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DOE OSTI2026

Design update on the transition beamline for the CEBAF Energy Upgrade

For Jefferson Lab’s 22GeV upgrade, two new permanent-magnet Fixed-Field Alternating Gradient (FFA) arcs will be integrated to serve the accelerator’s six highest-energy recirculation passes. Connecting these FFA arcs to the existing linear accelerator (linac) requires a carefully engineered transition section. The current design has two parts where the first part adiabatically matches the beam dispersion and orbit trajectories, while the second part aligns the Twiss parameters (alpha and beta functions) with those at the linac entrance. Given the tight spatial constraints and multiple matching requirements, a genetic algorithm is being explored to optimize the beam optics matching. This paper presents the current progress in developing and optimizing this transition.

Accelerator Physics↗

DOE OSTI2020

Gaussian Process Optimization of Sensitivity-Based Similarity Metrics between New Nuclear Applications and New/Existing Benchmarks [Slides]

This presentation discusses Nuclear Criticality Safety (NCS) and how designing safe, new nuclear criticality experiments requires expert judgement, which could take years of experience. Sensitivity/uncertainty (S/U) analysis can be utilized by less experienced individuals to conservatively estimate uncertainties in important parameters, such as k eff , in newly proposed nuclear experiments. The presentation poses the question of how this analysis can be performed and states that the answer lies in matching new nuclear experiments with existing benchmark experiments using similarity metrics. By increasing the criticality safety of the application in this work, higher mass limits could be used in PF-4 operations. Additionally, the presentation discusses MCNP6.2®, Whisper-1.1, the software that can be used in this analysis. Also discussed is the fact that International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks rarely match new nuclear applications and that there are significant differences in given set of materials and/or geometry. If there are no benchmarks that match the application, the presentation discusses the possibility of creating new benchmarks. In conclusion, this work presents a Gaussian process (GP) optimization scheme that was used to generate new benchmarks with the highest sensitivity-based similarity metrics to user-defined nuclear applications. The Gaussian process optimization successfully designed 3 new experimental benchmarks that were highly correlated to the application of interest and had k eff values near critical. Optimization over c k,i-r has shown that investigating specific isotope reactions for different applications is crucial to designing benchmark experiments. Partial contribution from Pu dominates c k similarity metric. Future work includes testing new stand-alone similarity metrics or new combinations of similarity metrics as the design criterion of this optimization – design criterion is application dependent.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Density Tailored Capillary Discharge (Final Technical Report)

This final report describes efforts to validate a novel way to drive capillary discharges in order to achieve true matched guiding of a focused laser beam traveling along the capillary. Achieving such matched guiding is important for laser plasma accelerators, such as ones based upon laser wakefield acceleration. During this Phase II program, a computer model, which was specifically designed to predict the time-dependent behavior of the capillary discharge, was exercised to determine whether unconventional ways to drive the discharge may yield matched guiding. A custom power supply was built to drive the capillary discharge in the unconventional manner specified by the model. Experiments performed at STI Optronics seemed to support the predictions of this model; however, subsequent more accurate measurements performed at Lawrence Berkeley National Laboratory did not agree with the model predictions.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Space Charge Driven Emittance Growth and the Effect of Octupoles in IOTA

The Integrable Optics Test Accelerator (IOTA) at Fermilab is a small machine dedicated to a broad frontier accelerator physics program. An important aspect of this program is to investigate the potential benefits of the resonance free tune spread achievable with integrable optics to store and accelerate high intensity proton beams for which space charge is significant. In this context, a good understanding of proton beam emittance growth and particle loss mechanisms is essential. Assuming nominal design parameters, simulations show that for a bunched beam, the bulk of emittance growth takes place immediately following injection, typically within tens of turns. We attempt to account for this growth using a simplified RMS mismatch theory; some of its limitations and possible improvements are briefly discussed. We then compare theoretical predictions to simulations performed using the PIC code pyORBIT. Further exploring ways to mitigate emittance growth and reduce particle loss, we compare two beam matching strategies: (1) matching at the injection point (2) matching at the center of the nonlinear (octupole) insertion region where $\beta_x = \beta_y$. To observe how nonlinearity affects emittance growth and whether it dominates growth due to mismatch, we track two different distributions. Finally, we explore the potential of using octupoles in a quasi-integrable configuration to mitigate growth using a variety of initial distributions both at reduced and full intensities.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)

We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. 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 CO2 EOR projects utilizing the water-alternating-gas (WAG) process. 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. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.

