Performing Neutron Imaging of Mock Uranium Fuel Rods with a Robotic Manipulator

This paper describes an effort under way at the University of Texas at Austin (U.T. Austin) with collaboration from Los Alamos National Laboratory (LANL) to implement a robotic manipulator as the motion control system for neutron imaging tasks. This effort includes taking state-of-the-art robotic technologies out of the realm of pure research and using them to automate non-destructive imaging tasks in nuclear facilities. To illustrate the advantages of using a robotic manipulator with neutron imaging, mock-up depleted uranium fuel rods, each consisting of five pellets prepared from urania powder, were characterized by thermal neutron radiography. To simulate cracks and voids resulting from irradiation and burn-up in a fuel pin, tungsten and gadolinium inclusions were embedded in the mock-up pellets. A Motoman SIA5 7 Degree Of Freedom (DOF) industrial manipulator handled the fuel rods and provided advanced motion capabilities and imaging techniques that would be difficult to achieve with only linear and rotary motion stages. The robotic manipulator provides the following capabilities and advantages over ordinary motion stages with regards to imaging and motion control: autonomously image multiple samples without worker intervention, computed tomography scanning, helical scanning, orientation of the sample in 3D space, reduced radiation dose to workers, increased sample throughput, and better process control. The neutron imaging was performed in a beam port at U.T. Austin’s TRIGA Mark II research reactor at a thermal neutron flux of 5.3x106 ncm2s and thermal-to-epithermal ratio of 8.1x104 ± 10% ncm2s. The neutrons in this beam port are cooled to an effective beam temperature of 39 ± 6 K. A scintillator-mirror-camera system was utilized to acquire digital radiographs. The scintillator used was a copper, aluminum, and gold doped 6LiF ZnS neutron detection screen, and the camera was an Andor iXon+ EMCCD. The Robot Operating System (ROS), which is a flexible framework for writing robot software, was used for motion planning of the robot as well as a tool for facilitating interprocess communication between the imaging acquisition device and the robotic manipulator. ROS has made it easier than ever before to integrate the latest developments in the research community into practical robotic systems. The ultimate goal of this research and development work is to bring state-of-the-art robotics to bear on automation in non-destructive imaging applications. The tasks involved required the precision and repeatability of traditional motion stages and the flexibility made possible by the advanced motion planning capabilities of the robotic manipulator. Another goal of this effort is the characterization of irradiated fuel pins or even spent fuel, as well as offer a better guidance for expensive destructive examination of irradiated fuel pins by the non-destructive evaluation techniques. To date, the integrated system has demonstrated successful imaging of the mock-up uranium fuel rods with the necessary precision and repeatability. These early demonstrations serve as a first proof-of-concept that the advanced robotic technologies developed in research laboratories can provide for advanced non-destructive imaging abilities and applications.

References
  1. Yaskawa, “SIA5D,” Motoman Robotics. http://www.motoman.com/datasheets/SIA5D.pdf. 2012.
  2. Laux, R., “Theoretical Application of Dual Robotic Systems for Radiographic Tomography,” Materials Evaluation, pp. 513-516. 2013.
  3. Hashem, J., “Automating X-Ray and Neutron Non-Destructive Testing Applications,” Proc. of the ANS Winter Mtg., Washington, DC. 2013.
  4. Applied Scintillation Technologies, “SECUREX-ND,” http://www.appscintech.com/products/securex-nd. 2014.
  5. Andor Technology, “Hardware Guide iXonEM +,” www.andor.com, Version 1.2. 2008.
  6. Tremsin, A., “Non-Destructive Studies of Fuel Pellets by Resonance Absorption Radiography and Thermal Neutron Radiography,” Journal of Nuclear Materials, 440(1-3), pp. 633-646. 2013
  7. Quigley, M., “ROS: an open-source Robot Operating System,” ICRA Workshop on Open Source Software, Kobe, Japan. 2009
  8. ROS.org, “RViz Package Summary,” http://wiki.ros.org/rviz. 2014.
  9. Schroeder, K., 2013, “A Black Box Model for Estimating Joint Torque in an Industrial Serial Manipulator,” Proc. 2013 ASME IDETC/CIE, ASME, Portland, OR.
  10. ASTM E545-05, “Standard Test Method for Determining Image Quality in Direct Thermal Neutron Radiographic Examination,” ASTM International, West Conshohocken, PA., 2005.
  11. MathWorks, “Image Processing Toolbox,” http:// http://www.mathworks.com/products/image/. 2015.
  12. Jimenez, E., 2013, “High Performance Graphics Processor based Computed Tomography Reconstruction Algorithms for Nuclear and Other Large Scale Applications,” Sandia Report SAND2013-8059, Albuquerque, NM. 2013.
Metrics
Usage Shares
Total Views
38 Page Views
Total Shares
0 Tweets
38
0 PDF Downloads
0
0 Facebook Shares
Total Usage
38