Mr. Humberto Nakanishi

November 4, 2014

Hello all,

This kind of visualition is a very nice new feature. I used to export the tables to another program to do this.

I have just one suggestion. It would be nice to create those series based in table organized in lines also and not only in columns.

Regards,

Humberto

September 3, 2014

Hey Karsten,

The .zip worked. :D
There is the file.

Cheers,

Humberto

PCD.vtp.zip

August 29, 2014

Hey Karsten,

I tryed to upload the file in the first message, but I got an error message: "You are'nt permitted to upload this kind of file."

There are another way to send it to you?

I added the code writed into the .vtp file to the message. Maybe you can have an idea about the problem with it.

Cheers,

Humberto

<?xml version="1.0"?>
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      <CellData>
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      <Points>
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      </Points>
      <Verts>
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      </Verts>
      <Lines>
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        <DataArray type="Int64" Name="offsets" format="appended" RangeMin=""                     RangeMax=""                     offset="23212"               />
      </Lines>
      <Strips>
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        <DataArray type="Int64" Name="offsets" format="appended" RangeMin=""                     RangeMax=""                     offset="28484"               />
      </Strips>
      <Polys>
        <DataArray type="Int64" Name="connectivity" format="appended" RangeMin=""                     RangeMax=""                     offset="28684"               />
