Firm:

          

UES, Inc.

          

   

Address:

          

4401 Dayton-Xenia Road, Dayton, OH 45432

          

   

Phone:

          

(937) 426-6900                                                                                                                                                                                

          

   

Name:

          

Veeraraghavan Sundar

          

   

E-mail:

          

vsundar@ues.com

          

   

Address:

          

4401 Dayton-Xenia Road, OH 45432 - 1894

          

   

Phone:

          

(937) 429-6900                                                                                                                                                                                

          

   

Name:

          

Ms. Louise Tincher

          

   

E-mail:

          

ltincher@ues.com

          

   

Address:

          

4401 Dayton-Xenia Road, OH 45432 - 1894

          

   

Phone:

          

(937) 426-6900                                                                                                                                                                                

          

   

Estimated Technology Readiness Level (TRL) :                                                                                                                                                          
Begin: 4
End: 7

          

          

     

Technical Abstract (Limit 2000 characters, approximately 200 words):

X-ray computed tomography (XCT/CT) is a widely used nondestructive evaluation (NDE) method for quality control and post-build inspection in additively manufactured (AM) components. AM practitioners increasingly recognize the limitations of such NDE methods and the need to validate the capability of these methods on an ongoing basis. Automated, metallography-based serial sectioning offers a reliable method to establish ground truth data on the flaw populations as well as microstructural variations of AM components. UES proposes a project aimed at establishing comparison methods and workflows for validating CT with ground truth from serial sectioning, and developing probability of detection (POD) curves for multiple materials and defect types. The knowledge gained from these efforts will inform CT scan strategies for improved flaw detection in AM components, evaluate flaw detectability in CT using serial sectioning as a ground truth comparison, and quantify the risk of the flaws absent from the CT data sets. In addition, improving the capabilities of an automated defect recognition (ADR) algorithm can improve NDE throughput.

          

          

     

Potential NASA Applications (Limit 1500 characters, approximately 150 words):

• NASA experimenting with AM across a broad spectrum of applications and projects.
• AM has potential applications in the Lunar and Lagrange FabLabs, as well as the Mars Multi-Material FabLab for self sustainment at remote destinations 
• Improving AM via NDE has positive implications for 100% inspected directives on Orion missions.

          

          

     

Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words):

• Reliable NDE/NDI of completed components remains a barrier to wider utilization of AM components.
• Limitations in the availability of probability of detection (POD) data will drive wider adoption of AM.
• Validated interest in improving automated defect recognition algorithms.

          

          

     

Duration:     24