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At least 1,333 records · Page 74

GEOS: A performance portable multi-physics simulation framework for subsurface applications

GEOS is a simulation framework focused on solving tightly coupled multi-physics problems with an initial emphasis on subsurface reservoir applications. Currently, GEOS supports capabilities for studying carbon sequestration, geothermal energy, hydrogen storage, and related subsurface applications. The unique aspect of GEOS that differentiates it from existing reservoir simulators is the ability to simulate tightly coupled compositional flow, poromechanics, fault slip, fracture propagation, and thermal effects, etc. Extensive documentation is available on the GEOS documentation pages (GEOS Documentation, 2024). Note that GEOS, as presented here, is a complete rewrite of the previous incarnation of the GEOS referred to in (Settgast et al., 2017).

58 GEOSCIENCES↗

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗

Assessing the Long-Term Stability of Anion Exchange Membranes for Electrochemical CO 2 Reduction

Materials and cell components used in CO 2 electrolysis have largely been adapted from technologies initially developed for water electrolysis and fuel cells. However, electrochemical CO 2 reduction introduces distinct material challenges due to the unique chemical environment in this process. Here, in this study, we conducted ex-situ 1000 h stability tests on commonly used anion exchange membranes, exposing them exclusively to electrolytes and organic molecules used or produced during CO 2 electrolysis, at concentrations relevant to and compatible with postseparation processes. Notably, 15% w/w n-propanol and 5 M acetic acid caused complete dissolution or partial disintegration of the membranes unless cross-linking was present and remained stable throughout the test. When the membranes stayed physically intact, most of them exhibited excellent chemical stability in alkaline medium containing alcohols or formic acid, which was confirmed by vibrational spectroscopy and ion exchange capacity measurements. However, exposure to alcohol-and acid-containing solutions led to a substantial increase in swelling and water uptake, with potential implications for mechanical stability, ion/product crossover, and compression management of adjacent components. The potential effects of CO 2 electroreduction products on membrane stability, their subsequent impact on electrolyzer performance, and mitigation strategies are discussed.

CO2RR↗

Performing a multi-unit level-3 PSA with MACCS

MACCS (MELCOR Accident Consequence Code System), WinMACCS, and MelMACCS now facilitate a multi-unit consequence analysis. MACCS evaluates the consequences of an atmospheric release of radioactive gases and aerosols into the atmosphere and is most commonly used to perform probabilistic safety assessments (PSAs) and related consequence analyses for nuclear power plants (NPPs). WinMACCS is a user-friendly preprocessor for MACCS. MelMACCS extracts source-term information from a MELCOR plot file. The current development can combine an arbitrary number of source terms, representing simultaneous releases from a multi-unit facility, into a single consequence analysis. The development supports different release signatures, fission product inventories, and accident initiation times for each unit. The treatment is completely general except that the model is currently limited to collocated units. A major practical consideration for performing a multi-unit PSA is that a comprehensive treatment for more than two units may involve an intractable number of combinations of source terms. This paper proposes and evaluates an approach for reducing the number of calculations to be tractable, even for sites with eight or ten units. The approximation error introduced by the approach is acceptable and is considerably less than other errors and uncertainties inherent in a Level 3 PSA.

42 ENGINEERING↗

Negative Muon Count for the FNAL Muon g-2 Experiment

The primary goal of the FNAL Muon g-2 Experiment, located in Batavia, IL, USA, is to measure the anomalous magnetic dipole moment, a μ = (g-2)/2, of a muon to a precision of 0.14 ppm. Initial results from the experiment confirm a discrepancy between the experimental value of the muon anomaly compared with the theoretical value first discovered by the Brookhaven Muon g-2 Experiment in 2001. This discrepancy hints at new physics. However, running the experiment with negative muons is essential in order to verify the experimental value of the muon anomaly. As neither experiments nor simulation studies pertaining to the muon anomaly have been performed with negative muons, the goal of this work is to estimate the rates of negative muons arriving at the FNAL Muon g-2 experiment so that scientists can estimate the time required to run the experiment with negative muons. In order to do this, we performed several simulations of the Muon Campus, which delivers muons to the FNAL Muon g-2 Experiment, using the G4Beamline v. 3.06 at the National Energy Research Computing Center. We performed separate simulations for different sections of the muon campus, and simulations were repeated twice, once for negative muons and once for positive muons. An initial 10 9 protons were shot on target for both the negative and positive muon simulations. We found that the rate of negative muons arriving at the experiment was 0.549 times the rate of positive muons arriving at the experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A direct numerical simulation of Jet A flame kernel quenching

