Simulation Virtual Insight Into Previously Unexplored Friction Mechanisms

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Prof. Dr. Michael Moseler, head of the Tribology business field at the Fraunhofer Institute for Mechanics of Materials IWM, has developed a digital twin that can describe lubrication under high load and predict the design and operating conditions for energy-efficient machines.

Friction is ubiquitous. Where components move against each other, energy is consumed. According to calculations, this costs up to 20 percent of global energy consumption—despite many technological solutions for reducing friction, such as new lubricants and coatings.

Prof. Dr. Michael Moseler, head of the tribology division at the Fraunhofer Institute for Mechanics of Materials IWM in Freiburg and professor for the simulation of functional nanosystems at the University of Freiburg (Germany), has developed a digital twin for lubricated friction contacts to unlock the untapped potential for energy savings and sustainability in friction. The challenge: to make experimentally inaccessible friction-causing processes in technical systems calculable. This includes processes that occur on the atomic level, such as viscosity changes of lubricants in nanoscale friction gaps or the sliding of the thus solidified lubricant over material surfaces.

Predict The Behavior of The Friction System

A novel approach to computer simulations is employed here. Simulation methods and computational models that describe the mechanisms on different scales are combined into a single tool to capture the friction-causing features and predict the behavior of the friction system. Once the cause-effect relationships between the atomic processes and the energy-consuming friction are mathematically described for the respective technical system, it can also be optimized.

This is How The Digital Twin Makes Friction Calculable

The calculations utilize molecular dynamics simulations on an extreme scale, taking into account the atomistic effects in this area of friction. A key aspect of the project is the development of physically based material models that accurately reproduce the behavior observed in molecular dynamics. For instance, precise constitutive equations for the rheology and tribochemical reactions of lubricant films a few nanometers thick under gigapascal pressures need to be determined. These are integrated into continuum equations and form the core of the digital twin, which aims to make thermo-elasto-hydrodynamic lubrication in highly stressed components (e.g., rolling bearings and gear pairings) calculable. The project will use automated workflows for molecular high-throughput calculations of friction contacts under a variety of load parameters. Additionally, the latest generation of machine-learned interatomic potentials (MLIPs), which offer quantum mechanical accuracy at a fraction of the computational cost, will be deployed.

More Sustainability And Energy Efficiency in Machines, Devices, And Vehicles

It is the combination of extreme-scale atomistic simulations, machine-trained AI force fields, and the integration of the resulting physical constitutive equations into a continuum description of the highly stressed lubricant that makes the research approach unique and provides a virtual insight into previously unexplored and inaccessible friction mechanisms. Other success factors include the intelligent and efficient use of enormous computing capacity for simulating up to one billion atoms and the development of a powerful digital infrastructure for the resulting data streams and data analysis.

In five years, the digital twin is expected to ensure greater sustainability and energy efficiency in machines, devices, and vehicles by bridging the gap between atomic friction phenomena and the design of bearings and gearboxes.

For the implementation of the ambitious research project, Moseler has received an "ERC Advanced Grant" of 2.7 million dollars for five years from the European Research Council. An ERC Grant is one of the most prestigious awards in European research funding.

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