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At least 1,261 records · Page 70

Real-time infrared spectroscopy coupled with blind source separation for nuclear waste process monitoring

On-line infrared absorbance spectroscopy enables rapid measurement of solution-phase molecular species. Many spectra-to-concentration models exist for spectral data, with some models able to handle overlapping spectral bands and nonlinearities. However, model accuracy is limited by the quality of training data used in model fitting. The process spectra of nuclear waste simulants at the Savannah River Site display incongruity between training and process spectra; the glycolate spectral signature in the training data does not match the glycolate signature in Savannah River National Laboratory process data. A novel blind source separation algorithm is proposed that preprocesses spectral data so that process spectra more closely resemble training spectra, thereby improving model quantification accuracy when unexpected sources of variation appear in process spectra. The novel blind source separation preprocessing algorithm is shown to improve nitrate quantification from an R 2 of 0.934 to 0.988 and from 0.267 to 0.978 in two instances analyzing nuclear waste simulants from the Slurry Receipt Adjustment Tank and Slurry Mix Evaporator cycle at the Savannah River Site.

Crouse, Steven H.↗

The Preparation and Characterization of Co–Ni Nanoparticles and the Testing of a Heterogenized Co–Ni/Alumina Catalyst for CO Hydrogenation

Samples of well-controlled nanoparticles consisting of alloys of cobalt and nickel of different atomic ratios were synthesized using wet chemical methods with oleylamine as the solvent and the reducing agent. These materials were characterized by a variety of techniques, including high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), X-ray energy dispersive spectroscopy (EDS), and X-ray diffraction (XRD). Small amounts of heterogenized catalysts were prepared using alumina as the support. However, the potential for use of Co–Ni catalysts in CO hydrogenation was explored using a larger amount of Co–Ni/alumina catalyst prepared from standard aqueous impregnation methods and tested in a continuously stirred tank reactor (CSTR) for Fischer–Tropsch synthesis (FTS). Results are compared to a reference catalyst containing only cobalt. The heterogenized catalysts were characterized using synchrotron methods, including temperature programmed reduction with extended X-ray absorption fine structure spectroscopy and X-ray absorption near edge spectroscopy (TPR-EXAFS/XANES). The characterization results support intimate contact between Co and Ni, strongly suggesting alloy formation. In FTS testing, drawbacks of Ni addition included decreased CO conversion on a per gram catalyst basis, although Ni did not significantly impact the turnover number of cobalt, and produced slightly higher light gas selectivity. Benefits of Ni addition included an inverted induction period relative to undoped Co/Al2O3, where CO conversion increased with time on-stream in the initial period, and the stabilization of cobalt nanoparticles at a lower weight % of Co.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Substitution of Co with Ni in Co/Al 2 O 3 Catalysts for Fischer–Tropsch Synthesis

The effect of cobalt substitution with nickel was investigated for the Fischer–Tropsch synthesis reaction. Catalysts having different Ni/Co ratios were prepared by aqueous incipient wetness co-impregnation, characterized, and tested using a continuously stirred tank reactor (CSTR) for more than 200 h. The addition of nickel did not significantly modify the morphological properties measured. XRD, STEM, and TPR-XANES results showed intimate contact between nickel and cobalt, strongly suggesting the formation of a Co-Ni solid oxide solution in each case. Moreover, TPR-XANES indicated that nickel addition improves the cobalt reducibility. This may be due to H 2 dissociation and spillover, but is more likely the results of a chemical effect of intimate contact between Co and Ni resulting in Co-Ni alloying after activation. FTS testing revealed a lower initial activity when nickel was added. However, CO conversion continuously increased with time on-stream until a steady-state value (34%–37% depending on Ni/Co ratio) was achieved, which was very close to the value observed for undoped Co/Al 2 O 3 . This trend suggests nickel can stabilize cobalt nanoparticles even at a lower weight percentage of Co. Currently, the cobalt price is 2.13 times the price of nickel. Thus, comparing the activity/price, the catalyst with a Ni/Co ratio of 25/75 has better performance than the unpromoted catalyst. Finally, nickel-promoted catalysts exhibited slightly higher initial selectivity for light hydrocarbons, but this difference typically diminished with time on-stream; once leveling off in conversion was achieved, the C 5+ selectivities were similar (≈ 80%) for Ni/Co ratios up to 10/90, and only slightly lower (≈ 77%) at Ni/Co of 25/75.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Non-Idealities in Lab-Scale Kinetic Testing: A Theoretical Study of a Modular Temkin Reactor

