Experimental identification of stress concentrations in piezoresistive nanocomposites via electrical impedance tomography

H. Hassan; T. N. Tallman

doi:10.1117/12.2513468

27 March 2019 Experimental identification of stress concentrations in piezoresistive nanocomposites via electrical impedance tomography

H. Hassan, T. N. Tallman

Author Affiliations +

Proceedings Volume 10970, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2019; 109701A (2019) https://doi.org/10.1117/12.2513468
Event: SPIE Smart Structures + Nondestructive Evaluation, 2019, Denver, Colorado, United States

Abstract

Piezoresistive nanocomposites hold incredible potential for structural health monitoring (SHM). The electrical conductivity of these materials is influenced by strain, making them self-sensing. Electrical impedance tomography (EIT) is a low-cost, non-invasive method of imaging the internal conductivity distribution of a domain. To date, EIT has most often been used to detect damage. However, localizing incipient damage for failure prediction may situationally be a more useful capability from a SHM perspective. Herein, we explore the potential of EIT to identify stress concentration-induced conductivity changes in piezoresistive nanocomposites. First, a nanocomposite specimen with a circular hole is manufactured. Next, displacements are applied in small increments and boundary voltage data is collected after each increment of displacement such that conductivity images can be produced as the stress concentration intensifies. These results demonstrate that the proposed approach allows for accurate spatial localization of stress concentrations in deformed nanocomposites via EIT-imaged conductivity changes and therefore has potential to enable greatly advanced failure prediction capabilities.

Conference Presentation

Citation Download Citation

H. Hassan and T. N. Tallman "Experimental identification of stress concentrations in piezoresistive nanocomposites via electrical impedance tomography ", Proc. SPIE 10970, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2019, 109701A (27 March 2019); https://doi.org/10.1117/12.2513468

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