02 PETROLEUM↗

DOE OSTI2021

PELICAN Design, Test Planning, and Commissioning Results

To support design efforts for the Versatile Test Reactor (VTR) core assemblies, an experimental facility has been designed and constructed at Argonne National Laboratory to match the hydraulic flow conditions within the VTR’s primary heat transport system (PHTS). This facility, the Pressure drop Experimental Loop for Investigations of Core Assemblies in advanced Nuclear reactors, PELICAN, provides the ability to measure pressure drop across a full-scale fuel assembly containing prototypic axial reflectors, fuel, and plena components. The PELICAN facility was designed and built to offer maximum flexibility, allowing testing from short sub-sections all the way to the full-length core fuel assemblies. The report presents the high-level program objectives, a summary of the facility design, instrumentation, and control systems, and the testing procedure. The outcomes from facility characterization efforts and first test matrix results are then presented and then, finally, the conclusion contains a summary of the future work to be performed. This test facility was designed to match the hydraulic conditions of the flowing sodium in the VTR using water as a surrogate fluid. To do so, the water is elevated to a temperature of 110°C where its viscosity matches that of sodium, and with a 50-HP centrifugal pump, is capable of generating full scale flow rates to achieve prototypic Reynolds and Euler number flow conditions. To prevent boiling, the system is maintained at elevated pressure of at least 2.7-3.0 bar (40-44 psig). A set of 15 tests have been used to perform checkout activities in order to commission the device, survey the capabilities of PELICAN, and generate experimental data at isothermal conditions and over a range of flow rates up to 44 kg/s (700 GPM) to produce datasets used in the verification and validation of VTR design and modeling efforts. Initial testing focused on facility characterization, which assessed the operational capabilities of various control systems. The thermal control system was qualified, including the thermal response of the loop to the heat added by self- and auxiliary heaters, the chiller and heat exchanger systems for removing excess heat, and their coupled ability to maintain steady-state isothermal conditions as desired. Additionally, the pressure control system was verified to ensure necessary operating environments that promote pump health and prevent boiling of loop inventory at high temperatures could be met. With these systems in place, the first set of matrix tests have been carried out using orifice plates with inner diameters of 2.25-inches and 2.5-inches. Orifice plate flow behavior is well covered in scientific literature, and the results find good agreement with the measured pressure drop vs flow rate and those of theoretical predictions. This initial testing not only helps to validate the experiment, but it also produces a high quality data set for a geometry that is easily reproducible for simulations. Finally, the report is concluded with a discussion of the work to come and provides a snapshot of the test articles in the experimental pipeline whose designs are being inspired by the current designs from the VTR.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