The Temkin reactor can be applied for industrial relevant catalyst testing with unmodified catalyst particles. It was assumed in the literature that this reactor behaves as a cascade of continuously stirred tank reactors (CSTR). However, this assumption was based only on outlet gas composition or inert residence time distribution measurements. The present work theoretically investigates the catalytic CO2 methanation as a test case on different catalyst geometries, a sphere, and a ring, inside a single Temkin reaction chamber under isothermal conditions. Axial gas-phase species profiles from detailed computational fluid dynamics (CFD) are compared with a CSTR and 1D plug-flow reactor (PFR) model using a sophisticated microkinetic model. In addition, a 1D chemical reactor network (CRN) model was developed, and model parameters were adjusted based on the CFD simulations. Whereas the ideal reactor models overpredict the axial product concentrations, the CRN model results agree well with the CFD simulations, especially under low to medium flow rates. This study shows that complex flow patterns greatly influence species fields inside the Temkin reactor. Although residence time measurements suggest CSTR-like behavior, the reactive flow cannot be described by either a CSTR or PFR model but with the developed CRN model.

Wehinger, Gregor D. (ORCID:0000000217743391)↗

Grid-Scale Ternary-Pumped Thermal Electricity Storage for Flexible Operation of Nuclear Power Generation under High Penetration of Renewable Energy Sources

In this work, the integration of a grid-scale ternary-Pumped Thermal Electricity Storage (t-PTES) with a nuclear power generation to enhance operation flexibility is assessed using physics-based models and digital real time simulation. A part of the electricity from the nuclear power generation is delivered to the grid, and the balance is used to power a heat pump that can be augmented by an auxiliary resistive load element to increase the charging rate of the thermal storage. This increases the thermal potential between hot and cold thermal stores (usually solid materials or molten salts inside large storage tanks). The thermal energy is transformed back into electricity by reversing the heat pump cycle. Different transient scenarios including startup, shutdown, and power change for grid-connected operation are simulated to determine the behavior of the hybrid nuclear-t-PTES system operating under variable loads that constitute a departure from conventional, baseload nuclear plant operation schemes. Ternary refers to the three modes operation: (i) heat pump (including heating coil), (ii) heat engine, and (iii) simultaneous operation of heat pump (including heating coil) and heat engine during changeover from pumping to generation or vice-versa. The controllability of t-PTES in the short timescales as a dynamic load is used to demonstrate operational flexibility of hybrid nuclear plants for flexible operation through advanced load management. The integration of t-PTES into nuclear power systems enhances the system flexibility and is an enabler for high penetration of renewable energy resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Experimental Investigation of the Heat Transfer between Finned Tubes and a Bubbling Fluidized Bed with Horizontal Sand Mass Flow

The sandTES technology utilizes a fluidized bed counter current heat exchanger for thermal energy storage applications. Its main feature is an imposed horizontal flow of sand (SiO2) particles fluidized by a vertical air flow across a heat exchanger consisting of several horizontal rows of tubes. Past international research on heat transfer in dense fluidized beds has focused on stationary (stirred tank) systems, and there is little to no information available on the impact of longitudinal or helical fins. Previous pilot plant scale experiments at TU Wien led to the conclusion that the currently available correlations for predicting the heat transfer coefficient between the tube surface and the surrounding fluidized bed are insufficient for the horizontal sand flow imposed by the sandTES technology. Therefore, several smaller test rigs were designed in this study to investigate the influence of different tube arrangements and flow conditions on the external convective heat transfer coefficient and possible improvements by using finned tubes. It could be shown that helically finned tubes in a transversal arrangement, where the horizontal sand flow is perpendicular to the tube axes, allows an increase in the heat transfer coefficient per tube length (i.e., the virtual heat transfer coefficient) by a factor of 3.5 to about 1250 W/m2K at ambient temperature. Based on the literature, this heat transfer coefficient is expected to increase at higher temperatures. The new design criteria allow the design of compact, low-cost heat exchangers for thermal energy storage applications, in particular electro-thermal energy storage.

