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Naval and Ocean Renewable Energy Hydrodynamics

Bradford Knight applies computational fluid dynamics and data-driven modeling to study vessel dynamics, including hull-propeller-rudder interaction, maneuvering, and turbine fluid flows.

In this video, Knight introduces research in his group.

A recent study presents a multifidelity computational fluid dynamics (CFD) framework for the design and optimization of ducted hydrokinetic turbines. These turbines harness energy from riverine and marine currents, and the ducted configuration enhances flow control and energy capture. The framework integrates three levels of fidelity: low-fidelity body-force models for rapid initial optimization, medium-fidelity blade element momentum theory coupled with CFD for capturing duct-rotor interactions, and high-fidelity rotating sliding mesh simulations for final validation.

High-performance computing was essential for executing the most detailed simulations, which were performed on the UMass UNITY cluster. This resource enabled the team to balance computational cost with accuracy across design stages, validating their models against experimental data and refining turbine performance predictions. The study demonstrates how strategic use of computational resources can accelerate renewable energy technology development.

 

Bradford Knight
Assistant Professor of Ocean Engineering University of Rhode Island

Research projects

A Future of Unmanned Aerial Vehicles
Yale Budget Lab
Volcanic Eruptions Impact on Stratospheric Chemistry & Ozone
Towards a Whole Brain Cellular Atlas
Tornado Path Detection
The Kempner Institute - Unlocking Intelligence
The Institute for Experiential AI
Taming the Energy Appetite of AI Models
Surface Behavior
Studying Highly Efficient Biological Solar Energy Systems
Software for Unreliable Quantum Computers
Simulating Large Biomolecular Assemblies
SEQer - Sequence Evaluation in Realtime
Revolutionizing Materials Design with Computational Modeling
Remote Sensing of Earth Systems
Quantum Computing in Renewable Energy Development
Pulling Back the Quantum Curtain on ‘Weyl Fermions’
New Insights on Binary Black Holes
NeuraChip
Network Attached FPGAs in the OCT
Monte Carlo eXtreme (MCX) - a Physically-Accurate Photon Simulator
Modeling Hydrogels and Elastomers
Modeling Breast Cancer Spread
Impact of Marine Heatwaves on Coral Diversity
IceCube: Hunting Neutrinos
Genome Forecasting
Global Consequences of Warming-Induced Arctic River Changes
Exact Gravitational Lensing by Rotating Black Holes
Evolution of Viral Infectious Disease
Evaluating Health Benefits of Stricter US Air Quality Standards
Ephemeral Stream Water Contributions to US Drainage Networks
Energy Transport and Ultrafast Spectroscopy Lab
Electron Heating in Kinetic-Alfvén-Wave Turbulence
Discovering Evolution’s Master Switches
Dexterous Robotic Hands
Developing Advanced Materials for a Sustainable Energy Future
Detecting Protein Concentrations in Assays
Denser Environments Cultivate Larger Galaxies
Deciphering Alzheimer's Disease
Dancing Frog Genomes
Cyber-Physical Communication Network Security
Asteroid Data Mining
Analyzing the Gut Microbiome
Adaptive Deep Learning Systems Towards Edge Intelligence
Accelerating Rendering Power
ACAS X: A Family of Next-Generation Collision Avoidance Systems
Computation + Machine Intelligence | Wu Tsai Institute
Computational Modeling of Biological Systems
Computational Molecular Ecology
Social Capital and Economic Mobility
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