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Identification of internal properties of fibres and micro-swimmers

Proceedings of the Royal Society. A, Mathematical, physical, and engineering sciences, 2017-01, Vol.473 (2197), p.20160517-20160517 [Peer Reviewed Journal]

2017 The Author(s) ;Copyright The Royal Society Publishing Jan 2017 ;Distributed under a Creative Commons Attribution 4.0 International License ;2017 The Author(s) 2017 ;ISSN: 1364-5021 ;EISSN: 1471-2946 ;DOI: 10.1098/rspa.2016.0517 ;PMID: 28265186

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  • Title:
    Identification of internal properties of fibres and micro-swimmers
  • Author: Plouraboué, Franck ; Thiam, E. Ibrahima ; Delmotte, Blaise ; Climent, Eric
  • Subjects: Active Filament ; Bayesian analysis ; Bead Models ; Constraint modelling ; Engineering Sciences ; Estimators ; Fibers ; Fibre Dynamics ; Fluids mechanics ; Mechanics ; Parameter estimation ; Parameter Identification ; Parameters ; Stokesflows
  • Is Part Of: Proceedings of the Royal Society. A, Mathematical, physical, and engineering sciences, 2017-01, Vol.473 (2197), p.20160517-20160517
  • Description: In this paper, we address the identifiability of constitutive parameters of passive or active micro-swimmers. We first present a general framework for describing fibres or micro-swimmers using a bead-model description. Using a kinematic constraint formulation to describe fibres, flagellum or cilia, we find explicit linear relationship between elastic constitutive parameters and generalized velocities from computing contact forces. This linear formulation then permits one to address explicitly identifiability conditions and solve for parameter identification. We show that both active forcing and passive parameters are both identifiable independently but not simultaneously. We also provide unbiased estimators for generalized elastic parameters in the presence of Langevin-like forcing with Gaussian noise using a Bayesian approach. These theoretical results are illustrated in various configurations showing the efficiency of the proposed approach for direct parameter identification. The convergence of the proposed estimators is successfully tested numerically.
  • Publisher: England: The Royal Society Publishing
  • Language: English
  • Identifier: ISSN: 1364-5021
    EISSN: 1471-2946
    DOI: 10.1098/rspa.2016.0517
    PMID: 28265186
  • Source: Hyper Article en Ligne (HAL) (Open Access)
    Alma/SFX Local Collection
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