Result Dissemination

Mike Tonks, Damien Tourret

How you present and disseminate your results is also a critical aspect of applying the phase-field method. Here, we provide recommended practices on disseminating your results.

For postprocessing and plotting:

Present dimensional results whenever possible

The phase-field method is inherently dimensional, meaning that each of its model parameters have specific dimensions in terms of length, time, energy, etc. This values vary for different materials and systems, based on material properties such as free energies, diffusivities, interfacial energies, and so on. However, it is a common practice to nondimensionalize a model to simplify the numerical solution. Nondimensionalization has also been used to avoid the need to have accurate material properties for a specific material system. In those cases, results are qualitative at best and are not material specific.

It is always recommended to present material-specific results using dimensional properties whenever possible. Therefore, if you nondimensionalize your model, dimensionalize your results before plotting.

Automate postprocessing and plot generation

When preparing your results for dissemination, wether for a presentation, report, or paper, you will find yourself finding things that need to be changed and having to regenerate figures and plots. This is a normal part of research. However, the work required to regenerate figures and plots can be significantly reduced using automated scripts or well-defined and documented reproducible protocol. The goal is to reduce the amount of "manual" operations to a minimum.

For plots, data is often outputted from research codes and then plotted using software such as Excel, Python, Matlab, or GNUPlot. With Python, Matlab, and GNUPlot, plots can be generated and then edited manually or scripts can be used that define all aspects of the plot. The use of scripts may make the time it takes to create the plot the first time slightly longer but will reduce the time to regenerate the plots to almost zero. Scripts also ensure that your plots have a consistent look when regenerated.

For images, ...

In your papers

Provide all of the information needed for someone else to reproduce your results

Clearly state all assumptions, including for equations you take from the literature

Prove that your new models solve correctly using simple problems before doing large demonstration problems