25 ENERGY STORAGE↗

Seawater Acidification and Bubble Plume Dispersion from Accidental Subsea CO 2 Pipeline Rupture: A Multiphase CFD Study

If a CO 2 reservoir or transmission pipeline were to leak, both the surrounding ecology and maritime traffic safety could be put at risk. To better understand and prepare for this risk, multiphase Computational Fluid Dynamics (CFD) models were built in ANSYS Fluent to capture the behavior of a leak once it enters the water. A 3D Eulerian–Eulerian model was used for validation, while a simplified 2D model was applied to simulate conditions at a 50-m depth. The models integrate bubble dynamics, gas holdup, CO 2 dissolution, dissolved species transport, and seawater acidification into a unified CFD framework. Mass transfer was calculated using the Hughmark correlation, and local seawater temperature and salinity were factored in to determine dissociation behavior and the relevant Henry’s Law constant. To confirm the 3D model’s accuracy, results were checked against two experimental datasets: the QICS field study and the Hauser Tank experiments. The team also modeled a hypothetical release scenario at the High Island 10L site and compared the results with earlier published work. The results show that at a depth of 50 m, the surrounding water column can completely absorb a CO 2 release at a rate of 35 kg/s, since the gas dissolves into the seawater as it rises toward the surface. Beyond confirming this mitigation capacity, the simulations shed light on how a leak would actually unfold in the environment, including the shape and movement of the rising bubble plume, how much CO 2 dissolves along the way, and the resulting shifts in seawater pH and pCO 2 . Together, this provides a practical framework for assessing how CO 2 leaks could affect marine environments in the Gulf of Mexico.

54 ENVIRONMENTAL SCIENCES↗

Uncertainty-Guided Prediction Horizon of Phase-Resolved Ocean Wave Forecasting Under Data Sparsity: Experimental and Numerical Evaluation

Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often depend on environmental sensors (e.g., waverider buoys, wave-sensing LIDAR). Challenges arise when upstream sensor data are missing, sparse, or phase-shifted due to drift. This study investigates the performance of two machine learning models, time-series dense encoder (TiDE) and long short-term memory (LSTM), for forecasting phase-resolved ocean surface elevations under varying degrees of data degradation. We introduce the τ-trimming algorithm, which adapts the prediction horizon based on uncertainty thresholds derived from historical forecasts. Numerical wave tank (NWT) and wave basin experiments are used to benchmark model performance under short- and long-term data masking, spatially coarse sensor grids, and upstream phase shifts. Results show under a 50% probability of upstream data loss, the τ-trimmed TiDE model achieves a 46% reduction in error at the most upstream target, compared to 22% for LSTM. Furthermore, phase misalignment in upstream data introduces a near-linear increase in forecast error. Under moderate model settings, a ±3 s misalignment increases the mean absolute error by approximately 0.5 m, while the same error is accumulated at ±4 s using the more conservative approach. These findings inform the design of resilient, uncertainty-aware wave forecasting systems suited for realistic offshore sensing environments.

42 ENGINEERING↗

Integrated Electrocoagulation, Ultrafiltration, Membrane Distillation, and Crystallization for Treating Produced Water

Produced water (PW) generated from hydraulic fracturing operations was treated using an integrated electrocoagulation, ultrafiltration, membrane distillation, and crystallization process (EC UF MDC). The aim was to determine the viability of this integrated process for maximizing water recovery. The results obtained here indicate that optimizing the various unit operations could lead to increased recovery of PW. Membrane fouling limits all membrane separation processes. A pretreatment step to suppress fouling is essential. Here, removal of total suspended solids (TSS) and total organic carbon (TOC) was achieved by electrocoagulation (EC) followed by ultrafiltration (UF). The hydrophobic membrane used in membrane distillation may be fouled by dissolved organic compounds. Reducing membrane fouling is essential to increase the long-term durability of the membrane distillation (MD) system. In addition, combining membrane distillation with crystallization (MDC) can help reduce scale formation. By inducing crystallization in the feed tank, scale formation on the MD membrane was suppressed. The integrated EC UF MDC process can impact Water Resources/Oil & Gas Companies. Conservation of surface and groundwater is possible by treating and reusing PW. Additionally, treating PW reduces the amount of PW disposed in Class II disposal wells and promotes more environmentally sustainable operations.

