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At least 379 records · Page 21

Physical model and experimental validation of a high temperature proton exchange membrane electrochemical hydrogen pump cell for efficient single-stage extraction of low concentration hydrogen gas

There is interest in valorization of existing natural gas infrastructure to facilitate the co-transportation of hydrogen via blending of hydrogen gas initially at limited concentrations of 1–20 vol% H2 and to subsequently extract hydrogen at fuel cell quality standards (SAE J2719/ISO14687-2). High temperature proton exchange membrane electrochemical hydrogen pump (HT-PEM EHP) based on phosphoric acid doped polybenzimidazole (PA-PBI) exhibits good performance at elevated temperatures (>120 °C), which provides desirable tolerance to non-methane natural gas constituents that are problematic for lower temperature based EHP. To better understand the suitability of the HT-PEM EHP for such gas separation processes, a two-dimensional model of EHP based on PA-PBI was developed. The model is validated for several relevant operating conditions and across cells with differing amounts of phosphoric acid content in the electrodes. Operando micro x-ray computed tomography (CT) imaging of an HT-PEM EHP was used to further validate physical parameters and assumptions of the model. The impacts of pressure, relative humidity of the anode feed, and concentration of feed gases on separation performance are investigated. This study shows that a specific energy of separation of 5.1 kWh/kg H2 at a hydrogen recovery factor (HRF) of 50 vol% can be achieved in a single stage with the EHP, producing fuel cell quality hydrogen purity of 99.99 vol% H2 from a 2 vol% H2/CH4 feed blend, while pressurizing the product H2 at a pressure ratio of 1.3 relative to feed pressure.

Stansberry, John M↗

Inter-well connectivity detection in CO 2 WAG projects using statistical recurrent unit models

Routine well-wise injection and production measurements contain significant information on subsurface structure and properties. Data-driven technology that interprets surface data into subsurface structure or properties can assist operators in making informed decisions by providing a better understanding of field assets. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO 2 EOR projects utilizing the water-alternating-gas (WAG) process. SRU is a special type of recurrent neural network (RNN) that allows for better characterization of temporal trends, by learning various statistics of the input at different time scales. In our application, the complete states (injection rate, pressure and cumulative injection) at injectors and pressure states at producers are fed to SRU as the input and the phase rates at producers are treated as the output. Once the SRU is trained and validated, it is then used to assess the connectivity of each injector to any producer using permutation variable importance method, wherein inputs corresponding to an injector are shuffled and the increase in prediction error at a given producer is recorded as the importance (connectivity metric) of the injector to the producer. This method is tested in both synthetic and field-scale cases. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. This significantly improves confidence in our data-driven procedure. The novelty of this work is that it is purely data-driven method and can directly interpret routine surface measurements to intuitive subsurface knowledge. Furthermore, the streamline-based validation procedure provides physics-based backing to the results obtained from data analytics. This study results in a reliable and efficient data analytics framework that is well-suited for large field applications.

42 ENGINEERING↗

Quantifying CO 2 Plume Stabilization at Carbon Storage Projects, North Dakota, USA

This study presents an approach for quantifying when injected carbon dioxide (CO 2 ) stabilizes pursuant to carbon capture and storage (CCS) project permitting and site closure requirements. The distribution of mobile-phase CO 2 (CO 2 plume) will evolve within the storage reservoir during and after injection through both physical and chemical trapping mechanisms. CCS policies generally agree that the CO 2 plume’s migratory behavior in post-injection should demonstrate nonendangerment to the environment but do not provide specific guidance on how to meet the definition of plume stabilization, generating some uncertainty for operators. Plume stability herein means the CO 2 plume 1) changes size minimally and predictably in the storage reservoir such that it will not cross key boundaries identified in the permit and 2) does not pose a threat to human health, underground sources of drinking water (USDWs), and the environment because of lateral migration to areas where leakage pathways may exist. Published literature on plume metrics was reviewed to determine which metric(s) may be most appropriate for determining CO 2 plume stability. A technical approach that defines plume stabilization by estimating the rate of change in the geographic footprint of the CO 2 plume with respect to time was developed and illustrated using a case study from North Dakota, USA, as a proposed solution for CCS operators to apply at the project permitting stage. Any prospective CCS operator may benefit from using the same approach to inform the selection of pore space lease and monitoring areas and develop post-injection site care plans.

