34 citations · 77 across the 9 of their papers we have counts for
9 papers
Toward ultra-efficient high-fidelity prediction of bed morphodynamics of large-scale meandering rivers using a novel LES-trained machine learning approach
Zexia Zhang, Mehrshad Gholami Anjiraki, Hossein Seyedzadeh +2
Flood-induced deformation of the bed topography of fluvial meandering rivers could lead to river bank displacement, structural failure of the infrastructures, and the propagation o…
Toward ultra-efficient high fidelity predictions of wind turbine wakes: Augmenting the accuracy of engineering models via LES-trained machine learning
Christian Santoni, Dichang Zhang, Zexia Zhang +3
This study proposes a novel machine learning (ML) methodology for the efficient and cost-effective prediction of high-fidelity three-dimensional velocity fields in the wake of util…
On the morphodynamics of a wide class of large-scale meandering rivers: Insights gained by coupling LES with sediment-dynamics
Ali Khosronejad, Ajay B. Limaye, Zexia Zhang +3
In meandering rivers, interactions between flow, sediment transport, and bed topography affect diverse processes, including bedform development and channel migration. Predicting ho…
Prediction of three-dimensional flood-flow past bridge piers in a large-scale meandering river using convolutional neural networks
Zexia Zhang, Kevin Flora1, Seokkoo Kang +2
The prediction of statistical properties of turbulent flow in large-scale rivers is important for river flow analysis. Large-eddy simulations (LESs) provide a powerful tool for suc…
Uncertainty Quantification of Large-Eddy Simulation Results of Riverine Flows: A Field and Numerical Study
K. Flora, A. Khosronejad
We present large-eddy simulations (LESs) of riverine flow in a study reach in the Sacramento River, California. The riverbed bathymetry was surveyed in high-resolution using a mult…
A computational study of expiratory particle transport and vortex dynamics during breathing with and without face masks
Ali Khosronejad, Seokkoo Kang, Fabian Wermelinger +2
We present high-fidelity numerical simulations of expiratory biosol transport during normal breathing under indoor, stagnant air conditions with and without a facial mask. We inves…
Three-dimensional realizations of flood flow in large-scale rivers using the neural fuzzy-based machine-learning algorithm
Zexia Zhang, Ajay B. Limaye, Ali Khosronejad
Machine learning methods have been extensively used to study the dynamics of complex fluid flows. One such algorithm, known as adaptive neural fuzzy inference system (ANFIS), can g…
Eulerian numerical modeling of contaminant transport in Lower Manhattan, New York City, from a point-source release under the dominant wind condition: Insights gained via LES
Wayne R. Oaks, Kevin Flora, Ali Khosronejad
Released pollutants and poisonous chemicals in the highly-populated urban areas can spread via wind flow and affect the health, safety, and wellbeing of those close to the source a…
Fluid dynamics simulations show that facial masks can suppress the spread of COVID-19 in indoor environments
Ali Khosronejad, Christian Santoni, Kevin Flora +4
The Coronavirus disease outbreak of 2019 has been causing significant loss of life and unprecedented economical loss throughout the world. Social distancing and face masks are wide…