Monte Carlo N-Particle Transport Performance of Predicting Digital Radiographic IQI Inspection

Conference · Thu Jan 23 04:00:00 EST 2025

OSTI ID:2571364

Dinova, Vincent A. ^[1]; Resz, Matthew D. ^[1]; Robinson, Benjamin S. ^[1]

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1. Savannah River National Laboratory (SRNL), Aiken, SC (United States)

The identification of porosity, geometric noncompliance, and other defect types are critical to the qualification of materials and components. X-ray radiographic nondestructive testing is a common industrial inspection method for process quality control and component qualification and certification. Digital radiography provides a quick and efficient alternative when compared to traditional film-based inspection. The quality of radiographic inspection is dependent on equipment specifications, such as the source spot size and detector pixel size, and the specific parameters selected for use for the radiographic technique. To evaluate if an x-ray system and technique is sufficient for a given requirement, a radiographic image quality indicator (IQI) can be used. Radiographic IQIs in hard to machine materials or hard to manufacture defects can be time consuming and expensive to manufacture. This study was conducted to evaluate current Savannah River National Laboratory (SRNL) x-ray imaging systems with a custom tantalum IQI and using Monte Carlo simulations to predict the performance of future systems. The tantalum IQI was tested using a Siefert Isovolt 420 keV x-ray tube with a Perkin Elmer XRD 1611 flat panel with 100-micron pixels. Using the Monte Carlo N-Particle transport software, the radiographic tally was used to simulate the photon flux through an identical tantalum IQI. These simulations provided a benchmark as to the best theoretical identification on a given system using our tantalum IQI. The simulations were refined to match SRNL’s current systems’ noise levels, leading to confidence in their ability to predict the performance of other systems that may be purchased and deployed in the future at the Savannah River Site. Future studies will be conducted to prove this research can be extended to artificially evaluate the ability for systems to identify critical defect sizes through x-ray radiographic inspection, drastically reducing the cost and time burdens of producing high-fidelity radiographic test articles.

• Research Organization: Savannah River National Laboratory (SRNL), Aiken, SC (United States)
• Sponsoring Organization: DOE; EM
• DOE Contract Number: 89303321CEM000080
• OSTI ID: 2571364
• Report Number(s): SRNL-STI-2025-00028
• Country of Publication: United States
• Language: English

Related Subjects

MCNP
digital X-ray radiography
image quality indicators
non-destructive testing