Jonathan F. MacArt

18 papers Journal 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	OGF: An online gradient flow method for optimizing the statistical steady-state time averages of unsteady turbulent flows. J. Comput. Phys. Tom Hickling, Jonathan F. MacArt, Justin A. Sirignano, Den Waidmann
2026	J	`jnl`	Online optimisation of machine learning collision models to accelerate direct molecular simulation of rarefied gas flows. J. Comput. Phys. Nicholas Daultry Ball, Jonathan F. MacArt, Justin A. Sirignano
2025	J	`jnl`	A TVD neural network closure and application to turbulent combustion. J. Comput. Phys. Seung Won Suh, Jonathan F. MacArt, Luke N. Olson, Jonathan B. Freund
2025	J	`jnl`	Active Control of Turbulent Airfoil Flows Using Adjoint-based Deep Learning. CoRR Xuemin Liu, Tom Hickling, Jonathan F. MacArt
2025	J	`jnl`	Corrigendum to "A TVD neural network closure and application to turbulent combustion" [Journal of Computational Physics 523 (2025)/113638]. J. Comput. Phys. Seung Won Suh, Jonathan F. MacArt, Luke N. Olson, Jonathan B. Freund
2025	J	`jnl`	OGF: An Online Gradient Flow Method for Optimizing the Statistical Steady-State Time Averages of Unsteady Turbulent Flows. CoRR Tom Hickling, Jonathan F. MacArt, Justin A. Sirignano, Den Waidmann
2025	J	`jnl`	Physics-Based Machine Learning Closures and Wall Models for Hypersonic Transition-Continuum Boundary Layer Predictions. CoRR Ashish S. Nair, Narendra Singh, Marco Panesi, Justin A. Sirignano, Jonathan F. MacArt
2025	J	`jnl`	oRANS: Online optimisation of RANS machine learning models with embedded DNS data generation. CoRR Daniel Dehtyriov, Jonathan F. MacArt, Justin A. Sirignano
2024	J	`jnl`	A TVD neural network closure and application to turbulent combustion. CoRR Seung Won Suh, Jonathan F. MacArt, Luke N. Olson, Jonathan B. Freund
2024	J	`jnl`	Sampling-based Distributed Training with Message Passing Neural Network. CoRR Priyesh Kakka, Sheel Nidhan, Rishikesh Ranade, Jonathan F. MacArt
2023	J	`jnl`	Dynamic Deep Learning LES Closures: Online Optimization With Embedded DNS. CoRR Justin A. Sirignano, Jonathan F. MacArt
2023	J	`jnl`	PDE-constrained models with neural network terms: Optimization and global convergence. J. Comput. Phys. Justin A. Sirignano, Jonathan F. MacArt, Konstantinos Spiliopoulos
2022	J	`jnl`	Deep Learning Closure Models for Large-Eddy Simulation of Flows around Bluff Bodies. CoRR Justin A. Sirignano, Jonathan F. MacArt
2021	J	`jnl`	Embedded training of neural-network sub-grid-scale turbulence models. CoRR Jonathan F. MacArt, Justin A. Sirignano, Jonathan B. Freund
2021	J	`jnl`	PDE-constrained Models with Neural Network Terms: Optimization and Global Convergence. CoRR Justin A. Sirignano, Jonathan F. MacArt, Konstantinos Spiliopoulos
2020	J	`jnl`	DPM: A deep learning PDE augmentation method with application to large-eddy simulation. J. Comput. Phys. Justin A. Sirignano, Jonathan F. MacArt, Jonathan B. Freund
2019	J	`jnl`	DPM: A deep learning PDE augmentation method (with application to large-eddy simulation). CoRR Jonathan B. Freund, Jonathan F. MacArt, Justin A. Sirignano
2016	J	`jnl`	Semi-implicit iterative methods for low Mach number turbulent reacting flows: Operator splitting versus approximate factorization. J. Comput. Phys. Jonathan F. MacArt, Michael E. Mueller