Jonathan F. MacArt

According to our database, Jonathan F. MacArt authored at least 9 papers between 2016 and 2025.

Collaborative distances:

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

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