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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2023

Physics-Informed Deep Learning for Reconstruction of Spatial Missing Climate Information in the Antarctic

Understanding the influence of the Antarctic on the global climate is crucial for the prediction of global warming. However, due to very few observation sites, it is difficult to reconstruct the rational spatial pattern by filling in the missing values from the limited site observations. To tackle this challenge, regional spatial gap-filling methods, such as Kriging and inverse distance weighted (IDW), are regularly used in geoscience. Nevertheless, the reconstructing credibility of these methods is undesirable when the spatial structure has massive missing pieces. Inspired by image inpainting, we propose a novel deep learning method that demonstrates a good effect by embedding the physics-aware initialization of deep learning methods for rapid learning and capturing the spatial dependence for the high-fidelity imputation of missing areas. We create the benchmark dataset that artificially masks the Antarctic region with ratios of 30%, 50% and 70%. The reconstructing monthly mean surface temperature using the deep learning image inpainting method RFR (Recurrent Feature Reasoning) exhibits an average of 63% and 71% improvement of accuracy over Kriging and IDW under different missing rates. With regard to wind speed, there are still 36% and 50% improvements. In particular, the achieved improvement is even better for the larger missing ratio, such as under the 70% missing rate, where the accuracy of RFR is 68% and 74% higher than Kriging and IDW for temperature and also 38% and 46% higher for wind speed. In addition, the PI-RFR (Physics-Informed Recurrent Feature Reasoning) method we proposed is initialized using the spatial pattern data simulated by the numerical climate model instead of the unified average. Compared with RFR, PI-RFR has an average accuracy improvement of 10% for temperature and 9% for wind speed. When applied to reconstruct the spatial pattern based on the Antarctic site observations, where the missing rate is over 90%, the proposed method exhibits more spatial characteristics than Kriging and IDW.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Selective One-Dimensional 13 C– 13 C Spin-Diffusion Solid-State Nuclear Magnetic Resonance Methods to Probe Spatial Arrangements in Biopolymers Including Plant Cell Walls, Peptides, and Spider Silk

Two-dimensional (2D) and 3D through-space 13 C– 13 C homonuclear spin-diffusion techniques are powerful solid-state nuclear magnetic resonance (NMR) tools for extracting structural information from 13 C-enriched biomolecules, but necessarily long acquisition times restrict their applications. In this work, we explore the broad utility and underutilized power of a chemical shift-selective one-dimensional (1D) version of a 2D 13 C– 13 C spin-diffusion solid-state NMR technique. The method, which is called 1D dipolar-assisted rotational resonance (DARR) difference, is applied to a variety of biomaterials including lignocellulosic plant cell walls, microcrystalline peptide fMLF, and black widow dragline spider silk. 1D 13 C– 13 C spin-diffusion methods described here apply in select cases in which the 1D 13 C solid-state NMR spectrum displays chemical shift-resolved moieties. Furthermore, this is analogous to the selective 1D nuclear Overhauser effect spectroscopy (NOESY) experiment utilized in liquid-state NMR as a faster (1D instead of 2D) and often less ambiguous (direct sampling of the time domain data, coupled with increased signal averaging) alternative to 2D NOESY. Selective 1D 13 C– 13 C spin-diffusion methods are more time-efficient than their 2D counterparts such as proton-driven spin diffusion (PDSD) and dipolar-assisted rotational resonance. The additional time gained enables measurements of 13 C– 13 C spin-diffusion buildup curves and extraction of spin-diffusion time constants TSD, yielding detailed structural information. Specifically, selective 1D DARR difference buildup curves applied to 13 C-enriched hybrid poplar woody stems confirm strong spatial interaction between lignin and acetylated xylan polymers within poplar plant secondary cell walls, and an interpolymer distance of ~0.45–0.5 nm was estimated. Additionally, Tyr/Gly long-range correlations were observed on isotopically enriched black widow spider dragline silks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Lattice Strain Measurement of Core@Shell Electrocatalysts with 4D Scanning Transmission Electron Microscopy Nanobeam Electron Diffraction

