466 citations
- United States ArmyUS21 papers
- United States Army Corps of EngineersUS11 papers
- Coastal and Hydraulics LaboratoryUS10 papers
- University of VirginiaUS7 papers
- University of ArizonaUS5 papers
- Carnegie Mellon UniversityUS4 papers
- Landau Institute for Theoretical PhysicsRU4 papers
- Northeastern UniversityUS4 papers
- University of Illinois Urbana-ChampaignUS4 papers
- DEVCOM Army Research LaboratoryUS3 papers
- P.N. Lebedev Physical Institute of the Russian Academy of SciencesRU3 papers
- Stanford UniversityUS3 papers
9 papers · 1 filter
Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry
Mojtaba Forghani, Yizhou Qian, Jonghyun Lee +4
Estimation of riverbed profiles, also known as bathymetry, plays a vital role in many applications, such as safe and efficient inland navigation, prediction of bank erosion, land s…
Deep learning-based fast solver of the shallow water equations
Mojtaba Forghani, Yizhou Qian, Jonghyun Lee +4
Fast and reliable prediction of river flow velocities is important in many applications, including flood risk management. The shallow water equations (SWEs) are commonly used for t…
A Nodal Immersed Finite Element-Finite Difference Method
David Wells, Ben Vadala-Roth, Jae H. Lee +1
The immersed finite element-finite difference (IFED) method is a computational approach to modeling interactions between a fluid and an immersed structure. This method uses a finit…
Cyber Resilience in IoT network: Methodology and example of assessment through epidemic spreading
Emanuele Bellini, Franco Bagnoli, Alexander A. Ganin +1
Cyber Resilience is an important property of complex systems and is important consideration in developing specific IoT applications. This work aims at introducing a novel approach…
Relationship among state reopening policies, health outcomes and economic recovery through first wave of the COVID-19 pandemic in the U.S
Alexandre K. Ligo, Emerson Mahoney, Jeffrey Cegan +5
State governments in the U.S. have been facing difficult decisions involving tradeoffs between economic and health-related outcomes during the COVID-19 pandemic. Despite evidence o…
Neural Ordinary Differential Equations for Data-Driven Reduced Order Modeling of Environmental Hydrodynamics
Sourav Dutta, Peter Rivera-Casillas, Matthew W. Farthing
Model reduction for fluid flow simulation continues to be of great interest across a number of scientific and engineering fields. Here, we explore the use of Neural Ordinary Differ…