The safe operation of aeronautical engines requires an understanding of flame ignition, propagation and extinction. In this study, direct numerical simulations are performed using a 29 species reduced chemical mechanism for jet fuel surrogate Jet A to understand the flame quenching process. Here, initially laminar spherical flames of varying sizes and equivalence ratios are subject to an identical periodic domain of decaying and isotropic high intensity turbulence with a turbulent Reynolds number of 2400. All cases become quenched, except for the larger kernel with lower Karlovitz number. An analysis of the flame structure shows broadened preheat zone, flame shortening on the product side, differential species diffusion and partial fuel pyrolysis in the fresh mixture. Two extinction mechanisms are identified arising from flame shortening and high flame stretch. Flame shortening occurs due to turbulence-chemistry interactions that resemble the flame–flame interaction in a laminar counterflow reactant-to-reactant configuration, which contorts and breaks up the ignition kernel. Flame stretch is a local effect that attenuates the heat release rate and causes the flame to retreat towards the product mixtures, similar to what has been observed for reactant-to-product laminar counterflow flames. Chemical explosive mode analysis was also performed to quantify the flame structure and local combustion mode. The diffusion–reaction balance in pinched-off flame islands favors extinction of these smaller structures, while auto-ignition modes are observed within the flame kernel after fresh mixture is engulfed and preheated in the product kernel. Statistics of the density-weighted displacement speed conditional on local combustion mode indicates strong correlation between the local extinction mode and negative displacement speed. The local balance between diffusion and reaction ultimately determines the propensity for local extinction in both laminar and turbulent flames, the extent of which has an impact on global flame propagation.

42 ENGINEERING↗

Quasi-static to Dynamic Response and Microstructure Development of Tantalum-Tungsten Alloys

Lawrence Livermore National Laboratory (LLNL) has a need to understand the quasi-static to dynamic mechanical response and microstructure evolution of tantalum-tungsten (Ta-W) alloys made by conventional wrought processing and additive manufacturing (AM). This two-year work scope will be performed at the Colorado School of Mines (Mines) and will include quasi-static (e.g., 10 -3 s -1 ) mechanical testing in tension and compression, along with high strain rate (Kolsky) pressure bar testing in tension and compression (e.g., 10 3 s -1 ), without and with temperature variations. Gas gun experiments at higher strain rates (e.g., over 10 3 s -1 ) will also be pursued. Complementary microstructure characterization will be performed on undeformed and deformed samples to fundamentally understand the role of processing on the microstructure characteristics and resulting deformation mechanisms that dictate the mechanical response of these alloys with variations in strain rate, temperature, and strain state. Alloys of interest will be Ta-based, containing up to 10 wt.% W. LLNL will supply initial wrought-processed material for sample machining. LLNL will also supply samples built by AM during the project for testing. Arc melting and casting may also be performed at Mines to produce small quantities of different alloys for machining and exploratory testing on an as-needed basis. This project will support multiple postdocs and graduate students at Mines, training them with the knowledge, skills, and abilities needed to study materials under extreme conditions of interest to the National Nuclear Security Agency.

36 MATERIALS SCIENCE↗

Geant4-based Analysis of Faraday Cup Performance for PIP-II Laser Wire Scanner System

The Proton Improvement Plan-II (PIP-II) accelerator upgrade at Fermilab marks a significant advancement in high-energy physics research. This initiative aims to enhance Fermilab's accelerator complex by replacing the existing linear accelerator (linac) with a warm front end (WFE) capable of accelerating H- beams up to 2.1 MeV. Subsequently, a superconducting linac (SCL), that further accelerates these beams up to 800 MeV. To accurately measure the transverse beam profile, traditional wire scanners will be utilized in the WFE section, while Laser wire scanners will be implemented along the SCL. The Faraday cup for the Laser wire scanners has been designed using the GEANT4 simulation toolkit. This poster presents a detailed analysis of its performance along the SCL, focusing on electron absorption, secondary electron emission, backscattering, etc.

