Recorded at CDFAM Computational Design Symposium, NYC 2024
Presentation Abstract
Sandia National Labs is a systems integrator and design agency with additional production responsibility for critical components. As such, advanced and additive manufacturing offer significant potential value to our mission responsibilities. Novel functionality and efficiencies can be achieved through complex part geometries, design of new or functionally graded composites or nano-structured materials, and the leveraging of data via a “network of things” and machine-learned models for integrated AI controls and process optimization. Taken together, if fully realized, these developments hold out promise for a new era of digitally integrated product realization that is precise, responsive, and “smart”. However, shortcomings in establishing the technical basis for determining reliable performance margins persist due to the complex, coupled physical processes that create the final material as the part itself is being built. Developing sufficient scientific understanding of these processes to achieve the levels of control required for rapid realization and qualification of processes or parts is itself a challenge. A true design for AM methodology must further invert this scientific understanding to achieve targeted performance margins. This presentation details a number of ongoing efforts to develop a physics-based modeling framework for advanced and additive manufacturing that is predictive of process outcomes based on settings and can be used to provide optimized design workflows. Examples are shown for DIW stress pads and cushions and metal laser powder bed fusion.
This work was supported by the LDRD program at SNL, managed and operated by NTESS under DOE NNSA contract DE-NA0003525.
Speaker Bio
Jeremy Lechman is manager of the Energetics, Multiphase and Soft Matter Sciences Department, Engineering Sciences Center, Sandia National Laboratories
CDFAM Computational Design Symposium series brings together leading experts in computational design from industry, academia and software development for two days of knowledge sharing and networking.
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