03 NATURAL GAS↗

Design and requirements of a hydrogen component reliability database (HyCReD)

Hydrogen technologies are expected to play a key role in the decarbonization of several sectors including energy storage and transportation. Rigorous investigation and quantification of the risk and reliability issues associated with hydrogen technologies will be critical to ensuring both their wider adoption and safe, economical operations. Quantitative risk assessment (QRA) is an important tool that has been used to enable the safe deployment of many engineering systems, including hydrogen fueling stations and hydrogen storage systems. However, QRA studies require reliability data which is currently lacking for expanding applications of hydrogen systems. Here, to address this gap, we present a new structure for a hydrogen component reliability database (HyCReD) that can be used to generate reliability data to be used in QRA, reliability, safety studies, maintenance planning, and more. Building on our previous work examining four major hydrogen safety data collection tools (West et al., 2022) [1], our approach in this work was to consult scientific literature on reliability data collection as well as a number of existing reliability engineering databases in the oil & gas, chemical processing, and nuclear power plant sectors. The evaluation of these databases led to identifying best practices to be implemented in a data collection framework for a hydrogen component reliability database. Based on these best practices, a set of 24 requirements for the proposed database are presented, covering its characteristics and the types of data to be collected. We define the structure of the HyCReD database and 25 data elements to be collected, spanning system description, failure, shutdown, or near-miss events, and maintenance events. The data elements are then defined according to international standards used in the safety and reliability practice and potential choice lists are provided for each field. Since this database is being piloted for hydrogen fueling stations, a generic station component hierarchy developed by West (2021) [2] is used to standardize system data. Finally, we demonstrate populating the database with information extracted from five narrative reports on hydrogen fueling station incidents.

08 HYDROGEN↗

Structural Interconversion between Agglomerated Palladium Domains and Mononuclear Pd(II) Cations in Chabazite Zeolites

Palladium-exchanged zeolites are candidate materials for passive NO x adsorption in automotive exhaust aftertreatment, where mononuclear Pd cations behave as precursors to the purported NO x adsorption sites. Yet, the structures of zeolite lattice binding sites capable of stabilizing mononuclear Pd 2+ ions, and the mechanisms that interconvert agglomerated PdO and Pd domains into mononuclear Pd 2+ ions during Pd redispersion treatments, remain incompletely understood. In this work, we use a suite of spectroscopic methods and quantitative site titration techniques to characterize mononuclear and agglomerated Pd species on zeolites with varying material properties and treatment history. Aqueous-phase methods to introduce Pd onto NH 4 -form zeolites initially form mononuclear [Pd(NH 3 ) 4 ] 2+ complexes, but subsequent thermal treatments (573–723 K; air) lead to in situ formation of H 2 that first reduces Pd 2+ to metallic Pd domains, which are then oxidized by air to PdO domains. Progressive treatment of Pd-zeolites in air to higher temperatures (723–1023 K) converts larger fractions of agglomerated PdO to mononuclear Pd 2+ , as quantified by H 2 temperature programmed reduction, because higher temperature treatments facilitate Pd redispersion toward deeper locations within chabazite (CHA) crystallites, which is corroborated by complementary titrimetric and spectroscopic data. Pd-CHA zeolites synthesized with similar bulk Pd and framework Al content, but varying framework Al arrangement, provide evidence that six-membered rings (6-MR) hosting paired Al sites (Al–O–(Si–O) x –Al, x = 1, 2) stabilize Pd 2+ ions and that otherwise isolated Al sites can stabilize [PdOH] + species, identifiable by an IR OH stretch at 3660 cm –1 . These findings clarify the underlying chemical processes and gas environments that cause Pd agglomeration in zeolites and their subsequent redispersion to mononuclear Pd 2+ ions, which prefer binding at 6-MR paired Al sites in CHA, and indicate that higher temperature air treatments lead to more uniform Pd spatial distributions throughout zeolite crystallites.

