Metamodel-based approach for stochastic free vibration analysis of functionally graded carbon nanotube reinforced plates. (15th September 2016)

• Record Type: Journal Article
• Authors: García-Macías, Enrique; Castro-Triguero, Rafael; Friswell, Michael I.; Adhikari, Sondipon; Sáez, Andrés
• Is Part Of: Composite structures. Volume 152(2016)
• Page Start: 183
• Page End: 198
• Publication Date: 2016-09-15
• Subjects: Uncertainty quantification -- Kriging -- RS-HDMR -- Carbon nanotube -- Functionally graded materials -- Finite element method; Composite construction -- Periodicals; Composites -- Périodiques; 624.18
• DOI: 10.1016/j.compstruct.2016.05.019
• Languages: English
• ISSNs: 0263-8223

Abstract

Highlights: The CNT distribution and material parameters considered as a sources of uncertainty. Power-law and truncated Gaussian functions to define CNT variability along thickness. Kriging and RS-HDMR are employed as surrogate models. Abstract: The remarkable mechanical and sensing properties of carbon nanotubes (CNTs) suggest that they are ideal candidates for high performance and self-sensing cementitious composites. However, there is still a lack of deeper knowledge of the uncertainty associated with their incorporation into functionally graded composite materials (FGM). The influence of these uncertainties can be critical for future applications in the field of Structural Health Monitoring (SHM), techniques that usually require high accuracy modeling. Most researchers restrict the aim of their studies to the analysis of composite materials with uniform or linear grading profiles. This study sheds new light on the basis of stochastic representation of the grading profiles and analyzes the propagation of its uncertainty into the response of FG-CNT reinforced plates. The finite element method (FEM) is employed to study the individual and interactive effects of the mechanical properties (matrix/CNTs) and grading profiles via power-law distributions. The effects of stochastic uncertainties on the overall properties of the composite material are represented using probability theory.