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DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang↗

DOE OSTI2023

Charged particle reconstruction in CLAS12 using Machine Learning

In this work, we present studies of track parameter reconstruction from raw information in CLAS12 detector's Drift Chambers, using Machine Learning (ML). We study the resolution of tracks reconstructed with different types of ML models/algorithms, including Multi-Layer Perceptron (MLP), Extremely Randomized Trees (ERT) and Gradient Boosting Trees (GBT) using simulated data. We find that the resulting ML model is capable of reconstructing track parameters (particle momentum, and polar and azimuthal angles) with accuracy similar to Hit Based (HB) tracking code, but $150$ times faster. Moreover, physics reactions can be identified using the particles reconstructed by the neural network in real-time (with a rate of about $34~kHz$) during experimental data collection. The developed model can be used in numerous applications, such as triggering specific physics reactions in real-time, detector performance monitoring, and real-time detector calibration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Differentiable modelling to unify machine learning and physical models for geosciences

Process-based modelling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. Here, in this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.

58 GEOSCIENCES↗

DOE OSTI2023

An Initial Look at the Magnetic Design of a 150 mm Aperture High-Temperature Superconducting Magnet With a Dipole Field of 8 to 10 T

High-temperature superconducting REBa 2 Cu 3 O 7-$x$ (rebco) conductors have the potential to generate a high magnetic field over a broad temperature range. The corresponding accelerator magnet technology, still in its infancy, can be attractive for future energy-frontier particle colliders such as a multi-TeV muon collider. To help develop the technology, we explore the requirements and potential characteristics of a rebco magnet, operating at 4.2 or 20 K, with a dipole field of 8-10 T in a clear aperture of 150 mm. We use the canted cos $\theta$ magnet configuration to reduce the electromagnetic stresses on the conductors. We present the resulting dipole fields, field gradients for combined-function cases, conductor stresses, magnet dimensions and conductor lengths. We also discuss the conductor performance that is required to achieve the target dipole field at 4.2 and 20 K. In conclusion, the information can provide useful input to the development of rebco magnet and conductor technology for collider-ring magnets in a muon collider.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Water Level Data from Wells PLM1 and PLM6 for the East River Watershed, Colorado

This dataset (Williams et al., 2020) contains the original un-QA/QC-ed water level data for PLM1 and PLM6 and has been obsoleted. The data contained within this dataset is not to be used. Refer to Faybishenko et al., 2022 (DOI: 10.15485/1866836) for the latest QA/QC-ed data available via ESS-DIVE.This data set contains water level data for the PLM1 and PLM6 wells. PLM1 and PLM6 are location identifiers used by the Watershed Function SFA project for two groundwater monitoring wells along an elevation gradient located along the lower montane life zone of a hillslope near the Pumphouse location. These wells used to monitor subsurface water and carbon inventories and fluxes at the East River Watershed, Colorado, USA. Complete metadata information on the PLM1 and PLM6 wells are available in the related data package reference Varadharajan C, et al (2020). https://doi.org/10.15485/1660962.Data are reported in .csv files per well. The latitude and longitude of each location are given in a file called locations.csv. These data are used for determining the seasonally dependent flow of groundwater under the PLM hillslope. The downslope flow of groundwater in combination with data on groundwater chemistry can be used to estimate rates of solute export from the hillslope to the floodplain and river.These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1977

Wintertime density perturbations near 50 km in relation to latitude

Standard and reference atmospheres which depict the horizontal distribution of air density in the stratosphere and mesosphere are not realistic in that they do not provide information on the large departures from standard that may occur during a given month, nor on the time- and space-scales of atmospheric perturbations responsible for these departures. In the present paper, it is shown how this information can be obtained from a special analysis of satellite radiance measurements. Plots of the mean zonal radiance, obtained with the VTPR instrument, and the corresponding 50-km density show not only the expected strong poleward gradient of density, but also a strong density surge from late December to early January, affecting all latitudes.

Quiroz, R. S.↗

NASA NTRS1989

Thermal structure and heat balance of the outer planets

Current knowledge of the thermal structure and energy balance of the outer planets is summarized. The Voyager spacecraft experiments have provided extensive new information on the atmospheric temperatures and energetics of Jupiter, Saturn and Uranus. All three planets show remarkably small global-scale horizontal thermal contrast, indicating efficient redistribution of heat within the atmospheres or interiors. Horizontal temperature gradients on the scale of the zonal jets indicate that the winds decay with height in the upper troposphere. This suggests that the winds are driven at deeper levels and are subjected to frictional damping of unknown origin at higher levels. Both Jupiter and Saturn have internal power sources equal to about 70 percent of the absorbed solar power. This result is consistent with the view that significant helium differentiation has occurred on Saturn. Uranus has an internal power no greater than 13 percent of the absorbed solar power, while earth-based observations suggest Neptune has an internal power in excess of 100 percent of the absorbed solar power.