Wijethunga, S. A.K.↗

Sub-pilot-scale Production of High-Value Products from U.S. Coals

Investigators from the University of Utah, University of Wyoming and Marshall University pursued a program to study the conversion of raw coal to high-value products of carbon fiber and silicon carbide. Team members also developed an initial framework for a data portal that can incorporate laboratory data on coal processing and product quality, and also work with tools for machine learning for data analysis, data visualization and economic assessment. Experimental R&D efforts focused on the conversion of raw coal to coal tar and other byproducts, and the resulting tar intermediates were upgraded to form anisotropic and isotropic pitch materials. These pitch materials were produced from coal using both thermal (pyrolysis) and chemical (mild solvolysis liquefaction) decomposition of raw coal. Four different coals were studied: Utah bituminous coal (Sufco), Wyoming PRB coal (Black Thunder), Illinois bituminous coal (Illinois #6), and West Virginia bituminous coal (Flying Eagle). Both metallurgical-grade coking coals and lower-grade steam coals were investigated, and controlled secondary gas-phase reactions were used during a two-stage pyrolysis process to induce cracking and condensation reactions among the pyrolytic tar species. This approach successfully improved the performance of the lower grade coals for yielding pitch materials, with properties more consistent with a commercial-grade pitch that had previously demonstrated success for quality carbon fiber production. The use of waste plastic materials was also studied, to help improve physical and chemical characteristics of the intermediate tars and final pitch product; in particular, for lowering the pitch softening point to an acceptable level for melt spinning carbon fiber. Mild solvolysis liquefaction was also used as a method for producing pitch for carbon fiber production. As expected, significantly higher pitch yields were obtained using this approach, and waste plastic materials were also successfully used to reduce pitch softening point to an acceptable level. The plastic materials were also utilized to create a solvent for the mild solvolysis process, and this plastic-derived solvent was shown to provide results consistent with more expensive commercial chemical solvents, and could thus avoid the need for costly recovery and recycle of a liquefaction solvent. Additional experimental R&D focused on the production of silicon carbide (β-SiC) from the residual char byproduct from pitch production, and also on the production of carbon fiber from the anisotropic pitch. SiC was successfully synthesized using a mixture of residual char and sandstone at a ratio of 1:1. Reaction temperature and residence time were optimized and yielded a product purity of 81%. For carbon fiber production, the most successful pitch samples were obtained from the mild solvolysis liquefaction approach, combined with the use of a plastic (HDPE)-derived solvent. Fiber properties improved over time as laboratory fiber production methodologies improved, and final yields of carbon fiber were obtained with a diameter of 12.14 ± 1.10 um, Modulus of 173.73 ± 15.25 GPa, and Tensile Strength of 1.04 ± 0.10 GPa. A proof-of-concept Modern Community Research Data Portal (MCRDP) was developed and deployed for coal and coal-derived pitch characterization, with the full support of (i) remote web-based access, (ii) distributed analysis, (iii) interactive visualization and exploration, (iv) shared and long-term data access, (v) advanced query capabilities and (vi) real-time collaboration. The Coal to Products Data Portal “coaltoproducts.org” provides researchers with space to store and share data within a project, tools for analyzing and understanding data for scientific investigation, and the ability to publish data to the broader community for reproducibility. The portal leverages the Material Commons 2.0 (MC) platform developed by the Center for PRedictive Integrated Structural Materials Science (PRISMS) of the University of Michigan, to achieve long-term longevity of data collections and, more importantly, collaborative science. A number of data visualization tools were also assessed and implemented for interrogating the experimental and modeling data. The machine learning portion of this project analyzed datasets from two different coal conversion processes performed on a diverse set of coal samples from both the coal pyrolysis experiments and the solvent liquefaction experiments. The work was initiated by exploring standard regression models on the pyrolysis data, aiming to understand the impact of sample characteristics and processing conditions on key product metrics. Over the course of the project, the focus expanded to include a variety of machine learning tools, delving into both supervised and unsupervised learning methods. Models tested on the pyrolysis data included linear, ridge, lasso, elastic-net, Gaussian process, random forest regression, and AutoSklearn, and the approach was continually refined to enhance predictive accuracy and model interpretability. Similar techniques were applied to the liquefaction data with an additional focus on feature engineering. Along with mesophase content, additional outputs of interest were the pitch yield, softening point, and QI content. Insights derived from these analyses are crucial in determining the factors influencing the quality and yield of coal-derived products. As the work progressed, the research evolved from foundational model comparisons to analyses of random forests, decision paths, and feature importance scores. A thorough market analysis was performed to examine the prospects of coal-based carbon fibers. The best opportunities for coal come from its lower and more stable price relative to petroleum, particularly for subbituminous coals, which is the primary advantage that a coal refinery may have over a petroleum refinery. Before a commercial CTP production facility can be modeled, however, several things need to be understood regarding the nature of the would-be coal refinery. These include the technology to be deployed, the size of facility, the volume(s) of co-product(s), and the waste and emissions profile of the plant. The volume of co-products and waste may be substantial and will require separate market analysis to ensure viability. In the near-term, the importance of coal tar pitch, in the form of carbon pitch, to the aluminum and steel industries is likely to overshadow the alternative use of this material as an input for carbon fiber. The importance of steel and aluminum in building materials, and the need for carbon materials in their manufacturing, will ensure that demand for these products remains for the long run. In addition, carbon fiber may also be the best substitute for steel and aluminum well into the future. While society will eventually be able to shift production of much of its electricity needs to renewables, it will not be able to shift away from fossil fuels for production of high-strength construction and vehicular materials. Demand for carbon fiber is expected to increase quickly, but the volume of carbon fiber and the amount of coal that would be needed to produce even a sizeable share of this market may still be relatively small compared to current coal production. Thus, other coal-based products like graphene, graphite, carbon foams, resins, and carbon-based building products will play important roles in sustaining coal production as coal-fired power generation continues to decline.