42 ENGINEERING↗

Identifying Critical Infrastructure in Imagery Data Using Explainable Convolutional Neural Networks

To date, no method utilizing satellite imagery exists for detailing the locations and functions of critical infrastructure across the United States, making response to natural disasters and other events challenging due to complex infrastructural interdependencies. This paper presents a repeatable, transferable, and explainable method for critical infrastructure analysis and implementation of a robust model for critical infrastructure detection in satellite imagery. This model consists of a DenseNet-161 convolutional neural network, pretrained with the ImageNet database. The model was provided additional training with a custom dataset, containing nine infrastructure classes. The resultant analysis achieved an overall accuracy of 90%, with the highest accuracy for airports (97%), hydroelectric dams (96%), solar farms (94%), substations (91%), potable water tanks (93%), and hospitals (93%). Critical infrastructure types with relatively low accuracy are likely influenced by data commonality between similar infrastructure components for petroleum terminals (86%), water treatment plants (78%), and natural gas generation (78%). Local interpretable model-agnostic explanations (LIME) was integrated into the overall modeling pipeline to establish trust for users in critical infrastructure applications. The results demonstrate the effectiveness of a convolutional neural network approach for critical infrastructure identification, with higher than 90% accuracy in identifying six of the critical infrastructure facility types.

97 MATHEMATICS AND COMPUTING↗

Simulating vibro-acoustic damping of bubbles in fluids

Bubbles in fluids are common occurrence due to impurities, thermal or flow variations. They are sometimes considered detrimental to the flow and more importantly surrounding structural integrity. On the other hand, bubbles were used positively towards damping vibrations in fluid filled structures [1] and as barriers or curtains in the removal of plastic waste from water ways [2] and also in noise attenuation from offshore windfarms [3]. In the latter two cases, engineers hypothesized these curtains help marine life from sound pollution from surrounding machinery and ships. In this paper the authors discuss two cases to study the effect of bubble size and bubble density. In the first experiment a curtain of air bubbles was introduced in a water body and sound transmission loss (STL) through this curtain was studied. In a second experiment, a stainless-steel tank filled with liquid mercury is infused with helium bubbles and the vibration levels were monitored.

Kappagantu, Ramana↗

Critical feature and seawater testing of cross-flow rotor components fabricated with additive manufacturing

Advanced manufacturing (AM) materials were investigated for their suitability for use in cross-flow turbine rotors. AM materials were categorized into 3 classes – plastics, metals, and ceramics – and reviewed for suitability based on a set of engineering requirements and criteria. Two plastics and two metals were selected to undergo further testing: Essentium CF25, Markforged Onyx, Titanium Ti-6Al-4V, and Inconel 718. Dogbone-shaped specimens were printed from each material in two sets. The first set was tensile tested to get a material baseline. The second set was submerged in the seawater tanks at PNNL-Sequim for 6 months to determine water uptake, corrosion, and biofouling resistance and then subsequently tensile tested. While few macroscopic changes could be observed after seawater testing, the plastic materials degraded significantly as compared to baseline, while the metal material properties remained consistent. Titanium and Inconel are used consistently by industry in extreme conditions, and the materials show promising performance for marine energy use cases.

McVey, James R.↗

Tidal Turbine Benchmarking Project: Stage I - Steady Flow Blind Predictions: Preprint

This paper presents the first blind prediction stage of the Tidal Turbine Benchmarking Project being conducted and funded by the UK's EPSRC and Supergen ORE Hub. In this first stage, only steady flow conditions, at low and elevated turbulence (3.1%) levels, were considered. Prior to the blind prediction stage, a large laboratory scale experiment was conducted in which a highly instrumented 1.6m diameter tidal rotor was towed through a large towing tank in well-defined flow conditions with and without an upstream turbulence grid. Details of the test campaign and rotor design were released as part of this community blind prediction exercise. Participants were invited to use a range of engineering modelling approaches to simulate the performance and loads of the turbine. 26 submissions were received from 12 groups from across academia and industry using solution techniques ranging from blade resolved computational fluid dynamics through actuator line, boundary integral element methods, vortex methods to engineering Blade Element Momentum methods. The comparisons between experiments and blind predictions were extremely positive helping to provide validation and uncertainty estimates for the models, but also validating the experimental tests themselves. The exercise demonstrated that the experimental turbine data provides a robust data set against which researchers and design engineers can test their models and implementations to ensure robustness in their processes, helping to reduce uncertainty and provide increased confidence in engineering processes. Furthermore, the data set provides the basis by which modellers can evaluate and refine approaches.

