Transmission, Distribution & Storage

This review provides a comprehensive examination of artificial intelligence methods applied to the design optimization and performance prediction of composite-based hydrogen storage vessels with a focus on composite overwrapped pressure vessels. Targeted at researchers engineers and industrial stakeholders in materials science mechanical engineering and renewable energy sectors the paper aims to bridge traditional mechanical modeling with evolving AI tools while emphasizing alignment with standardization and certification requirements to enhance safety efficiency and lifecycle integration in hydrogen infrastructure. The review begins by introducing HSV types their material compositions and key design challenges including high-pressure durability weight reduction hydrogen embrittlement leakage prevention and environmental sustainability. It then analyzes conventional approaches such as finite element analysis multiscale modeling and experimental testing which effectively address aspects like failure modes fracture strength liner damage dome thickness winding angle effects crash behavior crack propagation charging/discharging dynamics burst pressure durability reliability and fatigue life. On the other hand it has been shown that to optimize and predict the characteristics of hydrogen storage vessels it is necessary to combine the conventional methods with artificial intelligence methods as conventional methods often fall short in multi-objective optimization and rapid predictive analytics due to computational intensity and limitations in handling uncertainty or complex datasets. To overcome these gaps the paper evaluates hybrid frameworks that integrate traditional techniques with AI including machine learning deep learning artificial neural networks evolutionary algorithms and fuzzy logic. Recent studies demonstrate AI’s efficacy in failure prediction design optimization to mitigate structural risks structural health monitoring material property evaluation burst pressure forecasting crack detection composite lay-up arrangement weight minimization material distribution enhancement metal foam ratio optimization and optimal material selection. By synthesizing these advancements this work underscores AI’s potential to accelerate development reduce costs and improve HSV performance while advocating for physics-informed models robust datasets and regulatory alignment to facilitate industrial adoption.

Underground hydrogen storage (UHS) in salt caverns is emerging as a promising solution for the transition to a sustainable energy future. However a thorough understanding of hydrogen flow mechanisms through salt rock is essential to ensure safe and efficient storage operations. In this study we conducted hydrogen flow experiments in salt rocks using the pressure pulse decay (PPD) method covering a range of hydrogen pore pressures from 0.4 MPa to 7.5 MPa within the slip and transitional flow regimes (Knudsen numbers between 0.04 and 1.5). The Knudsen numbers were determined by measuring the pore size distribution (PSD) of the salt rock samples and assigning an average pore size to each sample based on the measured PSD. Our results indicate that the intrinsic permeability of the tested salt rock samples ranges from 5 × 10− 21 m2 to 1.0 × 10− 20 m2 . However a significant enhancement in apparent permeability up to 10 times the intrinsic permeability was observed particularly at lower pressures. This permeability enhancement is attributed to the nanoscale pore structure of salt rocks where the mean free path of hydrogen becomes comparable to the pore sizes leading to a shift from slip flow to the transitional flow regime. The results further reveal that the first-order slip model underestimates the apparent permeability in the transitional flow regime despite its satisfactory accuracy in the slip region. Moreover the higher-order slip model demonstrates acceptable accuracy across both the slip and transitional flow regimes.

As industry moves from fossil fuels to green energy substituting hydrocarbons with hydrogen as an energy carrier seems promising. Hydrogen can be stored in salt caverns depleted hydrocarbon fields and saline aquifers. Among other criteria these storage solutions must ensure storage safety and prevent leakage. The ability of a caprock to prevent fluid from flowing out of the reservoir is thus of utmost importance. In this review the main factors influencing fluid flow are examined. These are the wettability of the caprock formation the interfacial tension (IFT) between the rock and the gas or liquid phases and the ability of gases to diffuse through it. To achieve effective sealing the caprock formation should possess low porosity a disconnected or highly complicated pore system low permeability and remain strongly water-wet regardless of pressure and temperature conditions. In addition it must exhibit low rock–liquid IFT while presenting high rock–gas and liquid–gas IFT. Finally the effective diffusion coefficient should be the lowest possible. Among all of the currently reviewed formations and minerals the evaporites low-organic-content shales mudstones muscovite clays and anhydrite have been identified as highly effective caprocks offering excellent sealing capabilities and preventing hydrogen leakages.

