Calibration of Polyvinylidene fluoride (PVDF) stress gauges under high-impact dynamic compression by machine learning

The shared materials are for calibration of PVDF stress gauges under high-impact dynamic compression by machine learning. Details will be found in the submitted paper to JAP, with a DOI to be updated in the next version. 

‘data.csv’: experimental data used for machine learning
‘training.jpynb’: notebook to train the model 
‘model.joblib’: one example of the trained  model 

The model is used for calibrating the PVDF stress gauge from 0.3 to 10 GPa, best appropriate with remnant polarization from 6.7 to 8.3 μC/cm2 and active sensing thickness from 20 to 30 μm.