01 COAL, LIGNITE, AND PEAT↗

FEED Study of Carbon Capture Inc. DAC and CarbonCure Utilization Using United States Steel's Gary Works Waste Plant

Direct Air Capture (DAC) has been proposed as a means of reducing atmospheric concentrations of CO2. While DAC has been evaluated through lab-scale, bench-scale, and small-scale pilot units, large-scale deployment has not been achieved. Feasibility studies are one tool to understand the potential design, operation, performance, and impact of commercial-scale DAC. This paper presents the results of a feasibility study for a passive DAC system deployed at >100,000 tpy scale in three different regions across the U.S. and awarded to Carbon Collect by the U.S. Department of Energy National Energy Technology Laboratory (DOE NETL). The MechanicalTree™technology has been designed and engineered by Carbon Collect based on the concept initially developed at Arizona State University Center for Negative Carbon Emissions. It uses a tower of stacked, sorbentcontaining disks supported by a lifting mechanism, exposed to the air to capture CO2 during the adsorption phase. The disks are then lowered into a regeneration chamber for vacuum and steam regeneration to produce CO2 product during the desorption step. The modular tree design allows large installations with repeatable, mass-manufactured units connected to common utilities such as steam supply, vacuum, and CO2 processing for compression and geologic storage. The passive DAC system eliminates the equipment and energy of forced air fans by using natural air circulation to contact the sorbent with the CO2 in the air. Because of this, the performance is dependent on the wind speed in addition to the temperature and relative humidity. Performance and flow rate fluctuations were incorporated into equipment and facility design with considerations for turndown to 10% of maximum rated flow to allow operation in all seasons. The feasibility study was undertaken to evaluate the technology in different regions and climates. Three locations were selected for this study representing different climates: Alabama (hot and humid), California (hot and arid), and Wyoming (continental). For each region, the adsorption/desorption cycle was optimized including tuning the heat integration and cycle timings. The performance of individual trees was then scaled to the full facility with the same design of more than 20,000 trees common between all regions. The installations had expected average CO2 capture rates of between 330,000 and 485,000 tonnes of CO2 per year depending on the climate. The initial engineering design for the facility at each location was performed with cost and performance estimates for the trees, carbon purification and compression, and the balance of plant. To supply thermal and electrical energy for the facility, carbon-free or low-carbon power must be considered. Options for low-carbon, continuous thermal and electrical energy were considered. The best-performing option from those considered was identified to be an electrically-heated molten salt energy storage system, powered by an on-site photovoltaic field. During molten salt thermal discharge, steam is produced from heat exchange with the molten salt and used to generate power in a steam turbine as well as steam for regenerating the DAC carbon trees. The thermal and electrical supply and analysis is presented in the context of low-carbon power for carbon removal. Modelling and economics of transportation and geologic storage of the CO2 is considered and presented for each location. The results of the feasibility study are incorporated into the presented techno-economic and life-cycle assessments. This work is intended to provide an understanding of the performance, cost, and impact of capturing CO2 at the commercial scale and the impact of climate and regional siting on the considered passive DAC system.

