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Journal Articles

On-Sun Testing of a High-Temperature Solar Receiver’s Flux Distribution

Samia Afrin, Nazmul Hossain, Zhiwen Ma, V. M. Krushnarao Kotteda, Antara Badhan, Vinod Kumar

J. Sol. Energy Eng. April 2022, 144(2): 021001.

Paper No: SOL-21-1142

DOI: https://doi.org/10.1115/1.4052550

Published Online: October 19, 2021

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Topics: Solar energy, Testing, High temperature, Modeling, Temperature, Furnaces

Proceedings Papers

Performing Fourier Transform on a Velocity Profile From Atmospheric Turbulence Studies

Richard Adansi, Jose Terrazas, Arturo Rodriguez, V. M. Krushnarao Kotteda, Vinod Kumar, Aldo Rubio, Edgar Avalos

Proc. ASME. FEDSM2021, Volume 1: Aerospace Engineering Division Joint Track; Computational Fluid Dynamics, V001T02A035, August 10–12, 2021

Paper No: FEDSM2021-65812

DOI: https://doi.org/10.1115/FEDSM2021-65812

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Topics: Fourier transforms, Turbulence

Proceedings Papers

Causal Inference Analysis to Find Relationships Found in Boundary-Layer Transition – Part I: Theoretical

Arturo Rodriguez, Jose Terrazas, Richard Adansi, V. M. Krushnarao Kotteda, Jorge A. Munoz, Vinod Kumar

Proc. ASME. FEDSM2021, Volume 1: Aerospace Engineering Division Joint Track; Computational Fluid Dynamics, V001T02A050, August 10–12, 2021

Paper No: FEDSM2021-61843

DOI: https://doi.org/10.1115/FEDSM2021-61843

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Topics: Boundary layers, Turbulence, Flow (Dynamics), Computational fluid dynamics, Fluctuations (Physics), Reynolds number, Vehicles, Defense industry, Design, Fluid dynamics

Proceedings Papers

A Novel Mathematical Framework for the Venous Valve Leaflet Morphology Extracted From In-Vitro Images Using Machine Learning Assisted Stereological Analysis

V. M. Krushnarao Kotteda, Herb F. Janssen, Christopher Harris, Vinod Kumar

Proc. ASME. FEDSM2021, Volume 3: Fluid Mechanics; Micro and Nano Fluid Dynamics; Multiphase Flow, V003T05A008, August 10–12, 2021

Paper No: FEDSM2021-65744

DOI: https://doi.org/10.1115/FEDSM2021-65744

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Topics: Machine learning, Valves, Risk, Blood flow, Algorithms, Biomedicine, Blood, Cancer, Cloud computing, Computer software

Proceedings Papers

Three-Dimensional Two-Phase Flow Simulations of Water Braking Phenomena for High-Speed Test Track Sled

Jose Terrazas, Arturo Rodriguez, Vinod Kumar, Richard Adansi, V. M. Krushnarao Kotteda

Proc. ASME. FEDSM2021, Volume 1: Aerospace Engineering Division Joint Track; Computational Fluid Dynamics, V001T02A009, August 10–12, 2021

Paper No: FEDSM2021-65799

DOI: https://doi.org/10.1115/FEDSM2021-65799

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Topics: Braking, Computational fluid dynamics, Engineering simulation, Multiphase flow, Simulation, Two-phase flow, Water, Brakes, Inflow, Vehicles

Proceedings Papers

Fractal and Convolutional Analysis for Deep Atmospheric Turbulence Using Machine Learning

Nicholas Dudu, Arturo Rodriguez, Gael Moran, Jose Terrazas, Richard Adansi, V. M. Krushnarao Kotteda, Christopher Harris, Vinod Kumar

Proc. ASME. FEDSM2021, Volume 1: Aerospace Engineering Division Joint Track; Computational Fluid Dynamics, V001T02A051, August 10–12, 2021

Paper No: FEDSM2021-65798

DOI: https://doi.org/10.1115/FEDSM2021-65798

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Topics: Fractals, Machine learning, Turbulence, Dimensions, Artificial neural networks, Flow (Dynamics), Large eddy simulation, Scalars, Shapes, Trains

Proceedings Papers

Aerodynamic Performance of Design for a CO 2 Dragster

Brandon Paez, Arturo Rodriguez, Nicholas Dudu, Jose Terrazas, Richard Adansi, V. M. Krushnarao Kotteda, Julio C. Aguilar, Vinod Kumar

Proc. ASME. FEDSM2021, Volume 1: Aerospace Engineering Division Joint Track; Computational Fluid Dynamics, V001T02A040, August 10–12, 2021

Paper No: FEDSM2021-65793

DOI: https://doi.org/10.1115/FEDSM2021-65793

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Topics: Carbon dioxide, Design, Fluid structure interaction

Journal Articles

Quantifying Uncertainty in the Residence Time of the Drug and Carrier Particles in a Dry Powder Inhaler

Antara Badhan, V. M. Krushnarao Kotteda, Samia Afrin, Vinod Kumar

ASME J. Risk Uncertainty Part B. September 2021, 7(3): 031004.

