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Nanomechanical properties of thermal arc sprayed coating using continuous stiffness measurement and artificial neural network

Title
Nanomechanical properties of thermal arc sprayed coating using continuous stiffness measurement and artificial neural network
Author
이한승
Keywords
Nanoindentation; Continuous stiffness measurement; Nanomechanical properties; Artificial neural network
Issue Date
2019-05
Publisher
ELSEVIER SCIENCE SA
Citation
SURFACE & COATINGS TECHNOLOGY, v. 366, Page. 266-276
Abstract
Instrumented indentation continuous stiffness measurement (CSM) method is applied to investigate the nano mechanical properties of the aluminum and zinc arc thermal spray aluminum coating. This study shows that individual component within a multi-phase material can be differentiated through the stiffness characteristic transition in a single indentation. Using this approach, the nanomechanical properties of the individual phases can be isolated and quantified using statistical deconvolution method. This paper further demonstrates that through the use of computational simulation and artificial neural network, the nanomechanical properties can be predicted based on experimental nanoindentation loading and unloading, where the load-unload responses of an individual material phase can be replicated once the nanomechanical properties are made known. This study shows that CSM method is able to predict the material's elasticity and plasticity properties, including elastic modulus, hardness, yield strength and work hardening, of individual aluminum and zinc components of the thermal arc spray coating.
URI
https://www.sciencedirect.com/science/article/pii/S0257897219303093http://repository.hanyang.ac.kr/handle/20.500.11754/121802
ISSN
0257-8972
DOI
10.1016/j.surfcoat.2019.03.041
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > ARCHITECTURE(건축학부) > Articles
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