An Integrated Approach to Cyber-Enabled Additive Manufacturing using Physics based, Coupled Multi-scale Process Modeling

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Pal, Deepankar
Patil, Nachiket
Nikoukar, Mohammad
Zeng, Kai
Haludeen Kutty, Khalid
Stucker, Brent E.

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University of Texas at Austin


The complexity of localized and dynamic boundary conditions in additive manufacturing processes makes it difficult to track in-situ thermo-mechanical changes at different length scales within a part using experimental equipment such as a FLIR1 system and other NDE2 techniques. Moreover, in-situ process monitoring is limited to providing information at an exposed surface of the build. As a result, an understanding of the bulk microstructure and behavior of a part still requires rigorous post-process microscopy and mechanical testing. In order to circumvent the limited feedback obtained from in-situ experiments and to better understand material response, a novel 3D dislocation density based thermo-mechanical finite element framework has been developed. This framework solves for the in-situ response 2 orders of magnitude faster than currently used state-of-the-art modeling software since it has been specifically designed for additive manufacturing platforms. Various aspects of this simulation tool have been and are being validated using research grants from NSF3, ONR4, AFRL5, NIST6 and NAMII7. This modeling activity has many potential commercial impacts, such as to predict the anisotropic performance of AM-produced components before they are built and as a method to enable in-situ closed-loop process control by monitoring the process and comparing it to predicted responses in real time (as the model will be used to predict results faster than an AM machine can build a part). This manuscript provides an overview of various software modules essential for creation of a robust and reliable AM software suite to address future needs for machine development, material (alloy) development and geometric optimization.


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