Paper No: RISK-20-1107

DOI: https://doi.org/10.1115/1.4050250

Published Online: May 28, 2021

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Topics: Drugs, Particulate matter, Density, Uncertainty quantification, Flow (Dynamics)

Proceedings Papers

Characterization of Flow Regimes in Gas-Solid Fluidized Beds via a Data Driven Framework

V. M. Krushnarao Kotteda, Anitha Kommu, Vinod Kumar

Proc. ASME. FEDSM2020, Volume 3: Computational Fluid Dynamics; Micro and Nano Fluid Dynamics, V003T05A053, July 13–15, 2020

Paper No: FEDSM2020-20126

DOI: https://doi.org/10.1115/FEDSM2020-20126

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Topics: Flow (Dynamics), Fluidized beds, Particulate matter, Simulation, Acoustic emissions, Drugs, Dynamic systems, Fluidization, Heat transfer coefficients, Machine learning

Proceedings Papers

Trilinos Solvers Scalability on a MFiX-Trilinos Framework Applied to Fluidized Bed Simulations

Arturo Rodriguez, V. M. Krushnarao Kotteda, Luis F. Rodriguez, Vinod Kumar, Jorge A. Munoz

Proc. ASME. FEDSM2020, Volume 2: Fluid Mechanics; Multiphase Flows, V002T04A033, July 13–15, 2020

Paper No: FEDSM2020-20250

DOI: https://doi.org/10.1115/FEDSM2020-20250

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Topics: Engineering simulation, Fluidized beds, Multiphase flow, Simulation, Computational fluid dynamics, FORTRAN, Linear systems, Algorithms, Architecture, Flow (Dynamics)

Proceedings Papers

Parametric Optimization of a Dry Powder Inhaler

V. M. Krushnarao Kotteda, Antara Badhan, Vinod Kumar

Proc. ASME. FEDSM2020, Volume 3: Computational Fluid Dynamics; Micro and Nano Fluid Dynamics, V003T05A059, July 13–15, 2020

Paper No: FEDSM2020-20391

DOI: https://doi.org/10.1115/FEDSM2020-20391

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Topics: Optimization, Particulate matter, Engineering simulation, Simulation, Algorithms, Boundary-value problems, Computational fluid dynamics, Flow (Dynamics), Gaussian distribution, Machine learning

Proceedings Papers

Stochastic Analysis of LES Atmospheric Turbulence Solutions With Generative Machine Learning Models

Arturo Rodriguez, Carlos R. Cuellar, Luis F. Rodriguez, Armando Garcia, V. S. Rao Gudimetla, V. M. Krushnarao Kotteda, Jorge A. Munoz, Vinod Kumar

Proc. ASME. FEDSM2020, Volume 1: Fluid Applications and Systems; Fluid Measurement and Instrumentation, V001T01A001, July 13–15, 2020

Paper No: FEDSM2020-20127

DOI: https://doi.org/10.1115/FEDSM2020-20127

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Topics: Machine learning, Turbulence

Proceedings Papers

Parameter Sensitivity and Statistical Correlation Found in Atmospheric Turbulence Studies

Luis F. Rodriguez, Vinod Kumar, Arturo Rodriguez, V. M. Krushnarao Kotteda, V. S. Rao Gudimetla, Jorge A. Munoz

Proc. ASME. FEDSM2020, Volume 2: Fluid Mechanics; Multiphase Flows, V002T03A041, July 13–15, 2020

Paper No: FEDSM2020-20254

DOI: https://doi.org/10.1115/FEDSM2020-20254

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Topics: Computational fluid dynamics, Turbulence

Proceedings Papers

Uncertainty Quantification of a Fluidized Bed Reactor

V. M. Krushnarao Kotteda, Anitha Kommu, Vinod Kumar, William Spotz

Proc. ASME. AJKFluids2019, Volume 5: Multiphase Flow, V005T05A051, July 28–August 1, 2019

Paper No: AJKFluids2019-4844

DOI: https://doi.org/10.1115/AJKFluids2019-4844

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Topics: Fluidized beds, Uncertainty quantification, Biomass, Particulate matter, Flow (Dynamics), Fuel gasification, Sensitivity analysis, Uncertainty, Coal, Combustion

Proceedings Papers

Uncertainty Quantification of Molten Hafnium Infusion Into a B 4 C Packed-Bed

Arturo Schiaffino, V. M. Krushnarao Kotteda, Vinod Kumar, Arturo Bronson, Sanjay Shantha-Kumar

Proc. ASME. AJKFluids2019, Volume 2: Computational Fluid Dynamics, V002T02A041, July 28–August 1, 2019

Paper No: AJKFluids2019-5281

DOI: https://doi.org/10.1115/AJKFluids2019-5281

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Topics: Uncertainty quantification, Metals, Manufacturing, Metal matrix composites, Modeling, Temperature, Boron, Ceramics, Chaos, Chemical reactions

