“…Considering the above, to date, in-silico wear prediction models of artificial human implants attract the attentions of researchers to obtain complete tribological theoretical and numerical models useful for the in-silico testing (O'Brien et al, 2015;Mattei et al, 2016;Affatato et al, 2018), which could avoid the standard in-vitro time-consuming investigation procedures (simulators) and could contribute as tool for a more and more accurate tribological design of human prostheses. Obviously, the accurate wear prediction of artificial joints requires to develop detailed tribological models accounting for the complexity and the multiscale of wear phenomenon (Vakis et al, 2018) which requires scientific knowledge in many fields, such as contact mechanics (Popov, 2010), topographic contact surfaces characterization (Merola et al, 2016), new materials formulations (Affatato et al, 2015), stress-strain analysis and FEM/BEM simulations (Ruggiero et al, 2018;Ruggiero and D'Amato R, 2019), musculoskeletal multibody modeling (Zhang et al, 2017), unsteady synovial lubrication modeling (boundary/mixed, hydro-dynamic and EHD) (Ruggiero and Sicilia, 2020), tribo-corrosion (Tan et al, 2016), metal transfer phenomena (Affatato et al, 2017), biomaterials characterizations (Ruggiero et al, 2016), etc. Moreover, innovative biomaterials and manufacturing procedures (e.g., 3D printing), novel surface modification (coatings) constitute new and exciting research areas (Ten Kate et al, 2017).…”