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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dynamic Modeling and Simulation of a Subcritical Coal-Fired Power Plant under Load-Following Conditions

Dynamic models for power plants that capture realistic general process trends and effects of manipulated variables are needed to improve load-following, while minimizing carbon footprint. In this work, a dynamic modeling approach and simulation results for subcritical coal-fired power plant components are presented. These encompass simulation of the dynamics in the fireside, including the effects of fuel, air combustion, and the dynamics of the entire waterside and power generation sections. This model development enables the simulation and analysis of the important short and long-time scale dynamics of components such as heaters, evaporative loop, and power generation units. Furthermore, additional variables in the power generation section are introduced to improve model accuracy, extending the prediction capability of subcritical power plant models and opening new opportunities for research in operator training, optimization, and advanced model-based controller design that are based on these models. The change in process gain for different ramp rates associated with disturbance signals that affect process variables is also explored and a correlation developed. This provides opportunities to study disturbance rejection control implementation and adaptation for scenarios with such variations in ramp rates. The prediction capabilities of selected components are compared to data available in literature, with the obtained root mean squared error ranges that reflect the model performance and quality of predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Water–Hydrocarbon Interactions in Anionic Pyrene Monohydrate

Interactions between water and polycyclic aromatic hydrocarbons are essential in many aspects of chemistry, from interstellar and atmospheric processes to interfacial hydrophobicity and wetting phenomena. Despite their growing importance, the intermolecular potentials of the water-hydrocarbon interactions are underdeveloped compared to water-water potentials, and there are similarly few experimental probes that are sensitive to the details of the water-hydrocarbon potential. We present a combined experimental and computational study of anionic pyrene monohydrate, one of the simplest water/hydrocarbon clusters. The action spectrum in the OH region of the mass-selected cluster ion provides a rigorous benchmark for intermolecular potentials and computational methodologies. We identify missing intermolecular interactions and shortcomings in conventional dynamics calculations by comparing experimental data to density functional theory and classical molecular dynamics calculations. Kinetic trapping is prevalent, even for one water molecule and one pyrene molecule, leading to slow equilibration in conventional molecular dynamics calculations, even on nanosecond timescales and at low temperatures (50 K). At constant energy, temperature fluctuations for the pair of molecules are substantial. Immersing the system in a bath of soft spheres and employing parallel tempering alleviates kinetic trapping and dampens temperature fluctuations, bringing the system closer to the thermodynamic limit. With such augmented sampling, a simple, flexible water model reproduces the linewidth and the asymmetric broadening of the symmetric OH stretching mode, which we assign to spectral diffusion. In the OH stretching region, dynamics calculations predict a more intense antisymmetric peak than experiments observe but do not predict the bimodal split symmetric peak that the experiments show. Furthermore, our work suggests that electronic polarization, missing in the empirical force field, is responsible for the first discrepancy and that quantum nuclear effects, captured neither in density functional theory nor in classical dynamics, may be responsible for the second.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Barium stars as tracers of s -process nucleosynthesis in AGB stars: II. Using machine learning techniques on 169 stars

Barium (Ba) stars are characterised by an abundance of heavy elements made by the slow neutron capture process (s-process). This peculiar observed signature is due to the mass transfer from a stellar companion, bound in a binary stellar system, to the Ba star observed today. The signature is created when the stellar companion is an asymptotic giant branch (AGB) star. We aim to analyse the abundance pattern of 169 Ba stars using machine learning techniques and the AGB final surface abundances predicted by the FRUITY and Monash stellar models. We developed machine learning algorithms that use the abundance pattern of Ba stars as input to classify the initial mass and metallicity of each Ba star’s companion star using stellar model predictions. We used two algorithms. The first exploits neural networks to recognise patterns, and the second is a nearest-neighbour algorithm that focuses on finding the AGB model that predicts the final surface abundances closest to the observed Ba star values. In the second algorithm, we included the error bars and observational uncertainties in order to find the best-fit model. The classification process was based on the abundances of Fe, Rb, Sr, Zr, Ru, Nd, Ce, Sm, and Eu. We selected these elements by systematically removing s-process elements from our AGB model abundance distributions and identifying the elements whose removal had the biggest positive effect on the classification. We excluded Nb, Y, Mo, and La. Our final classification combined the output of both algorithms to identify an initial mass and metallicity range for each Ba star companion. With our analysis tools, we identified the main properties for 166 of the 169 Ba stars in the stellar sample. The classifications based on both stellar sets of AGB final abundances show similar distributions, with an average initial mass of M = 2.23 M ⊙ and 2.34 M ⊙ and an average [Fe/H] = –0.21 and –0.11, respectively. We investigated why the removal of Nb, Y, Mo, and La improves our classification and identified 43 stars for which the exclusion had the biggest effect. We found that these stars have statistically significant and different abundances for these elements compared to the other Ba stars in our sample. We discuss the possible reasons for these differences in the abundance patterns.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Functionally discrete fine roots differ in microbial assembly, microbial functional potential, and produced metabolites