42 ENGINEERING↗

Baselining Activity and Stability of ORR Catalysts and Electrodes for Proton Exchange Membrane Fuel Cells for Heavy-Duty Applications

Activity and stability of electrodes with Pt and PtCo alloy catalysts supported on high surface area carbon, hereafter to as a-Pt/C and d-PtCo/C, were evaluated for heavy-duty applications. Both catalysts had nearly identical Pt loading (50-wt% Pt on carbon and 0.25 mg Pt cm −2 ) and had undergone thermal treatment to stabilize them by growing the average particle size to 4–5 nm. Both were subjected to 90,000 (90 k) standard accelerated stress tests (AST) cycles consisting of 0.6–0.95 V square wave potentials, 3-s hold at upper and lower potential limits in H 2 /N 2 at 1.5 atm, 80 °C and 100% RH. Test protocols were developed to monitor the performance losses and characterize them in terms of activity for the oxygen reduction reaction (ORR), oxygen transport in the electrode and proton transport in the membrane and cathode catalyst layer. Despite the nearly double initial ORR activity, the PtCo/C electrode degraded faster due to the leaching of Co from the catalyst that had started even before the imposition of the AST potential cycles. Commensurate with Co leaching, Co poisoning of ionomer is responsible for the inferior performance of d-PtCo/C electrode at high current densities both before and after AST.

30 DIRECT ENERGY CONVERSION↗

Effects of Port Angle on Scavenging of an Opposed Piston Two-Stroke Engine

Opposed-piston 2-stroke (OP-2S) engines have the potential to achieve higher thermal efficiency than a typical diesel engine. However, the uniflow scavenging process is difficult to control over a wide range of speeds and loads. Scavenging performance is highly sensitive to pressure dynamics, port timings, and port design. This study proposes an analysis of the effects of port vane angle on the scavenging performance of an opposed-piston 2-stroke engine via simulation. A CFD model of a three-cylinder opposed-piston 2-stroke was developed and validated against experimental data collected by Achates Power Inc. One of the three cylinders was then isolated in a new model and simulated using cycle-averaged and cylinder-averaged initial/ boundary conditions. This isolated cylinder model was used to efficiently sweep port angles from 12 degrees to 29 degrees at different pressure ratios. Results indicate that scavenging performance is correlated with the bulk swirl ratio generated by these port angles. Scavenging performance is also sensitive to the pressure ratio across the engine. It was concluded that, for a given pressure ratio, the smallest port angle produces the best scavenging; however, previous work indicates lower bulk swirl ratio during combustion can have an impact on emissions formation.

