[TOC]
All contents of this example are stored in the ~/layed model
folder.
Adaptive_ forward_ Jn_ R2. m
. The subroutines are in the ~/fun
file. When the main function runs, the temporary variable is saved in ~/text_ File
. The optimized mesh is saved in the ~/mesh
file../model_ test_ Jn*.mph
and ./model_ test_Jn*.m
are the test files. We can use ./model_ test_Jn*.m
to generate ./model_ test_ Jn*.mph
.The path
in the .m
script should be consistent with the path
of the target output MPH file.model1_Jn.zip
. When the main function runs, the grid adaptive optimization results with a posteriori error estimator of the the current normal (Jn) discontinuity are obtained. If you need to obtain the mesh adaptation results estimated by other posterior errors, you need to use model1_ res_ Jn_ Bn_ Bt.zip
. The suffix after the underline indicates the type of a posteriori error estimator. At the same time, you need to adjust the MPH loading path
in the main function Adaptive_ forward_ Jn_ R2. m
.All contents of this example are stored in the ~/complex model
folder.
Adaptive_forward_Jn. m
. The subroutines are in the ~/fun
file. When the main function runs, the temporary variable is saved in ~/data
.The mesh optimizing process, the optimized mesh and their MT responses are saved in the ~/Non_ComplexModel
file.MT3D_errJ_J.zip
. When the main function runs, the grid adaptive optimization results with a posteriori error estimator of the the current normal (Jn) discontinuity are obtained. If you need to obtain the mesh adaptation results estimated by other posterior errors, you need to use model2_res_Jn_Bn_Bt.zip
. The suffix after the underline indicates the type of a posteriori error estimator. At the same time, you need to adjust the MPH loading path
in the main function Adaptive_ forward_ Jn_ R2. m
.All result data of two examples are stored in the ~/data
folder, and be put in the ~/data/case1
and ~/data/case2
folders.
The .csv
files can be divided into two types. One is the observation data f*_R*_obs_***.csv
. Their frequency, mesh refinement method (Bi-section and Oct-section), element type (hybrid mesh and tetrahedral), response type (apparent resistivity and phase), and response mode (xy and yx) are different; The other is the information of mesh refinement iteration process, f*_R*_iters_info_***. csv
, their frequency, mesh refinement method (Bi-section and Oct-section), element type (hybrid mesh and tetrahedral) are different.
The refined mesh is saved in .vtu
format in the mesh_errJ_***_R*.Zip
file in case1 and case2 files, their mesh types are different. ***
is tet
or hyb
, which respectively represents tetrahedral mesh and hybrid mesh; Their refinement methods are different, R*
is R2
or R8
, which respectively represents Bi-section refinement and Oct-section refinement.
eg. In the "complex model", you can set the frequency and mesh optimization iterations in the script ~/complex model/Adaptive_forward_Jn.m
.
Line 36
shows the frequency setting. Here only one frequency of 1Hz is set, freq=[1]. If the frequencies of 1, 10, 100 and 1000Hz are need to be set, freq=[1, 101001000]. Other frequency settings and so on.
Line 37
is the frequency setting. Only two mesh optimization iteration steps are set here, AdaptLevel=[2]. If three grid optimization iteration steps are needed to be set, AdaptLevel=[3]. The number of other grid optimization iterations is set and so on.
eg. The export path in ~/complex model/MT3D_errJ_J.mph
needs to be manually set to be consistent with the path in the script ~/layered model/Adaptive_forward_Jn_R2.m
.
eg. You can set the mesh refinement type through the script model_MPH.study('std*').feature('freq').set('meshadaptmethod', ' *** ')
. As shown in lines 67 and 68
in ~/layered model/Adaptive_forward_Jn_R2.m
, model_MPH.study('std3').feature('freq').set('meshadaptmethod', 'longest')
is a script of Bi-section , model_MPH.study('std3').feature('freq').set('meshadaptmethod', 'regular')
is a script of Oct-section .
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