Traditionally, fine roots were grouped using arbitrary size categories, rarely capturing the heterogeneity in physiology, morphology and functionality among different fine root orders. Fine roots with different functional roles are rarely separated in microbiome-focused studies and may result in confounding microbial signals and host-filtering across different root microbiome compartments. Using a 26-year-old common garden, we sampled fine roots from four temperate tree species that varied in root morphology and sorted them into absorptive and transportive fine roots. The rhizoplane and rhizosphere were characterized using 16S rRNA gene and internal transcribed spacer region amplicon sequencing and shotgun metagenomics for the rhizoplane to identify potential microbial functions. Fine roots were subject to metabolomics to spatially characterize resource availability. Both fungi and bacteria differed according to root functional type. We observed additional differences between the bacterial rhizoplane and rhizosphere compartments for absorptive but not transportive fine roots. Rhizoplane bacteria, as well as the root metabolome and potential microbial functions, differed between absorptive and transportive fine roots, but not the rhizosphere bacteria. Functional differences were driven by sugar transport, peptidases and urea transport. Our data highlights the importance of root function when examining root-microbial relationships, emphasizing different host selective pressures imparted on different root microbiome compartments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Metal Scrap Upcycling with Shear Assisted Processing and Extrusion (ShAPE)

The overarching objective of this project is to convert metal scraps, such as aluminum, titanium, and other alloys provided by the industry, into extruded tubing, wires, and rods. Upcycling of scrap will be accomplished using Shear Assisted Processing and Extrusion (ShAPE). This approach is a new solution for recycling. The specific aims of this project are as follows: 1. Receive metal scrap under a Material Transfer Agreement (MTA), in the form of billets, from select industry partners that meet the following requirements: outer diameter of 1.245 inches (+/-0.003 inches), inner diameter drilled with a 0.404-inch drill bit, and a length of 4.0 inches (+/-0.01 inches). The billet must be cast or compacted to greater than 98% density. If the industry partner does not have the capabilities to prepare the billets, PNNL can make introductions to third-party entities as needed. Industry partners will also provide a composition analysis as weight percent. 2. Extrude metal scrap via the ShAPE process at PNNL. 3. Evaluate and benchmark the extrudate material properties per the ASTM B557-15 – Testing Tubulars Standard or similar wire and rod standards. 4. Characterize the extrudate microstructure for any of the following: grain size, second phase composition, and texture. Additional testing may include corrosion per the ASTM B117 standard and electro-potential. 5. Deliver specimens to industry partners under an MTA for additional third-party evaluations. Industry partners will, in return, provide a non-proprietary report on any testing, including testing per the ASTM B557-15, ASTM B117, and other industry standards. 6. PNNL will develop data and insights to support intellectual property capture, a published non-proprietary technical report, research collaborations, and commercialization opportunities.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Statistical evaluation of microscale stress conditions leading to void nucleation in the weak shock regime

