Non-destructive inspection of spent fuel casks through 14.1 MeV neutron interrogation

Dry casks for spent nuclear fuel (SNF) ensure the safe storage of SNF and provide radiation shielding. However, thick dry casks encompassing several outer layers of steel and concrete make the non-destructive inspection of the SNF a challenging task. Several approaches have been proposed for dry-cask non-destructive inspection, including the use of cosmic ray muons, high-energy X rays, passive gamma rays emitted by the SNF. None of these methods is applicable in accidental situations, when the inspection time is limited. This work demonstrates the use of fast-neutron interrogation for the rapid nondestructive assay of dry SNF storage casks. Monte Carlo simulation-based studies were performed to verify the content of the dry casks. A Geant4 model was established based on a realistic system consisting of a HI-STAR 100 cask, an MPC-68 canister and basket, and a GE-14 fuel assembly. The system was irradiated by 14.1 MeV neutrons produced by a D-T neutron generator. Several spent fuel assemblies diversion scenarios were simulated. The angular and energy distribution of the scattered neutrons were used to identify missing fuel pins. A fuel assembly in the cask with at least 75% of its pins removed can be identified with a drop in the backscattered neutron signature larger than 2σ, compared to a fully loaded scenario. An iterative reconstruction algorithm enhanced with a convolutional neural network (CNN) was applied to obtain a cross-sectional image of the fuel inside the cask using the scattered and transmitted neutron signals. The proposed imaging approach allows locating the position of a missing fuel assembly with at least 6 of the 92 pins removed when performing tomographic imaging of a canister with an overall scan time of less than two hours, using a commercial neutron generator with a source strength of 10^10 n/s in the 4π solid angle. An extended cask inspection method, including the time-correlated characteristic gamma rays emitted via neutron inelastic scattering, was developed and used to identify damages within the canister structure. The results showed that a small cavity (0.1 cm×7.5 cm×5 cm) in the canister sidewall can be identified with a confidence level of 95% in a 20-minute measurement. This signature is correlated in time with the neutron emission. Therefore, it can be used to locate the position of the neutron interactions with selected elements by detecting the alpha particle associated with the neutron emission. This method was used to reconstruct an elemental image of iron present in the cask, which reveals the steel structures. Peripheral and central damages in the honeycomb structure can be identified in the empty and assembly-loaded canisters. Using this method, structural damages located in the peripheral or central area of an empty canister can be imaged in a six-day measurement with a confidence level of 95%, and in a fifty-day measurement in a fully loaded canister, when using a commercial associated-particle neutron generator with a source strength of 10^8 n/s. As associated particle (AP) generator technology advances and higher source strengths will become available, shorter measurement times will be possible. This unique approach to inspect cask structural damages is highly penetrating, non destructive, and does not require the detector to be directly in contact with the outer canister surface, which is a radiation area. Additionally, single-pin resolution can be obtained using this method when detecting the scattered gamma rays in the 50 keV-15 MeV energy range. Both simulated models were validated through small-scale experiments in the laboratory. The combined neutron and gamma-ray signatures that we have identified provide a new rapid inspection approach for verifying the loading conditions of the SNF as well as the integrity of the canister system.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Nuclear, Plasma, Radiolgc Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2023

Author dc:creator

• Liu, Zhihua

Contributors dc:contributor

• Di Fulvio, Angela
• Kozlowski, Tomasz
• Meng, Ling Jian
• Grosse Perdekamp, Matthias
• Uddin, Rizwan

• Neutron Tomography
• Spent Nuclear Fuel
• Dry Cask Storage
• Nondestructive Assay
• Fast Iterative Shrinkage-thresholding Algorithm
• Associated Particle Technique

Statement dc:rights

• Copyright 2023 Zhihua Liu

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/120402

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F120402