Tuesday, March 22, 2022 from 7:00 PM to 8:30 PM PDT
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Rachel Horzewski 
Pacific Northwest AIAA 

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March 2022 
Tech Talk

Tuesday, March 22, 2022 via Zoom 
7:00 - 8:30 pm PDT

Smarter Testing with Digital Twins - Strength Prediction for Aerospace Applications 


Dr. Mahesh Chengalva and Dr. Vivian Dang 


Speaker Bio: Dr. Mahesh Chengalva 

Mahesh is an Associate Technical Fellow in the Product Development organization at Boeing Commercial Airplanes (BCA). His Boeing career started at Boeing’s Defense and Space division in Mesa, Arizona, working on the Apache attack helicopter. Later, as part of the team that designed the 787-9 Side-of-Body airframe structure, he transferred to the Seattle area to work at BCA. He led a team developing automated strength prediction methods for metallic, composite and additively manufactured aerospace structures that have enabled virtual testing for a range of applications. Mahesh has nine issued US patents and has contributed to numerous technical publications and presentations throughout his career.

Speaker Bio: Dr. Vivian Dang

Vivian T. Dang currently works as an engineering manager for the Advanced Metallic Materials, Standard Parts & Assembly team within the Product Development organization. She has been at the Boeing Company for over 16 years. Since beginning her career at the Boeing Company in 2005, Vivian has experience in the areas of program management, technical training, and structural engineering. In the area of structural engineering, Vivian supported activities for various airplane programs, which involved the application of progressive failure analysis techniques to future airplanes, parametric modeling, as well as full allowables development for thermoplastics.

Talk Abstract

The rapid increase in computing resources throughout the industry is enabling a digital transformation unlike anything preceding it. Every stage from concept to production is being digitized and working with digital twins is gradually becoming the industry norm. ‘Smarter Testing’ methods where virtual testing using digital twins to gain insight precedes actual physical testing are invaluable in minimizing the amount of expensive physical testing that is required. Since all structural failure essentially starts with local material failure, a thorough characterization of the damage/failure criteria is necessary before implementation in simulation models. Moreover, by empowering the simulation model itself to make key decisions on material damage/failure, a significant increase in predictive capability is enabled. This approach is the subject of the presentation, details of which will be presented along with production applications at Boeing and the future potential for a range of additional applications in fatigue, damage tolerance and flutter for aerospace structures.