FY22 Progress on Computational Modeling of the Water-Based NSTF

This report summarizes the system-level modeling effort by Argonne National Laboratory (Argonne) of the Natural convection Shutdown heat removal Test Facility (NSTF) in FY22. As an extension of the effort from FY21, this year’s work focuses primarily on the two-phase modeling of the NSTF using RELAP5-3D, particularly with the inclusion of the cavity model. The results from simulations were used to compare against experimental data for benchmarking purposes of the RELAP5 deck. Additionally, RELAP5 was used as a predictive tool to guide planned test operations and identify expected system behaviors. In the first part of this report, details are provided of the cavity omitted model where heat flux is applied directly as a boundary condition to the risers. The general trend predicted by the RELAP5 model matches that from the experimental data when a single-phase natural circulation flow is first established, followed by an oscillatory two-phase period and finally a stable two-phase flow. However, the onset of oscillations is predicted early by the model due to the smaller thermal mixing region in the tank. However, by expanding the simulated thermal mixing region in the tank, the onset of oscillations predicted by the model is able to match that from the experiment. These oscillations where studied in depth and are deduced to be flashing-induced instability. The model was then modified to simulate an accident scenario case where a representative heat load based on the full-scale Framatome’s 625 MW t SC-HTGR was applied directly to the riser channels. The simulated initial and boundary conditions were identical to those performed experimentally, facilitating direct comparisons between the predicted and experimental results. It was determined that the results showed some discrepancies remain, likely due to the overprediction of vapor generation rate by the computer model. In the second part of this report, the cavity model is re-introduced where it is observed that the RELAP5 prediction is now able to capture the major trends of the observed flow commonly observed during two-phase conditions. However, the onset of oscillations is once again predicted early by the model, possibly caused by the underprediction of heat loss from the heater and cavity. This is likely due to the omission of support structures in the cavity that can act as additional pathways for heat to escape to the environment. To overcome the underprediction of heat loss, part of the insulation surrounding the cavity side panels and the back of the heaters are removed to allow heat to escape directly to the environment, which then improves the RELAP5 prediction. Parametric studies are also performed to investigate the effects of heater power, tank inventory level, and tank gas space pressure on flow behaviors, also in direct comparison to conditions tested experimentally. User option-61 in the RELAP5-3D input deck, which changes the heat transfer coefficient correlations used for calculating the vapor generation, is also investigated where it is found that by enabling the option, the overall duration of oscillations is increased and matches that from the experiment better. The RELAP5 model is further benchmarked with a header inlet- throttling case where it is observed that the prediction from the model fails to capture some major features observed in the experiment. By using a modified loss coefficient curve for the valve, the accuracy of the prediction is improved where most of the major features observed in the experiment are predicted by the model. Lastly, the model is benchmarked with an inventory depletion scenario where it is observed that despite the modeling limitation of RELAP5, the prediction shows good agreement with the experimental data where major trends and features are captured by the model. Future work will see continued development of the current RELAP5-3D input deck of the NSTF to both improve the accuracy of the model’s predictive capability and continuing serving the experimental program. The mutually beneficial relationship between analysis and experimental efforts has become integral to the parent NSTF program, and the greater objective to fully understand and accurately predict the heat removal performance of a full scale RCCS concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Rapid Computational Identification of Therapeutic Targets for Pathogens

Biological threats continue to persist and evolve as an important challenge to national security. There are multiple ways in which novel viral pathogens could emerge to pose a serious threat to human health. This project developed a pathogen target identification tool that can rapidly respond to a novel or emerging viral biological threat. A set of computational tools were developed that provide detailed information on the newly sequenced genes, their protein products and the drug target sites for the proteins that are best suited for biological countermeasure development. Three key innovations were developed in the project. 1) Development of a new extensive database of protein pocket structures with structure-based search algorithms to rapidly link novel protein targets with the complete collection of previously experimentally solved protein structures. 2) A novel clustering pipeline was introduced to group matching structures and associated small-molecule binding ligands into a consensus protein pocket with the associated small-molecule chemotypes predicted to fit in the pocket site. The matching experimentally solved structures were used to inform the value of different target sites. 3) Where there are viral protein targets with pockets structurally matched to similar human proteins, a biological knowledge graph, which links molecular interactions with human disease, was used to further assess the potential negative impact of a viral protein target with similarities to human proteins that could have important off target side effects. In total, the project produced a new resource for rapid and detailed assessment of promising targets for countermeasures, reflecting the ongoing wet lab, clinical, and computational data being collected. These capabilities will improve the ability to respond to a biological threat in multiple domains.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Measurement of the Dispersion in the CeC Beamlines

The coherent electron cooling requires to match the relativistic factors of the hadron and electron beam within 10 -4 accuracy. Initial matching is based on the energy measurement of the electron beam using solenoid with accuracy about 10 -3 (the hadron relativistic factor can be found from the revolution frequency). Further matching is done with observation of the recombination rate with fine tuning based on the cooling rate. The last two steps require change of the electron energy which is achieved by change of the linac voltage. The interaction of the hadron and electron beams is affected by the transverse overlap of two beams. To minimize the effect, we need zero dispersion in the common section. The merge of the beams a dogleg transfer line is used containing two dipoles and three quadrupoles. The zeroing of dispersion is performed by settings of the quadrupoles. We have developed two ways to measure the dispersion. In the first mostly commonly used we change both dipoles by the same value creating the mismatch between the electron energy and bending magnet. In the compensated dogleg the position in the second dipole should not change, and the trajectory angle will change by the same amount as deflecting angle but in opposite direction. Therefore, the trajectory in the common section will not change. The value of the dispersion can be calculated from the beam displacement divided by the relative chang of the dipoles’ current. The second method is based on the change of the electron beam energy using linac. This method requires electron orbit alignment with linac axis to avoid beam steering. The results are shown in Fig.1 and Fig. 2. The first figure shows the dispersion prior the correction, and the second figure after the correction.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Application of prophage sequence analysis to investigate a disease outbreak involving Salmonella Adjame, a rare serovar and implications for the population structure