Conrath, B. J.↗

NASA NTRS1992

Cassini/CIRS capabilities for aerosol, cloud, and surface measurements

Information that should be revealed by the Cassini Composite Infrared Spectrometer (CIRS) about the aerosol, cloud, and surface properties of Titan are addressed. Limb sounding data will be used to determine aerosol abundances, scale heights, and gradients between 80 and 400 km for various latitudes. Stratospheric condensate cloud top altitudes and column abundances will be inferred as functions of latitude. A search for new species will be conducted. Thermal maps between 500 and 550/cm will be used to investigate tropospheric methane clouds and surface topography; time resolution provided by different orbits will be used to distinguish the two.

Samuelson, Robert E.↗

NASA NTRS1993

The thickness of eucritic crust in the HED parent body

Because cumulate eucrites are generally thought to be located at the lower part in eucritic crust on a diogenitic mantle in the HED parent body, the burial depth of cumulate eucrites gives information on the thickness of the eucritic crust. We estimated the burial depth and cooling rate of cumulate eucrites, Serra de Mage and Moore County on the basis of the width of augite lamellae and compositional gradients of Ca in pyroxenes by numerically solving the diffusion equation. We obtained the burial depth of the eucrites of 7-8 km and cooling rate of 0.00016-0.0002 degrees C/yr.

Miyamoto, M.↗

NASA NTRS2026

Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder

Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.

Mahyar Garshasbi↗

DOE OSTI2022

Differential holography

Differential Holography technology measures the amplitude and/or phase of, e.g., an incident linearly polarized spatially coherent quasi-monochromatic optical field by optically computing the first derivative of the field and linearly mapping it to an irradiance signal detectable by an image sensor. This information recorded on the image sensor is then recovered by a simple algorithm. In some embodiments, an input field is split into two or more beams to independently compute the horizontal and vertical derivatives (using amplitude gradient filters in orthogonal orientations) for detection on one image sensor in separate regions of interest (ROIs) or on multiple image sensors. A third unfiltered beam recorded in a third ROI directly measures amplitude variations in the input field to numerically remove its contribution as noise before recovering the original wavefront using a numerical in algorithm. When combined, the measured amplitude and phase constitute a holographic recording of the incident optical field.

Ravizza, Frank↗

DOE OSTI2025

Entanglement, trace anomaly, and confinement in QCD

We formulate confinement in quantum chromodynamics (QCD) as an entropic surface phenomenon. Quark and gluon quantum information is localized on a transverse, entangling two-sphere of radius 𝑅 𝐸⁢𝐸 ; at this radius the QCD vacuum—partitioned by a hadron into interior and exterior regions—reaches its maximal entanglement entropy. Lattice-QCD determinations of the scalar (trace) gravitational form factors fix both 𝑅 𝐸⁢𝐸 and the transverse trace-anomaly density 𝜌 ℎ ⁡(𝑅 𝐸⁢𝐸 ), yielding a parameter-free slope 𝑐 ℎ = 8⁢𝜋 2 ⁢𝑅𝑆$^2_{𝐸⁢𝐸}$𝜌 ℎ ⁡(𝑅 𝐸⁢𝐸 ) and a mechanical entropy 𝑆 𝐸⁢𝐸 ⁡(𝑦) = 𝑐 ℎ ⁢𝑦 that grows linearly with rapidity 𝑦. The entropy gradient ∂ 𝑅 𝑆 𝐸⁢𝐸 changes sign at 𝑅 𝐸⁢𝐸 : it pushes colored degrees of freedom outward for 𝑟 <𝑅 𝐸⁢𝐸 and pulls them inward for 𝑟 >𝑅 𝐸⁢𝐸 , thereby localizing them on the codimension-2 entangling two-sphere Σ ⊥ = 𝑆$^2_{𝑅_{𝐸⁢𝐸}}$ (which, in the infinite-momentum frame (IMF), projects onto the transverse plane)—the “information wall.” This provides a high-energy (large-𝑦) entropic confinement diagnostic that complements—rather than replaces—Wilson’s area-law criterion, which probes long-distance dynamics near the rest frame (𝑦 → 0). Imposing unitarity on an entropic ansatz for the amplitude yields 𝜎⁡(𝑠) ∝ 𝑦 𝛿 . World data favor 𝛿 = 2 for elastic 𝑝⁡𝑝⁡($𝑝\bar{⁡𝑝}$) scattering and heavy-quark photoproduction, whereas 𝜙 photoproduction favors a softer 𝛿 = 0.387. All extracted cross sections remain well below the Froissart-Martin bound. These results provide a confinement criterion quantified directly from nonperturbative QCD inputs, unifying the trace anomaly, entanglement entropy, and high-energy scattering within a single quantitative framework.