benchmarking↗

Pool-Based Tow System for Testing Tethered Hydrokinetic Devices Being Developed to Harvest Energy From Ocean Currents

Abstract The immense potential for ocean current energy harvesting is being actively explored as the push for renewable energy becomes more urgent. This paper demonstrates a tow testing platform built to examine and validate mathematical models related to the performance of tethered, underwater, hydrokinetic devices in development to harvest energy from ocean currents, and presents experimental results illustrating how such a system can be used. The platform has been modularly designed to allow for the testing of various tethered, underwater energy-generation systems, including kite-based systems, coaxial turbines, and duct sails. Previous research on tethered energy-generating systems has primarily been focused on airborne systems. Additionally, the limited experimental research on tethered, underwater energy-generation systems has relied on a rigid rod for mechanical and electrical connections between the test articles and instrumentation. The tow testing platform presented in this paper accomplishes the mechanical and electrical connection through a dual-function tether, featuring internal conductors and an external sheath to support towing loads. The goal of this platform was to enable the emulation of ocean currents, which are largely unidirectional, and to retrofit a regular pool into a cost-effective, adaptable, small-scale tow tank test bed. The capabilities of the system include two-way communication with tethered devices, multiple towing profiles in order to emulate different flow regimes, real-time control, and differential velocities via dual winch operation.

Engineering↗

Production of ice-nucleating particles (INPs) by fast-growing phytoplankton

Sea spray aerosol contains ice-nucleating particles (INPs), which affect the formation and proper ties of clouds. Here, we show that aerosols emitted from fast-growing marine phytoplankton produce effective immersion INPs, which nucleate at temperatures significantly warmer than the atmospheric homogeneous freezing (-38.0 °C) of pure water. Aerosol sampled over phytoplankton cultures grown in a Marine Aerosol Ref erence Tank (MART) induced nucleation and freezing at temperatures as high as -15.0 °C during exponential phytoplankton growth. This was observed in monospecific cultures representative of two major groups of phy toplankton, namely a cyanobacterium (Synechococcus elongatus) and a diatom (Thalassiosira weissflogii). Ice nucleation occurred at colder temperatures (-28.5 °C and below), which were not different from the freezing temperatures of procedural blanks, when the cultures were in the stationary or death phases of growth. Ice nucleation at warmer temperatures was associated with relatively high values of the maximum quantum yield of photosystem II ( Φ PSII ), an indicator of the physiological status of phytoplankton. High values of Φ PSII indicate the presence of cells with efficient photochemistry and greater potential for photosynthesis. For comparison, field measurements in the North Atlantic Ocean showed that high net growth rates of natural phytoplankton assemblages were associated with marine aerosol that acted as effective immersion INPs at relatively warm temperatures. Data were collected over 4 d at a sampling station maintained in the same water mass as the water column stabilized after deep mixing by a storm. Phytoplankton biomass and net phytoplankton growth rate (0.56 d -1 ) were greatest over the 24 h preceding the warmest mean ice nucleation temperature (-25.5 °C). Collectively, our laboratory and field observations indicate that phytoplankton physiological status is a useful predictor of effective INPs and more reliable than biomass or taxonomic affiliation. Ocean regions associated with fast phytoplankton growth, such as the North Atlantic during the annual spring bloom, may be significant sources of atmospheric INPs.

