Jonathan F. MacArt

According to our database, Jonathan F. MacArt authored at least 14 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

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

J. Comput. Phys., 2026

Online optimisation of machine learning collision models to accelerate direct molecular simulation of rarefied gas flows.

Nicholas Daultry Ball, Jonathan F. MacArt, Justin A. Sirignano

J. Comput. Phys., 2026

2025

Active Control of Turbulent Airfoil Flows Using Adjoint-based Deep Learning.

Xuemin Liu, Tom Hickling, Jonathan F. MacArt

CoRR, October, 2025

oRANS: Online optimisation of RANS machine learning models with embedded DNS data generation.

Daniel Dehtyriov, Jonathan F. MacArt, Justin A. Sirignano

CoRR, October, 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, July, 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

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

2024

Sampling-based Distributed Training with Message Passing Neural Network.

Priyesh Kakka, Sheel Nidhan, Rishikesh Ranade, Jonathan F. MacArt

CoRR, 2024

2023

PDE-constrained models with neural network terms: Optimization and global convergence.

Justin A. Sirignano, Jonathan F. MacArt, Konstantinos Spiliopoulos

J. Comput. Phys., May, 2023

Dynamic Deep Learning LES Closures: Online Optimization With Embedded DNS.

Justin A. Sirignano, Jonathan F. MacArt

CoRR, 2023

2022

Deep Learning Closure Models for Large-Eddy Simulation of Flows around Bluff Bodies.

Justin A. Sirignano, Jonathan F. MacArt

CoRR, 2022

2021

Embedded training of neural-network sub-grid-scale turbulence models.

Jonathan F. MacArt, Justin A. Sirignano, Jonathan B. Freund

CoRR, 2021

2020

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

2016

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