Color confinement↗

DOE OSTI2024

Inoculated biocrust cover and functions diverged over a gradient of soil textures and water availability

Restoring biological crust (biocrust) in disturbed drylands is challenging due to the difficult environmental conditions, such as limited soil moisture, low soil nutrients, and extreme temperatures, that impede growth. Understanding how the key components of biocrust—mosses, lichens, and cyanobacteria—react to different environmental factors informs the optimal timing, locations, and species composition for biocrust reintroduction, thereby increasing the likelihood of establishment. Here, we inoculated soils with a diverse range of biocrust organisms, analogous to seeding an area with diverse vascular plant seeds, and varied environmental conditions to observe how these changes influenced the development and functions of reintroduced biocrust. We found that by manipulating soil texture and time spent wet, we can change the proportional cover of biocrust within a restoration‐like setting. Specifically, we found that 4 months after inoculation, finer textured soils that received more water become dominated by moss cover, while coarser textured soils with less water remained dominated by cyanobacteria cover, and the interactions between texture and time spent wet strongly influenced cover. We found biocrust morphological group cover had a small, but detectable, effect on ecosystem functions (soil stability and nitrogenase activity, a proxy for nitrogen fixation), but that environmental conditions had a stronger impact on the functions we measured. Manipulative experiments in controlled environments, like this one, can help elucidate the mechanisms underlying the establishment rate and patterns of biocrusts post‐inoculation, and inform implementation of inoculations in the field.

Environmental Sciences & Ecology↗

NASA NTRS1973

Heat flow and convection demonstration (Apollo 14)

Apollo 14 Astronaut Stuart A. Roosa conducted a group of experiments during the lunar flyback on February 7, 1971, to obtain information on heat flow and convection in gases and liquids in an environment of less than 0.000001 g. Flow observations and thermal data have shown that: (1) as expected, there are convective motions caused by surface tension gradients in a plane liquid layer with a free upper surface; (2) heat flow in enclosed liquids and gases occurs mainly by diffusive heat conduction; and (3) some convective processes, whose characteristics are not fully known, add to the heat transfer. The raw data are presented, and the analysis approach is given.

Bannister, T. C.↗

NASA NTRS1990

Clutter filter design considerations for Airborne Doppler radar detection of windshear

The problem of clutter rejection when processing down-looking Doppler radar returns from a low altitude airborne platform is a paramount problem. With radar as a remote sensor for detecting and predicting windshear in the vicinity of an urban airport, dynamic range requirements can exceed 50 dB because of high clutter to signal ratios. This presentation describes signal processing considerations in the presence of distributed and/or discrete clutter interference. Previous analyses have considered conventional range cell processing of radar returns from a rigidly mounted radar platform using either the Fourier or the pulse-pair method to estimate average windspeed and windspeed variation within a cell. Clutter rejection has been based largely upon analyzing a particular environment in the vicinity of the radar and employing a variety of techniques to reduce interference effects including notch filtering, Fourier domain line editing, and use of clutter maps. For the airborne environment the clutter characteristics may be somewhat different. Conventional clutter rejection methods may have to be changed and new methods will probably be required to provide useful signal to noise ratios. Various considerations are described. A major thrust has been to evaluate the effect of clutter rejection filtering upon the ability to derive useful information from the post-filter radar data. This analysis software is briefly described. Finally, some ideas for future analysis are considered including the use of adaptive filtering for clutter rejection and the estimation of windspeed spatial gradient directly from radar returns as a means of reducing the effects of clutter on the determination of a windshear hazard.

Baxa, Ernest G., Jr.↗

NASA NTRS1995

Shape optimization of single- and two-element airfoils on multiblock grids

A multiblock, discrete sensitivity analysis method is used to couple a direct optimization method and a flow analysis method. The domain is divided into smaller subdomains for which the sensitivities are obtained separately. Then, an effective sensitivity equation is solved to complete the coupling of all the sensitivity information. The flow analysis is based on the thin-layer Navier-Stokes equations solved by an implicit, upwind-biased, finite-volume method. The method of feasible directions is used for the present gradient-based optimization approach. First, a transonic airfoil is optimized to investigate the behavior of the method in highly nonlinear flows as well as the effect of different blocking strategies on the procedure. A supercritical airfoil is produced from an initially symmetric airfoil with multiblocking affecting the path but not the final shape. Secondly, a two-element airfoil is shape optimized in subsonic flow to demonstrate the present method's capability of shaping aerodynamically interfering elements simultaneously. For a very low and a very high Reynolds number cases, the shape of the main airfoil and the flap are optimized to yield improved lift-to-drag ratios.

Lacasse, James M.↗

DOE OSTI2020

Calibration of parallel bond parameters in bonded particle models via physics-informed adaptive moment optimisation

This study proposes an automated calibration procedure for bond parameters in bonded discrete element modelling. By exploring the underlying physical correlations between microscopic parameters of bonds and macroscopic strength parameters of the continuum to be modelled, the microscopic shear strength and tensile strength are identified as independent variables for calibration purpose. Then a physics-informed iterative scheme is proposed to automatically approximate the bond parameters by viewing the micro-macro relation as an implicitly defined mathematical mapping function. As a result of highly non-convex features of this implicit mapping, the adaptive moment estimation (Adam), which is especially suitable for problems with noisy gradients, is adopted as the basic iterative scheme, in conjunction with other numerical techniques to approximately evaluate the partial derivatives involved. The whole procedure offers a simple and effective framework for bond parameter calibration. Finally, a numerical example of SiC ceramic is provided for validation. By compared with some existing calibration methods, the proposed method shows significant advantages in terms of calibration efficiency and accuracy.

42 ENGINEERING↗

NASA NTRS2013

MODIS 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region

MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.

MODIS↗