Licensing Opportunity: System and Method for Artifact Reduction of Computed Tomography Reconstruction Leveraging Artificial Intelligence and a Priori Known Model for the Object of Interest
Closed Special Notice Posted
- Solicitation number
- 2024-08-29_A
- Agency
-
Department of Energy
- Responses due
- Set-aside
- No set-aside
Opportunity facts
- Place of performance
- Oak Ridge, Tennessee 37830, United States
- Points of contact
Notice details come from SAM.gov. Updated .
About this opportunity
The Department of Energy has published a Special Notice for a Licensing Opportunity related to a system and method for artifact reduction of computed tomography (CT) reconstruction leveraging artificial intelligence (AI) and a priori known model for the object of interest. This advanced technology, developed by Oak Ridge National Laboratory (ORNL), is called Simurgh and aims to revolutionize industrial CT imaging by incorporating AI to enhance the speed and accuracy of nondestructive testing for complex parts, leading to significant cost reductions.
The purpose of this Special Notice is to make this Simurgh technology available for licensing. The technology enables high-quality CT reconstructions from sparse and low-exposure scans, significantly improving defect detection and reducing scan times by 12 to 20 times compared to traditional methods. It can be applied across various industries, including aerospace, automotive, biomedical, and energy, and is particularly well-suited for Industry 4.0 applications due to its scalability and high-throughput evaluation capabilities. The Special Notice provides details on the key benefits of the Simurgh technology and invites interested parties to contact ORNL for more information. There is no set-aside for this licensing opportunity, and the due date for responses is October 14, 2024.
Notice text
Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.
Computed tomography (CT) is a critical technology in nondestructive evaluation (NDE) for industries such as aerospace, automotive, biomedical, and energy. Traditional CT methods face challenges in detecting defects in dense and complex components due to limitations in scan speed, resolution, and artifact management. Simurgh revolutionizes industrial CT imaging by incorporating artificial intelligence (AI), resulting in cost reduction through enhanced speed and offering superior accuracy in nondestructive testing for complex parts.
Simurgh is an AI-powered CT framework developed by Oak Ridge National Laboratory (ORNL). This advanced technology integrates AI algorithms with physics-based modeling and computer-aided design data to enhance the quality and speed of CT scans. Simurgh enables high-quality reconstructions from sparse and low-exposure scans, significantly improving defect detection, and greatly reducing scan times.
Applications and Industries
- Additive manufacturing (AM): Qualifies complex AM parts by providing rapid, high-resolution CT scans to detect flaws and ensure part integrity.
- Aerospace and automotive: Enhances safety and performance through accurate defect detection in critical components.
- Biomedical devices: Improves the quality assurance of medical implants and devices, ensuring patient safety.
- Energy industry: Assists in the evaluation of components used in energy production, enhancing reliability and efficiency.
Benefits
- Increased speed: Delivers scan times of 12 to 20 times faster than traditional methods.
- Enhanced accuracy: Improves defect detection capabilities by four times. Simurgh has reliably demonstrated that it can identify flaws as small as 50 µm–100 µm depending on material and related high energy industrial X-ray system capabilities with significantly faster scan times.
- Cost reduction: Lowers operational costs by reducing scan times, the need for extensive post-processing and manual input, and associated labor costs.
- Versatility: Applicable across various industries including aerospace, automotive, biomedical, electronics, and advanced manufacturing.
- Scalability: Facilitates high-throughput evaluation and testing, making it ideal for Industry 4.0 applications.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
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