Introduction Outbreak investigation of foodborne salmonellosis is hindered when the food source is contaminated by multiple strains of Salmonella , creating difficulties matching an incriminated organism recovered from patients with the specific strain in the suspect food. An outbreak of the rare Salmonella Adjame was caused by multiple strains of the organism as revealed by single-nucleotide polymorphism (SNP) variation. The use of highly discriminatory prophage analysis to characterize strains of Salmonella should enable a more precise strain characterization and aid the investigation of foodborne salmonellosis. Methods We have carried out genomic analysis of S. Adjame strains recovered during the course of a recent outbreak and compared them with other strains of the organism ( n = 38 strains), using SNPs to evaluate strain differences present in the core genome, and prophage sequence typing (PST) to evaluate the accessory genome. Phylogenetic analyses were performed using both total prophage content and conserved prophages. Results The PST analysis of the S. Adjame isolates showed a high degree of strain heterogeneity. We observed small clusters made up of 2-6 isolates ( n = 27) and singletons ( n = 11) in stark contrast with the three clusters observed by SNP analysis. In total, we detected 24 prophages of which only four were highly prevalent, namely: Entero_p88 (36/38 strains), Salmon_SEN34 (35/38 strains), Burkho_phiE255 (33/38 strains) and Edward_GF (28/38 strains). Despite the marked strain diversity seen with prophage analysis, the distribution of the four most common prophages matched the clustering observed using core genome. Discussion Mutations in the core and accessory genomes of S. Adjame have shed light on the evolutionary relationships among the Adjame strains and demonstrated a convergence of the variations observed in both fractions of the genome. We conclude that core and accessory genomes analyses should be adopted in foodborne bacteria outbreak investigations to provide a more accurate strain description and facilitate reliable matching of isolates from patients and incriminated food sources. The outcomes should translate to a better understanding of the microbial population structure and an 46 improved source attribution in foodborne illnesses.

Gao, Ruimin↗

DOE OSTI2020

Analyzing the Validity of Brazilian Testing Using Digital Image Correlation and Numerical Simulation Techniques

Characterizing the mechanical behavior of rocks plays a crucial role to optimize the fracturing process in unconventional reservoirs. However, due to the intrinsic anisotropy and heterogeneity in unconventional resources, fracture process prediction remains the most significant challenge for sustainable and economic hydrocarbon production. During the deformation tracking under compression, deploying conventional methods (strain gauge, extensometer, etc.) is insufficient to measure the deformation since the physical attachment of the device is restricted to the size of the sample, monitoring limited point-wise deformation, producing difficulties in data retrieval, and a tendency to lose track in failure points, etc. Where conventional methods are limited, the application of digital image correlation (DIC) provides detailed and additional information of strain evolution and fracture patterns under loading. DIC is an image-based optical method that records an object with a camera and monitors the random contrast speckle pattern painted on the facing surface of the specimen. To overcome the existing limitations, this paper presents numerical modeling of Brazilian disc tests under quasi-static conditions to understand the full-field deformation behaviors and finally, it is validated by DIC. As the direct tensile test has limitations in sample preparation and test execution, the Brazilian testing principle is commonly used to evaluate indirectly the tensile strength of rocks. The two-dimensional numerical model was built to predict the stress distribution and full-field deformation on Brazilian disc under compression based on the assumptions of a homogenous, isotropic and linear elastic material. The uniaxial compression test was conducted using the DIC technique to determine the elastic properties of Spider Berea sandstone, which were used as inputs for the simulation model. The model was verified by the analytical solution and compared with the digital image correlation. The numerical simulation results showed that the solutions matched reasonably with the analytical solutions where the maximum deviation of stress distribution was obtained as 14.59%. The strain evolution (normal and shear strains) and displacements along the central horizontal and vertical planes were investigated in three distinguishable percentages of peak loads (20%, 40%, and 90%) to understand the deformation behaviors in rock. The simulation results demonstrated that the strain evolution contours consistently matched with DIC generated contours with a reasonable agreement. The changes in displacement along the central horizontal and vertical planes showed that numerical simulation and DIC generated experimental results were repeatable and matched closely. In terms of validation, Brazilian testing to measure the indirect tensile strength of rocks is still an issue of debate. The numerical model of fracture propagation supported by digital image correlation from this study can be used to explain the fracturing process in the homogeneous material and can be extended to non-homogeneous cases by incorporating heterogeneity, which is essential for rock mechanics field applications.

