@article{
 title = {2D and 3D Roughness Characterization},
 type = {article},
 year = {2020},
 identifiers = {[object Object]},
 pages = {1495-1519},
 volume = {53},
 websites = {http://link.springer.com/10.1007/s00603-019-01977-4},
 month = {3},
 day = {10},
 id = {2e1349a9-e599-3c0c-985f-c5b363220c9e},
 created = {2020-09-25T20:56:24.662Z},
 file_attached = {true},
 profile_id = {4d39811a-ee39-3db8-860f-1e8ebeaaa4e2},
 last_modified = {2021-02-03T03:45:10.809Z},
 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The quantification of surface roughness for the purpose of linking its effect to mechanical and hydrodynamic behavior has taken many different forms. In this paper, we present a thorough review of commonly used 2D and 3D surface roughness characterization methods, categorized as statistical, fractal, and directional. Statistical methods are further subdivided into parametric and functional methods that yield a single value and function to evaluate roughness, respectively. These statistical roughness metrics are useful as their resultant outputs can be used in estimating shear and flow behavior in fractures. Fractal characterization methods treat rough surfaces and profiles as fractal objects to provide parameters that characterize roughness at different scales. The directional characterization method encompasses an approach more closely linked to shear strength and is more suitable for estimating the influence of fracture roughness on mechanical responses. Overall, roughness characterization methods provide an effective objective measure of surface texture that describe its influence on the mechanics of surfaces without requiring qualitative description.},
 bibtype = {article},
 author = {Magsipoc, Earl and Zhao, Qi and Grasselli, Giovanni},
 journal = {Rock Mechanics and Rock Engineering},
 number = {3}
}

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