A Multi-Fidelity Workflow for Conceptual Design Using Graph Neural Network-Based Field Prediction Surrogate Model
Published in Computers & Fluids, 2026
This journal article presents a multi-fidelity conceptual design workflow that uses a graph neural network-based field prediction surrogate model to augment low-fidelity aerodynamic analysis with high-fidelity CFD information.
Paper DOI: https://doi.org/10.1016/j.compfluid.2026.107153
Paper PDF: https://yiren6.github.io/files/Shen-et-al_2026_cnf.pdf
Recommended citation: Shen, Y.; Needels, J.; Alonso, J. (2026). "A Multi-Fidelity Workflow for Conceptual Design Using Graph Neural Network-Based Field Prediction Surrogate Model." Computers & Fluids. 317, 107153.
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