Here, we investigate the heterogeneity of the stress state driven by anisotropic deformation response at the single crystal level through five statistical volume element (SVE) calculations of polycrystalline BCC tantalum. This work focuses on grain boundaries as a prominent material defect type prone to void nucleation based upon experimental observations of predominantly intergranular void nucleation in this material. The SVEs are constructed to be statistically representative of larger volumes of material and are meshed such that mean and standard deviation of grain size and orientation information is reconstructed. The computational meshes feature hexahedral (brick) elements and smooth conformal grain boundaries where significant stress concentration is known to occur, a tail effect of interest in the extreme events process of dynamic ductile damage. An existing micromechanical crystallographic plasticity model shown to capture the single crystal behavior of BCC tantalum well is used to perform the polycrystal calculations. The model includes representation of the non-Schmid effect of non-planar screw dislocation kinetics in tantalum. A three-dimensional stress state time profile predicted by damage modeling of a flyer plate impact experiment is applied as boundary conditions to each SVE. Resulting grain boundary stress state statistics are strongly non-Gaussian. Significant structural evolution is observed within the compressive hold before unloading into tension in the stress profile. Strong angular dependence of grain boundary traction magnitude with shock direction is observed. Non-Schmid effects continue to suggest their influence on propensity of microstructural defect types to nucleate voids. A general void nucleation criterion is proposed using probability theory. The general framework is specified to polycrystalline BCC tantalum in the weak shock regime to include the SVE calculations and literature molecular dynamics calculations of grain boundary void nucleation strength. Probability density functions (PDFs) are used to describe the interaction between the local stress state heterogeneity and the distributed grain boundary void nucleation strength state. A causation entropy maximization procedure removes the requirement for ad hoc selection of a PDF functional form and provides a rigorous procedure for data-based PDF determination. The resulting physically informed PDF describes the spatial appearance frequency of nucleated voids as a function of applied macroscale pressure. Lower length scale physics are thus packaged in a precise and computationally efficient way to provide computational plasticity insight to macroscale dynamic ductile damage models.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ring Model Development and Validation for Prismatic HTGR Core Thermal-hydraulics and Safety Analysis

Because of the complex core geometry, prismatic high temperature gas-cooled reactors (prismatic HTGRs) often exhibit complex thermal fluid behaviors during both normal operating and transient conditions. Most HTGR designs rely on passive safety system for decay heat removal, such as the reactor cavity cooling system (RCCS). During postulated accidents like Pressurized Conduction Cooldown (PCC) event, the decay heat is first radially transferred from the core region to the reactor vessel outer surface, then to the RCCS cooling panels. The peak fuel temperature is controlled by heat transfer mechanisms with two distinctive characteristic length scales, i.e., the core-wise effective heat conduction and local heat conduction in the fuel pellet scale. As both length scales are essential to determine the fuel temperature, from the modeling perspective, computer codes must be able to capture heat transfer in both scales. This is challenging for both computational fluid dynamics (CFD) tools because of extremely large amount of computation resources required, and for system analysis codes because of the challenge to model the complex core geometry. Under the support of DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, efforts have been pursued to support HTGR technology development and its modeling and simulation needs. There is a particular need for advanced modeling and simulation tools to predict thermal-fluid behavior during safety-related transients. In our previous studies, the ring model was adopted in SAM and further developed to simulate the normal operating condition and a PCC event using the MHTGR-350 design of General Atomics as the reference design. This current work represents a continuation of these previous efforts, and the focus is to critically review and examine simplifications and assumptions made to develop the ring model, and to perform code validation using experimental data from an integral-effect test facility, the High Temperature Test Facility (HTTF) at the Oregon State University. In this study, the test PG-27 from the HTTF test suite was selected for code validation purpose. The test PG-27 is a transient test designed to simulate the PCC event of the MHTGR design. Very good agreements between SAM prediction and experimental measurements were found in both coolant and solid structure temperatures during the transient.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Machining of Alloy 709 Creep-fatigue Specimens from G. O. Carlson Heat

Alloy 709 has been selected as the next candidate material for Section III, Division 5 qualification in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC) for elevated-temperature nuclear construction. The qualification data package requires an assortment of information and material data including tensile, creep, and creep-fatigue performance at elevated temperatures from different material heats. The goal of the project is to generate a dataset to support qualification of Alloy 709 material for ASME BPVC design code. Working towards the project goal, Idaho National Laboratory needs to conduct a series of tests on three different heats to support the A709 code case development. At present, there is a gap in the data package for one of the heats: Heat number 58776 manufactured by G.O. Carlson. To address this data gap, Argonne National Laboratory transmitted five plates of A709 heat 58776 manufactured by G.O. Carlson to Idaho National Laboratory. These plates were solution annealed at 1150°C and heat treated at 775°C for 10 hours. The objective of this specification is to procure a series of creep-fatigue specimens to support the qualification data package. The creep-fatigue specimen design captures the cyclic material performance at elevated temperature. The material performance data generated from specimens machined herein will support the ASME BPVC code case development and establish design limits, and design life curves for Alloy 709 material.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Simulation, Challenge Testing and Validation of Solutions for Residential and Commercial Occupancy Sensing/Counting and CO2 Sensing (Final Report)