33 ADVANCED PROPULSION SYSTEMS↗

ORNL_AISD_NiNb

This dataset describes the nickel-niobium solid solution binary alloy, where the two constituent elements nickel (Ni) and niobium (Nb) are randomly placed on an underlying crystal lattice. This dataset for nickel-niobium (Ni-Nb) alloys available includes the formation energy and bulk modulus for each crystal structure. Each atomic sample has a disordered phase which is obtained starting from an initial regular crystal structure of type body-centered cubic (BCC), face-centered cubic (FCC), or hexagonal compact packed (HCP). The geometry optimization ensures that all the alloy samples reached the equilibrium with negative formation energy. We perform geometry optimizations using the LAMMPS simulation package [1], a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. We utilized the embedded atom model (EAM) potential for Ni and Nb developed in a previous study [2]. The potential could describe behaviors of the liquid and solid phases of Ni-Nb alloy. The structural factors and angular distributions of three atoms are well-matched with X-ray and ab initio-based molecular dynamics data. We prepared the three different crystals with different initial lattice parameters (3.52 Ã… for FCC, 3.32 Ã… for BCC, and 3.5 Ã… for HCP). We performed energy minimization in two steps. Firstly, we minimized the structures with an isotropic unit cell to minimize the side effects from our arbitrary lattice parameters for all other compositions. Then, we applied geometry optimization with a triclinic (non-orthogonal) unit cell to fully minimize the stress components to calculate the elastic constants. In this procedure, we chose 10,000 as the maximum number of allowable steps aimed at obtaining fully relaxed atomic geometries. The dataset consists of three sets of crystal structures. The first set contains 46,086 irregular crystal structures, each of them with 54 atoms, obtained through optimization starting from a regular BCC crystal structure. The second set contains 24,543 irregular crystal structures, each of them with 32 atoms, obtained through optimization starting from a regular FCC crystal structure. The third set contains 39,303 irregular crystal structures, each of them with 48 atoms, obtained through optimization starting from a regular HCP crystal structure. The atomic configurations within each set span the possible compositional range. The three sets have been unified in a global dataset, which is extremely heterogeneous in terms of crystal structures, lattice volumes, and atomic configurations. Organization of files inside the dataset: the dataset contains three subdirectories called • BCC_opt • FCC_opt • HCP_opt based on the type of initial regular structure used to start the geometry optimization. Inside each of these folders, every atomic structure is identified by a string “A_B_Câ€, where A denotes the number of Nb in the system, B denotes index of structure with a given Nb number, and C denotes the total number of structures generated with a given Nb number. For each optimized crystal structure identified by the unique string of characters “A_B_Câ€, three files are provided: • A_B_C_opt.xyz: The optimized geometries in xyz format • A_B_C_opt.cfg: The optimized geometries in cfg format. It includes cell information and atomic energy, and forces calculated from LAMMPS. • A_B_C.elastic: Raw data of 21 elastic constants from LAMMPS output. • A_B_C.bulk: Calculated upper and lower bounds of bulk modulus and averaged one based on Voigt-Reuss-Hill approach from *.elastic. References: [1] A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in 't Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, and S. J. Plimpton. LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comp. Phys. Comm., 271:108171, 2022. [2] Y Zhang, R Ashcraft, MI Mendelev, CZ Wang, and KF Kelton. Experimental and molecular dynamics simulation study of structure of liquid and amorphous ni62nb38 alloy. The Journal of chemical physics, 145(20):204505, 2016.

36 MATERIALS SCIENCE↗

An Initial Microstructurally Informed Model of High Burnup Structure Formation in UO 2 Fuel

The microstructure of a UO 2 fuel pellet changes as burnup increases, impacting fuel performance. Predicting and characterizing high burnup structure (HBS) and dark zone formation is a key part of supporting burnup limit extensions for light water reactors. This paper describes a model developed through fitting radially resolved pellet data obtained from recently published microstructural characterization data. The model predicts grain size and grain character, in addition to pore density and size, with fitting dependencies on power history variables. Separately fitting power history variables to microstructural parameters allows for insight into the underlying physical phenomena for future model development. Additionally, experimental data have been correlated to an HBS fraction to facilitate the development of a model capable of predicting a total fuel restructured fraction at the engineering scale. In conclusion, this two-step approach provides a coupling from reactor power history to microstructural data to fractional HBS and creates a basis to model HBS-dependent parameters in a fuel performance code.

High burnup structure↗

Prediction of laser beam spatial profiles in a high-energy laser facility by use of deep learning

We adapt the significant advances achieved recently in the field of generative artificial intelligence/machine-learning to laser performance modeling in multipass, high-energy laser systems with application to high-shot-rate facilities relevant to inertial fusion energy. Advantages of neural-network architectures include rapid prediction capability, data-driven processing, and the possibility to implement such architectures within future low-latency, low-power consumption photonic networks. Four models were investigated that differed in their generator loss functions and utilized the U-Net encoder/decoder architecture with either a reconstruction loss alone or combined with an adversarial network loss. We achieved inference times of 1.3 ms for a 256 × 256 pixel near-field beam with errors in predicted energy of the order of 1% over most of the energy range. It is shown that prediction errors are significantly reduced by ensemble averaging the models with different weight initializations. These results suggest that including the temporal dimension in such models may provide accurate, real-time spatiotemporal predictions of laser performance in high-shot-rate laser systems.

