Estimation of geometrically necessary dislocation density from filtered EBSD data by a local linear adaptation of smoothing splines. Issue 3 (7th May 2019) - Seret, Anthony
Abstract : An implementation of smoothing splines allowing for an intuitive calibration of the fitting versus smoothing trade‐off and directly applicable to any grid/neighbourhood is proposed to reduce orientation noise in electron backscatter diffraction (EBSD) data, and subsequently estimate more accurate geometrically necessary dislocation (GND) densities. In particular, the local linear adaptation of smoothing splines filter reasonably preserves sub‐boundaries and GND structures. Abstract : An implementation of smoothing splines is proposed to reduce orientation noise in electron backscatter diffraction (EBSD) data, and subsequently estimate more accurate geometrically necessary dislocation (GND) densities. The local linear adaptation of smoothing splines (LLASS) filter has two advantages over classical implementations of smoothing splines: (1) it allows for an intuitive calibration of the fitting versus smoothing trade‐off and (2) it can be applied directly and in the same manner to both square and hexagonal grids, and to 2D as well as to 3D EBSD data sets. Furthermore, the LLASS filter calculates the filtered orientation gradient, which is actually at the core of the method and which is subsequently used to calculate the GND density. The LLASS filter is applied on a simulated low‐misorientation‐angle boundary corrupted by artificial orientation noise (on a square grid), and on experimental EBSD data of a compressed Ni‐base superalloy (acquired on a square grid) and of a dual austenitic/martensitic steel (acquired on an hexagonal grid). The LLASS filter leads to lower GND density values as compared to raw EBSD data sets, as a result of orientation noise being reduced, while preserving true GND structures. In addition, the results are compared with those of filters available in the MTEX toolbox.