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Proceedings Paper

Develop an piezoelectric sensing based on SHM system for nuclear dry storage system
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Paper Abstract

In US, there are over 1482 dry cask storage system (DCSS) in use storing 57,807 fuel assemblies. Monitoring is necessary to determine and predict the degradation state of the systems and structures. Therefore, nondestructive monitoring is in urgent need and must be integrated into the fuel cycle to quantify the “state of health” for the safe operation of nuclear power plants (NPP) and radioactive waste storage systems (RWSS). Innovative approaches are desired to evaluate the degradation and damage of used fuel containers under extended storage. Structural health monitoring (SHM) is an emerging technology that uses in-situ sensory system to perform rapid nondestructive detection of structural damage as well as long-term integrity monitoring. It has been extensively studied in aerospace engineering over the past two decades. This paper presents the development of a SHM and damage detection methodology based on piezoelectric sensors technologies for steel canisters in nuclear dry cask storage system. Durability and survivability of piezoelectric sensors under temperature influence are first investigated in this work by evaluating sensor capacitance and electromechanical admittance. Toward damage detection, the PES are configured in pitch catch setup to transmit and receive guided waves in plate-like structures. When the inspected structure has damage such as a surface defect, the incident guided waves will be reflected or scattered resulting in changes in the wave measurements. Sparse array algorithm is developed and implemented using multiple sensors to image the structure. The sparse array algorithm is also evaluated at elevated temperature.

Paper Details

Date Published: 1 April 2016
PDF: 11 pages
Proc. SPIE 9806, Smart Materials and Nondestructive Evaluation for Energy Systems 2016, 98060U (1 April 2016); doi: 10.1117/12.2219899
Show Author Affiliations
Linlin Ma, Univ. of South Carolina (United States)
Bin Lin, Univ. of South Carolina (United States)
Xiaoyi Sun, Univ. of South Carolina (United States)
Stephen Howden, Univ. of South Carolina (United States)
Lingyu Yu, Univ. of South Carolina (United States)


Published in SPIE Proceedings Vol. 9806:
Smart Materials and Nondestructive Evaluation for Energy Systems 2016
Norbert G. Meyendorf; Theodoros E. Matikas; Kara J. Peters, Editor(s)

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