Carbon dioxide sensors used for monitoring and control applications in buildings are known to be sensitive to long term drift and can be affected by variations in temperature, humidity, other gas interferents, pressure and other factors that cannot be corrected through the typical auto-calibration methods often embedded in the sensor electronics. This investigation was part of the Category D defined in the ARPA-E Saving Energy Nationwide in Structures With Occupancy Recognition (SENSOR) Financial Assistance Funding Opportunity Announcement No. DE-FOA-0001737, FFDA No. 81.135, January 18, 2017. The FOA defined target criteria for the evaluation of the Category C commercial CO2 sensors selected for review and development through the ARPA-E SENSOR program and charged the Iowa State Category D team with developing an evaluation methodology for Category C sensors in accordance with these criteria. As part of the work, the Iowa State team chose to engage the standards community in the development of the evaluation methodology. Standard development work in the D22.05 Indoor Air and D22.03 Ambient Atmospheres and Source Emissions subcommittees of ASTM International Committee D22 on Air Quality on the evaluation of low cost sensors and provision of guidance for using indoor carbon dioxide concentrations to evaluate indoor air quality and ventilation is of particular relevance to the Category D efforts. To date, three draft standards with specific input by the Iowa State Category D team have passed the subcommittee balloting stage and are being balloted in December 2022 and January 2023 in the main D22 committee. In addition to the aforementioned standards to which the PI was a contributing author, intellectual property developed in this project pertaining to “An Automated System for Evaluation of the Long Term Performance of Carbon Dioxide Sensors” and “An Automated Ground Truth System for Real-Time Reliability Assessment, Capture of Control Decisions and Energy Savings Measurements for Occupancy Recognition Systems and Other Applications” are the other major deliverables of the project. These standards and the developed intellectual property are expected to benefit the public in a number of ways stemming from their provision of means to benchmark the performance of carbon dioxide and other sensor systems. In particular, there is high interest in techniques to demonstrate the performance of low-cost carbon dioxide sensors which can be used for typical HVAC applications (e.g., demand controlled ventilation, outdoor and indoor air monitoring, estimation of occupancy, etc.).

42 ENGINEERING↗
DOE OSTI2021

Application of NEAMS Codes to Capture MSR Phenomena

This report documents work completed in FY21 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program’s Molten Salt Reactor (MSR) Application Drivers activity at Argonne. The common focus was on identifying the modeling and simulation functional requirements for designing, licensing, and operating MSRs and applying those capabilities already developed in NEAMS tools to example problems of interest. The four main parts of this report each focuses on a specific area of simulation physics as it relates to MSR phenomena: fuel evolution, chemistry, computational fluid dynamics (CFD), and systems analysis. In terms of fuel evolution, which includes depletion, decay, on-line separations, and transmutation, the current state of computational capabilities for modeling this behavior in liquid-fueled molten salt reactor is discussed. Some of the functional requirements to accomplish the various applications of MSR fuel depletion modeling are highlighted, followed by a summary of recent approaches and code development activities. The chemistry functional requirements were discussed in the context of several applications of high importance for MSRs, such as corrosion, salt chemistry, and species transport. Each of these types of chemistry modeling have considerable impact on various aspects of reactor applications, including informing on reactor designs, improving operational efficiencies, analyzing safety and reactivity concerns, and estimating the mechanistic source term of the reactor. A brief overview is also provided on code development activities ongoing under NEAMS relevant to chemistry modeling of MSRs. In terms of CFD applications, the state-of-the-art spectral element code, Nek5000 was used to model the fluid dynamics within a full core of the Molten Salt Fast Reactor (MSFR) concept designed as part of the Euratom EVOL project. This concept was selected as the challenge problem because of its similar features to several U.S. industry concepts. The goal was to model some of the fast MSR design challenges, including potential large internal re-circulations, the need of accurate tracking of delayed neutron precursors (DNP), and the lack of relevant thermal-hydraulics models/correlations, etc. Therefore, a series of CFD models were created for the MSFR core cavity using a k – τ model two-equation model for the turbulence. These first full core results demonstrated that any potential recirculation zones could be properly identified with the current NEAMS CFD capabilities. The development of these models will also set the stage for future testing of Nek5000’s functionalities to model other MSR thermal-fluid phenomena. Lastly, the validation of SAM against experimental data from the Molten Salt Reactor Experiment, which started in FY19, continues with the inclusion of modeling the reactivity insertion tests. This involved using SAM and its point kinetics model for flowing fuel salt to recreate the time dependent power changes and response after positive reactivity insertions at the 1, 5, and 8 MWt power levels. Through these exercises, several code modifications were suggested to the SAM development team and accommodated to enable closer agreement with solid technical and physical justifications. These include adding a moderator reactivity feedback coefficient as an available input and modifying the solution approach for the point kinetics model. Additional SAM development suggestions for flowing fuel MSRs include adding the capability to allow the moderator power change proportionally with the reactor power and enabling specification of the power and DNP distributions separately.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Non-equilibrium plasma co-upcycling of waste plastics and CO 2 for carbon-negative oleochemicals