54 ENVIRONMENTAL SCIENCES↗

Atmospheric H 2 observations from the NOAA Cooperative Global Air Sampling Network

Abstract. The NOAA Global Monitoring Laboratory (GML) measures atmospheric hydrogen (H2) in grab samples collected weekly as flask pairs at over 50 sites in the Cooperative Global Air Sampling Network. Measurements representative of background air sampling show higher H2 in recent years at all latitudes. The marine boundary layer (MBL) global mean H2 was 552.8 ppb in 2021, 20.2 ± 0.2 ppb higher compared to 2010. A 10 ppb or more increase over the 2010–2021 average annual cycle was detected in 2016 for MBL zonal means in the tropics and in the Southern Hemisphere. Carbon monoxide measurements in the same-air samples suggest large biomass burning events in different regions likely contributed to the observed interannual variability at different latitudes. The NOAA H2 measurements from 2009 to 2021 are now based on the World Meteorological Organization Global Atmospheric Watch (WMO GAW) H2 mole fraction calibration scale, developed and maintained by the Max Planck Institute for Biogeochemistry (MPI-BGC), Jena, Germany. GML maintains eight H2 primary calibration standards to propagate the WMO scale. These are gravimetric hydrogen-in-air mixtures in electropolished stainless steel cylinders (Essex Industries, St. Louis, MO), which are stable for H2. These mixtures were calibrated at the MPI-BGC, the WMO Central Calibration Laboratory (CCL) for H2, in late 2020 and span the range 250–700 ppb. We have used the CCL assignments to propagate the WMO H2 calibration scale to NOAA air measurements performed using gas chromatography and helium pulse discharge detector instruments since 2009. To propagate the scale, NOAA uses a hierarchy of secondary and tertiary standards, which consist of high-pressure whole-air mixtures in aluminum cylinders, calibrated against the primary and secondary standards, respectively. Hydrogen at the parts per billion level has a tendency to increase in aluminum cylinders over time. We fit the calibration histories of these standards with zero-, first-, or second-order polynomial functions of time and use the time-dependent mole fraction assignments on the WMO scale to reprocess all tank air and flask air H2 measurement records. The robustness of the scale propagation over multiple years is evaluated with the regular analysis of target air cylinders and with long-term same-air measurement comparison efforts with WMO GAW partner laboratories. Long-term calibrated, globally distributed, and freely accessible measurements of H2 and other gases and isotopes continue to be essential to track and interpret regional and global changes in the atmosphere composition. The adoption of the WMO H2 calibration scale and subsequent reprocessing of NOAA atmospheric data constitute a significant improvement in the NOAA H2 measurement records.

Pétron, Gabrielle↗

Energy Storage Technologies and U.S. Department of War Requirements

This report offers an overarching primer the energy storage market and assessment of each technology’s suitability for U.S. Department of War applications. We find that battery energy storage is the most promising technology for energy storage applications in terms of energy density and cost. While commercial and advanced Li-ion can satisfy certain electric mobility (e.g., cars, midsized vehicles) and electric flight application (e.g. drones) needs of DoW, next generation technologies like Li metal solid-state batteries, and conversion chemistries (Li-air, Li-CFx) are needed for heavy duty applications like armored vehicles, tanks, airplanes, jets. Batteries should also be supplemented with technologies such as supercapacitors and next-generation flywheels to provide short bursts of high energy for high power needs. Thermal energy storage solutions (sensible and latent heat) and fuel cells (PEMFC and SOFC) are good alternatives for supporting energy storage applications in terms of energy density and cost. Gravity-based energy storage promises the least energy density with high cost and should only be used for niche DoW applications. Of the different gravity energy storage technologies reviewed, pumped-hydro, flywheel, and compressed air energy storage are promising, while solid gravity energy storage appears the least attractive. Military facilities requiring 14 days of energy storage can benefit from flow batteries, especially commercial VFRBs and next generation iron-air systems. While VFRBs are expensive, iron-air batteries have the coupled benefits of low cost and good energy density promising 100+ hours of storage.

25 ENERGY STORAGE↗

Next Generation Multi-Use Heavy-Duty High-Flow Direct-Fill Hydrogen Refueling Station with Standardized Design (CRADA Final Report)

The Contractor will build a liquid hydrogen (LH2) fueling station model that is capable of simulating the amount of hydrogen transferred from the liquid storage tank to the vehicle, depending on the station’s design and control scheme. This modeling work will allow the Parties to seek the design and control scheme of an LH2 station that can fill a targeted number of vehicles while meeting a time-average flow rate of 10 kg/min for each fill. While evaluating a high dispensing performance station design and control scheme, the Contractor will analyze the design and control scheme are economically viable.

08 HYDROGEN↗