Real-time electrical impedance monitoring of carbon fiber–reinforced polymer laminates undergoing quasi-static indentation
KAUST DepartmentComposite and Heterogeneous Material Analysis and Simulation Laboratory (COHMAS)
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
KAUST Grant NumberBAS/1/1315-01-01
Online Publication Date2018-09-20
Print Publication Date2019-01
Permanent link to this recordhttp://hdl.handle.net/10754/628794
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AbstractLaminated composites are vulnerable to damage from out-of-plane loading, particularly impact loading, and the incurred damage is often only detected by evaluating the post-impact condition of the composites. Real-time monitoring techniques are desirable for early detection of damage. Utilizing changes in the electrical properties of composites to track incurred damage is promising, but the interpretation of such measurements is still challenging. Here, an electro-mechanical system is introduced to understand how well we could detect mechanical degradation in carbon-fiber-reinforced polymer (CFRP) plates undergoing a quasi-static indentation (QSI) test, which is representative of an impact load. The system measures the in-situ, real-time changes in impedance and phase angle along the specified conductivity paths. Two different electrode configurations are proposed and tested. In all studied cases, the system effectively detected severe damage, characterized by an immediate reduction in strength, in CFRP. Using our proposed electrode configurations, we discovered that the early detection of barely visible damage strongly depends on two factors: (i) the location of the injection-measurement points with respect to the damage, and (ii) the orientation of the measurement paths with respect to the fibers orientation in the laminated CFRP surface.
CitationAlmuhammadi K, Yudhanto A, Lubineau G (2018) Real-time electrical impedance monitoring of carbon fiber–reinforced polymer laminates undergoing quasi-static indentation. Composite Structures. Available: http://dx.doi.org/10.1016/j.compstruct.2018.09.030.
SponsorsThis research was supported by King Abdullah University of Science and Technology (KAUST) Baseline Research Funds under award number BAS/1/1315-01-01, and by Collaborative Research Grants under award number URF/1/2281-01-01. The authors would like to thank Mr. Meshal Abdulkareem (KAUST Core Lab) for his assistance in building the data acquisition system; Ms. Ohoud Alharbi (KAUST Core Lab) and Mr. Ran Tao (COHMAS) for their assistance in SEM imaging.