Dear Chamara,
Sorry, I was not aware that the current version 7.12 of DP_MICRESS does not yet support text(ascii) output. This will be possible with the next version which will come together with the release of MICRESS 6.4. What you have chosen instead was "VTK(ascii)".
The advantage of "text(ascii)" format is that it consists of text lines which are identical with the image lines. With a suitable text editor (like Notepad++ or MICpad) which displays the full lines with scrollbars (without wrapping) it is possible to "see" the image although it is build up of numbers (it may be necessary to replace "0" with "000" in order to align correctly). Thus, you can manually edit or construct initial microstructures. This is what I wanted to propose.
Contrarily, the vtk format has a header with the dimensions and therefore does not need the carriage return as end of line character. Therefore, vtkfiles are typically organized in lines of 4 columns, and you cannot recognize where an image line ends and where the next starts.
At present, the only "official" method to export MICRESS results as "text(ascii)" is to use the ASCII output filter of the old DP_MICRESS version 6.1 which you still can download from the MICRESS page. Alternatively, you could also write a script which does the conversion - or ask Ralph whether he would give you a beta version of the new DP_MICRESS7.1.16 ...
Bernd
Primary Dendrite Arms spacing (PDAS) prediction
Re: Primary Dendrite Arms spacing (PDAS) prediction
Hej Bernd,
Thanks for the input. I got the beta version from Ralph. Probably I will write a Matlab script for this. It might be difficult to edit the text ascii file manually .
BR
Chamara
Thanks for the input. I got the beta version from Ralph. Probably I will write a Matlab script for this. It might be difficult to edit the text ascii file manually .
BR
Chamara
Re: Primary Dendrite Arms spacing (PDAS) prediction
Dear Chamara,
as I said, if you 'search & replace' all existing integer numbers by using leading "0"'s in order to give them the same string length, the appearance is quite "graphical". For applying corrections by text-editing (e.g. you start with an already existing rectangular grain and just add some noise at the flat surface) this I think is quite a reasonable method. Completely creating an initial microstructure from scratch may be quite annoying of course...
Alternatively, you can always take the route starting from a painting tool, export to pgm and get the text(ascii) format via the pgm_to_micress script...
Bernd
as I said, if you 'search & replace' all existing integer numbers by using leading "0"'s in order to give them the same string length, the appearance is quite "graphical". For applying corrections by text-editing (e.g. you start with an already existing rectangular grain and just add some noise at the flat surface) this I think is quite a reasonable method. Completely creating an initial microstructure from scratch may be quite annoying of course...
Alternatively, you can always take the route starting from a painting tool, export to pgm and get the text(ascii) format via the pgm_to_micress script...
Bernd
Re: Primary Dendrite Arms spacing (PDAS) prediction
Dear Bernd:
I am interested in the PDAS(Primary Dendrite Arms spacing) and SDAS(Secondary Dendrite Arms spacing) prediction during solidification process via MICRESS. I have established the binary and ternary phase field model of steel, but all the SDAS I got through simulation is less than the experimental value, even half the directional solidification results. How can I solve this deviation?
And when I investigated the PDAS, the cooling rate and temperature gradient is according to the directional solidification. But there is difference between the simulation and experiments. When the cooling rate is small, the secondary dendrite is difficult to grow in simulation while in experiment we can find obvious secondary dendrites.What can I do to deal with this difference?
Thanks a lot.
I am interested in the PDAS(Primary Dendrite Arms spacing) and SDAS(Secondary Dendrite Arms spacing) prediction during solidification process via MICRESS. I have established the binary and ternary phase field model of steel, but all the SDAS I got through simulation is less than the experimental value, even half the directional solidification results. How can I solve this deviation?
And when I investigated the PDAS, the cooling rate and temperature gradient is according to the directional solidification. But there is difference between the simulation and experiments. When the cooling rate is small, the secondary dendrite is difficult to grow in simulation while in experiment we can find obvious secondary dendrites.What can I do to deal with this difference?
Thanks a lot.
Re: Primary Dendrite Arms spacing (PDAS) prediction
Dear Shenyz,
The first question I would address is which are exactly the experimental conditions. It is important to know whether the approximation as directional solidification ("Bridgman approximation") is sufficient, or whether latent heat has to be taken into account during simulation.
A second point is whether the simulation domain is representative. If the domain is too small, the result is strongly influenced by the initial condition which you set by choosing the initial microstructure and temperature.
A third point which may be important is that the PDAS is strongly dependent on solidification history (in the simulation as well as in the experiment). If in the simulation the PDAS (due to the initial situation) is close to the lower limit, no side branches may form at all, which may be different in the experiment.
Furthermore, the selection of the PDAS as well as the tendency to form side branches depends on numerical parameters if the spatial resolution of the simulation is low. It is recommendable to use the "mob_corr" option.