Strain engineering enables the direct modification of atomic bonding and is currently an active area of research aimed at improving electrocatalytic activity. However, directly measuring the lattice strain of individual catalyst nanoparticles is challenging, especially at the scale of a single unit cell. In this study, we quantitatively map the strain present in rhodium@platinum (core@shell) nanocube electrocatalysts using conventional aberration-corrected scanning transmission electron microscopy (STEM) and the recently developed technique of 4D-STEM nanobeam electron diffraction. We demonstrate that 4D-STEM combined with data preconditioning allows for quantitative lattice strain mapping with subpicometer precision and without the influence of scan distortions. When combined with multivariate curve resolution, 4D-STEM allows us to distinguish the nanocube core from the shell and to quantify the unit cell size as a function of distance from the core–shell interface. Our results demonstrate that 4D-STEM has significant precision and accuracy advantages in strain metrology of catalyst materials compared to aberration-corrected STEM imaging and is beneficial for extracting information about the evolution of strain in catalyst nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Fourfold alkyl wrapping of a copper(II) porphyrin thwarts macrocycle π–π stacking in a compact supramolecular package

Porphyrins are valuable constituents in optoelectronic, catalytic, and other applications, yet control of intermolecular π–π stacking is invariably essential to attain the desired properties. Superstructures built onto the porphyrin, often via meso -aryl groups, can afford facial encumbrance that suppresses π–π stacking, although some molecular designs have provided insufficient facial coverage and many have entailed cumbersome syntheses. In this study, a copper(II) porphyrin bearing four meso substituents, namely, {10,20-bis[2,6-bis(octyloxy)phenyl]-5,15-dibromoporphinato}copper(II), [Cu(C 64 H 82 Br 2 N 4 O 4 )], was prepared by metalation of the corresponding free-base porphyrin and was characterized by single-crystal X-ray diffraction. The crystal structure reveals a dihedral angle of 111.1 (2)° for the plane of the meso -aryl group relative to the plane of the porphyrin, with both aryl groups tilted in the same direction. Each of the four octyloxy groups exhibits a gauche conformation for the –OCH 2 CH 2 – unit but is extended with four or five anti (–CH 2 CH 2 –/H) conformations thereafter, causing each octyl group to span the dimension of the macrocycle. In a global frame of reference where the two Br atoms define the north/south poles and the two aryl groups are at antipodes on the equator, two octyl groups of one aryl unit project over the northern hemisphere (covering pyrroles A and B ), whereas those of the other aryl unit project over the southern hemisphere (covering pyrroles C and D ). Together, the four octyl groups ensheath the two faces of the porphyrin in a self-wrapped assembly. The closest approach of the Cu atom to an octyl methylene C atom (position 6) is 3.5817 (18) Å, the mean separations of neighboring porphyrin planes are 8.059 (4) and 4.693 (8) Å along the a and c axes, respectively, and the center-to-center distances between the Cu atoms of neighboring porphyrins are 10.2725 (4), 12.2540 (6), and 12.7472 (6) Å along the a , b , and c axes, respectively. The Hirshfeld surface analysis and two-dimensional (2D) fingerprint plots provide information concerning contact interactions in the supramolecular assembly of the solid crystal.

Chemistry↗

DOE OSTI2025

Clustering Algorithm for AM Parts using GSH and EDT with Autoencoder

SAND2025-10103O The Clustering Algorithm for AM Parts Using GSH and (EDT With Autoencoder is a software tool. It uses a clustering algorithm for additive manufacturing (AM) parts using generalized spherical harmonics (GSH) and Euclidean distance transform (EDT) with an autoencoder to quantify material microstructure. The tool offers improved sensitivity to microstructural changes compared to traditional approaches. The tool integrates multiple microstructural properties, such as grain morphology, crystallographic orientation, and material phase information, to provide a comprehensive analysis of material microstructures. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Rodgers, Theron [Sandia National Lab. (SNL-CA), Li↗

DOE OSTI2022

The Strange Case of Ground-Coupled Airwaves on Seismoacoustic Stations at Local to Near-Regional Scales