58 GEOSCIENCES↗

DOE OSTI2022

Multiphysics Simulation of the NASA SIRIUS-CAL Fuel Experiment in the Transient Test Reactor Using Griffin

After approximately 50 years, NASA is restarting efforts to develop nuclear thermal propulsion (NTP) for interplanetary missions. Building upon nuclear engine tests performed from the late 1950s to the early 1970s, the present research and testing focuses on advanced materials and fabrication methods. A number of transient tests have been performed to evaluate materials performance under high-temperature, high-flux conditions, with several more experiments in the pipeline for future testing. The measured data obtained from those tests are being used to validate the Griffin reactor multiphysics code for this particular type of application. Griffin was developed at Idaho National Laboratory (INL) using the MOOSE framework. This article describes the simulation results of the SIRIUS-CAL calibration experiment in the Transient Reactor Test Facility (TREAT). SIRIUS-CAL was the first transient test conducted on NASA fuels, and although the test was performed with a relatively low core peak power, the test specimen survived a temperature exceeding 900 K. Griffin simulations of the experiment successfully matched the reactor’s power transient after calibrating the initial control rod position to match the initial reactor period. The thermal-hydraulics model largely matches the time-dependent response of a thermocouple located within the experiment specimen to within the uncertainty estimate. However, the uncertainty range is significant and must be reduced in the future.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Characterizing Families of Spectral Similarity Scores and Their Use Cases for Gas Chromatography–Mass Spectrometry Small Molecule Identification

Metabolomics provides a unique snapshot into the world of small molecules and the complex biological processes that govern the human, animal, plant, and environmental ecosystems encapsulated by the One Health modeling framework. However, this “molecular snapshot” is only as informative as the number of metabolites confidently identified within it. The spectral similarity (SS) score is traditionally used to identify compound(s) in mass spectrometry approaches to metabolomics, where spectra are matched to reference libraries of candidate spectra. Unfortunately, there is little consensus on which of the dozens of available SS metrics should be used. This lack of standard SS score creates analytic uncertainty and potentially leads to issues in reproducibility, especially as these data are integrated across other domains. In this work, we use metabolomic spectral similarity as a case study to showcase the challenges in consistency within just one piece of the One Health framework that must be addressed to enable data science approaches for One Health problems. Here, using a large cohort of datasets comprising both standard and complex datasets with expert-verified truth annotations, we evaluated the effectiveness of 66 similarity metrics to delineate between correct matches (true positives) and incorrect matches (true negatives). We additionally characterize the families of these metrics to make informed recommendations for their use. Our results indicate that specific families of metrics (the Inner Product, Correlative, and Intersection families of scores) tend to perform better than others, with no single similarity metric performing optimally for all queried spectra. This work and its findings provide an empirically-based resource for researchers to use in their selection of similarity metrics for GC-MS identification, increasing scientific reproducibility through taking steps towards standardizing identification workflows.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Identifying Circumgalactic Medium Absorption in QSO Spectra: A Bayesian Approach

