Subsurface damage detection via noncontact laser based surface level strain sensing smart skin with carbon nanotubes. (1st June 2023)

• Record Type: Journal Article
• Authors: Pal, Ashish; Meng, Wei; Bachilo, Sergei M.; Bruce Weisman, R.; Nagarajaiah, Satish
• Is Part Of: Engineering structures. Volume 284(2023)
• Publication Date: 2023-06-01
• Subjects: Subsurface damage -- Strain-sensing smart skin -- Noncontact laser surface strain maps -- Digital image correlation -- Nondestructive testing; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2023.116017
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: Subsurface damage detection using noncontact laser based surface level smart strain sensing skin (S 4 ) with single walled carbon nanotubes is studied in this paper for the first time. The S 4 method uses single-wall carbon nanotubes in a thin polymer coating as optically interrogated fluorescent strain sensors. A set of aluminum specimens with internal cavities representing damage were coated both with S 4 films and with digital image correlation (DIC) speckle patterns. The strain maps obtained from S4 point-wise laser scanning agreed well with FEM predictions, while DIC strain maps were not very precise. S4 maps revealed strain map features with superior accuracy. It is concluded that S4 strain mapping can be used as a valuable tool non-destructive evaluation method for detecting and visualizing subsurface damage in structural elements for structural health monitoring. Abstract: Subsurface damage may remain undetected for long periods and accumulate until it leads to structural failure. Non-destructive measurements of surface strain can provide critical data for detecting early symptoms of hidden damage and helping to prevent serious consequences. This study investigates the capabilities of the developed method called strain-sensing smart skin (S 4 ) to find internal damage. The S 4 method uses single-wall carbon nanotubes in a thin polymer coating as optically interrogated fluorescent strain sensors to measure the strain map. A set of aluminum specimens with internal cavities representing damage were coated both with S 4 films and with digital image correlation (DIC) speckle patterns. Maps of surface strain from the two methods were then compared (after the application of tensile stress to the specimens) to compute finite element method (FEM) strain maps. The strain maps obtained from S 4 point-wise laser scanning agreed well with FEM predictions, while DIC strain maps were not very precise. S 4 maps revealed strain map features with superior accuracy. It is concluded that S 4 strain mapping can be used as a non-destructive evaluation method for detecting and visualizing subsurface damage in structural elements for structural health monitoring.