Here we investigate the application of ground-coupled airwaves observed by seismoacoustic stations at local to near-regional scales to detect signals of interest and determine back-azimuth information. Ground-coupled airwaves are created from incident pressure waves traveling through the atmosphere that couple to the earth and transmit as a seismic wave with retrograde elliptical motion. Previous studies at sub-local scales (<10 km from a source of interest) found the back-azimuth to the source could be accurately determined from seismoacoustic signals recorded by acoustic and 3-component seismic sensors spatially separated on the order of 10 to 150 m. The potential back-azimuth directions are estimated from the coherent signals between the acoustic and vertical seismic data, via a propagation-induced phase shift of the seismoacoustic signal. A unique solution is then informed by the particle motion of the 3-component seismic station, which was previously found to be less accurate than the seismoacoustic-sensor method. We investigate the applicability of this technique to greater source-receiver distances, from 50-100 km and up to 400 km, which contains pressure waves with tropospheric and stratospheric ray paths, respectively. Specifically, we analyze seismoacoustic sources with ground truth from rocket motor fuel elimination events at the Utah Test and Training Range (UTTR) as well as a 2020 rocket launch in Southern California. From these sources we observe evidence that while coherent signals can be seen from both sources on multiple seismoacoustic station pairs, the determined ground-coupled airwave back-azimuths are more complicated than results at more local scales. Our findings suggest more complex factors including incidence angle, coupling location, subsurface material, and atmospheric propagation effects need to be fully investigated before the ground-coupled airwave back-azimuth determination method can be applied or assessed at these further distances.

58 GEOSCIENCES↗

DOE OSTI2021

Searching for Interstellar Quantum Communications

The modern search for extraterrestrial intelligence began with the seminal publications of Cocconi & Morrison and Schwartz & Townes, who proposed searching for narrowband signals in the radio spectrum and optical laser pulses. Over the last six decades, more than 100 dedicated search programs have targeted these wavelengths, all with null results. All of these campaigns searched for classical communications, that is, for a significant number of photons above a noise threshold, with the assumption of a pattern encoded in time and/or frequency space. I argue that future searches should also target quantum communications. They are preferred over classical communications with regard to security and information efficiency, and they would have escaped detection in all previous searches. The measurement of Fock state photons or squeezed light would indicate the artificiality of a signal. I show that quantum coherence is feasible over interstellar distances and explain for the first time how astronomers can search for quantum transmissions sent by ETI to Earth using commercially available telescopes and receiver equipment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

A Unified Tracer Analysis of DESI DR2 Baryon Acoustic Oscillations

We improve upon previous efforts to optimally combine overlapping galaxy samples in the DESI baryon acoustic oscillation analysis. By weighting each galaxy by its linear bias, overlapping galaxies are combined into a single, unified catalog, naturally avoiding double counting of cosmic volume and including all auto- and cross- information at the catalog level. Improvements over the previous effort include the addition of QSO out to $z=1.6$ to account for all overlapping DR2 tracers and redshift-dependent bias treatment to improve reconstruction. We report distance measurements using this unified tracer, and find them to be highly consistent with the baseline DR2 BAO analysis. We also test for tracer-dependent systematics within the DESI data, and find no evidence of tracer-dependent systematics within $0.8

Sanders, N. [Ohio U., Athens] (ORCID:0009000800202↗

DOE OSTI2020

Towards a self-consistent analysis of the anisotropic galaxy two- and three-point correlation functions on large scales: application to mock galaxy catalogues

We establish a practical method for the joint analysis of anisotropic galaxy two- and three-point correlation functions (2PCF and 3PCF, respectively) on the basis of the decomposition formalism of the 3PCF using tripolar spherical harmonics. We perform such an analysis with MultiDark-Patchy mock catalogues to demonstrate and understand the benefit of the anisotropic 3PCF. We focus on scales above $80\, h^{-1}\, {\rm Mpc}$, and use information from the shape and the baryon acoustic oscillation (BAO) signals of the 2PCF and 3PCF. We also apply density field reconstruction to increase the signal-to-noise ratio of BAO in the 2PCF measurement, but not in the 3PCF measurement. In particular, we study in detail the constraints on the angular diameter distance and the Hubble parameter. We build a model of the bispectrum or 3PCF that includes the non-linear damping of the BAO signal in redshift space. We carefully account for various uncertainties in our analysis including theoretical models of the 3PCF, window function corrections, biases in estimated parameters from the fiducial values, the number of mock realizations to estimate the covariance matrix, and bin size. The joint analysis of the 2PCF and 3PCF monopole and quadrupole components shows a $30{{\ \rm per\ cent}}$ and $20{{\ \rm per\ cent}}$ improvement in Hubble parameter constraints before and after reconstruction of the 2PCF measurements, respectively, compared to the 2PCF analysis alone. Furthermore, this study clearly shows that the anisotropic 3PCF increases cosmological information from galaxy surveys and encourages further development of the modelling of the 3PCF on smaller scales than we consider.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Source Characterization of the Declared North Korean Nuclear Tests From Regional Distance Coda Wave Spectral Ratios

