MASTER’S THESIS · U SENSE IT
Developing and validating GAP & FLUSH methods for complex profiles
My internship and Master’s thesis focused on developing new Python GAP and FLUSH algorithms for complex profiles acquired with the G3F system, then testing and validating those methods on real measured data. I built GAPFLUSH Studio as a desktop engineering environment to inspect segmentation, execute and compare candidate algorithms, visualise the geometric construction behind each result, analyse failure cases and perform repeatable profile-by-profile checks. The objective was not only to obtain a GAP or FLUSH value, but to understand when each method is geometrically valid, how robustly it behaves across different profile morphologies, and what technical evidence supports accepting or rejecting its result.