Mechanical recycling and chemical upcycling by thermochemical reactions have been the major approaches for recycling end-of-life plastics. Herein, we report an electrified approach to upcycle waste plastics into carbon-negative commodity chemicals using greenhouse gas CO 2 as the oxidant and additional carbon source. In this non-equilibrium plasma process, waste polyolefins were oxidatively depolymerized by plasma-activated CO 2 to produce oleochemicals and hydrocarbon chemicals in a single-step process at high reaction rates. In addition, a mixture of CO 2 and a small amount of O 2 was employed as plasma gases to selectively produce fatty alcohols from polyolefins. Based on this atmospheric pressure, non-solvent, and non-catalyst process, up to 97.6% of fatty alcohols could be produced within minutes. In this article, the co-conversion approach was demonstrated using common polyolefins and real-world mixed waste plastics to obtain comparable results. The techno-economic analysis estimates the internal rate of return to be 42.2% and 43.5% for the plasma-based conversion of waste plastics, depending on the plasma gas composition. Lifecycle assessment indicates the global warming potential is between −3.33 and −3.07 kg CO 2e per kg of plastic.

42 ENGINEERING↗
DOE OSTI2021

VirION2: a short- and long-read sequencing and informatics workflow to study the genomic diversity of viruses in nature

Microbes play fundamental roles in shaping natural ecosystem properties and functions, but do so under constraints imposed by their viral predators. However, studying viruses in nature can be challenging due to low biomass and the lack of universal gene markers. Though metagenomic short-read sequencing has greatly improved our virus ecology toolkit—and revealed many critical ecosystem roles for viruses—microdiverse populations and fine-scale genomic traits are missed. Some of these microdiverse populations are abundant and the missed regions may be of interest for identifying selection pressures that underpin evolutionary constraints associated with hosts and environments. Though long-read sequencing promises complete virus genomes on single reads, it currently suffers from high DNA requirements and sequencing errors that limit accurate gene prediction. Here we introduce VirION2, an integrated short- and long-read metagenomic wet-lab and informatics pipeline that updates our previous method (VirION) to further enhance the utility of long-read viral metagenomics. Using a viral mock community, we first optimized laboratory protocols (polymerase choice, DNA shearing size, PCR cycling) to enable 76% longer reads (now median length of 6,965 bp) from 100-fold less input DNA (now 1 nanogram). Using a virome from a natural seawater sample, we compared viromes generated with VirION2 against other library preparation options (unamplified, original VirION, and short-read), and optimized downstream informatics for improved long-read error correction and assembly. VirION2 assemblies combined with short-read based data (‘enhanced’ viromes), provided significant improvements over VirION libraries in the recovery of longer and more complete viral genomes, and our optimized error-correction strategy using long- and short-read data achieved 99.97% accuracy. In the seawater virome, VirION2 assemblies captured 5,161 viral populations (including all of the virus populations observed in the other assemblies), 30% of which were uniquely assembled through inclusion of long-reads, and 22% of the top 10% most abundant virus populations derived from assembly of long-reads. Viral populations unique to VirION2 assemblies had significantly higher microdiversity means, which may explain why short-read virome approaches failed to capture them. These findings suggest the VirION2 sample prep and workflow can help researchers better investigate the virosphere, even from challenging low-biomass samples. Our new protocols are available to the research community on protocols.io as a ‘living document’ to facilitate dissemination of updates to keep pace with the rapid evolution of long-read sequencing technology.