36 MATERIALS SCIENCE↗

Synthetic Methanol/Fischer–Tropsch Fuel Production Capacity, Cost, and Carbon Intensity Utilizing CO 2 from Industrial and Power Plants in the United States

Captured CO 2 is a potential feedstock to produce fuel/chemicals using renewable electricity as the energy source. In this study, we explored resource availability and synergies by region in the United States and conducted cost and environmental analysis to identify unique opportunities in each region to inform possible regional and national actions for carbon capture and utilization development. This study estimated production cost of synthetic methanol and Fischer–Tropsch (FT) fuels by using CO 2 captured from the waste streams emitted from six industrial [ethanol, ammonia, natural gas (NG) processing, hydrogen, cement, and iron/steel production plants] and two power generation (coal and NG) processes across the United States. The results showed that a total of 1594 million metric ton per year of waste CO 2 can be captured and converted into 85 and 319 billion gallons of FT fuels and methanol, respectively. FT fuels can potentially substitute for 36% of the total petroleum fuels used in the transportation sector in 2018. Technoeconomic analysis shows that the minimum selling prices for synthetic FT fuels and methanol are 1.8–2.8 times the price of petroleum fuel/chemicals, but the total CO 2 reduction potential is 935–1777 MMT/year.

54 ENVIRONMENTAL SCIENCES↗

Kinetics, Products, and Brown Carbon Formation by Aqueous-Phase Reactions of Glycolaldehyde with Atmospheric Amines and Ammonium Sulfate

Glycolaldehyde (GAld) is a C 2 water-soluble aldehyde produced during the atmospheric oxidation of isoprene and many other species and is commonly found in cloudwater. Previous work has established that glycolaldehyde evaporates more readily from drying aerosol droplets containing ammonium sulfate (AS) than does glyoxal, methylglyoxal, or hydroxyacetone, which implies that it does not oligomerize as quickly as these other species. Here, we report NMR measurements of glycolaldehyde’s aqueous-phase reactions with AS, methylamine, and glycine. Reaction rate constants are smaller than those of respective glyoxal and methylglyoxal reactions in the pH range of 3–6. In follow-up cloud chamber experiments, deliquesced glycine and AS seed particles were found to take up glycolaldehyde and methylamine and form brown carbon. At very high relative humidity, these changes were more than 2 orders of magnitude faster than predicted by our bulk liquid NMR kinetics measurements, suggesting that reactions involving surface-active species at crowded air–water interfaces may play an important role. The high-resolution liquid chromatography–electrospray ionization–mass spectrometric analysis of filter extracts of unprocessed AS + GAld seed particles identified sugar-like C 6 and C 12 GAld oligomers, including proposed product 3-deoxyglucosone, with and without modification by reactions with ammonia to diimine and imidazole forms. Chamber exposure to methylamine gas, cloud processing, and simulated sunlight increased the incorporation of both ammonia and methylamine into oligomers. Many C 4 –C 16 imidazole derivatives were detected in an extract of chamber-exposed aerosol along with a predominance of N-derivatized C 6 and C 12 glycolaldehyde oligomers, suggesting that GAld is capable of forming brown carbon SOA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Continental-Scale Geographic Trends in Barometric-Pumping Efficiency Potential: A North American Case Study

Barometric pumping is a gas transport mechanism that has important implications for many applications involving subsurface gas seepage processes. Here, this study provides the first continental-scale analysis of barometric-pumping efficiency potential based on meteorology. We quantified the barometric-pumping efficiency potential at 1,257 locations across the continental US and Canada. The results provide continental-scale geographic dependencies of barometric-pumping efficiency potential, indicating a significant correlation with latitude and a nonlinear dependence on longitude. The analysis also indicates that variability in barometric-pumping efficiency potential decreases with distance from the coast and as elevation increases. Locations far from the coastline are more likely to have upper mid-range potentials, while higher elevation locations are more likely to have low potentials. The highest barometric-pumping efficiency potentials are mostly found around the Gulf of St. Lawrence around 50°N. Locations along the Atlantic coast exhibit large-scale variations in potentials with a clear increasing trend with latitude.

58 GEOSCIENCES↗

Low-temperature gas-phase formation of cyclopentadiene and its role in the formation of aromatics in the interstellar medium

The cyclopentadiene (C 5 H 6 ) molecule has emerged as a molecular building block of nonplanar polycyclic aromatic hydrocarbons (PAHs) and carbonaceous nanostructures such as corannulene (C 20 H 10 ), nanobowls (C 40 H 10 ), and fullerenes (C 60 ) in deep space. However, the underlying elementary gas-phase processes synthesizing cyclopentadiene from acyclic hydrocarbon precursors have remained elusive. Here, by merging crossed molecular beam experiments with rate coefficient calculations and comprehensive astrochemical modeling, we afford persuasive testimony on an unconventional low-temperature cyclization pathway to cyclopentadiene from acyclic precursors through the reaction of the simplest diatomic organic radical—methylidyne (CH)—with 1,3-butadiene (C 4 H 6 ) representing main route to cyclopentadiene observed in TaurusMolecular Cloud. This facile route provides potential solution for the incorporation of the cyclopentadiene moiety in complex aromatic systems via bottom–up molecular mass growth processes and offers an entry point to the low-temperature chemistry in deep space leading eventually to nonplanar PAHs in our carbonaceous Universe.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time projection chamber for GADGET II

