About this Abstract |
Meeting |
MS&T24: Materials Science & Technology
|
Symposium
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Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
|
Presentation Title |
Accelerating Materials Development via ICME Automation: A Laser Beam Powder Bed Fusion Case Study |
Author(s) |
David Hicks, Reese Eichhorn, Amberlee S. Haselhuhn |
On-Site Speaker (Planned) |
David Hicks |
Abstract Scope |
Development of materials for industry-relevant applications demands a comprehensive investigation of a material’s chemistry-process-structure-properties-performance relationships based on its manufacture. Additively manufactured components highlight this need, as the simultaneous creation of the material and part lead to unique properties compared to conventional processing techniques. However, no one tool encompasses these aspects of materials development, necessitating linkages to multiple simulations. Generating these connections is manual and labor-intensive, slowing modeling efforts. Herein, a computational tool is presented that automates setup, execution, post-processing, and inter-software communication between commercial software packages. This code automatically transfers and transforms the relevant data within the toolchain, alleviating the burden of expert-knowledge in different domains. Through automation, high-throughput simulations are leveraged to support manufacturing parameter exploration and model sensitivity analyses. The flexible architecture is demonstrated for an aluminum alloy and pure tungsten manufactured via laser-beam powder bed fusion, showcasing key features of the software. |