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Mechanical Engineering Commons

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Aerospace Engineering

Missouri University of Science and Technology

Aluminum

Publication Year

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Full-Text Articles in Mechanical Engineering

Heat Treatments For Minimization Of Residual Stresses And Maximization Of Tensile Strengths Of Scalmalloy® Processed Via Directed Energy Deposition, Rachel Boillat-Newport, Sriram Praneeth Isanaka, Jonathan Kelley, Frank Liou Mar 2024

Heat Treatments For Minimization Of Residual Stresses And Maximization Of Tensile Strengths Of Scalmalloy® Processed Via Directed Energy Deposition, Rachel Boillat-Newport, Sriram Praneeth Isanaka, Jonathan Kelley, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Scalmalloy® is an Al-Mg-Sc-Zr-Based Alloy Specifically Developed for Additive Manufacturing (AM). This Alloy is Designed for Use with a Direct Aging Treatment, as Recommended by the Manufacturer, Rather Than with a Multistep Treatment, as Often Seen in Conventional Manufacturing. Most Work with Scalmalloy® is Conducted using Powder Bed Rather Than Powder-Fed Processes. This Investigation Seeks to Fill This Knowledge Gap and Expand Beyond Single-Step Aging to Promote an overall Balanced AM-Fabricated Component. for This Study, Directed Energy Deposition (DED)-Fabricated Scalmalloy® Components Were Subjected to Low-Temperature Treatments to Minimize Residual Stresses Inherent in the Material Due to the Layer-By-Layer Build Process. …


Searching For Unknown Material Properties For Am Simulations, Aaron Flood, Rachel Boillat, Sriram Praneeth Isanaka, Frank W. Liou Nov 2023

Searching For Unknown Material Properties For Am Simulations, Aaron Flood, Rachel Boillat, Sriram Praneeth Isanaka, Frank W. Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Additive manufacturing (AM) simulations are effective for materials that are well characterized and published; however, for newer or proprietary materials, they cannot provide accurate results due to the lack of knowledge of the material properties. This work demonstrates the process of the application of mathematical search algorithms to develop an optimized material dataset which results in accurate simulations for the laser directed energy deposition (DED) process. This was performed by first using a well-characterized material, Ti-64, to show the error in the predicted melt pool was accurate, and the error was found to be less than two resolution steps. Then, …