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Meeting 2018 TMS Annual Meeting & Exhibition
Symposium Computational Method and Experimental Approaches for Model Development and Validation, Uncertainty Quantification, and Stochastic Predictions
Presentation Title Large Scale Sensitivity of Uncertain Parameters on Optimal Control Solutions: An Example in Additive Manufacturing
Author(s) Bart van Bloemen Waanders, Joseph Hart
On-Site Speaker (Planned) Bart van Bloemen Waanders
Abstract Scope Additive manufacturing introduces considerable flexibility and efficiency in the overall design process. However a range of variability and uncertainties have been observed in material properties of final parts. The complexity of the dynamics and the large number of operating settings create an insurmountable challenge to manually control AM machines in a way that result in predicable material properties. To address these challenges, we have implemented a capability to determine the sensitivity of uncertain parameters to an optimal control strategy. Our solution procedure consist of solving coupled outer and inner problems in which the inner problem solves for a control solution constrained by dynamics and the outer-problem solves a directional derivative with the KKT operators from the inner problem. We demonstrate our technique on a simple thermal formulation in addition to a more complex problem conducive to AM processes.
Proceedings Inclusion? Planned: Supplemental Proceedings volume


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New Advances in Semi-empirical Interatomic Potentials - the Modified Embedded Atom Method (MEAM)
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Property Localization: Quantifying the Uncertainty of Inferred Constitutive Models for Grain Boundaries
The Current State of Phase Field Benchmark Problems Developed by CHiMaD/NIST
The OpenKIM Testing Framework for Interatomic Potentials
The Role of Data Analysis in Uncertainty Quantification: Examples from Materials Science
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Uncertainty Quantification for Solute Transport Modeling
Uncertainty Quantification in Materials Strength Models Using Bayesian Inference
Uncertainty Quantification of the Effect of Charge Noise on Silicon Quantum Dots
Utilizing Error in First-principle Lattice Constants to Discover Novel Low-dimensional Materials

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