Long-reads↗
DOE OSTI2022

Gasification of Coal and Biomass: The Route to Net-Negative-Carbon Power and Hydrogen

One promising process that is a candidate for meeting the goals of the US Department of Energy’s 21st Century Power Plant initiative is to gasify a mixture of coal and biomass to yield a syngas, which can have CO2 removed and then be used to produce hydrogen as well as an off-gas that can be used to flexibly produce power. This concept would overall be carbon net-negative and readily meet the 21st Century Power Plant initiative targets of smaller scale MW generation, high ramp rates and turndown, feedstock flexibility, and high efficiency—at a reasonable cost. Moreover, adding the large-scale production of “ultra-green” hydrogen yields a system tailored for the coming hydrogen economy, providing long-term energy storage and an attractive co-product for sale. The objective of the work being led by the Electric Power Research Institute, Inc. (EPRI), with support by Bechtel Corporation (Bechtel), Gas Technology Institute (GTI), Hamilton Mauer International, Inc. (HMI), Nebraska Public Power District (NPPD), NexantECA, Inc. (Nexant), and Wärtsilä, is to perform a front-end design and engineering (FEED) study on an oxygen-blown gasification system coupled with water-gas shift, pre-combustion CO2 capture, and pressure-swing adsorption working off a coal/biomass mix to yield high-purity hydrogen and a fuel off-gas that can generate power. Several designs are being considered that will be capable of producing 50 MW net from a flexible generator, over 8500 kg/hr of hydrogen, and net-negative CO2 emissions, at an efficiency of 50% net HHV. The plant would be hosted at an NPPD site, where opportunities for enhanced oil recovery and sequestration have been investigated and the need for low-carbon power and hydrogen is imminent. The principal biomass to be used is corn stover—prevalent in Nebraska where the plant will be located—mixed with Powder River Basin (PRB) coal, necessitating a gasifier that can use this feedstock and be flexible to allow other types. Waste plastics will also be reviewed for use. Two oxygen-blown gasifiers have been identified as candidates that have done testing with biomass including corn stover: the GTI gasifier—a high-pressure, fluidized-bed type—and HMI’s, a lower pressure moving-bed type. Both have relative advantages that are being investigated in the Phase I design study, with a resultant down select of one system for which the FEED will be performed in Phase II. The technical tasks for the proposed project are: • Design Development: Completion of design activities necessary to provide inputs for the FEED study. Multiple design cases will be assessed with the selection of the optimal one for the FEED. • Investment Case Preparation: Development of the draft investment case for the proposed process with business cases performed for the proposed host site and two other locations. • Host Site Selection: Evaluation of the two potential host sites within NPPD’s portfolio to select the preferred candidate based on technical, economic, and environmental considerations. • Environmental Information Volume (EIV) Development: Completion of the EIV for the host site. • FEED Study: Completion of a FEED study based on the design selected in Phase I. A Greenhouse Gas Life Cycle Analysis will also be performed for the process. • Update Investment Case: Finalization of the investment case based on findings from the FEED. The advantages of the proposed project are significant. Having an engaged U.S. power utility willing to provide a host site that will produce energy from coal plus a deep and experienced team is critical; the process meets all the goals of DOE’s 21st Century Power Plant initiative at an estimated total plant cost of ~$880M and a production cost of hydrogen of ~$2/kg-H2 while producing net-negative carbon power. If developed, this process has real commercial potential in the United States—supported by EPRI’s initial review of the considerable interest from selected U.S. utilities—and elsewhere around the globe. The process has fewer environmental hurdles compared to other concepts, lowering regulatory and protest risks—providing a pathway to preserving the viability of a critical indigenous energy source by transforming its use to match a changing world. This presentation will outline the motivation for the effort, summarize project plans, work completed to date, results of the Design Development task, and detailed work scope for the remainder of the project.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Assessment of oil and gas fields in California as potential CO 2 storage sites