We present a study of candidate galaxy–absorber pairs for 43 low-redshift QSO sightlines (0.06 < z < 0.85) observed with the Hubble Space Telescope/Cosmic Origins Spectrograph that lie within the footprint of the Sloan Digital Sky Survey with a statistical approach to match absorbers with galaxies near the QSO lines of sight using only the SDSS Data Release 12 photometric data for the galaxies, including estimates of their redshifts. Our Bayesian methods combine the SDSS photometric information with measured properties of the circumgalactic medium to find the most probable galaxy match, if any, for each absorber in the line-of-sight QSO spectrum. We find ~630 candidate galaxy–absorber pairs using two different statistics. The methods are able to reproduce pairs reported in the targeted spectroscopic studies upon which we base the statistics at a rate of 72%. The properties of the galaxies comprising the candidate pairs have median redshift, luminosity, and stellar mass, all estimated from the photometric data, $z$ = 0.13, L = 0.1$L$ * , and $\mathrm{log}({M}_{* }/{M}_{\odot })=9.7$. The median impact parameter of the candidate pairs is ~430 kpc, or ~3.5 times the galaxy virial radius. The results are broadly consistent with the high Ly$α$ covering fraction out to this radius found in previous studies. In conclusion, this method of matching absorbers and galaxies can be used to prioritize targets for spectroscopic studies, and we present specific examples of promising systems for such follow-up.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Late-time Hubble Space Telescope Ultraviolet Spectra of SN 2023ixf and SN 2024ggi Show Ongoing Interaction with Circumstellar Material

We present far- and near-ultraviolet (UV) spectra of the type II supernovae (SNe) SN 2023ixf from days 199 to 722 and SN 2024ggi at days 41 and 232. Both SNe show broad, blueshifted, and asymmetric UV emission lines with an initial maximum velocity of ∼9000 km s −1 and narrow unresolved emission in C ivλλ1548.9, 1550.8. We compare the optical and UV emission-line profiles, showing that they evolve from two distinct velocity profiles to a single profile tracing the UV emission. We interpret this as shock power from interaction with circumstellar material coming to dominate over the radioactive-decay power from the inner ejecta. Comparing our observations to radiative transfer models with injected shock power, we find SN 2024ggi is best matched by P shock,abs = 1 × 10 41 erg s −1 at day 40; SN 2023ixf at day 300 and SN 2024ggi at day 200 are best matched by P shock,abs = 1 × 10 40 erg s −1 ; and SN 2023ixf at day 600 is best matched by Pshock,abs = 5 × 10 39 erg s −1 . From these models, we find that the mass-loss rate of both SNe increased just before the explosion. For SN 2023ixf, our mass-loss rates go from 4 × 10 −5 M ⊙ yr −1 at 600 yr before explosion to 2 × 10 −2 M ⊙ yr − 1 at 15 yr prior to explosion. For SN 2024ggi, we find a mass-loss rate of 9 × 10 −5 M ⊙ yr −1 at 150 yr before explosion and 1 × 10 −3 M ⊙ yr −1 at 30 yr before explosion.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Spectroscopy of the Hamburg Meteorite, Michigan H4

Spectroscopic studies of the Hamburg (Michigan H4) meteorite using visible–near-infrared (VNIR), mid-infrared (MIR), Raman, and Mössbauer data reproduce the results of more conventional laboratory measurements of petrology and geochemistry. This combination provides general information on the mineral modes of silicates, although spectroscopy was performed on different splits of this meteorite, and varying results may be explained by heterogeneity that is typical of ordinary chondrites. Raman also detects small features assigned to first-order D and G carbon bands, while Mössbauer data show the presence of Fe oxides and carbides. The electron microprobe (EMPA) composition of olivine in this meteorite is accurately measured to be Fo 81.3 , while MIR and Raman closely agree with Fo 80 and Fo 82 , respectively, and Mössbauer, at Fo 60 − Fo 70 , is in the ballpark. Similarly, P. R. Heck et al. report pyroxenes with compositions of Fs 16 Wo 1 , while Raman suggests a somewhat similar composition of Fs 28 Wo 0 . Both VNIR and MIR detect the presence of small amounts of feldspar, while EMPA identifies its composition as An 14 Ab 8 Or 5 . VNIR data were matched to spectral libraries of meteorite and asteroid data and shown to closely match other L and H meteorites. The best spectral matches to the Michigan H4 meteorite are to asteroid classes L/H/LL/URE, EH/EL/AUB, and CO/CV from M. D. Dyar et al.; objects in this group are intermediate in semimajor axis lengths for their orbits. The results highlight the strengths and weaknesses of each technique and show their collective strength when applied together to a single meteorite sample.