The global energy sector is aiming to substantially reduce CO2 emissions to meet the UN climate goals. Among the proposed strategies underground storage solutions such as radioactive disposal CO2 NH3 and underground H2 storage (UHS) have emerged as promising options for mitigating anthropogenic emissions. These approaches require rigorous research and development (R&D) often involving laboratory-scale experiments to establish their feasibility before being scaled up to pilot plant operations. Microorganisms which are ubiquitous in laboratory environments can significantly influence geochemical reactions under variable experimental conditions of porous media and a salt cavern. We have selected a consortium composed of Bacillus sp. Enterobacter sp. and Cronobacter sp. bacteria which are typically present in the laboratory environment. These microorganisms can contaminate the rock sample and develop experimental artifacts in UHS experiments. Hence it is pivotal to sterilize the rock prior to conduct experimental research related to effects of microorganisms in the porous media and the salt cavern for the investigation of UHS. This study investigated the efficacy of various disinfection and sterilization methods including ultraviolet irradiation autoclaving oven heating ethanol treatments and gamma irradiation in removing the microorganisms from silica sand. Additionally the consideration of their effects on mineral properties are reviewed. A total of 567 vials each filled with 9 mL of acid-producing bacteria (APB) media were used to test killing efficacy of the cleaning methods. We conducted serial dilutions up to 10−8 and repeated them three times to determine whether any deviation occurred. Our findings revealed that gamma irradiation and autoclaving were the most effective techniques for eradicating microbial contaminants achieving sterilization without significantly altering the mineral characteristics. These findings underscore the necessity of robust cleaning protocols in hydrogeochemical research to ensure reliable reproducible data particularly in future studies where microbial contamination could induce artifacts in laboratory research.

This study examined the effects of microstructural alterations by controlling the surface carbon gradient via a thermal decarburizing process on hydrogen evolution adsorption and permeation along with neutral aqueous corrosion behavior of an ultra-high-strength steel with a tensile strength of 2.4 GPa. Microstructural analyses showed that an optimized decarburizing process at 1100 ◦C led to partial transformation to ferrite without precipitating Fe3C in a marked fraction. Electrochemical impedance spectroscopy along with the permeation results revealed that there was a notable decrease in hydrogen evolution and subsurface hydrogen concentration. Moreover immersion test in a neutral aqueous condition showed slower corrosion kinetics with a comparatively uniform corroded surface indicating improved corrosion resistance. However the extent of improvement is significantly limited under non-optimized decarburizing conditions specifically when the temperature is below or above 1100 ◦C due to insufficient decarburization or the formation of coarse-spheroidized Fe3C particles accompanied by a porous subsurface layer. In particular a far greater adsorption tendency at bridge sites on Fe3C (001) in a pre-charged surface is highlighted. This study provides insight that the adjustment of the carbon gradient through an optimized annealing process can be an effective technical strategy to overcome the critical drawbacks of ultrastrong martensitic steels under hydrogen-rich or corrosive conditions.

The rapid adoption of hydrogen fuel cell vehicles (HFCVs) in the Beijing–Tianjin–Hebei (BTH) hub accentuates the mismatch between renewable-based hydrogen supply in Hebei and concentrated demand in Beijing and Tianjin. We develop a mixed-integer linear model that co-configures a hydrogen pipeline network and optimizes hourly flow schedules to minimize annualized cost and CO2 emissions simultaneously. For 15000 HFCVs expected in 2025 (137 t d−1 demand) the Pareto-optimal design consists of 13 production plants 43 pipelines and 38 refueling stations delivering 50767 t yr−1 at 68% pipeline utilization. Hebei provides 88% of the hydrogen 70% of which is consumed in the two megacities. Hourly profiles reveal that 65% of electrolytic output coincides with local wind–solar peaks whereas refueling surges arise during morning and evening rush hours; the proposed schedule offsets the 4–6 h mismatch without additional storage. Transport distances are 40% < 50 km 35% 50–200 km and 25% > 200 km. Raising the green hydrogen share from 10% to 70% increases total system cost from USD 1.56 bn to USD 2.73 bn but cuts annual CO2 emissions from 142 kt to 51 kt demonstrating the trade-off between cost and decarbonization. The model quantifies the value of sub-day pipeline scheduling in resolving spatial–temporal imbalances for large-scale low-carbon hydrogen supply.