Abstract Seismic observations of underground nuclear explosions provide crucial data on source yield and depth that cannot easily be estimated from other geophysical methods. However, it is difficult to obtain reliable yield estimates for test sites for which we do not have direct seismic calibration experiments. To obtain source information from uncalibrated sites and paths, local and regional seismic records of six, proximal, declared underground nuclear explosions in North Korea are used to compute spectral ratios of narrow‐band waveform envelopes of body‐wave coda that remove path and site effects to reveal precise, relative source moment. The yields of these explosions are obtained from the observed source ratios by simultaneously fitting the classical source model of Mueller and Murphy (1971), https://doi.org/10.1785/bssa0610061675 to all event pairs. The source model provides an impressive fit to the observations considering that the P phase coda derived source spectral ratios did not require a prior knowledge of the source or regionally calibrated corrections to be applied to the data. However, the observed corner frequencies from S wave coda spectral ratios are lower than the source model predictions, but are well fit by models calculated using the corner frequency consistent with the Fisk conjecture. The results presented here provide novel constraints on the spectral distributions of the energy radiated by the sources of the DPRK test series, and allows for an independent evaluation of existing estimated source model parameters.

58 GEOSCIENCES↗

DOE OSTI2022

Differences in soil organic matter between EcM- and AM-dominated forests depend on tree and fungal identity

As global change shifts the species composition of forests, we need to understand which species characteristics affect soil organic matter (SOM) cycling to predict future soil carbon (C) storage. Recently, whether a tree species forms a symbiosis with arbuscular (AM) versus ectomycorrhizal (EcM) fungi has been suggested as a strong predictor of soil C storage, but there is wide variability within EcM systems. In this study, we investigated how mycorrhizal associations and the species composition of canopy trees and mycorrhizal fungi related to the proportion of soil C and nitrogen (N) in mineral associations and soil C:N across four sites representing distinct climates and tree communities in the eastern US broadleaf forest biome. In two of our sites, we found the expected relationship of declining mineral-associated C and N and increasing soil C:N ratios as the basal area of EcM-associating trees increased. However, across all sites these soil properties strongly correlated with canopy tree and fungal species composition. Sites where the expected pattern with EcM basal area was observed were (1) dominated by trees with lower quality litter in the Pinaceae and Fagaceae families and (2) dominated by EcM fungi with medium-distance exploration type hyphae, melanized tissues, and the potential to produce peroxidases. Here, this observational study demonstrates that differences in SOM between AM and EcM systems are dependent on the taxa of trees and EcM fungi involved. Important information is lost when the rich mycorrhizal symbiosis is reduced to two categories.

mineral-associated organic matter↗

DOE OSTI2023

Temperature Uncertainty Modeling with Proxy Structural Data as Geostatistical Constraints for Well Siting: An Example Applied to Granite Springs Valley, NV, USA

Utilizing existing temperature and structural information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aim of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations . The data used to support the modeling are measured temperatures and structural proxies from 3D geologic modeling, the latter considered "secondary" data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally likely temperature models (i.e., realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: Vprior and entropy. Vprior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e., linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g., dilation versus distance to fault termination) should be used given the specific geothermal system. In general, Vprior from local varying mean results identify locations that are close to high values for the structural proxies: areas with highe r probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comp arison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

3D temperature modeling↗

DOE OSTI2023

Segmenting the target audience for transportation demand management programs: An investigation between mode shift and individual characteristics

