Unsupervised bivariate data clustering for damage assessment of carbon fiber composite laminates.
Damage assessment is a key element in structural health monitoring of various industrial applications to understand well and predict the response of the material. The big uncertainty in carbon fiber composite materials response is because of variability in the initiation and propagation of damage. D...
Main Authors: | Zazilah May, M K Alam, Muhammad Shazwan Mahmud, Noor A'in A Rahman |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2020-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0242022 |
Similar Items
-
Denoising of Hydrogen Evolution Acoustic Emission Signal Based on Non-Decimated Stationary Wavelet Transform
by: Zazilah May, et al.
Published: (2020-11-01) -
Effects of large damage on residual strength of carbon fiber reinforced composite laminates
by: Zanial, Muhammad Munir
Published: (2014) -
Characterizing the fatigue damage in non-traditional laminates of carbon fiber composites using radiography
by: Rast, Joshua David
Published: (2009) -
EFFECTS OF FIBERGLASS ON RESIDUAL STRENGTH AND DAMAGE MITIGATION IN UNIDIRECTIONAL CARBON FIBER LAMINATE COMPOSITES
by: Burgelin, John Patrick
Published: (2009) -
Electrical Impedance Characterization for Damage Detection in Carbon Fiber-Reinforced Polymer (CFRP) Laminated Composites
by: Almuhammadi, Khaled H.
Published: (2018)