The established Gaseous Detector with Germanium Tagging (GADGET) detection system is used to measure weak, low-energy 𝛽-delayed proton decays. It consists of the Gaseous Proton Detector equipped with a MICROMEGAS (MM) readout to detect protons and other charged particles calorimetrically, surrounded by the Segmented Germanium Array (SeGA) for high-resolution detection of prompt 𝛾 rays. To upgrade GADGET's Proton Detector to operate as a compact time projection chamber (TPC) for the detection, three-dimensional imaging and identification of low-energy 𝛽-delayed single- and multiparticle emissions mainly of interest to astrophysical studies. A new high granularity MM board with 1024 pads has been designed, fabricated, installed, and tested. A high-density data acquisition system based on generic electronics for TPCs (GET) has been installed and optimized to record and process the gas avalanche signals collected on the readout pads. The TPC's performance has been tested using a 220 Rn 𝛼-particle source and cosmic-ray muons. In addition, decay events in the TPC have been simulated by adapting the attpcroot data analysis framework. Furthermore, a novel application of two-dimensional convolutional neural networks for GADGET II event classification is introduced. The optimization of data throughput is also addressed. The GADGET II TPC is capable of detecting and identifying 𝛼 particles as well as measuring their track direction, range, and energy. The extracted energy resolution of the GADGET II TPC using P10 gas is about 5.4% at 6.288 MeV ( 220 Rn 𝛼 events), computed using charge integration. Based on a systematic simulation study, we estimated the detection efficiency of the GADGET II TPC for protons and 𝛼 particles, respectively. It has also been demonstrated that the GADGET II TPC is capable of tracking minimum-ionizing particles (i.e., cosmic-ray muons). From these measurements, the electron drift velocity was measured under typical operating conditions. In addition to being one of the first generation of micropattern gaseous detectors (MPGDs) to utilize a resistive anode applied to low-energy nuclear physics, the GADGET II TPC will also be the first TPC surrounded by a high-efficiency array of high-purity germanium 𝛾-ray detectors. As a result, the TPC of GADGET II has been designed, fabricated, and tested and is ready for operation at the Facility for Rare Isotope Beams for radioactive-beam-line experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Integrated Modeling and Optimal Operation of Multi-Energy System for Coastal Community

Focusing on remote, isolated, and underserved communities, a multi-energy system is designed in this research which is capable of utilizing different energy sources in a more coordinated and energy-efficient way to support various demands, such as fresh water, electricity, hydrogen, thermal demand, etc. The energy sources considered are renewables (wind, solar, marine) and natural gas. The energy conversion process includes water desalination, gas combustion, water electrolyzation, and different types of storage (hydrogen tank, electricity, thermal, etc.) are designed to serve as buffers in supply-demand balancing. Sets of experiments are designed to demonstrate the effectiveness of the proposed operating model and investigate the impact of uncertainties from renewable generations and demands.

Chen, Yang↗

Extensive Attention Mechanisms in Graph Neural Networks for Materials Discovery

We present our research where attention mechanism is extensively applied to various aspects of graph neural net- works for predicting materials properties. As a result, surrogate models can not only replace costly simulations for materials screening but also formulate hypotheses and insights to guide further design exploration. We predict formation energy of the Materials Project and gas adsorption of crystalline adsorbents, and demonstrate the superior performance of our graph neural networks. Moreover, attention reveals important substructures that the machine learning models deem important for a material to achieve desired target properties. Our model is based solely on standard structural input files containing atomistic descriptions of the adsorbent material candidates. We construct novel methodological extensions to match the prediction accuracy of state-of-the-art models some of which were built with hundreds of features at much higher computational cost. We show that sophisticated neural networks can obviate the need for elaborate feature engineering. Our approach can be more broadly applied to optimize gas capture processes at industrial scale.

