodes); 79 rawresults=prognostic_core(models, inputs,PrognosticAnalysisEnum(),NoneAnalysisEnum());79 rawresults=prognostic_core(models,PrognosticAnalysisEnum(),NoneAnalysisEnum()); 80 80 new_thickness=rawresults.h_g; 81 81 -
issm/trunk/src/m/solutions/jpl/transient3d.m
r3799 r3839 84 84 %Deal with temperature first 85 85 displaystring(md.verbose,'\n%s',[' computing temperatures...']); 86 [results(n+1).t_g models.t.loads melting_offset]=thermal_core_nonlinear(models.t, inputs,ThermalAnalysisEnum(),TransientAnalysisEnum());86 [results(n+1).t_g models.t.loads melting_offset]=thermal_core_nonlinear(models.t,ThermalAnalysisEnum(),TransientAnalysisEnum()); 87 87 inputs=add(inputs,'temperature',results(n+1).t_g,'doublevec',1,models.t.parameters.NumberOfNodes); 88 88 … … 96 96 97 97 %Deal with velocities. 98 rawresults=diagnostic_core(models ,inputs);98 rawresults=diagnostic_core(models); 99 99 results(n+1).u_g=rawresults.u_g; results(n+1).p_g=rawresults.p_g; 100 100 … … 102 102 displaystring(md.verbose,'\n%s',[' computing new thickness...']); 103 103 inputs=add(inputs,'velocity',results(n+1).u_g,'doublevec',3,models.p.parameters.NumberOfNodes); 104 rawresults=prognostic_core(models, inputs,PrognosticAnalysisEnum(),NoneAnalysisEnum());104 rawresults=prognostic_core(models,PrognosticAnalysisEnum(),NoneAnalysisEnum()); 105 105 new_thickness=rawresults.h_g; 106 106
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