DSM is proud to announce that our research scientist Leonid Pastukhov has received the “Best Presentation 2020 Award” at the Integrated Computational Materials Engineering (ICME) 2020 Virtual Conference, which ran from October 6 to 8. His presentation was selected out of more than 34 entries exploring the impact of ICME across various industries worldwide.
The annual conference invites hundreds of executives, R&D specialists, manufacturing professionals, engineers, and designers to share knowledge on the manufacturing, material and part performance trends that are transforming production processes globally. Each year, the ICME committee and presentation audiences collectively determine the “Best Presentation Award” winner.
In November, two winners were announced under separate categories, "Industrializing ICME" and "Innovating with ICME.” Pastukhov, who won in the "Ïnnovating with ICME" category, will receive the coveted 3D-printed Representative Volume Elements (RVE) trophy printed by Stratasys.
ICME applications are key to DSM’s strategic goals to increase adoption of digitization and digitalization technologies, which were announced in 2019. This transition is essential to enabling us to build more intimate relationships with our customers, implement automation and data analytics tools that drive greater operational efficiency, and support new business models that leverage artificial intelligence.
A hybrid modelling approach
Digitization and digitalization are particularly relevant to improving our material design and testing processes through predictive engineering. Typically, material performance assessments are done by conducting individual tests that are highly accurate, yet time-consuming, or simulating tests using pre-existing data, which can be done quickly, but with limited accuracy.
Pastukhov’s presentation, “Virtual material testing and development of material models for enabling more accurate and faster application design optimization,” responds to this challenge and offers a solution. His hybrid modelling approach combines physics-based models with machine learning algorithms based on in-depth stress-stain material data. This creates a reliable, robust framework for predicting material behaviour for different fibre weight fractions, temperatures, and moisture levels with exceptionally high precision.
Virtual material modelling enables our teams to quickly produce Digimat material cards analyzing how specific grades of polymers and polymer composites will perform relative to our customers’ requirements. This leads to better customer support before production cycles begin, and accurately verifies how our solutions perform against competing materials.
The technology also has the potential to significantly shorten production cycle times. The ability to manage a part’s entire design and optimization virtually means that only one cycle of validation testing is required once final parts are molded. For material suppliers, this translates to substantial time and cost savings.
Pastukhov, who holds a master’s degree from Queen Mary University of London, and a PhD in Mechanical Engineering from the Eindhoven University of Technology, is based at the DSM Materials Science Center in Geleen, the Netherlands. Since joining DSM in January 2020, his research has been focused on developing predictive models of durability and mechanical performance in polymers and polymer composites.
“For me, it’s great to see that the work that has been done in my first year with the company is appreciated both within DSM and externally,” said Pastukhov. “It’s been rewarding to see the virtual modeling framework proved successful in efficiently generating reliable and comprehensive data, and exciting that it can be readily expanded to more materials, since it is based on underlying physics.”
Interested in learning more about how virtual material modelling can help you find materials optimized for your needs? Contact us today.