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Multi-Mode Imaging for TRISO-fueled Pebble Identification

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-SC0020733
Agency Tracking Number: 0000261147
Amount: $1,099,996.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: 37b
Solicitation Number: DE-FOA-0002381
Timeline
Solicitation Year: 2021
Award Year: 2021
Award Start Date (Proposal Award Date): 2021-08-23
Award End Date (Contract End Date): 2023-08-22
Small Business Information
108 Hessel Boulevard, Suite 101
Champaign, IL 61820-6574
United States
DUNS: 792045713
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Angela Di Fulvio
 (475) 201-7312
 difulvio@illinois.edu
Business Contact
 William Dick
Phone: (475) 201-7312
Email: wdick@illinoisrocstar.com
Research Institution
 Board of Trustees of the University of Illinois
 
1901 S. First Street STE A
Champaign, IL 61820-7406
United States

 Nonprofit College or University
Abstract

A common nuclear reactor design uses fuel in the form of billiard ball sized pebbles, which flow through the core continuously and can be reinserted into the core until target burnup is reached. Understanding how much radiation and damage a pebble accrues as it passes through the core, as well as the reactivity effects of reinserting an irradiated pebble into the core, are critical to designing safe and economical fuel handling protocols. To address these issues, requires tracking individual pebbles as they move through the core and adjusting for damage to surfaces. Pebbles can be identified by the unique microstruc- ture of their fuel matrices through neutron multiplicity counting, which is identified upon loading and tracked thereafter. During reactor operation, the pebbles are scanned and identified using a deep learning identification algorithm so that the radiation and damage accrued by each individual pebble can be tracked. In addition to experimental methods, detailed pebble flow will be simu- lated using open source software that allows each pebble’s trajectory to be calculated. Surface interactions can be computed and stored, providing abrasion characteristics for each pebble. Two methods were demonstrated during Phase I for pebble identification; a non-destructive assay using a fast-neutron multiplicity counter and computed tomography. An ac- companying computational pebble tracking method was utilized to develop a preliminary trajectory prediction model. A software platform will be developed to determine pebble identification from burnup and predicted trajectory. Non-destructive assay techniques will be extended to fuel pebbles and pebble fuel particle identification through computed tomography will be fully developed. Ma- chine learning, informed from the computational work, will be employed to determine the pebble path through the core. Software will be developed to be licensed to prospective vendors who are developing pebble bed reactor concepts. The experimental method will be marketed to federal entities, vendors, and regulators interested in better characterization of these fuel types.

* Information listed above is at the time of submission. *

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