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Evaluation of the advanced artificial athlete and Hall effect sensors for measuring strain in multi-layer sports surfaces

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posted on 02.03.2020 by David Cole, Paul Fleming, Kelly Morrison, Steph Forrester
Computer models are a useful means to explore the loading behaviour of third generation (3G) artificial turf sports surfaces; however, measuring the material stress–strain behaviour under realistic high loading rates is challenging. Therefore, the purpose of this study was two-fold: to evaluate the advanced artificial athlete (AAA) for measuring strain behaviour of polymeric sports surfaces under high loading rates typical of player interactions; and to evaluate Hall effect sensors (HES) for measuring strain behaviour of an individual layer within multi-layer sports surfaces. An independent optical measurement system (GOM) provided gold standard sample deformation and strain. Forty-five impacts onto three test samples were measured simultaneously using the three systems. Poor agreement was found between AAA and GOM peak sample deformations and strain (systematic bias 2.4 mm, 95% confidence intervals ± 1.3 mm, strain RMSD 29%), largely attributable to errors in the AAA time of initial contact. Using a regression equation to correct this time led to much better agreement in AAA peak deformations and strain (systematic bias 0.1 mm, 95% confidence intervals ± 0.7 mm, strain RMSD 8%). Good agreement was found between the HES and GOM (systematic bias 0.2 mm, 95% confidence intervals ± 0.4 mm, strain RMSD 11%). The corrected AAA and HES methods can measure deformation of polymeric sports surfaces under realistic loading rates to an accuracy of < 1 mm. In terms of strain, errors increase with decreasing peak sample deformation indicating that both systems should be used with caution for peak deformations < ~ 4–5 mm.

History

School

  • Architecture, Building and Civil Engineering
  • Mechanical, Electrical and Manufacturing Engineering
  • Science

Department

  • Physics

Published in

SN Applied Sciences

Volume

2

Issue

3

Publisher

Springer Science and Business Media LLC

Version

VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Acceptance date

24/01/2020

Publication date

2020-02-24

Copyright date

2020

ISSN

2523-3963

eISSN

2523-3971

Language

en

Depositor

Dr Steph Forrester. Deposit date: 28 February 2020

Article number

484

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