Toward Robotic Inspection of Dry Storage Casks for Spent Nuclear Fuel

C. J. Lissenden, S. Choi, H. Cho, A. Motta, K. Hartig, X. Xiao, S. Le Berre, S. Brennan, K. Reichard, R. Leary, B. McNelly, I. Jovanovic

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Extended dry storage of spent nuclear fuel makes it desirable to assess the structural integrity of the storage canisters. Stress corrosion cracking of the stainless steel canister is a potential degradation mode especially in marine environments. Sensing technologies are being developed with the aim of detecting the presence of chloride-bearing salts on the surface of the canister as well as whether cracks exist. Laser-induced breakdown spectroscopy (LIBS) methods for the detection of Chlorine are presented. In addition, ultrasonic-guided wave detection of crack-like notches oriented either parallel or perpendicular to the shear horizontal wave vector is demonstrated using the pulse-echo mode, which greatly simplifies the robotic delivery of the noncontact electromagnetic acoustic transducers (EMATs). Robotic delivery of both EMATs and the LIBS system is necessary due to the high temperature and radiation environment inside the cask where the measurements need to be made. Furthermore, the space to make the measurements is very constrained and maneuverability is confined by the geometry of the storage cask. In fact, a large portion of the canister surface is inaccessible due to the presence of guide channels on the inside of the cask's overpack, which is strong motivation for using guided waves for crack detection. Among the design requirements for the robotic system are to localize and track where sensor measurements are made to enable return to those locations, to avoid wedging or jamming of the robot, and to tolerate high temperatures and radiation levels.

Original languageEnglish (US)
Article number031602
JournalJournal of Pressure Vessel Technology, Transactions of the ASME
Volume139
Issue number3
DOIs
StatePublished - Jun 1 2017

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Mechanics of Materials
  • Mechanical Engineering

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