Cong, Guojing↗

Utah FORGE: Geochemical Data for Cold Groundwaters and Produced Geothermal Fluids

Geochemical data for cold groundwaters and produced geothermal fluids around the Utah FORGE site. The data is compiled into four tables in the attached Excel File. Table 1 is a compilation of compositions (anions, cations, weak acids, oxygen, hydrogen, and carbon isotopes) for cold groundwaters and produced geothermal waters in the Milford valley, Utah. Table 2 is a compilation of noble gas (He, Ne, Ar) and He and Ne isotopic compositions for cold groundwaters and produced geothermal waters in the Milford valley, Utah. Table 3 provides values for calculated advective and diffusive fluxes of helium. Table 4 provides values of calculated subsurface stored heat between the Opal Mound fault and the Utah FORGE site, which are related to volumes of recently solidified magmatic heat sources.

15 GEOTHERMAL ENERGY↗

Organic Iodide Sorption from Dilute Gas Streams

Reprocessing used nuclear fuel releases volatile radionuclides, including 129 iodine (I), into the off-gas of a processing plant. Volatile radioiodine could be present in several forms, depending on the chemistry of the process used and the off-gas stream. Inorganic I 2 is expected to be the predominant I species in the dissolver off-gas (DOG), with minor organic iodides present. The bulk of the I is expected to volatilize into the DOG in parts-per-million-level (ppm) concentrations. In contrast, in the vessel off-gas (VOG), most of the volatile I is expected to be found as organic iodides, such as CH 3 I, C 4 H 9 I, and C 12 H 25 I. These species are expected to be present in parts-per-billion-level (ppb) concentrations but require abatement, even at low expected concentrations, to meet regulatory emissions limits in the United States. Historically, studies of I abatement by Ag-functionalized sorbents have focused on inorganic I in the DOG, but in the last few years, more research attention has been given to organic iodides, especially longer chain species, such as C 4 H 9 I, and C 12 H 25 I. This report has three main goals: (1) to present new data generated at Oak Ridge National Laboratory (ORNL) in FY21 on the sorption behavior of organic iodides on AgZ, (2) to summarize and synthesize organic iodide data produced by ORNL and Idaho National Laboratory (INL) over the last 4 years to answer questions on organic iodides behavior outlined in the 2018 joint test plan (Jubin et al. 2018), and (3) to propose a VOG abatement system design that can provide the capture efficiencies required to meet I emission limits. The 2021 ORNL experimental campaign tested the effects of organic iodide speciation and concentration in the off-gas, superficial velocity of the off-gas, and effects of aging on AgZ sorbent capacity. These studies found that the sorption rate of organic iodides by AgZ depends on the hydrocarbon chain length and the concentration in the off-gas. Higher molecular weight organic iodides adsorb to AgZ more slowly than I. At a concentration of 50 ppm concentration in the off-gas, CH 3 I loads 8% slower, C 4 H 9 I loads 20% slower, and C 12 H 25 I loads 40% slower than I. The lowest concentration loading rates calculated were in 5 ppm organic iodide gas streams in which AgZ gained on average 0.14 mg I/g sorbent/hour in the bench scale test system. Thus, longer sorbent beds might be needed to accommodate slower loading rates onto AgZ in lower concentration gas streams. Although sorption rate varies as a function of hydrocarbon chain length, the saturation concentration of the sorbent for these I-bearing species does not vary. Aging AgZ in a humid air stream for 9 months drops the overall sorbent capacity by ~35% for CH 3 I, ~50% for C 4 H 9 I, and ~40% for C 12 H 25 I. This results in a saturation capacity between 35 and 70 mg I/g sorbent for the aged AgZ. In conjunction with recent data produced by INL, these data are used to estimate the mass transfer zone (MTZ) and decontamination factor (DF) for sorbent beds of AgZ. Sorption tests performed with iodide gas concentrations of about 1 ppm and higher at a superficial gas velocity of 10 m/min, indicate that MTZ depths for these conditions tend to range between about 8-20 cm. Tests performed at lower concentrations between 50-90 ppb and at gas superficial velocities of 1, 10, and 20 m/min indicate that the MTZ depth increases with increasing superficial gas velocity. The 20 m/min test indicates that the MTZ for those conditions was at least 22 cm, and doubling the superficial gas velocity from 10 to 20 m/min could roughly double or triple the MTZ depth. Doubling and tripling the bounding MTZ depth of 20 cm for the body of MTZ estimates made at with 10 m/min superficial velocity would extend the MTZ for a superficial velocity of 20 m/min to 40-60 cm. This bounding limit applies to all of the organic iodides that have been tested. These results also indicate that the sorption rate-limiting step is not sensitive to the superficial gas velocity; otherwise the MTZ depth would not have increased approximately in proportion to the increase in the gas superficial velocity. This further suggests that the rate limiting step is not associated with mass transfer of the sorbate to the sorbent surface, or mass transfer of the reaction byproducts from the sorbent surface, but is associated with sorption or chemical reactions on the sorbent surface or in sorbent pores. Deep bed testing at INL has established DFs of >2,000 for I, CH 3 I, and C 4 H 9 I under a range of conditions (Soelberg et al. 2021, Bruffey et al. 2019). DF does not seem to be affected by the concentration of the organic iodide in the gas stream over the range of 1 to 50 ppm. Thus, if the MTZ is accommodated in sorbent bed design for the DOG and VOG, then regulatory DFs will be met. To meet the third objective outlined in this report, these experimental data were used to update an engineering evaluation of the VOG first completed in 2016. The updated VOG design can be found in an accompanying document (Welty et al., 2021; INL- LTD-21-64587). This report finds that the VOG will decrease in both size and complexity, relative to previous designs, and will still meet regulatory requirements for all iodine forms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Tracer Gas Model Development and Verification in PFLOTRAN

