About this Abstract |
Meeting |
1st World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
|
Symposium
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First World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
|
Presentation Title |
Modeling and Simulation of Additively Manufactured Lattice Structures to Support Component Qualification |
Author(s) |
Andrew Thomas Swanson |
On-Site Speaker (Planned) |
Andrew Thomas Swanson |
Abstract Scope |
Additively manufactured (AM) lattices and cellular structures give designers unique capabilities such as tunable material properties, custom surface texturing, and the ability to optimize a component’s strength and/or weight. Designers are faced with challenges for the qualification of these structures caused by high costs and the need to quantify AM material variability and reliability. To address this barrier a qualification approach for lattices that doesn’t use extensive hardware testing is needed. This can be accomplished by coupling high-fidelity finite element simulations validated through physical testing with machine learning algorithms. By conducting designed computer experiments with the validated finite element model gaussian process metamodels can be developed. These metamodels are then used for Monte Carlo simulations that assess the margins and uncertainty of key performance indicators. This data can be used as qualification evidence to show a component can reliably meet performance requirements for the material uncertainty from additive manufacturing. |
Proceedings Inclusion? |
Undecided |