most citedInterplay of Sensor Quantity, Placement and System Dimensionality on Energy Sparse Reconstruction of Fluid Flows

34 citations · 88 across the 9 of their papers we have counts for

collaborators

10 papers

physics.flu-dyn2019

Slope Dependent Turbulence over Two-dimensional Wavy Surfaces

Balaji Jayaraman, Saadbin Khan

Knowledge of turbulent flows over non-flat surfaces is of major practical interest in diverse applications. Significant work continues to be reported in the roughness regime at hig…

physics.flu-dyn2019★ 19 cited

Modification of Turbulent Boundary Layer Coherent Structures with Drag Reducing Polymer Solution

Yasaman Farsiani, Zeeshan Saeed, Balaji Jayaraman +1

The modification of dominant coherent structures that extend through the log-region of a drag reduced turbulent boundary layer is studied via examination of two-point correlations…

eess.SP2019★ 4 cited

Wind Estimation Using Quadcopter Motion: A Machine Learning Approach

Sam Allison, He Bai, Balaji Jayaraman

In this article, we study the well known problem of wind estimation in atmospheric turbulence using small unmanned aerial systems (sUAS). We present a machine learning approach to…

physics.flu-dyn2019

Quad-rotor Flight Simulation in Realistic Atmospheric Conditions

Behdad Davoudi, Ehsan Taheri, Karthik Duraisamy +2

In trajectory planning and control design for unmanned air vehicles, highly simplified models are typically used to represent the vehicle dynamics and the operating environment. Th…

physics.flu-dyn2018

On the Trajectory Dependence of Atmospheric Boundary Layer Turbulence Sensing using Small Unmanned Vehicles

Balaji Jayaraman, Sam Allison, He Bai

Atmospheric turbulence, especially in the near-surface boundary layer is known to be under-sampled due to the need to capture a wide separation in length and time-scales and limita…

physics.flu-dyn2018★ 4 cited

Characterization of a Canonical Helicopter Hub Wake

Christopher E. Petrin, Balaji Jayaraman, Brian R. Elbing

The current study investigates the long-age wake behind rotating helicopter hub models composed of geometrically simple, canonical bluff body shapes. The models consisted of a 4-ar…

physics.flu-dyn2018★ 11 cited

The Surprising Transition in Atmospheric Boundary Layer Turbulence Structure from Neutral to Moderately Convective Stability States and Mechanisms Underlying Large-scale Rolls

Balaji Jayaraman, James G. Brasseur

The vectoral wind structure of daytime atmospheric boundary layer (ABL) turbulence is strongly dependent on the balance between shear-driven turbulence production of horizontal flu…

physics.comp-ph2018★ 34 cited

Interplay of Sensor Quantity, Placement and System Dimensionality on Energy Sparse Reconstruction of Fluid Flows

Chen Lu, Balaji Jayaraman

Reconstruction of fine-scale information from sparse data is relevant to many practical fluid dynamic applications where the sensing is typically sparse. Fluid flows in an ideal se…

physics.comp-ph2018★ 2 cited

Assessment of End-to-End and Sequential Data-driven Learning of Fluid Flows

Shivakanth Chary Puligilla, Balaji Jayaraman

In this work we explore the advantages of end-to-end learning of multilayer maps offered by feed forward neural-networks (FFNN) for learning and predicting dynamics from transient…

physics.flu-dyn2018★ 14 cited

Sparse Convolution-based Markov Models for Nonlinear Fluid Flows

Chen Lu, Balaji Jayaraman, Joshua Whitman +1

Data-driven modeling for nonlinear fluid flows using sparse convolution-based mapping into a feature space where the dynamics are Markov linear is explored in this article. The und…