California's total annual greenhouse gas (GHG) emissions (425.3 MtCO 2 e) in 2018 were about 6.4% of the US total (6,677 MtCO 2 e) and around 1% of global emissions. About 39% of 2018 GHG emissions in California were from the industrial and electrical sectors. Many of these emissions were from large stationary point sources and were suitable for carbon capture retrofit with subsequent storage of the captured carbon dioxide (CO 2 ) in geological formations. Previous studies of California found suitable geology and CO 2 storage resource. This study refines and furthers prior work using a three-stage screening process of oil fields, gas fields, and underground natural gas storage (UGS) sites by combining criteria from previous studies while excluding sites that pose technical risk or are located in regions with surface restrictions including sensitive habitats and dense populations. In the first stage, 129 CO 2 storage sites in California were identified using qualification criteria based upon formation properties including geological conditions and pore pressure. The second stage identified sensitive sites by applying conservative screens including seismic activity, faulting, population density, restricted lands, and sensitive habitats. During the third stage, 61 CO 2 potential storage sites were identified by subtraction of stage 2 areas from stage 1. The potential storage volume in the third stage ranged from 1.0 to 2.0 GtCO 2 . Finally, we applied a scoring system with seven parameters to rank the 61 potential sites based on subsurface technical criteria. The scored sites are classified as high priority, medium priority, and sites for future study. Prospective CO 2 storage sites with high and moderate priority were selected and linked to CO 2 sources. There are 14 prospective sites (above 20 MtCO 2 storage resource per site) with a total storage resource of 1024 MtCO 2 distributed in Northern and Southern California. Of these sites, there are 9 potential CO 2 -EOR sites and 1 depleted oil field with a total estimated CO 2 storage volume of ~800 MtCO 2 in the Southern San Joaquin and Ventura Basin. These 10 prospective sites with a storage resource greater than 20 MtCO 2 could potentially deliver more than 20 years of storage with an average injection rate of 40 MtCO 2 /year. The remaining 4 highly prospective sites are in Northern California. Additionally, study results suggest that saline formations should be re-evaluated in concert with storage in oil, gas, and natural gas storage reservoirs.

58 GEOSCIENCES↗
DOE OSTI2023

Strategies to overcome mass transfer limitations of hydrogen during anaerobic gaseous fermentations: A comprehensive review

Fermentation of gaseous substrates such as carbon dioxide (CO 2 ) has emerged as a sustainable approach for transforming greenhouse gas emissions into renewable fuels and biochemicals. CO 2 fermentations are catalyzed by hydrogenotrophic methanogens and homoacetogens, these anaerobic microorganisms selectively reduce CO 2 using hydrogen (H 2 ) as electron donor. However, H 2 possesses low solubility in liquid media leading to slow mass transport, limiting the reaction rates of CO 2 reduction. Solving the problems of mass transport of H 2 could boost the advance of technologies for valorizing industrial CO 2 -rich streams, like biogas or syngas. The application could further be extended to combustion flue gases or even atmospheric CO 2 . In this work, an overview of strategies for overcoming H 2 mass transport limitations during methanogenic and acetogenic fermentation of H 2 and CO 2 is presented. Here, the potential for using these strategies in future full-scale facilities and the knowledge gaps for these applications are discussed in detail.

09 BIOMASS FUELS↗
DOE OSTI2023

Assessment of an E10 gasoline surrogate: Qualitative and quantitative comparisons of in-cylinder spray morphology

A minimum-component gasoline fuel surrogate that captures both chemical and physical behaviors of a full-distillate fuel is needed for high-fidelity CFD simulations. This study evaluates gasoline spray characteristics in a direct-injection spark-ignition engine under motored operation. Two fuels are compared; PACE-20, which is a 9-component surrogate formulation of RD5-87, is compared with its target fuel RD5-87, which is a full-boiling range research grade E10 gasoline. The spray morphologies of both fuels are recorded for a centrally-located direct-injection 8-hole spray subject to intake air cross-flow during the early part of the intake stroke. High-speed imaging recorded scattered light of the side and axial projections of the liquid spray. Quantitative metrics were developed and employed to facilitate comparison of spray morphologies as well as to identify the transition in spray morphology due to flash boiling. This paper builds on a previous study of RD5-87 where coolant temperature (20°C–100°C), in-cylinder pressure (40–110 kPa), engine speed (650–1950 rpm), and injection pressure (60–180 bar) were systematically changed to span operating conditions with and without flash boiling. Images of the PACE-20 morphology are selected for a sub-set of operating conditions from the previous study where distinctive morphology changes occurred. Visual inspection of the images and quantitative metrics demonstrate that the PACE-20 spray morphology is equivalent to that of the RD5-87 in most cases. The exception was for changes in the ambient-gas pressure where the flash-boiling transition occurred at ∼5 kPa higher in-cylinder pressure for PACE-20. Three empirical metrics, Merging Index, Asymmetry, and Flash Index are proposed here and they were found to be useful both as quantitative comparisons of the fuel morphologies, and for identifying the transition in spray morphology due to flash boiling.