58 GEOSCIENCES↗

DOE OSTI2025

The final WaZP galaxy cluster catalog of the Dark Energy Survey and comparison with SZE data

In this work, we present and characterize the galaxy cluster catalog detected by the WaZP cluster finder, which is not based on red-sequence identification, on the full six years of observations of the Dark Energy Survey (DES-Y6). The full catalog contains over 400k detected clusters with richnesses, Ngals, above 5 and that reach redshifts up to 1.3. We also provide a version of the catalog where the observation depth and richness computation are homogenized to be used for cosmology, containing 33k rich (Ngals >25) clusters. We compare our results with the previous WaZP catalog obtained from the DES first-year data release (DES-Y1). We find that essentially all clusters within the common footprint and depth limit are recovered. The deeper observations on DES-Y6 and the more complete available spectroscopic redshift sample lead to improvements in the redshifts of the clusters, resulting in an average scatter of 1.4% and offset of 0.2%. The optical clusters are also cross-matched with Sunyaev Zel'dovich Effect (SZE) cluster samples detected by the South Pole Telescope (SPT) and the Atacama Cosmology Telescope (ACT). We find that essentially all SZE clusters with reasonable overlapping footprint have a corresponding WaZP cluster. Conversely, 90% of the optical detections with richness greater than 150 have a counterpart in the deeper regions of the SZE surveys. Based on cross-match with the SZE catalogs, we also find that 15-20% of the SZE matched systems have more than one possible WaZP counterpart at the same redshift and within the SZE R500c, indicating possible interacting or unrelaxed systems. Finally, given the optical and SZE beams, WaZP and SZE centerings are found to be consistent. A more detailed study of the SZE-WaZP mass-richness relation will be presented in a separate paper.

Benoist, C. [OCA, Nice, Lab. Lagrange; LIneA, Rio ↗

DOE OSTI2022

Initial ASME code rule analysis on Simple and Full assessment

ASME & ASTM codes present simple and full assessment methodologies to qualify nuclear grade graphite components. This report explains the theory behind the statistical portion of the codes and describes the issues discussed in a 2020 workshop in the simple assessment, as well as the full assessment. The methodology for the full assessment was developed by Hindley []. He used a validation methodology to match the experimental average failure load of test specimens from several geometries to the calculated 50% POF load to tune the grouping criteria parameters based on an RMSE penalty function. The grouping criteria consists of a minimum volume to satisfy the weakest link theory of the Weibull distribution and a minimum stress range parameter. Hindley’s work found a minimum link volume of 10 times the grain size and a stress range parameter of 7% [satisfy the validation requirements. Several studies found that the link volume of 10 times the grain size was not satisfactory for the volume grouping criteria for graphite grades with fine grains. ASME 2021 code adopted a new volume grouping criteria based on fracture toughness for calculation of the process zone volume. However, errors were found in the ASME 2021 code process zone volume equation and the question is now open as to what volume grouping criteria is satisfactory. This report presents results from sensitivity studies that were done to evaluate the volume grouping criteria effect on the full assessment POF. This report also presents results from sensitivity studies on other aspects of the code that affect the POF, the mesh size and the choice of the Weibull threshold parameter. All three sensitivity studies: the volume grouping criteria, the mesh size, and the threshold parameter choice are found to affect the component qualification decision for components of structural reliability class 1 (SRC-1). The sensitivity analysis results are presented in the body of the report for NBG-18, which is the same grade of graphite as Hindley used in his thesis. Results from NBG-17, IG-110, 2114, and PCEA are presented in the Appendix. For NBG-18, it was found that increasing the threshold increases the POF, finer meshes result in higher POFs, and that smaller link volume requirements lead to higher POFs (which is inconsistent with Hindley’s findings). This report proposes a new validation study similar to Hindley’s []. The purpose of the new validation study is to tune the threshold, mesh size and grouping criteria based on results from multiple grades of graphite, including finer grain graphites T220 (1-3 microns) and NG-CT-50 (5 microns). The test specimens will be broken at 3 labs, such that we can measure between lab measurement variability, with at least 5 test specimens per lab such that the within lab uncertainty can also be measured. Hindley’s validation method tried matching the average experimental load with the median. The future study will attempt to match failures at lower percentiles, which would be closer to the SRC POF limit. We are currently looking into what geometries make sense and the best method to measure multi-axial stress states. These design decisions are still being set.

36 MATERIALS SCIENCE↗