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b+b2VsxF3zNWQopyL6aqP90fN85Hv60h1ekkFh+rEDn3hQow37SnziCkCl+/pH5skSiBwmKPt8pYyPHRnVg5TrcDHqUFjPYZq3D4vsflaOFCr7rbIf7oBH2Km3A3UW1Bvc6VMYa4XHHtcrpx2+7f+XeKBTf7mlnD8FMo4OueCveYLTjn7fLC9gpItsy0IV8lWhpp3wqBMtfpVJRuJ7viiOML6GGjeKqauos11p5MC9Rw5AWfqL7ZFOxJwd4t1lHVuCpK4FvT27U3DNZ1ISk46EZqXuL2uSpCxwC9xhK4/HZWSpyzL3DLQQ2fNLXsqC688XXy28efgMg+J0rY7D3OXS3nJ/FRcTTv07LRGAZzedvkVxNDmnD1Y9d2aYmzi7xmSJJXA9dMlylafMhRPfSr+WVeBTx7cv9d6VoNEd+GQMXMdXOzqbJuDGxCYt17uSHILgtPW0TqwD++5VheOVv3DYc/6JxNu9Jbw67Yxtxdygc7P+RPmBG8Inu47EXY9EHuZuHsblkOx63fVwnRVBGZzrMJH7kdjwPTCjJXwI4Q1nJ/seRGPqwKBYZVJSTjAvG1yViwFo+65ZdYJqaCR806TjUS89Dr89nkACYqmrwZOsqXD6lq3vkwOBU+n9A9+1snE2sYK3x07s/FoiZgh/i0HOpKadCMLedD4TXRfCabiNcUzYaSsANySnczv6Ipwc8zaQdOyGEy/1GrusZZCVsaHfn6hDOqqCmWxEpW4wdt74Pn3algy1cmRVesQYKhUMDHQgAv/HRy1AMPHrI4a9uGDgVftwuI/PG6LjTcUSFng6OamtZPmzjhZ4GD4doc3lkc/d3wtDYDvzn135IVD8fPZWV9/+QgQRVp3Tk1F4f18yxFJWt6rkDXKOicUjzqtsYLSnkREBzqrNzsnQ9ai99GHnamoWZC3rXFNQ6ExP0v+eyIOiN6LGDam5Yb474FuM+lwuWM1qk/rj8DW0yX+Qlm41pdUVf42G6UuEgoPmnKxIHLykn59PmLoUuOlv1DBxqv1xYSnED3llbmyt4oQ3yL/9h0tRx9YzGCadSrFk9Y/ByPlaPz8ZtyTXIli+jF3RqsafN1iHOcaUIcvdt6DntsbofX6NWf/iVZQbWSPnw3rwxrLIoeCQ0N/cVml/Ecp72H07MU1R2qcIL45i8cx0QsqGh6C/uwBOLHJa1nkRggs863SVnWFg1OS/dEawyj8iPgjuDEQVWWqz3KMw6jlrMR+mh7uFCYXrCMR4Nk3XEBOSwFdVrlV0HIqRHiJn2/SeHOyK/81HU0XvR48rjOVTMejzp+6k2UUTB1u52c7m4n9rnmsXJ+zkMTXz15KzUFU05zI7SDa/DBwvn2vSMWHI6FDwZdo+eU2k+IBz0KsEV3N8aKrCEaPDBSmZEtwilc9e/RVKRq1tYpqusrhSVOL52xVUDcV9CJO1UAxJNeUsbUO7GGLcnVXGjGnHNhGDWxFsGlfn1x9H8rWd9vuNPuHT0rbIUdqjTmiebRNctmdwNXY8yRkrxfUKwdoTt4fGfdTJiMzH+Ietz25jqYn4xKlo57PIv/m8tcCzXwvRx5B2umS/y+tBGht1VpWHEvCFr59hCbaPCXTfzUZck6F8A5V6cGeNJjzGty9IkzCZwNVg8MhZFSps7Hq/k5H8ofYrM20/vnjfn5vzsKgnvpbuZJsVHNs3R5unQsvn0gJN7V8UNScovRIVHRcGxk+QJur+T8x/1Uhnn/ZGPPjQDFopGV7K60EVUfTj1xWKYMpsUf6l0QFsgs/Br5wq8IFcVLgpHYt7s5uGdZbXQ+yalQNObERB45+iNo00oobu27oHvrUh6r+Vmf5lH842V6IW6e92RxcL6svhNg5YsVcgJVS7InxF6cW7rz3g8CT7yG+S8FYbE/YqPg1DLaB39trbkbCrzD9VkJ/NLQur7nCfvwRBuqTfbdmxIOzUKBKliMJHwnql0VDk2EwYHSsdl0qLp6Ic1tQTwM5mK0yPYGIa/2M4aafSVh7OV7168V0yKl0Rqg2UCD1y3UkVS4TVwOvnyD1ZKGH4/Uac2uaHlsddCw/kIcqdoenrGuoSE3OHN2/qgDfGK4+UmMvxMS65h/bThahq0e5tiykGNv8xBG/uhSr6Heficopg2/bzPtlWk7+qnZQLGamCripEdvcVAuL/ZEvHWTrQRNvO7Wnjei+wnzmx642HE1cHubi7Ue841O+QyP/8Ar0F1J2MbsLm2P2lyWeP4CfztxXFRVPnKreedrpuh9mL854ap8PxrpLu3SZI8IQHCDkIfQlArW5Weqa56KhTtzjFpQZC7Y2qcqoNfFg+Zbm994oEUe3S2ostxBgJmFIs+Ip2MbyW3t2iOZbdHWqJrYRQTpa+LnzGgmCNurScsVkPM9T3/FhCwWtdypCulwzUJppWcn5PRPWY3ybXP2yceu+At+Wfblo/7Ps6TzQ3779+MpVKpZu/EmwND/Oxn5tk1Uh3okQZ/0JRZBx4haUmS3GM+IZxhSjUojeyNuQtbEcYV5bTJ6sVEDayhqKF6pR8WLDiqsYYNCQWubgUI/kVqHeaq4mPOHW3BB2qw1zJkpyOzX6MV6r/Osr8/Bf3N5s7ezw7LwDzjAxSdZzD3C+u9qP9ZUHuHJIlXuf+SJEvjrvKjUIhr/EnxWIh8GF98Gb874RuFFjpEMajMK6nS7bomn5y2ate2+xWRzkd8i6XC1LwGmt2JMjTARQXhxjIdLmMi5/gmvJKBX3mWO/88SnYd2RnrJzY0QomA6kv+MhQyj/uYGDRToO3dpNT+ykIMs08eV1yUzs0D3c+jkvC/I5EfxLx3IwdXD/u8iJXISk73oQHJsPhh/MtChBBafeDkJGaQFWTt1sjO8ohC87m/zIUhHmWH5Tycol+Ei84RWDUpy7IFdRdrcckW2ybYXXKlHlWn9vrLQaOdM9aocSgXCnykrjgnrs/I+Qm3DJs/llV34b8mgsJ+rUD0Yd+VSC7D/8Gt1+Jg1J0PCj+0WX2OwAYuM+J4KHB6xOc3z9fc0X8oUdMYvbg7Avgrm2qSgUlBN73zTxRKBznFVjPY332bkMWcLjaX5xejgKNF6znbka0bE1AQ2y8286LiXBUtu1doCQDEsnzya7bymIaTzSnrKHlhNWDayso/H/l735wu8jSHhZJTQcN0IGq7/z8bg9FCxODntF0vpP/MdxpQevM7HEF0YfapgNPX5PK8uZHAg1u8SrBOahs1yj7T4fFQ8NlOuXNhWgZ1tJSuLGQjAVIY2VrwithWuFuS8U46vL0xD21BIY2DoYJ+4sg4Bxy96x9nIsjxmkkOoqMVf6h+hrkM6stNd2VR0alocKVGfq4e4ZxC75qAkX/jMGbRi5V9WnT+lH5g86kpTVPxz9JFpPfyPdBjXwgcb1kw6IbzSKiNvjgfPc2VGEGR9oE3VWR/kGIszbRSaAMRTb7Yx4d1SHYyVprp/zQyTsVde9/80Vg8pW/+9sZx/BR9TkuaVjPIQ1SO825ibi3UbNsz1TBDx7cOJLd3gK/ri2ypJUOJXx7Dv8PA2JcvpC5zaT8Of0Q06ZDJ8Y29+X/dMxYTyjuH2Igh4p6XRB0UyQ390ysY/IgswfO86Ug+ziZknZyFyYrV5f5SWej4M1aXSLdlSsGty0J8q4AH35mq+DjArRcJZdLNy+CGYEczcHSjFuiou+Jy6V4KXksn3r/TJYSEjtE9hbAUdt05I6nirM/5A+qOFcA2FGnufPJOtAfvrWWJa3AS97fMINh5rgwe/BkHCsHfMScZ9KB/rB4bLWrCXtH55JBEllC87bSH2btelLkz1OPa5dKO50h6lTXLe/vQ8c9ZKF8CMAHmKse1luhuCNpr72Ik1v9T8f6Db2ivybz4d/P9uytyUW2gkkQtabOChe5FToXZ8I21ajBC0JAiI+qzz1ps333QfTjuNqqYhg32jMZZ4GBh+FOKVIIrx4F5fu15HQeyzuXttXMnoZ3WXiJShwyZ0fNKD15w9Bti1NQ5k4QfflSenRbHBJWl6wz8/BhqdSSXlH8nBwK5U7eCwfrwhLTvfbqXBu6Q2Toc150DvjhYiSQpz4dSlVurMI7i0ydgw/i0H6qn/WXKMU05mXlSQ6yzA1uTqmzLUCHc80e7Y7VaFBXSn6+kQN2Da82Wlyqw7/HQteaoDcCw96783NeENXz3XCtR3agdwPFX/1g5rdfvHS4D9cCetfpozEmqFHUf/jnJo9fMgHRrPs3OEeup7jHrMPai1G0zfYB0AtklFxsO0hJlfLrKxfE47UrYwxrtyR/3vuGg0uf870u8qx8A+4PvlOLw6kXPK4uXUC3ittas0MToIAfTO/Wk4ymDtcBe1nUrCL/905Ufo01OgV6wnwEDElZqhxQ4GEr9TrsZ/vkMHsJuK6REiH7r6tIc3jFPh6Gr/o4M/E+idyWdUOWfC8WWrrMZEN2w4i5/ULudDZVdy45kke+s0Eo3qPU0FcOrll3c4CbMr8Jca4rhCmQVfO9zAUIejIEjcPdzGaz0xPTGiUwHxyytUvrRQdf2wHbznN/wseShqpwKX/HgRWYaf6gZa6Y7Wof811nC2+DuPpDvpaQQ1Y8P3RlqvSjCOHQ3/W17XjsA7DMIPgAISETot8WzXyF99Ylt+f63eY4c2VD9mLj+1Aibxre3SvOxiPH3KfT/VGj+DxwtVL/qCXi5M0FX+IQwy8v7flheHMeNIVvuoI3MnZ1HG6JQqqiZbMvj0xqFV9VU2i8WqYcdi1c7T85UbI1tw1l4ggDjuOyBUCrltF5vAEpcD6yVL5eHwqcu1WV53PT4OOmcKz6+1EsPIfq6R7R8KUnpmx1JZ0xF87MnpIkQJmawbJw7T+9WPgUCtsysREe0yCIUc2st4F1go65aDLdGhU42MujFc4m73s87EYciPFOYiKsZAvZ7pvFYBHjvnhtkuFaHu8z177UhFMOe/ZXTEvxqeTzz1ZU0rQPVdBYfhaiq+aG97vti3HM/sNob9EKzHkHO08e6AaN2Sen3sYW4vgWzLpHzrqIPfLtDsUDSgzfpc369mMXj9TpsOrOvDqTq8o0/kBuH+2/5gh9g/n5j1aOuMpt/DraNUd3LFDuHK4mEaeG0Lbvsz3nfAGh8nPS0qu/vhwgKH5NCkY8QHifS16YTDr5Xz6zTACjp6b1myh6ReL906bpSsx0O424jDReQQdC55Hc1rx2O4X4rBROxHS/x0YEzCio7P2No0naKF4f8nRVDgI27YfUUoD3L5MNukQ8VPb/aOUBQkP2kkiLg/JOBExkZ1SlI4Nq2P0mycp2E49UH6IKxN5m98/vHI9Cwu8X8q+FGXDl0OrbpI9F/En30jaBeRBOG/fjzxGWq45QV9hNkZF1ICL6vOSApim37ZyJhaiXulMpAKpCOJzOYJrqotBE1fpyo8l6F8/8GbldBk4LdXWdraWw6a3UqnToxLfB8aTg3yrcaniPE3BamEbflJ36TtN377L+S1/pvGxUsc2lapmGKUpMBNOdqDp0cI3TYcByDcmSDpc/Ye3+6G7pFHRW4iWqPi2QG+HRzcC7j/gcMNd7kn5pqdeqKccfRDO5A++Je/w1ZzByLgcVj+9IQwH7xHpq9dGQNRo7Lrad5q/bztFvjsbjezfHM+rn8ZiySqUrr03Dqt/LNN9aEwACzflYWhVErRNPor9KktGUE6YuvrTFOzZfGqb2WQqzC3K9qybTUPyT0/Pb9+JIATLfGRhIcNg5o6arGg6gu3DL/qcpyBWiiuGgdbfhtdNTm0qzYRna5n9xu9ZELh1hLnkbA4+WM3HfM3JpeWB6sVtvPn48WK32OuLVPw53cnhL8BrCW2FS/SFUBdg07/wsRAM97PuEOeLkKGRsyTCVILQhniLmROlGGcgFXlGlyG55hTD6h0VMNPZPS04XAkX3SeZFRPV+Nji2ZCiBvz3WGpfPf6cesftbcT9Qwl0jZ+boaYZZ7TJswN0