Kim, Namho↗
DOE OSTI2021

Robust implementation of generative modeling with parametrized quantum circuits

Although the performance of hybrid quantum-classical algorithms is highly dependent on the selection of the classical optimizer and the circuit ansätze, a robust and thorough assessment on-hardware of such features has been missing to date. From the optimizer perspective, the primary challenge lies in the solver’s stochastic nature, and their significant variance over the random initialization. Therefore, a robust comparison requires one to perform several training curves for each solver before one can reach conclusions about their typical performance. Since each of the training curves requires the execution of thousands of quantum circuits in the quantum computer, such a robust study remained a steep challenge for most hybrid platforms available today. In this work, we leverage on Rigetti’s Quantum Cloud Services (QCS™) to overcome this implementation barrier, and we study the on-hardware performance of the data-driven quantum circuit learning (DDQCL) for three different state-of-the-art classical solvers, and on two-different circuit ansätze associated to different entangling connectivity graphs for the same task. Additionally, we assess the gains in performance from varying circuit depths. To evaluate the typical performance associated with each of these settings in this benchmark study, we use at least five independent runs of DDQCL towards the generation of quantum generative models capable of capturing the patterns of the canonical Bars and Stripes dataset. In this experimental benchmarking, the gradient-free optimization algorithms show an outstanding performance compared to the gradient-based solver. In particular, one of them had better performance when handling the unavoidable noisy objective function to be minimized under experimental conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Theory and Simulation of Ultrafast Multidimensional Nonlinear X-ray Spectroscopy of Molecules (Final Report)

Emerging X-ray free electron laser (XFEL) beam sources offer new types of probes of matter with unprecedented spatial and temporal resolutions. These experimental advances must be met by robust theoretical and computational tools that provide predictive modeling capacity of the underlining electronic and structural dynamics. The latter will be essential for the design of sophisticated multi-pulse experiments and for their interpretation. The proposed research effort will focus on developing cutting- edge simulation tools for nonlinear multidimensional X-ray/optical spectroscopies and aims to address key questions in Priority Research Opportunities 1 (Probing and controlling electron motion within a molecule) and 3 (Capturing rare events and intermediate states in the transformation of matter) as mentioned in the BES Roundtable Report “Opportunities for Basic Research at the Frontiers of XFEL Ultrafast Science”. XFEL multidimensional nonlinear techniques, which combine sequences of X-ray and possibly optical pulses, provide a unique experimental toolbox for probing the dynamics of core and valence electronic excitations, as well as material structure. Predictive modeling of these dynamical processes requires the combination of analytical theory for nonlinear interactions of light and matter, robust quantum-chemical methodologies for the accurate description of electronic structure of various materials, and multiscale ab initio electron and nuclear dynamics techniques operating beyond Born-Oppenheimer approximation. These challenges will be addressed with three research thrusts (i) Develop and implement theoretical apparatus for modeling a broad range of multidimensional spectroscopic techniques enabled by present and upcoming XFEL facilities. This thrust also includes the incorporation of a computational module in the DOE supported open-source NWChem computational chemistry package as well as the development of other open-source codes ready for dissemination across a broad user base; (ii) Propose and design new multi-pulse experiments that make use of the capabilities of the incoming LCLS-II facility; (iii) Perform selected applications to specific molecular systems that can be carried out at LCLS-II and demonstrate how these X-ray sources may be used to study nonadiabatic dynamics through conical interactions, electronic correlations in multi-core excitons, and charge transfer/energy transfer processes. The proposed research will be carried out by a multi-disciplinary four-institution research team which combines academia and national laboratories and spans the broad and necessary expertise in theoretical spectroscopy, nonlinear optics, quantum chemistry, molecular non-adiabatic dynamics and code development. The work will be performed in a highly interactive team environment with junior researchers shared between institutions thus cementing cross- disciplinary interactions. The developed simulation tools will be immediately deployed for XFEL facility users, both experimentalists and theorists, via freely distributed codes and databases. Altogether, this project will facilitate establishing XFEL-based multidimensional spectroscopies as a novel diagnostic tool for monitoring electronic and structural dynamics in molecular materials.

74 ATOMIC AND MOLECULAR PHYSICS↗