Tracer gases, whether they are chemical or isotopic in nature, are useful tools in examining the flow and transport of gaseous or volatile species in the underground. One application is using detection of short-lived argon and xenon radionuclides to monitor for underground nuclear explosions. However, even chemically inert species, such as the noble gases, have bene observed to exhibit non-conservative behavior when flowing through porous media containing certain materials, such as zeolites, due to gas adsorption processes. This report details the model developed, implemented, and tested in the open source and massively parallel subsurface flow and transport simulator PFLOTRAN for future use in modeling the transport of adsorbing tracer gases.

07 ISOTOPE AND RADIATION SOURCES↗

Dynamic Species Reduction for Multi-Cycle CFD Simulations (Final Technical Report)

This project primarily sought to address some of the computational cost concerns of detailed simulations by developing improved methods of handling species transport, and chemical kinetics evaluation in a commercial 3D Computational Fluid Dynamics (CFD) environment. Secondary goals were to apply these techniques to fuels and conditions of interest to better understand the key species and reactions required to adequately capture cycle to cycle coupling. Improved modeling will lead to better understanding of these combustion modes and their dependence on fuel composition, which can then enable more clean and efficient engines, ultimately benefiting the consumer as well as the general public. Two approaches were used to address the computational cost. A “Dynamic Species Reduction” (DSR) procedure was developed to remove chemical species from the simulation during periods when chemical reactions were not expected to be important, particularly during gas exchange when temperatures are low and little fuel remains. This modelling procedure automatically detects relevant species to retain in the simulation domain based on their local concentration, removes species below a specified concentration threshold, and then adjusts the remaining species mass to conserve not only the number of H, C, and O atoms in each cell, but also the relative proportions between species and the heating value of the mixture in every cell. The second procedure was a “Product Directed Remapping” (PDR) updates the algorithm used to group individual computational cells for chemical kinetics evaluation to account for non-uniform temperature distributions and the CO to CO 2 ratio in the cells. The model techniques developed in this work successfully demonstrated computational performance improvements for a range of conditions relevant for Highly Dilute SI and HCCI engine operation. Runtime reductions of 10% were observed for small mechanisms, with further reductions of up to 36% observed for larger mechanisms. Improvements were primarily related to reducing the number of chemical species tracked during the gas exchange process using the Dynamic Species Reduction method. With smaller benefits observed from changes to the kinetics binning and evaluation strategy in the post combustion region using the PDR method. The results of this work show the potential for improved computational runtime for complicated simulations. They can and should be extended to additional conditions and new bio-derived and renewable fuels as they are developed and new kinetic mechanisms become available.

10 SYNTHETIC FUELS↗

HydroGEN STCH node support: FY25 Q1 quarterly report – LLNL's input

For reducing the cost of H 2 production by enhancing the efficiency and cyclability of water splitting reactions, we aim to understand the relationship between microstructure and surface reaction performance on perovskite oxides. In this quarter, mesoscale simulations were carried with various 3D porous microstructures to characterize the microstructure-dependent H 2 production. During the water splitting process, incoming gas including steam (H 2 O) passes through porous regions, which can induce local pressure variations according to the Bernoulli’s principle. Accordingly, we developed the mesoscale simulation method to characterize the reaction kinetics with inhomogeneous local pressures within porous microstructures.

08 HYDROGEN↗