LeK33iYPoOG26HXz4H+4r8lev3CtxhTX3c0jdBNtcToj2DDc3xUbozRWB3p44YmHcMWDOD+YdJxgOx8bhDqnNCVnz1BYjGsaHaaGI7vtYWtBfCQ6P++8FuQZjYnbYoMXzGLhSbfjmN35OHxR2Md75mgCSrfVX2HZmwQSjjOxsieDL8LZXcUnBSb/34sMqBTtdM7xSUPSbX+fkmAijhp6vFWJI4HfW5lTOYcMwu9bKuEtNP6WNBY9MENBw550bVn2TFwreRjPrJYFUeZrFutCs/GpR+ni5HOa7/A5czxUPg+hjrIV+kX5KGd8k+eeROv31aIZhuYFmMi0OKd0thDiAY601irCT/JplwiZYrgavCx/o1WCxgmV5ILAUqS6CQ6kvSpDUKH5use3KiBw4eCShGAVthb4X/cTq0Ei+cZRJjLwQG+m5PHlegSLxhk/0GkEX72W+B3hFjyMvbfFq64DC42ML/tbBmBcQR4OK/+Hv4Qkn5OYpimC4pd3ZR2zxWDA1Q3yKy5QOa8zMC3khdMbXgyM7PeD9/DlhiccQfjzFojgpxCQ5jT2sxqGwyL4ovGSbCS0HtcPMHNH4+KnJ3StyzGgp85PBdB4/fVPQ63E4ng4dQatEo+m8fqtF7NODwhoM77+SpvGN9k7e5SWhFJRoHYjSIXmmwl/7CI/EbPh1cIJQiTc52zUZBMnw6zCJUXgVDoaJO0XoE/BUOqB3JcuGSjJZKfPzMjEnIR/s+GzLHRXdLQ78ubAXnrt21zLXIROyFW97csD+bvwTPVuKho+zr8Nm6aiRJvEHUHjnbEfijP1kYUQaIxpjPQswur9bBJcPsXYYnp66FRyCUwe7Xmxe6QU++eG9O8dKseJxDqbK2UVWOKcK39pXwUbx2cP1/rU4I87Y/0JfOha01jhW48/aTnWvxFn2623qF5twcSWPwmwA12OYlFscwPYnb8ucvLV/6WrcR0BbO9NsDF6a0T2hA2Ok6LeiD5wQQczVZs46AkL4eAB1Rbf/52DBmJgZmjen+YLC6uzeQ5tDsdv+1M+715HIFHTUCS1Kgr7uBT2NYfEQI4q+6Do+iMo/7EtkvGoFpa38KH5Q+ZVO/Vqp5IQltYzodiQjBu/X14kD6SgvKz0rF1rKvJ3Rk9L1qXB0PbAiEcNEbH5AllbaD5x0IA/MqmNjHOZZdk/R9Px7fr9JpaPFOyJG5aZ2JSJuFS1Fc8jWThYLS2ibJ4N6avj4Sl5ORB5amCquJILg/VNPwUM86FjtXDy7C0q+ouK80RFC/DKtf+g3s8CHP96xmv8SSHGba4KC3QUQegnY6FWdzHaJM9B+20JPO4Sz6rwlkHyvwdf5djZINZJWFOJM8sqJedaq0AoGT8gMVqD/15DE6qDyrf7zJ+L6qHPc0eJoaIRc2e+Jl2NakFE1MKh4mOdmKoUni7ZMoiiWZVr9zeN4v8Ahk78qg==AQAAAACAAADEOwAAbB8AAA==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AAAAAACAAAAAAAAAAAAAAACAAAAAAAAAAAAAAACAAAAAAAAAAAAAAACAAAAAAAAAAQAAAACAAAAYTgAAUw8AAA==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AQAAAACAAACIAQAAggAAAA==eJwt0C0OwmAQBFCg/KoikSRcAIkrSQ0SiSTBIJF4DlCOQFLDEZAkNRwBSVKD5AYfYt+aJ0bMZLNO3Jg5Z1xwyYJbHnhmxTsbfpg474Ylj6z4YMtpTz9PrPlmnoUbXvhk4rov54v5INyx5o/FMLyy5WpkP78sPfbGxP0kbPgHGcAYDA==AAAAAACAAAAAAAAAAAAAAACAAAAAAAAA
  </AppendedData>
</VTKFile>

