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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Fractional Modeling in Action: A Survey of Nonlocal Models for Subsurface Transport, Turbulent Flows, and Anomalous Materials

Modeling of phenomena such as anomalous transport via fractional-order differential equations has been established as an effective alternative to partial differential equations, due to the inherent ability to describe large-scale behavior with greater efficiency than fully-resolved classical models. In this review article, we first provide a broad overview of fractional-order derivatives with a clear emphasis on the stochastic processes that underlie their use. We then survey three exemplary application areas – subsurface transport, turbulence, and anomalous materials – in which fractional-order differential equations provide accurate and predictive models. For each area, we report on the evidence of anomalous behavior that justifies the use of fractional-order models, and survey both foundational models as well as more expressive state-of-the-art models. We also propose avenues for future research, including more advanced and physically sound models, as well as tools for calibration and discovery of fractional-order models.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1981

On the spectrum of turbulent magnetic fields

Theoretical power spectra of magnetic fields subject to turbulent fluid motions in the kinematic regime are presented, and previous theories are reviewed, with reference to magnetic fields on the sun. Magnetic field diffusion in turbulence with persistent eddies is predicted to be described by an effective negative magnetic diffusivity. It is found that observations cannot be explained on the basis of turbulent kinematic theories unless the turbulent motions are three-dimensional, and the effective diffusivities are larger than the molecular diffusivities. Lower bounds on the turbulent viscosity are derived, suggesting that dynamical processes controlling the magnetic field spectrum occur at least 15,000 km below the surface. The results, which remain consistent with the assumption that effective diffusivity is uniform, suggest that surface magnetic field observations can be used as a diagnostic for subsurface flows.

Knobloch, E.↗
NASA NTRS1999

Characterization of Regolith Volatile Transport and Storage Properties by The MECA MSP 2001 Lander Payload

The diffusive and adsorptive properties of the Martian regolith influence the exchange of volatiles between the atmosphere and subsurface. Our quantitative knowledge of these properties is extremely poor -introducing substantial uncertainties in efforts to model long-term evolution of ground ice and diurnal, seasonal, and climatic cycles of CO2 and H20. This situation should significantly improve upon arrival of the 2001 Mars Surveyor Lander in 2002. In support of the Human Exploration and Development of Space (HEDS) enterprise, the 2001 mission will include a suite of instruments to characterize the nature of the Martian environment and assess whether it contains hazards that may threaten future human exploration. A major element of this effort is the Mars Environmental Compatibility Assessment (MECA) payload, which consists an optical microscopy system incorporating electrostatic, magnetic, and scratch-hardness materials testing palets, an atomic force microscope with imaging capabilities comparable to an SEM, a wet chemistry laboratory with four independent test cells, an electrometer on the robotic arm, material test patches, a camera also mounted on the arm, and a soil scoop for excavating down to about 50 cm into the soil. Although conceived to address the needs of HEDS, MECA payload is a sophisticated soil science laboratory that should provide a wealth of new data relevant to the volatile transport and storage properties of the regolith. Additional information os contained in the original.

Clifford, S. M.↗
DOE OSTI2022

Effects of Charged Solute-Solvent Interaction on Reservoir Temperature during Subsurface CO2 Injection

A short-term side-effect of CO2 injection is a developing low-pH front that forms ahead of the bulk water injectant, due to differences in solute diffusivity. Observations of downhole well temperature show a reduction in aqueous-phase temperature with the arrival of a low-pH front, followed by a gradual rise in temperature upon the arrival of a high concentration of bicarbonate ion. In this work, we model aqueous-phase transient heat advection and diffusion, with the volumetric energy generation rate computed from solute-solvent interaction using the Helgeson–Kirkham–Flowers (HKF) model, which is based on the Born Solvation model, for computing specific molar heat capacity and the enthalpy of charged electrolytes. A computed injectant water temperature profile is shown to agree with the actual bottom hole sampled temperature acquired from sensors. The modeling of aqueous-phase temperature during subsurface injection simulation is important for the accurate modeling of mineral dissolution and precipitation because forward dissolution rates are governed by a temperature-dependent Arrhenius model.