Last but no least, there is a strong dependence of the SDAS and PDAS on physical parameters like diffusion coefficient in the melt and interfacial energy which in general are not (or not sufficiently exactly) known. It may be necessary to calibrate e.g. the interfacial energy by fitting.
Bernd
The first question I would address is which are exactly the experimental conditions. It is important to know whether the approximation as directional solidification ("Bridgman approximation") is sufficient, or whether latent heat has to be taken into account during simulation.
A second point is whether the simulation domain is representative. If the domain is too small, the result is strongly influenced by the initial condition which you set by choosing the initial microstructure and temperature.
A third point which may be important is that the PDAS is strongly dependent on solidification history (in the simulation as well as in the experiment). If in the simulation the PDAS (due to the initial situation) is close to the lower limit, no side branches may form at all, which may be different in the experiment.
Furthermore, the selection of the PDAS as well as the tendency to form side branches depends on numerical parameters if the spatial resolution of the simulation is low. It is recommendable to use the "mob_corr" option.
Last but no least, there is a strong dependence of the SDAS and PDAS on physical parameters like diffusion coefficient in the melt and interfacial energy which in general are not (or not sufficiently exactly) known. It may be necessary to calibrate e.g. the interfacial energy by fitting.
Bernd
Re: Primary Dendrite Arms spacing (PDAS) prediction
Dear Bernd:
Thanks! In my simulation for directional solidification, in order to match experimental conditions I set the constant cooling rate and temperature gradient and choosed moving_frame. The domain is 1000*1000 μm and resolution is 1μm.
For initial microstructure, I use the systematic method with two dendrites at the left and right side of the domain (using symmetric boundary conditions) as you have said. And initial temperature in the bottom I choosed is about 20K less than the liquidus temperature. Due to the undercooling the seed will grow and develop with the cooling rate and temperature gradient.
When the growth of dendrites maintain constant and the speed of frame is basically unchanged, I think it reached steady state. The result as below, there is large amount of residual liquid phase between dendrites and little side branches in the tip possition.
Compared with others' Cellular automaton method as bellow, my result is more sparse. How can I get correct result？
Thanks! In my simulation for directional solidification, in order to match experimental conditions I set the constant cooling rate and temperature gradient and choosed moving_frame. The domain is 1000*1000 μm and resolution is 1μm.
For initial microstructure, I use the systematic method with two dendrites at the left and right side of the domain (using symmetric boundary conditions) as you have said. And initial temperature in the bottom I choosed is about 20K less than the liquidus temperature. Due to the undercooling the seed will grow and develop with the cooling rate and temperature gradient.
When the growth of dendrites maintain constant and the speed of frame is basically unchanged, I think it reached steady state. The result as below, there is large amount of residual liquid phase between dendrites and little side branches in the tip possition.
Compared with others' Cellular automaton method as bellow, my result is more sparse. How can I get correct result？
Re: Primary Dendrite Arms spacing (PDAS) prediction
Dear Shenyz,
it seems you did not attach an image...
Bernd
it seems you did not attach an image...
Bernd
Re: Primary Dendrite Arms spacing (PDAS) prediction
Dear Bernd:
I'm sorry failed to attach an image on the forum and I have sent you a email including the image.
I'm sorry failed to attach an image on the forum and I have sent you a email including the image.
Re: Primary Dendrite Arms spacing (PDAS) prediction
Dear Shenyz,
Wish you a happy new year!
Thanks for sending me your images. What I can see from the image of the phase field simulation, the numerical setting of the simulation was definitively poor. The spatial resolution seems to be far too low, so that you obtain a nearly sharp interface. It may also be due to an not suitable interface mobility.
My advice is to try a higher spatial resolution (and a smaller domain size first) and to use "mob_corr" for mobility selection. If you attach the input files (driving file and .ges5), I can give you more detailed advice.
Which is the problem you have with file attachment? If you use the "Attachments" box below your reply window and select the files there should be no problem.
Bernd
Wish you a happy new year!
Thanks for sending me your images. What I can see from the image of the phase field simulation, the numerical setting of the simulation was definitively poor. The spatial resolution seems to be far too low, so that you obtain a nearly sharp interface. It may also be due to an not suitable interface mobility.
My advice is to try a higher spatial resolution (and a smaller domain size first) and to use "mob_corr" for mobility selection. If you attach the input files (driving file and .ges5), I can give you more detailed advice.
Which is the problem you have with file attachment? If you use the "Attachments" box below your reply window and select the files there should be no problem.
Bernd
Re: Primary Dendrite Arms spacing (PDAS) prediction
Dear Bernd:
I'm so sorry that I was busy with other projects some time ago and ignored the forum....
Now there are the input files (driving file and .ges5), and would you give me more detailed advice.
I'm so sorry that I was busy with other projects some time ago and ignored the forum....
Now there are the input files (driving file and .ges5), and would you give me more detailed advice.