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Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...
Jin, W. et al Idaho National Laboratory
Apr 15, 2022
4 Resources
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Utah FORGE: Drilling Data for Student Competition

Diagnostic drilling data (Pason log files) from Well 58-32 (previously labeled MU-ESW1), which was drilled near Milford Utah during Phase 2B of the FORGE Project to confirm geothermal reservoir characteristics met requirements for the final FORGE site. This dataset includes both ...
Podgorney, R. et al Idaho National Laboratory
Dec 07, 2018
2 Resources
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Compatibility Study of Nanofiltration and Reverse Osmosis Membranes with 1 Cyclohexylpiperidenium Bicarbonate Solutions

The switchable polarity solvent forward osmosis (SPS FO) desalination process requires use of a polishing filtration step to remove trace quantities of draw solution from the product water stream. Selected nanofiltration (NF) and reverse osmosis (RO) membranes were tested for thei...
Adhikari, B. et al Idaho National Laboratory
Oct 01, 2015
2 Resources
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Dynamic Earth Energy Storage: Terawatt-year, Grid-scale Energy Storage Using Planet Earth as a Thermal Battery (GeoTES): Phase I Project Final Report

Final report for the DOE GTO funded research on geologic thermal energy storage (GeoTES), or commonly known as reservoir thermal energy storage (RTES). The results described in this report shed light on various aspects of RTES including project siting, operational performance, m...
Atkinson, T. et al Idaho National Laboratory
Sep 02, 2022
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