August 28, 2014

Hi Karsten and Joerg,

I tryed the procedure that Karsten sugested, but still caeses can't read the vtk file.

I'll try to use another VTK writer.

Cheers,

Humberto

August 26, 2014

Hello all,

I'm trying to import a VTK_PolyData (.vtp) into the Caeses. I'm using the Data Connection -> VTK option.

However, Caeses can't find any data on it, because no object is created in the Obejct Three.

I'm using the vtkXMLPolyDataWriter to write the VTK file. Is it supported? Should I use another writer?

Thanks a lot,

Humberto

ps.: Please, dont remember my about Brazil x Germany game! =~

February 26, 2014

Hi Arne,

Yes, it solves my problem.

thanks,

Humberto

February 25, 2014

Hello,

I would like to export a panel mesh (.pan) object with more decimal cases then the default configuration.

Does anyone know if it is possible?

Cheers,

Humberto

February 24, 2014

Hello Sabah,

I've already done it in the past.
Basically I run a configuration m-file that open the Framework in batch mode.
Then I use another file to control it using the send.keys commands (in Windows).

I will send you the files. Just ask me if you need.

Cheers,

Humberto

1st the configuration file

%% Configuration of the Matlab to run Friendship on Batch Mode

% Configure Matlab Classes
configuration

% Desactivate warning messages
warning('off')

% Import Power Shell Class
h = actxserver('WScript.Shell');

% Open Framework on batch
% dos('FrameworkBatch.bat&');
% pause(20)

global control
% Create the object to Control the FFramework
control = ControlFFramework();

% Open Project
h.AppActivate('C:\Windows\system32\cmd.exe');
command = ['openProject{(}{"}' control.ffFile '{"}{)}{enter}'];
h.SendKeys(command);

global design
design = PlaningShip_v11();
design.Bmax = 2*1.985;
design.Vk = 31;
design.CG = [0 1.406];
design.f = 0.578;
design.eps = 8;
design.Hs = 0.55;
design.Loa = 12.37;
design.Lpp = 12.37;
design.opCond = 'oper';
design.calcSlam = false;
design.Dp = 0.63;
design.P_D = 1.238;
design.EAR = 0.85;
design.Z = 4;
design.Np = 2;
design.propSeries = 'SeriesB';
design.useRaw = false;
design.etaR = 0.95;
design.cavCriteria = 'BackCav10';
design.Nwtb = 2;
design.waterCap = 500;
design.fuelCap = 1100;
design.nPas = 14;
design.useEngine = true;
design.engName = 'VolvoD6_435';

% Ap0 = 33;
% Dt0 = 0.457;
% intVol0 = 53.5;
% LCB0 = 0.4588;
% BxMaxDeck = 1.98;
% LOA = 12.37;

And now the Framework Controller

%------------------------------------------------------------------------
%                        ControlFFramework
%
%------------------------------------------------------------------------
% Makes the comunication between Matlab and the FRIENDSHIP-Framework.

classdef ControlFFramework
    
    %% Public properties
    properties
        
        % Variables vector
        % v(1) - alphaCenter
        % v(2) - Dstern
        % v(3) - Dbow
        % v(4) - xBase
        % v(5) - alphaChine
        % v(6) - BxLin
        % v(7) - Bxt
        % v(8) - CAp
        % v(9) - Dt
        % v(10) - ie
        % v(11) - xLin
        % v(12) - alphaBotF
        % v(13) - alphaBot0
        % v(14) - xPos
        % v(15) - deadxLin
        % v(16) - deadt
        % v(17) - deadLp
        % v(18) - H
        % v(19) - Lp
        % v(20) - sca0
        % v(21) - scaF
        varVec
        
    end
    
    %% Calculated Properties
    properties (SetAccess = private)
        
        FFParameters
        FFConstraints
        
        % FFramework file
        ffFile
    end
    
    %% Private porperties
    properties (SetAccess = private, GetAccess = public)
        % Frienship Server
        ffServer
        
        % Result file template
        resultTemplate
        constTemplate
        dummyFile
        varTemplate
        
        
        % Basys ship variables
        basysVarVec = [41 0.10 2.0106 9.1 11 3.339 3.118 0.905 0.457 40 4.664 25 0 7.5 15.55 11.54 45 0.875 11.44 0.9 0.9];
        
    end
    
    %% Constructor
    methods
        function obj = ControlFFramework(myVarVec)
            % Creates an ControlFFramework object
            % function obj = ControlFFramework(myVarVec)
            % - myVarVec: variables vector
            
            if nargin == 1
                obj.varVec = myVarVec;
            else
                
                obj.varVec = zeros(1,21);
            end
            
            obj.ffServer = actxserver('WScript.Shell');
            
            [name, patch] = uigetfile({'*.fdb'},'Select the FFramework file');
            obj.ffFile = [patch name];
            obj.varTemplate = [patch 'variables.txt'];
            
            aux = [patch regexprep(name,'.fdb','') '\manual_results\baseline'];
            
            obj.resultTemplate = [aux '\results.txt'];
            
            obj.constTemplate = [aux '\constraints.txt'];
            
            obj.dummyFile = [aux '\finished.txt'];
            
        end
    end
    
    %% Setters and Getters
    methods
        
        function obj = set.varVec(obj,myVarVec)
            
            test = size(myVarVec);
            if test(1) == 21 || test(2) == 21
                obj.varVec = myVarVec;
            else
                warning('Parameters:WrongRange','The size of varVec is not correct!')
            end
            
        end
        
    end
    
    %% Public Methods
    methods
        
        function result = sendVarVec(obj)
            % function result = obj.sendVarVec()
            % Export the variabkes to the FFramewor and force to project to
            % update
            
            % Delete template files
            delete(obj.resultTemplate)
            delete(obj.constTemplate)
            delete(obj.dummyFile)
            
