Our research highlights serve as a collection of feature articles detailing recent scientific achievements on GCS HPC resources.
A snapshot of one the TU Kaiserslautern team’s cutting simulations. These atomic-scale simulations were done on HPC resources at the High-Performance Computing Center Stuttgart and the Leibniz Supercomputing Centre in Garching. Image credit: Laboratory of Engineering Thermodynamics (LTD)/ TU Kaiserslautern
As humanity has advanced its knowledge and understanding of science and engineering, our ability to construct increasingly specialized and complex technologies has been anchored by our ability to understand material interactions at an increasingly small scale.
Many technical and industrial processes are considered tribological processes. Here, two surfaces in motion interact with one another, such as when two cogs in a machine thread with one another, or a manufacturing machine removes material to shape a part or component. In many cases, two solid materials interacting with one another can wear out the constituent pieces quickly or cause deformations in the material. Engineers often use lubricants to prolong the lifetime of parts and ensure smooth operating conditions.
While we have long used lubrication in the internal combustion engine, and gear boxes, and the machinery for manufacturing, we still have only a preliminary understanding of the fundamental behavior and processes at the atomic scale.
In order to better understand the function of lubrication in tribological processes, researchers from the Technische Universität Kaiserslautern (TUK) have been using high-performance computing (HPC) resources at the High-Performance Computing Center Stuttgart (HLRS) and the Leibniz Supercomputing Centre (LRZ) in Garching near Munich to study these interactions at the atomic scale. The team’s research was recently published in Langmuir.
“For the research community, understanding tribological systems is crucial, but very little effort is spent on simulating contact processes under the influence of lubricants at the atomic level,” says Simon Stephan, the TUK researcher leading this aspect of the team’s research. “Understanding the mechanisms and phenomena occurring in such systems will give us a chance to significantly improve tribological properties in a large variety of applications and also understand why certain fluids are good lubricants and others are not.”
The TUK researchers are focusing on nanoscopic fundamentals of lubricated contact processes under the auspices of two DFG funded projects: SFB 926 (Microscale Morphology of Component Surfaces), an interdisciplinary cooperation involving mechanical engineering, process engineering, and surface physics; and IRTG 2057 (Physical Modeling for Virtual Manufacturing Systems and Processes), an international graduate school for PhD students focusing on the physical modeling of manufacturing processes.
Slick simulations
While researchers understand the basic aspects of how lubricants influence tribological processes at the macro- and microscale, there is very little experimental data illuminating these processes on an atomic level. Observing these phenomena experimentally is practically impossible, as the contact zones are inaccessible due to their size and the fact that they are enclosed within solid parts. In addition, temperature and pressure conditions are usually extremely high where the contact takes place.
For these reasons, the TU Kaiserslautern researchers turned to molecular simulations to computationally examine tribological processes at the nanoscale.
Using the world-class supercomputing resources at HLRS and LRZ, it is becoming possible to create simulations that are both large enough to understand how tribological phenomena influence a real-world system and precise enough to capture the atomic-level details necessary for understanding them at a fundamental level.
“Tribological processes are a combination of many aspects that are happening simultaneously,” Stephan says. “You need a realistic model for your fluid molecules, your substrate atoms, and the fluid-substrate interactions, as well as a proper geometric set up, among other things. If you don’t model a big enough system, though, you can’t really see and understand how different phenomena interact, like the local temperature in the contact zone and the heat fluxes into the fluid and the solid bodies.”
Using the Hazel Hen supercomputer at HLRS and the SuperMUC supercomputer at LRZ to carry out its simulations, the team wanted to focus on the influence of the interactions between fluid and solid atoms in tribological processes in the context of how lubricants influence friction and cutting processes.
The team’s simulations were the first ever systematic investigation of the influence of the solid-fluid interaction energy on a nanoscopic contact process between two solid parts fully submerged in a liquid.
The researchers found that lubricants reduced friction by 25 percent and reduced the heat impact on the solid bodies by up to 20 percent. Using a large cluster of simulations, the team showed that the interactions between solid and fluid atoms have an important influence on the number of lubricant molecules being trapped in the contact zone and on other tribological properties.
Foundations for the future
The team’s model and simulations serve as a proof of concept for their computational approach. As computing power continues to increase, the researchers hope to be able to increase the simulation complexity by applying their approach to more realistic rough surfaces or more complex lubricant molecules.
While Stephan is happy with the hardware capabilities at the GCS centres, he is hopeful that next-generation machines with larger numbers of compute cores will allow the team to run simulations more frequently and flexibly, enabling the team to apply its approach to more specific applications and to extend their work to more complex (and realistic) scenarios.
“We are very satisfied with the access we have to the hardware at the GCS centres,” he said.” We hope that as the next generation machines come online and expand their core counts, we are able to get our simulations done 4 to 5 times faster than we can right now. That will ultimately allow us to perform our simulations in even more realistic directions.”
-Eric Gedenk
Related Publication: https://pubs.acs.org/doi/10.1021/acs.langmuir.9b01033