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    ADDOPT: An Additive Manufacturing Optimal Control Framework Demonstrated in Minimizing Layer-Level Thermal Variance in Electron Beam Powder Bed Fusion 

    Source: Journal of Manufacturing Science and Engineering:;2025:;volume( 147 ):;issue: 004:;page 41009-1
    Author(s): Khrenov, Mikhail; Frieden Templeton, William; Prabha Narra, Sneha
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The large temporal and spatial variations in temperature that can occur in layer-wise metal additive manufacturing (AM) lead to thermal excursions, resulting in property variations and defects. These variations cannot ...
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    Multi-Lattice Topology Optimization Via Generative Lattice Modeling 

    Source: Journal of Mechanical Design:;2025:;volume( 147 ):;issue: 005:;page 51707-1
    Author(s): Chen, Jiangce; Baldwin, Martha; Prabha Narra, Sneha; McComb, Christopher
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Additive manufacturing enables the fabrication of multi-lattice structures, an advanced design approach featuring heterogeneous lattices at the mesoscale which are arranged to achieve a diverse and purposeful distribution ...
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    Capturing Local Temperature Evolution During Additive Manufacturing Through Fourier Neural Operators 

    Source: Journal of Manufacturing Science and Engineering:;2024:;volume( 146 ):;issue: 009:;page 91001-1
    Author(s): Chen, Jiangce; Xu, Wenzhuo; Baldwin, Martha; Nijhuis, Björn; den Boogaard, Ton van; Grande Gutiérrez, Noelia; Prabha Narra, Sneha; McComb, Christopher
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: High-fidelity, data-driven models that can quickly simulate thermal behavior during additive manufacturing (AM) are crucial for improving the performance of AM technologies in multiple areas, such as part design, process ...
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