Tribo-Dynamics Digital Twins (TDDTs): prediction of friction and Frequency Response Function (FRF) in a dry sliding tribological contact

Assembled systems typically contain mechanical joints that are in physical contact and heavily influenced by friction and vibration. Friction is affected by contact stress, temperature, material, and roughness of contacting parts, from geometrical features at the macro- to nanoscale. Understanding and predicting the friction of contact helps to create designs that reduce wear, crack propagation, damage, and energy consumption. Recently, digital twins have been used in different mechanical engineering mechanisms and systems to predict crack, damage, and frequency response functions. Digital twins, with their system-level thinking, have promoted the idea of cross-industry development and ideology. The aim of the current study is to develop the digital twin-enabling technology for a simple dry contact under reciprocating motion. This enabling technology (digital twins) is the development of a grey-box model using conventional tribometer experimental data under cyclic loading and advanced multi-scale (contact mechanics to macro-scale dynamics) finite element analysis to provide an accurate estimation in a realistic time scale for digital twins. To demonstrate this, a ball and a flat plate made of steel (304) were used to create a physical twin. The test was run using a Universal Mechanical Tester (Broker UMT-3 tribometer) under speed and load sweep conditions to determine the coefficient of friction at different operating conditions. The experimental data for friction were collected and used for machine learning along with an FEA model using Abaqus which makes the digital twin. The machine learning part of the digital twin was used to predict the coefficient of kinetic friction under different operating conditions and can interoperate with other models to greatly expand the digital twin functionality. The predicted coefficient of friction was fed to FEA model to predict the mechanical behaviour of the system such as Frequency Response Function.