Evaluating Fluid/Rock Interactions for Energy Storage in Salt Caverns – Part II: Effect of Hydrogen on Salt Rock Dissolution in Brine

Energy & Fuels, Год журнала: 2025, Номер unknown

Опубликована: Янв. 30, 2025

Язык: Английский

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Pore-scale numerical investigation on the capillary trapping of hydrogen in natural sandstone under in-situ wettability condition: Implications for underground hydrogen storage in aquifers

International Journal of Hydrogen Energy, Год журнала: 2025, Номер 113, С. 509 - 522

Опубликована: Март 1, 2025

Язык: Английский

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Optimizing hydrogen storage in the subsurface using a reservoir-simulation-based and deep-learning-accelerated optimization method

International Journal of Hydrogen Energy, Год журнала: 2025, Номер 119, С. 317 - 328

Опубликована: Март 23, 2025

Язык: Английский

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Microfluidic Study on Green Remediation of Nonaqueous Phase Liquid (NAPL) Contamination in Heterogeneous Groundwater Systems Using Dihydrolevoclucosenone (Cyrene)

Environmental Science & Technology, Год журнала: 2025, Номер unknown

Опубликована: Март 27, 2025

One of the primary challenges in conventional remediation nonaqueous phase liquid (NAPL) contamination groundwater is heterogeneous nature system. Conventional agents are often carried away by flow high-permeability layers, making it difficult to access NAPL contaminants low-permeability layers and prone generate secondary contamination. This study explores use dihydrolevoclucosenone (Cyrene), a bioderived green solvent, as an alternative traditional remediating for remediation. Through microfluidic experiments accompanying numerical modeling, we demonstrate that Cyrene enhances dissolution mobilization contaminants, particularly zones, achieving residual reductions up 80% compared with water Tween 80 solutions. These findings underscore Cyrene's dual environmental benefits eco-friendly solvent both treating solid waste (e.g., stalks) remediation, paving way sustainable solutions management.

Язык: Английский

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Energy management of hydrogen tanks

Elsevier eBooks, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

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Hydrogeochemical modeling of hydrogen storage in depleted gas reservoirs: Insights from local and global sensitivity analysis

Applied Energy, Год журнала: 2025, Номер 391, С. 125940 - 125940

Опубликована: Апрель 22, 2025

Язык: Английский

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Pore-Scale Gas–Water Two-Phase Flow Mechanisms for Underground Hydrogen Storage: A Mini Review of Theory, Experiment, and Simulation

Applied Sciences, Год журнала: 2025, Номер 15(10), С. 5657 - 5657

Опубликована: Май 19, 2025

In recent years, underground hydrogen storage (UHS) has become a hot topic in the field of deep energy storage. Green hydrogen, produced using surplus electricity during peak production, can be injected and stored reservoirs extracted periods high demand. A profound understanding mechanisms gas–water two-phase flow at pore scale is great significance for evaluating sealing integrity UHS optimizing injection, as well space. The structure rocks, space channels fluids, significant impact on fluid processes. This paper systematically summarizes methods characterizing micro-pore reservoir rocks. applicability different techniques was evaluated compared. detailed comparative analysis made advantages disadvantages various numerical simulation tracking interfaces, along with an assessment their suitability. Subsequently, microscopic visualization seepage experimental techniques, including microfluidics, NMR-based, CT scanning-based methods, were reviewed discussed terms dynamic complex transport behaviors. Due to resolution, non-contact, non-destructive, scalable situ high-temperature high-pressure conditions, technology received increasing attention. research presented this provide theoretical guidance further characterization rocks scale.

Язык: Английский

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Insight into Underground Hydrogen Storage in Aquifers: Current Status, Modeling, Economic Approaches and Future Outlook

Energy & Fuels, Год журнала: 2025, Номер unknown

Опубликована: Май 22, 2025

Язык: Английский

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Advanced generalized machine learning models for predicting hydrogen–brine interfacial tension in underground hydrogen storage systems

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Май 30, 2025

The global transition to clean energy has highlighted hydrogen (H2) as a sustainable fuel, with underground storage (UHS) in geological formations emerging key solution. Accurately predicting fluid interactions, particularly interfacial tension (IFT), is critical for ensuring reservoir integrity and security UHS. IFT behavior, influencing structural residual trapping capacities. However, measuring H2-brine systems challenging due H2's volatility the complexity of conditions. This study applies machine learning (ML) techniques predict between H2 brine across various salt types, concentrations, gas compositions. A dataset was used variables such temperature, pressure, salinity, composition (H2, CH4, CO2). Several ML models, including Random Forests (RF), Gradient Boosting Regressor (GBR), Extreme (XGBoost), Artificial Neural Networks (ANN), Decision Trees (DT), Linear Regression (LR), were trained evaluated. RF, GBR, XGBoost achieved R2 values over 0.99 training, 0.97 testing, all exceeded 0.975 validation. These top models RMSE below 1.3 mN/m MAPE under 1.5%, confirming their high predictive accuracy. Residual frequency analysis APRE results further confirmed these ensemble models' low bias reliability, error distributions centered near zero. DT performed slightly lower, 0.93, while LR struggled model non-linear behavior IFT. novel equivalency metric introduced, transforming multiple into single parameter improving generalization maintaining prediction accuracy (R2 = 0.98). Sensitivity SHAP (Shapley Additive Explanations) revealed temperature dominant factor IFT, followed by CO2 concentration divalent salts (CaCl2, MgCl2) exhibited stronger impact than monovalent (NaCl, KCl). optimizes offering generalized, high-accuracy that captures nonlinear interactions systems. Integrating real-world experimental data ML-driven insights enhances simulation accuracy, improves injection strategies, supports toward solutions.

Язык: Английский

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Molecular dynamics simulations of hydrogen storage in various subsurface sandstone aquifers

Applied Surface Science, Год журнала: 2025, Номер unknown, С. 163693 - 163693

Опубликована: Май 1, 2025

Язык: Английский

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