ARCGen - Arc-length-based Averaging and Statistics

A generalized method for computing an average and statistical response corridors from experimental signals

Biofidelity response corridors are commonly used to assess the performance of surrogates such as computational models or anthropomorphic test devices while capturing the variability of experimental data. ARCGen represents a generalized method for computing response corridors and the characteristic average of experimental data capable of accommodating most types of input signals, including experimental data that is time-based, cross-variable, non-monotonic, and/or hysteretic. ARCGen is distributed as a single MATLAB function.

Please refer to the Github repository for full package documentation and usage, as well as the Hartlen and Cronin (2022) for rigorous coverage of the subject.

ARCGen is also available in Python!

ARCGen-Python is released under the open-sourced GNU GPL v3 license. No warranty or guarantee of support is provided. The authors hold no responsibility for the validity, accuracy, or applicability of any results obtained from this code.