A method to estimate the resistivity of composite structures using an inverse problem solving algorithm is presented that uses voltage distribution on the structure as data. Electrodes attached to the surface of the structure are used to obtain voltage data in response to current injection through a pair of these electrodes. The forward problem involves using the finite element method to predict the voltages at the electrodes using known values of resistivity. The inverse problem involves solving for the resistivity values using the experimentally measured voltage data. If the material does not have uniform properties, the computed resistivity values are average values. Damage or defect in a composite structure can significantly alter the average resistivity of the structure. To explore the possibility of using this approach to detect defects in manufacturing or damage due to loading, the effect of artificially induced damage/defect on the overall resistivity of the structure is studied.
Skip Nav Destination
Article navigation
January 2011
Research Papers
Inverse Method for Estimating Resistivity of Carbon Fiber Composite Structures
Sung-Uk Zhang,
Sung-Uk Zhang
Department of Mechanical and Aerospace Engineering,
University of Florida
, Gainesville, FL 32611
Search for other works by this author on:
Ashok V. Kumar
Ashok V. Kumar
Department of Mechanical and Aerospace Engineering,
University of Florida
, Gainesville, FL 32611
Search for other works by this author on:
Sung-Uk Zhang
Department of Mechanical and Aerospace Engineering,
University of Florida
, Gainesville, FL 32611
Ashok V. Kumar
Department of Mechanical and Aerospace Engineering,
University of Florida
, Gainesville, FL 32611J. Eng. Mater. Technol. Jan 2011, 133(1): 011009 (6 pages)
Published Online: December 2, 2010
Article history
Received:
January 21, 2010
Revised:
July 14, 2010
Online:
December 2, 2010
Published:
December 2, 2010
Citation
Zhang, S., and Kumar, A. V. (December 2, 2010). "Inverse Method for Estimating Resistivity of Carbon Fiber Composite Structures." ASME. J. Eng. Mater. Technol. January 2011; 133(1): 011009. https://doi.org/10.1115/1.4002627
Download citation file:
Get Email Alerts
Cited By
Evaluation of Machine Learning Models for Predicting the Hot Deformation Flow Stress of Sintered Al–Zn–Mg Alloy
J. Eng. Mater. Technol (April 2025)
Blast Mitigation Using Monolithic Closed-Cell Aluminum Foam
J. Eng. Mater. Technol (April 2025)
Irradiation Damage Evolution Dependence on Misorientation Angle for Σ 5 Grain Boundary of Nb: An Atomistic Simulation-Based Study
J. Eng. Mater. Technol (July 2025)
Related Articles
Damage in Composite NiMH Positive Electrodes
J. Eng. Mater. Technol (October,1998)
All-Perovskite Solid Oxide Fuel Cells, Synthesis and Characterization
J. Fuel Cell Sci. Technol (May,2009)
Analysis of Tube Hydroforming by Means of an Inverse Approach
J. Manuf. Sci. Eng (May,2003)
Related Proceedings Papers
Related Chapters
A Review on Prediction over Pressured Zone in Hydrocarbon Well Using Seismic Travel Time through Artificial Intelligence Technique for Pre-Drilling Planing
International Conference on Software Technology and Engineering, 3rd (ICSTE 2011)
Computational Inverse Problem Techniques in Vibroacoustics
Biomedical Applications of Vibration and Acoustics in Imaging and Characterizations
Applications of the BEM to Heat Transfer and Inverse Problems
Introduction to Finite Element, Boundary Element, and Meshless Methods: With Applications to Heat Transfer and Fluid Flow