Year-end Sale % OFF 
Abstract
Due to its inherited complexity, the polymer material parameters’ effect on the scratch resistance is difficult to detect. Using the scratch experimental results of a set of polypropylene (PP), the Self-Organizing Map (SOM) method, an artificial neural network algorithm, was adopted to study the effect of various material parameters on polymer scratch. Especially suitable for the analysis of high-dimensional data with nonlinear statistical relationships, SOM method helps to find out the influence of different material parameters on scratch behavior. This information can be used to estimate the possible performance of polymeric materials to certain extent without extra scratch experimental work. It also helps researchers to decide which group of properties should be paid more attention when studying the coupling effect of material parameters on polymer scratch resistance.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
