Calibration of adhesion models based on the extended Kalman filtering

G. L. S. SilvaDepartment of Mechanical Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, BrazilCorrespondence[email protected]

W. P. HernándezDepartment of Mechanical Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

L. A. BorgesDepartment of Mechanical Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

D. A. CastelloDepartment of Mechanical Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

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Victor G. Zavodinsky & Yuri G. Kabaldin. (2020) Modeling study of adhesion in the TiN/Ti, TiN/ZrN, TiN/Ti/ZrN, and TiN/Zr/ZrN layered systems. The Journal of Adhesion 96:7, pages 633-646.
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Articles from other publishers (2)

Emerson B. Albuquerque, Cynthia Guzman, Lavinia A. Borges & Daniel A. Castello. (2017) A Bayesian framework for the calibration of cohesive zone models. The Journal of Adhesion 94:4, pages 255-277.
Crossref

Yajun Zhang, Hao Wang & Hongjun Wang. (2017) Integrated Navigation Positioning Algorithm Based on Improved Kalman Filter. Integrated Navigation Positioning Algorithm Based on Improved Kalman Filter.

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Calibration of adhesion models based on the extended Kalman filtering

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Calibration of adhesion models based on the extended Kalman filtering

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