-
Federal
Airfoil Computational Fluid Dynamics - 2k shapes, 25 AoA's, 3 Re numbers
Department of Energy —
This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and... -
Federal
Airfoil Computational Fluid Dynamics - 9k shapes, 2 AoA's
Department of Energy —
This dataset contains aerodynamic quantities - including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and... -
Federal
Artificial Intelligence for Robust Integration of AMI and Synchrophasor Data to Significantly Boost Solar Adoption
Department of Energy —
The overarching goal of the project is to create a highly efficient framework of machine learning (ML) methods that provide consistent and accurate real-time... -
Federal
Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites
Department of Energy —
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to... -
Federal
Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets
Department of Energy —
This dataset contains turbine- and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric... -
Federal
Underwater Target Detection Software Demonstration on the RivGen Turbine
Department of Energy —
This repository includes data, object detection models, and processing scripts necessary to evaluate the accuracy of the object detection models created for the... -
Federal
Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results
Department of Energy —
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells... -
Federal
3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA
Department of Energy —
In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of... -
Federal
Super-Resolution for Renewable Energy Resource Data with Wind from Reanalysis (Sup3rWind)
Department of Energy —
The Super-Resolution for Renewable Energy Resource Data with Wind from Reanalysis (Sup3rWind) data is a collection of high-resolution historical wind, temperature,... -
Federal
Utah FORGE 6-3712: Report on a Data Foundation for Real-Time Identification of Microseismic Events
Department of Energy —
This submission is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report... -
Federal
Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI)
Department of Energy —
Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI) introduces machine learning methods to incorporate high-resolution Urban Heat Island... -
Federal
Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk
Department of Energy —
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in... -
Federal
Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions - September 2023 Report
Department of Energy —
This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum... -
Federal
Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32
Department of Energy —
This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-...