Nick Bierwisch, Saxonian Surface of Contact Mechanics, Nordhausen, Germany
A better understanding of your coating stacks and their behavior in the application is crucial for the optimization of complex engineering systems. In this context, a modeling approach, in conjunction with targeted laboratory and functional tests, is particularly attractive as it can accelerate the coating selection and achieve its goals within the desired application field. Indeed, such methodology helps to understand the coating system, including the substrate and all coatings and interfaces. Simulations can find coating limitations and guide the refinement of the coating architecture within a defined framework. A model which will contain as much digital information as possible about your sample - we call it a digital twin.
This work will showcase how the required data can be obtained by analyzing indentation and scratch measurements. SIO developed analytical models which dramatically speed up the simulation and optimization of complex contact conditions. With the help of these models, you can first dimension the relevant experiments. Afterwards you can use the experimental data from the indentation experiments to evaluate the true Young’s modulus and yield strength of each coating. By analyzing scratch tests, you can calculate critical values like the tensile stress.
In the second part of this talk we show how the digital twin can help you to find the best coating architecture for a new application by using the gathered digital data. Even if the contact conditions for the new application are not known exactly, you can use the digital simulations to narrow down the applicable samples from your portfolio.
Comparing the simulations with the results of your standard or benchmark tests could also help you to optimize the coating properties and increase the application performance.