Semi-implicit iterative methods for low Mach number turbulent reacting flows: Operator splitting versus approximate factorization. - Jonathan F. MacArt; Michael E. Mueller (J. Comput. Phys., 2016)

DPM: A deep learning PDE augmentation method with application to large-eddy simulation. - Justin A. Sirignano; Jonathan F. MacArt; Jonathan B. Freund (J. Comput. Phys., 2020)

Embedded training of neural-network sub-grid-scale turbulence models. - Jonathan F. MacArt; Justin A. Sirignano; Jonathan B. Freund (CoRR, 2021)

Deep Learning Closure Models for Large-Eddy Simulation of Flows around Bluff Bodies. - Justin A. Sirignano; Jonathan F. MacArt (CoRR, 2022)

Dynamic Deep Learning LES Closures: Online Optimization With Embedded DNS. - Justin A. Sirignano; Jonathan F. MacArt (CoRR, 2023)

PDE-constrained models with neural network terms: Optimization and global convergence. - Justin A. Sirignano; Jonathan F. MacArt; Konstantinos Spiliopoulos (J. Comput. Phys., 2023)

Sampling-based Distributed Training with Message Passing Neural Network. - Priyesh Kakka; Sheel Nidhan; Rishikesh Ranade; Jonathan F. MacArt (CoRR, 2024)

A TVD neural network closure and application to turbulent combustion. - Seung Won Suh; Jonathan F. MacArt; Luke N. Olson; Jonathan B. Freund (J. Comput. Phys., 2025)

Corrigendum to "A TVD neural network closure and application to turbulent combustion" [Journal of Computational Physics 523 (2025)/113638]. - Seung Won Suh; Jonathan F. MacArt; Luke N. Olson; Jonathan B. Freund (J. Comput. Phys., 2025)

OGF: An Online Gradient Flow Method for Optimizing the Statistical Steady-State Time Averages of Unsteady Turbulent Flows. - Tom Hickling; Jonathan F. MacArt; Justin A. Sirignano; Den Waidmann (CoRR, 2025)

Physics-Based Machine Learning Closures and Wall Models for Hypersonic Transition-Continuum Boundary Layer Predictions. - Ashish S. Nair; Narendra Singh; Marco Panesi; Justin A. Sirignano; Jonathan F. MacArt (CoRR, 2025)