This talk will cover recent advances in modelling aspects of a variety of tribological problems and show how in-silico experiments can be used to shed light on various physical, chemical and mechanical phenomena that affect tribological performance. The main themes discussed are the study of the influence of molecular processes on frictional, rheological and material response, the potential breakdown of continuum theories at the nano- and microscales, as well as multiscale and multiphysics aspects for computational models relevant to applications covering a variety of sectors, from automotive to biotribology and nanotechnology. Many systems involve two or more interlinked phenomena that are governed by mechanisms originating at different scales, for which complex multiscale and multiphysics models are needed. These are still challenging to develop and use as they require multidisciplinary expertise and collaborative effort. A few successful examples are provided in this talk, which show how to conduct successful virtual experiments and their necessary links to laboratory tests.
About the speakers
Prof. Daniele Dini
Faculty of Engineering, Department of Mechanical Engineering, Imperial College London
Professor Daniele Dini, D.Phil., CEng, FIMechE, MASME and FHEA holds a post as a Professor in Tribology. Professor Dini is Head of the Imperial College Tribology Group, one of the largest tribology groups in the world (about 60 full time researchers). Professor Dini’s research centres on the application of advanced modelling strategies to applied mechanics, materials, physics, chemistry, biomechanics and structural integrity, with a particular focus on tribology.
Dr. James P. Ewen
Faculty of Engineering, Department of Mechanical Engineering, Imperial College London
Dr. James P. Ewen is a Royal Academy of Engineering (RAEng) Research Fellow in the Tribology Group, Department of Mechanical Engineering, Imperial College London. James uses supercomputers to study solid-liquid interfaces with molecular simulations. He studies complex formulations to identify links between their nanoscale behaviour and macroscale performance.