Proceedings Papers

The CFD Modeling of the Water Braking Phenomena for the Holloman High-Speed Test Track

Jose Terrazas, V. M. Krushnarao Kotteda, Vinod Kumar, Robert Edmonds, Michelle Zeisset

Proc. ASME. AJKFluids2019, Volume 1: Fluid Mechanics, V001T01A053, July 28–August 1, 2019

Paper No: AJKFluids2019-5506

DOI: https://doi.org/10.1115/AJKFluids2019-5506

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Topics: Braking, Computational fluid dynamics, Modeling, Water

Proceedings Papers

CFD DEM Analysis of a Dry Powder Inhaler

Antara Badhan, V. M. Krushnarao Kotteda, Vinod Kumar

Proc. ASME. AJKFluids2019, Volume 2: Computational Fluid Dynamics, V002T02A003, July 28–August 1, 2019

Paper No: AJKFluids2019-4771

DOI: https://doi.org/10.1115/AJKFluids2019-4771

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Topics: Computational fluid dynamics, Computer software, Discrete element methods, Sensitivity analysis

Proceedings Papers

Machine Learning Approach to Predict the Flow Rate for an Immiscible Two-Phase Flow at Pore Scale for Enhanced Oil Recovery Application

Arturo Rodriguez, V. M. Krushnarao Kotteda, Luis F. Rodriguez, Vinod Kumar, Arturo Schiaffino, Zackery R. Nieto

Proc. ASME. FEDSM2018, Volume 2: Development and Applications in Computational Fluid Dynamics; Industrial and Environmental Applications of Fluid Mechanics; Fluid Measurement and Instrumentation; Cavitation and Phase Change, V002T09A003, July 15–20, 2018

Paper No: FEDSM2018-83050

DOI: https://doi.org/10.1115/FEDSM2018-83050

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Topics: Flow (Dynamics), Machine learning, Tertiary petroleum recovery, Two-phase flow, Petroleum extraction, Pressure drop, Surface tension, Viscosity, Algorithms, Brain

Proceedings Papers

Predicting the Depth of Penetration of Molten Metal Into a Pore Network Using TensorFlow

Arturo Schiaffino, V. M. Krushnarao Kotteda, Arturo Bronson, Sanjay Shantha-Kumar, Vinod Kumar

Paper No: FEDSM2018-83258

DOI: https://doi.org/10.1115/FEDSM2018-83258

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Topics: Metals, Algorithms, Machine learning, Boron, Flow (Dynamics), Liquid metals, Alloys, Brain, Ceramics, Dynamics (Mechanics)

Proceedings Papers

Numerical Simulation of Formation of Melt Jets in Melt-Coolant Interactions

Jorge Contreras-Serna, Arturo Schiaffino, V. M. Krushnarao Kotteda, Alejandro J. García-Cuéllar, Vinod Kumar

Paper No: FEDSM2018-83273

DOI: https://doi.org/10.1115/FEDSM2018-83273

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Topics: Computer simulation, Coolants, Jets, Water, Liquid metals, Vapors, Computational fluid dynamics, Pressure, Simulation, Algorithms

Journal citation

NARROW

On-Sun Testing of a High-Temperature Solar Receiver’s Flux Distribution

Performing Fourier Transform on a Velocity Profile From Atmospheric Turbulence Studies

Causal Inference Analysis to Find Relationships Found in Boundary-Layer Transition – Part I: Theoretical

A Novel Mathematical Framework for the Venous Valve Leaflet Morphology Extracted From In-Vitro Images Using Machine Learning Assisted Stereological Analysis

Three-Dimensional Two-Phase Flow Simulations of Water Braking Phenomena for High-Speed Test Track Sled

Fractal and Convolutional Analysis for Deep Atmospheric Turbulence Using Machine Learning

Aerodynamic Performance of Design for a CO 2 Dragster

Quantifying Uncertainty in the Residence Time of the Drug and Carrier Particles in a Dry Powder Inhaler

Characterization of Flow Regimes in Gas-Solid Fluidized Beds via a Data Driven Framework

Trilinos Solvers Scalability on a MFiX-Trilinos Framework Applied to Fluidized Bed Simulations

Parametric Optimization of a Dry Powder Inhaler

Stochastic Analysis of LES Atmospheric Turbulence Solutions With Generative Machine Learning Models

Parameter Sensitivity and Statistical Correlation Found in Atmospheric Turbulence Studies

Uncertainty Quantification of a Fluidized Bed Reactor

Uncertainty Quantification of Molten Hafnium Infusion Into a B 4 C Packed-Bed

The CFD Modeling of the Water Braking Phenomena for the Holloman High-Speed Test Track

CFD DEM Analysis of a Dry Powder Inhaler

Machine Learning Approach to Predict the Flow Rate for an Immiscible Two-Phase Flow at Pore Scale for Enhanced Oil Recovery Application

Predicting the Depth of Penetration of Molten Metal Into a Pore Network Using TensorFlow

Numerical Simulation of Formation of Melt Jets in Melt-Coolant Interactions

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