What is this repository for?
It's basically an automated fitting python app.
It works with nanoindentation experimental files, but it can be modified to other needs depending on the data to be fitted.
About its creation
The nanoindentation essay is used to get mechanical properties of materials at the nanometric scale. The process is basically composed by a very small tip (with a nanometric radius) that presses tha sample surface to construct the Load versus depth profile.
Image reference: [1]
To get statistical relevant information, a lot of profiles are generated per sample region. Therefore, I had to fit a lot of experimental curves and perfom some statistical analysis with them. It was always the same process of searching for some values in a text file, and use them into some equation to get a parameter. Then, I usually have to see how this important parameter changes from one measurement to another.
What does this repository comprise?
- fitting.py (the app itself)
- an image used in GUI
- example text files with experimental data to be fitted
The equation to be fitted:
The main equation that describes this essay is the following Hertz equation.
(eq. 1)
Where R is the tip radius and Er is the Reduced Young Modullus. The R value can present some small variation from one experiment to another. The Er value is a sample constant.
The R value can be extracted from the maximum load and depth.
(eq. 2)
The Scritpt process:
Get_Er_hmax_and_Measurement_lines(filename): Search the Er and hmax values, they are unique values on each text file. In addition, this function can also identify which lines present the Load x Depth essay data. Returns initial_data_line, final_data_line, Er, hmax(depth_max)
Get_Measurement_data(initial_data_line,final_data_line, filename): This function can extract two lists with experimental depths and load data from each text file, depending on initial and final data lines returned from previous function. Returns depth, load_experimental
Define_adjust_depth_range(depth): We want to plot only the loading part of the curve, so this funcion make a list with only the depth values on the loading part of the curve. Returns depth_loading
fitting_R(depth,depth_loading,load_experimental, Er, filename, hmax): This fuction calculates the R value based on maximum forces and depth (equation 2), and uses it to calculate the theoretical F for Pd values. This process is called Hertz fitting. The R value is returned to a list called R_list. Returns load_fitted, R
plot_experimental_and_fitted(depth, depth_loading, load_experimental, load_fitted,filename): This function plots the experimental and fitted curves, and saves the result as png files, where the R value is displayed for each curve.
plot_dispersion_and_Mean_R(R_list): Finally, we can see the R dispersion and mean.
main() and def Read_Files(): They are functions contructed to call the other functions.
[1]Ladani, L., Harvey, E., Choudhury, S. F., & Taylor, C. R. (2013). Effect of varying test parameters on elastic–plastic properties extracted by nanoindentation tests. Experimental Mechanics, 53(8), 1299-1309.