            % export variables File
            saveVarVec(obj.varVec,obj.varTemplate);
                                  
            obj.ffServer.AppActivate('C:\Windows\system32\cmd.exe');
            
            obj.ffServer.SendKeys('|variables.run{(}{)}{enter}');
            obj.ffServer.SendKeys('|export.run{(}{)}{enter}');
            obj.ffServer.SendKeys('getCurrentVariant{(}{)}.reduce{(}{)}{enter}');
            
            result = 'completed';
        end
        
        function closeProject(obj)
            % function result = obj.sendVarVec()
            % Export the variabkes to the FFramewor and force to project to
            % update
            
            obj.ffServer.AppActivate('C:\Windows\system32\cmd.exe');
            
            obj.ffServer.SendKeys('closeProject{(}{)}{enter}');
            obj.ffServer.SendKeys('n{enter}');
            obj.ffServer.SendKeys('exit{enter}');
            pause(10);
            obj.ffServer.SendKeys('exit{enter}');
        end
        
        function obj = readResultFiles(obj)
            % function obj = obj.readResultFile()
            % Reads the geometric and hydrostatic result file create by the
            % FFramework. Also read the file with the constraints calculate
            % by the FF.
            
            fid = -1;
            
            while fid == -1
                
                fid = fopen(obj.dummyFile);
            end
            
            fclose(fid);
            
            obj.FFParameters = readFile(obj.resultTemplate);
            obj.FFConstraints = readFile(obj.constTemplate);
            
        end
        
        function obj = setBasysHull(obj)
            % function obj = setBasysHull(obj)
            % Set the basys hull variables
            
            obj.varVec = obj.basysVarVec;
            obj.sendVarVec();
            
        end
    end
    
end

function read = readFile(fileName)
% function read = readFile(fileName)
% Read the file fileName

fid = fopen(fileName);
read = '';

% Positionate the file pointer
while ~strcmp(read,'Start')
    read = fscanf(fid,'%s',1);
end

% Read parameters
read = fscanf(fid,'%f',inf);

% Close file
fclose(fid);

end

function saveVarVec(varVec, fileName)
    
    label = 'alphaCenter Dstern Dbow xBase alphaChine BxLin Bxt CAp Dt ie xLin alphaBotF alphaBot0 xPos deadxLin deadt deadLp H Lp sca0 scaF';
    fid = fopen(fileName,'w');
    fprintf(fid,'%s\n\n',label);
    
    fprintf(fid,'%g ',varVec);
    fclose(fid);

end

November 20, 2013

Hi Stefan,

It's simple after the explanation.

Thanks,

Humberto

November 16, 2013

Hello all,

I've created a feature do calculate the Bereau Veritas design.
Now I wanna plot it using a panelMesh.

I tryed to used a unstructuredPanelMesh, using the command:

.setData(FVector3Series point data, FUnsignedSeries panel data, FListOf<FDoubleSeries> metaData, FListOf<FString> meta data names).

My question is: what should I use for the FUnsignedSeries panel data? I couldn't realise it by myself.

Thanks a lot,

Humberto

August 1, 2013

Thanks Ben,

Worked very well.

July 27, 2013

Hello all,

I created a project to integrate a program into the framework.
Now I want to use this program into another project.

I tryed the copy/paste procedure, but the files connections were losten.

How id the best way doing this?

Thanks,

Humberto

June 4, 2013

Hi,

I've set the Acadmic Edtion License on my notebook, How can I used this license in a different machine? Is it possible?

May 31, 2013

Thanks Konrad

May 30, 2013

Hello,

My notebook uses a 32-bit Windows 8. I installed the Caeses 64-bits version, my mistake.

I uninstalled the 64bits version and isntalled the 32bits version, but now I'm having an error message when opening the program (see attached image).

What should I do to fix it?

Thanks,

Humberto

ps.: I have the 64-bits Caeses version installed on my desktop.

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Mr. Humberto Nakanishi

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Posts posted by Mr. Humberto Nakanishi

TimeSeriesViewer - Plot your numerical Result Files with CAESES

Data Connection VTK-files

Data Connection VTK-files

Data Connection VTK-files

Data Connection VTK-files

Export Panel Mesh with more decimal cases

Export Panel Mesh with more decimal cases

Piloting CAESES from Matlab

Create UnstructuredPanelMesh

Create UnstructuredPanelMesh

Re-use Generic Interation with new projects

Re-use Generic Interation with new projects

Windows 8 Installation problem

Windows 8 Installation problem

Windows 8 Installation problem

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