Understanding the characteristics of travelers and situations that are more likely to switch from single occupancy vehicles (SOV) to more sustainable mobility options can help transportation agencies develop better behavior change strategies. Existing mode shift programs, however, rarely identify their target audience, which could make the programs less effective. Here, to investigate the demographics and trip characteristics of those who are more likely to shift from SOV to carpooling, public transit, and micromobility (e.g. walking, biking), a matrix decomposition audience segmentation method is proposed and applied on travel survey data. The results of this research show that for short-distance leisure or social trips, young and middle-income people are more likely to shift to these mobility options from SOV. This study provides a comprehensive and profound understanding of the characteristics of the target audience that can inform policies to create more targeted behavior change strategies to reach their sustainability goals.

42 ENGINEERING↗

DOE OSTI2023

The Chemodynamics of the Stellar Populations in M31 from APOGEE Integrated-light Spectroscopy

We present an analysis of nearly 1000 near-infrared, integrated-light spectra from APOGEE in the inner ~7 kpc of M31. We utilize full-spectrum fitting with A-LIST simple stellar population spectral templates that represent a population of stars with the same age, [M/H], and [α/M]. With this, we determine the mean kinematics, metallicities, α abundances, and ages of the stellar populations of M31's bar, bulge, and inner disk (~4–7 kpc). We find a nonaxisymmetric velocity field in M31 resulting from the presence of a bar. The bulge of M31 is less metal-rich (mean [M/H] = $0.149$$^{+0.067}_{-0.081}$ dex) than the disk, features minima in metallicity on either side of the bar ([M/H] ~ -0.2), and is enhanced in α abundance (mean [α/M] = $0.281$$^{+0.035}_{-0.038}$). The disk of M31 within ~7 kpc is enhanced in both metallicity ([M/H] = $-0.023$$^{+0.050}_{-0.052}$) and α abundance ([α/M] = $0.274$$^{+0.020}_{-0.025}$). Both of these structural components are uniformly old at ≃12 Gyr. We find the mean metallicity increases with distance from the center of M31, with the steepest gradient along the disk major axis (0.043 ± 0.021 dex kpc -1 ). This gradient is the result of changing light contributions from the bulge and disk. The chemodynamics of stellar populations encodes information about a galaxy's chemical enrichment, star formation history, and merger history, allowing us to discuss new constraints on M31's formation. Our results provide a stepping stone between our understanding of the Milky Way and other external galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

Modeling and Analysis of the Transport and Disposal of Beryllium Moderator Blocks and Greater than Class C (GTCC) Waste

Radioactive waste in the United states is categorized based on its source, radioactivity, and security risk. The categorization method employed by the Nuclear Regulatory Committee (NRC) for low-level radioactive waste is not currently applied to any waste generated by the Department of Energy (DOE) or disposed of in DOE facilities. As a result, there is a large volume of DOE-generated waste with characteristics similar to the NRC’s “Greater than Class C” (GTCC) waste category which presently do not have a path for long-term disposal. Much of this waste cannot undergo the standard commercial disposition process due to it being categorized as Transuranic (TRU) waste under DOE guidelines, due to elevated concentrations of key fission products. Possible solutions to this dilemma are explored in the Environmental Impact Statement for the “Disposal of Greater-Than-Class-C Low Level Radioactive Wave” (EIS-0375). This paper analyzes several EIS possible paths for disposal for this “orphaned” waste. One example that highlights this categorization issue is the spent beryllium cladding that has been extracted from the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) throughout its operational lifetime. These beryllium blocks surround the reactor’s main chambers and components and serve as neutron moderators. This paper will use this particular waste form to analyze the economic and technological viability of transporting and storing this material under the storage and transportation criteria of the Waste isolation Pilot Plant (WIPP), which was deemed the most feasible disposition path according to the EIS. The example of this waste form used in this paper that highlights this categorization issue is the spent beryllium cladding extracted from Idaho National Laboratory’s (INL) Advanced Test Reactor (ATR). These beryllium blocks surround the reactor’s components and serve as neutron moderators, and thus have accumulated high concentration of high-activity transuranic isotopes. This paper analyzed the viability of transporting and storing this material under the storage and transportation criteria of the five primary disposition paths covered in EIS-0375. An array of calculations was carried out to assess the viability of the various disposition paths for the beryllium shipments as well as other waste shipments that fall within the GTCC category. Modeling with MCNP 6.2 was conducted to determine whether the beryllium blocks could be safely stored and transported within a 72-B cask; the standard shipping container for remote-handled, transuranic waste, while also meeting regulatory limits at various disposition paths. A cost analysis of the transportation and long-term disposal paths mentioned in the EIS was also carried out using available data and information from similar waste shipments. Lastly, a geochemical analysis of the various geological repository discussed in the EIS was also carried out using the Geochemists Workbench Release 14. Long-term disposal of the beryllium blocks at the Waste Isolation Pilot Plant (WIPP) proved to be the most cost-effective long-term disposition option of the ones considered in the EIS. A dose rate calculation at both contact and remote-handling distances indicate that the analyzed beryllium shipments should not exceed the exposure limits at any of the considered locations. Greater-than-class-C waste has been left in a regulatory state of limbo for years, resulting in backlogs of inventory across several research sites in the United States. Due to its high activity and presence of transuranic isotopes, it is imperative to ensure that it remains inaccessible and sequestered both in its short-term interim as well as a long-term geologic time scale. The information and assessments done in the paper could potentially serve as a reference for any future shipments of this waste form at the WIPP facility as well as other disposition paths that may be considered in the future.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

