Conducted at the University of Tehran:
Development of an Intelligent Framework for Selecting Underground Hydrogen Storage Sites New
Researchers from the College of Engineering at the University of Tehran, by integrating artificial intelligence and multi-criteria decision-making, have presented an intelligent, data-driven framework for screening and ranking depleted gas reservoirs with the aim of underground hydrogen storage—an approach that can significantly reduce the time required to evaluate a large number of storage options.
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