  A method to infer and synthetically extrapolate roughness fields from
electron microscope scans of additively manufactured surfaces using an
adaptation of Rogallo's synthetic turbulence method [R. S. Rogallo, NASA
Technical Memorandum 81315, 1981] based on Fourier modes is presented. The
resulting synthetic roughness fields are smooth and are compatible with grid
generators in computational fluid dynamics or other numerical simulations.
Unlike machine learning methods, which can require over twenty scans of surface
roughness for training, the Fourier mode based method can extrapolate
homogeneous synthetic roughness fields using a single physical roughness scan
to any desired size and range. Five types of synthetic roughness fields are
generated using an electron microscope roughness image from literature. A
comparison of their spectral energy and two-point correlation spectra show that
the synthetic fields closely approximate the roughness structures and spectral
energy of the scan.