O’Hare Airport Short-Term Ground Transportation Modal Demand Forecast Using Gaussian Processes

Here, the principal objective of this study is to analyze the spatial and temporal variation of ground transportation airport demand and provide demand forecast to inform planning capability and explore alternatives for investments to accommodate airport growth. Because of its good adaptability and strong generalization ability for dealing with high-dimensional input, small-sample, and nonlinear spatial data, Gaussian process (GP) regression is used to provide forecast estimates using data from transportation network company (TNC) trips and urban rail passengers at Chicago's O'Hare International Airport. TNC airport trips differ significantly, with three times more distance, more than twice the travel time, and half of the share requests compared with nonairport trips. This highlights the need for separate demand models. Hourly analysis of the rail service indicates that this is likely heavily used by airport workers, whereas TNC services focus on travelers because of variations in the peak demand hours. Heteroscedastic GP regression is implemented because of differences in trip variance between night and day hours. Estimates are given for weekdays and weekend trips, and the 95% confidence intervals are calculated. The introduction of flight schedule information into the models shows marginal improvements in their performance. However, fitting a GP regression becomes computationally expensive with increased sample size and the introduction of spatial components. Transportation planners and policymakers can use the results and methods implemented in this study to optimize transportation assets and provide long-range simulations of the current and future conditions in the area.

42 ENGINEERING↗

DOE OSTI2023

A Telomerase-Activated Magnetic Resonance Imaging Probe for Consecutively Monitoring Tumor Growth Kinetics and In Situ Screening Inhibitors

Telomerase has long been considered as a biomarker for cancer diagnosis and a therapeutic target for drug discovery. Detecting telomerase activity in vivo could provide more direct information of tumor progression and response to drug treatment, which, however, is hampered by the lack of an effective probe that can generate an output signal without a tissue penetration depth limit. Here in this study, using the principle of distance-dependent magnetic resonance tuning, we constructed a telomerase-activated magnetic resonance imaging probe (TAMP) by connecting superparamagnetic ferroferric oxide nanoparticles (SPFONs) and paramagnetic Gd-DOTA (Gd(III) 1,4,7,10- tetraazacyclododecane-1,4,7,10-tetraazacyclododecane-1,4,7,10-tet-raacetic acid) complexes via telomerase-responsive DNA motifs. Upon telomerase-catalyzed extension of the primer in TAMP, Gd-DOTA-conjugated oligonucleotides can be liberated from the surface of SPFONs through a DNA strand displacement reaction, restoring the T 1 signal of the Gd-DOTA for a direct readout of the telomerase activity. Here we show that, by tracking telomerase activity, this probe provides consistent monitoring of tumor growth kinetics during progression and in response to drug treatment and enables in situ screening of telomerase inhibitors in whole-animal models. This study provides an alternative toolkit for cancer diagnosis, treatment response assessment, and anticancer drug screening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