47 OTHER INSTRUMENTATION↗

Distance‐based reconstruction of protein quaternary structures from inter‐chain contacts

Abstract Predicting the quaternary structure of protein complex is an important problem. Inter‐chain residue‐residue contact prediction can provide useful information to guide the ab initio reconstruction of quaternary structures. However, few methods have been developed to build quaternary structures from predicted inter‐chain contacts. Here, we develop the first method based on gradient descent optimization (GD) to build quaternary structures of protein dimers utilizing inter‐chain contacts as distance restraints. We evaluate GD on several datasets of homodimers and heterodimers using true/predicted contacts and monomer structures as input. GD consistently performs better than both simulated annealing and Markov Chain Monte Carlo simulation. Starting from an arbitrarily quaternary structure randomly initialized from the tertiary structures of protein chains and using true inter‐chain contacts as input, GD can reconstruct high‐quality structural models for homodimers and heterodimers with average TM‐score ranging from 0.92 to 0.99 and average interface root mean square distance from 0.72 Å to 1.64 Å. On a dataset of 115 homodimers, using predicted inter‐chain contacts as restraints, the average TM‐score of the structural models built by GD is 0.76. For 46% of the homodimers, high‐quality structural models with TM‐score ≥ 0.9 are reconstructed from predicted contacts. There is a strong correlation between the quality of the reconstructed models and the precision and recall of predicted contacts. Only a moderate precision or recall of inter‐chain contact prediction is needed to build good structural models for most homodimers. Moreover, GD improves the quality of quaternary structures predicted by AlphaFold2 on a Critical Assessment of Techniques for Protein Structure Prediction–Critical Assessments of Predictions of Interactions dataset.

59 BASIC BIOLOGICAL SCIENCES↗

Effect of dilute Rh on oxygen dissociation, spillover, and the oxidation of Cu across many orders of magnitude pressure

Knowledge of how trace amounts of more reactive metals influence the oxidation rate and mechanism of Cu surfaces is essential for developing strategies to optimize the performance of Cu-based catalysts. We find that the addition of 1% Rh to Cu(111) increases the initial O 2 dissociation rate by approximately 9-fold. CO poisoning experiments reveal that single Rh atoms activate O 2 and facilitate the spillover of atomic oxygen to Cu sites. Scanning tunneling microscopy (STM) and in situ X-ray photoelectron spectroscopy (XPS) support this mechanism, showing enhanced surface oxygen near Rh atoms. Here, a density functional theory (DFT)-based model demonstrates that Rh binds the O 2 precursor 0.15 eV more strongly than Cu(111) and lowers the O 2 dissociation barrier by 0.02 eV. Both single-crystal and nanoparticle experiments show that at low oxygen pressures, Rh enhances Cu oxidation, whereas at higher pressures, it inhibits deeper oxidation, as evidenced by in situ ultraviolet-visible (UV-vis) spectra.

36 MATERIALS SCIENCE↗

Thermodynamic parametric analysis of refueling heavy-duty hydrogen fuel-cell electric vehicles

Reliable design and safe operation of heavy-duty hydrogen refueling stations are essential for the successful deployment of heavy-duty fuel cell electric vehicles (FCEVs). Fueling heavy-duty FCEVs is different from light-duty vehicles in terms of the dispensed hydrogen quantities and fueling rates, requiring tailored fueling station design for each vehicle class. In particular, the selection and design of the onboard hydrogen storage tank system and the fueling performance requirements influence the safe design of hydrogen fueling stations. A thermodynamic modeling and analysis are performed to evaluate the impact of various fueling parameters and boundary conditions on the fueling performance of heavy-duty FCEVs. Here, we studied the effect of dispenser pressure ramp rate and precooling temperature, initial tank temperature and pressure, ambient temperature, and onboard storage design parameters, such as onboard storage pipe diameter and length, on the fueling rate and final vehicle state-of-charge, while observing prescribed tank pressure and temperature safety limits. An important finding was the sensitivity of the temporal fueling rate profile and the final tank state of charge to the design factors impacting pressure drop between the dispenser and vehicle tank, including onboard storage pipe diameter selection, and flow coefficients of nozzle, valves, and fittings. The fueling rate profile impacts the design and cost of the hydrogen precooling unit upstream of the dispenser.

08 HYDROGEN↗