Hydrogen (H2) is a promising energy carrier for decarbonization; however efficient storage remains a key challenge. Porous materials offer potential for enhanced H2 densification and may enable the development of next-generation lightweight storage systems. A major limitation of such materials is their fine powder form which hampers retention and processability. In this study composite membranes comprising a polymer of intrinsic microporosity (PIM-1) matrix and a polytriphenylamine (PTPA)-based conjugated microporous polymer (CMP) filler were developed. The composites are mechanically robust forming self-standing membranes that retain stability under high temperatures and humidity. H2 storage capacities of the membranes showed excess gravimetric uptakes of 1.03 wt% at 1 bar and 1.84 wt% at 50 bar (77 K) with total capacities reaching 3.22 wt% at 100 bar. These values are significantly higher than those of pristine PIM-1 which achieved 0.87 wt% 1.64 wt % and 2.89 wt% under the same conditions. Net adsorption isotherms demonstrate the potential of the composites to outperform conventional compression storage up to 10 bar at 77 K. Additionally the composites exhibit high mass transfer coefficients (3.42 min− 1 ) indicating strong H2 affinity and faster charging rates compared with the pristine PIM-1 membrane (2.79 min− 1 ).

The rock wettability is one of the most critical parameters that influences rock storage potential trapping and H2 withdrawal rate during Underground hydrogen storage (UHS). However the existing review articles on wettability of H2-brine-rock systems do not provide detailed information on complexities introduced by reservoir wettability influencing parameters such as high pressure temperature salinity conditions micro-biotic effects cushion gases and organic acids relevant to subsurface environments. Therefore a comprehensive review of existing research on various parameters influencing rock wettability during UHS and residual trapping of H2 was conducted in this study. Literature that provides insight into molecular-level interaction through machine learning and molecular dynamic (MD) simulations and role of surface-active chemicals such as nanoparticles surfactants and wastewater chemicals were also reviewed. The review suggested that UHS could be feasible in clean geo-storage formations but the presence of rock surface contaminants at higher storage depth and microbial effects should be accounted for to prevent over-estimation of the rock storage potentials. The H2 wettability of storage/caprocks and associated risks of UHS projects could be higher in rocks with high proportion of carbonate minerals organic-rich shale and basalt with high plagioclase minerals content. However treatment of rock surfaces with nanofluids surfactants methylene blue and methyl orange has proven to alter the rock wettability from H2-wet towards water-wet. Research results on effect of rock wettability on residually trapped hydrogen and snap-off effects during UHS are contradictory thus further studies would be required in this area. The review generally concludes that rock wettability plays prominent role on H2 storage due to the frequency and cyclic loading of UHS hence it is vital to evaluate the effects of all possible wettability influencing parameters for successful designs and implementation of UHS projects.

Hydrogen handling equipment suffers from interaction with their operating environment which degrades the mechanical properties and compromises component integrity. Hydrogen-assisted cracking is responsible for several industrial failures with potentially severe consequences. A thorough failure analysis can determine the failure mechanism locate its origin and identify possible root causes to avoid similar events in the future. Postmortem fractographic analysis can classify the fracture mode and determine whether the hydrogen-metal interaction contributed to the component’s breakdown. Experts in fracture classification identify characteristic marks and textural features by visual inspection to determine the failure mechanism. Although widely adopted this process is time-consuming and influenced by subjective judgment and individual expertise. This study aims to automate fractographic analysis through advanced computer vision techniques. Different materials were tested in hydrogen atmospheres and inert environments and their fracture surfaces were analyzed by scanning electron microscopy to create an extensive image dataset. A pre-trained Convolutional Neural Network was finetuned to accurately classify brittle and ductile fractures. In addition Grad-CAM interpretability method was adopted to identify the image regions most influential in the model’s prediction and compare the saliency maps with expert annotations. This approach offered a reliable data-driven alternative to conventional fractographic analysis.

This study investigates the performance degradation of X70 steel weld material in highpressure natural gas pipelines in the Sichuan-Chongqing region and its impact on pipeline safety by investigating their behavior under multiphysics environments including varying gas media (nitrogen methane hydrogen-blended) pressure conditions (0.1–10 MPa) and material regions (base metal vs. weld). A key novelty of this work is the introduction of a “degradation rate” metric to quantitatively assess the deterioration of weld mechanical properties. A key novelty of this work is the explicit introduction of a “degradation rate” metric to quantitatively assess the deterioration of weld mechanical properties. Slow strain rate tensile tests combined with fracture morphology and microstructure analysis reveal that welds exhibit inferior mechanical properties due to microstructural inhomogeneity and residual stresses including a yield stress reduction of 15.2–18.7%. The risk of brittle fracture was highest in the hydrogen-blended environment while nitrogen exhibited the most benign effect. Material region changes were identified as the most significant factor affecting degradation. This research provides crucial data and theoretical support for pipeline safety design and material performance optimization.