58 GEOSCIENCES↗
DOE OSTI2021

Groundwater Inflows to the Columbia River Along the Hanford Reach and Associated Nitrate Concentrations

Healthy river ecosystems require the interaction of many physical and biological processes to maintain their status. One physical process supporting biogeochemical cycling is hydrologic exchange (i.e., hydrologic exchange flows, HEFs) between relatively fast-flowing channel waters and slower-flowing surface and subsurface waters (lateral and vertical). Land uses adjacent to rivers have the potential to alter the water quality of off-channel surface and subsurface waters, and HEFs therefore have the potential to deliver solutes associated with river-adjacent land uses to rivers. HEFs can be nonpoint, diffuse sources of pollution, making the ultimate pollution source difficult to identify, especially in large rivers. Here, we seek to identify HEFs in the Columbia River near Richland, WA by looking for anomalies in temperature and electrical conductivity (EC) along the bed of the river in February, June, July, August, and November 2018. These are ultimately the “ends” of HEFs as they are locations of subsurface inflow to the river. We found these anomalies to be a combination of warmer or colder and higher (but not lower) EC than river water. We identified a majority of warm anomalies in February and July 2018, and majority cold anomalies in June, August, and November 2018. High-EC anomalies were found mostly in February, August, and November. Combined, we observe a shift from warm, high EC anomalies dominating in February to equivalent EC, warm anomalies in June, to equivalent EC, cool anomalies dominating July. In August, we also measured dissolved nitrate ($NO^-_3$) in-situ to determine whether anomalies were associated with increased $NO^-_3$ loading to the river, especially along the eastern shoreline, which is dominated by agricultural land use. Inflows along the eastern shoreline have greater concentrations of nitrate than river water (up to 10 mg $N–NO^-_3$/L). This research demonstrates that HEFs are temporally and spatially dynamic transferring heat and solutes to rivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Reactive Transport Modeling with Physics-Informed Machine Learning for Critical Minerals Applications

This study presents a physics-informed neural network (PINN) framework for reactive transport modeling for simulating fast bimolecular reactions in porous media. Accurate characterization of cAhemical interactions and product formation in surface and subsurface environments is essential for advancing critical mineral extraction and related geoscience applications. The proposed methodology sequentially addresses the flow and diffusion–reaction subproblems. The flow field is computed using a mixed formulation, while the diffusion–reaction system is modeled via two uncoupled tensorial diffusion equations reformulated in terms of chemical invariants. PINNs are employed to solve the governing equations, enabling data-efficient, mesh-free prediction of chemical concentration fields. The framework is validated through a series of benchmark problems involving flow in heterogeneous porous media. Initial verification is conducted using patch tests for the flow field, followed by validation of the transport problem with emphasis on preserving non-negativity of concentrations. The complete fast bimolecular reaction scenario is then solved, yielding spatial distributions of reactants and product species. Results demonstrate that the PINNs-based approach effectively captures sharp, mixing-limited reaction fronts and dispersive mixing behavior, offering reliable predictions of reactive plume evolution. These capabilities are crucial for evaluating long-term subsurface behavior in applications such as fluid storage, energy extraction, and efficient extraction of critical minerals.

42 ENGINEERING↗
NASA NTRS2022

Instantaneous Photosynthetically Available Radiation (IPAR) prediction models based on Neural Network for ocean waters.

Instantaneous photosynthetically available radiation (IPAR) at the ocean surface and its vertical profile below the surface play a critical role in models to calculate net primary productivity of marine phytoplankton. In this work, we report two IPAR prediction models based on neural network (NN) approach, one for open ocean and the other for coastal waters. These models are trained, validated, and tested using a large volume of synthetic datasets for open ocean and coastal waters simulated by a radiative transfer model. Our NN models are designed to predict IPAR under a large range of atmospheric and oceanic conditions. The NN models can compute subsurface IPAR profile very accurately up to euphotic zone depth. The root mean square errors associated with the diffuse attenuation coefficient of IPAR are less than 0.011 𝑚−1 and 0.036 𝑚−1 for open ocean and coastal waters respectively. The performance of the NN models is better than presently available semi analytical models, with significant superiority in coastal waters.

PACE↗
DOE OSTI2024

Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE). Pulsed infrared thermography (PIT) is a non-contact, one-sided NDE method that allows for imaging of internal defects in arbitrary size and shape metallic structures using heat transfer. PIT imaging is performed using compact instrumentation consisting of a flash lamp for deposition of a heat pulse, and a fast frame infrared (IR) camera for measuring surface temperature transients. However, limitations of imaging resolution with PIT include blurring due to heat diffusion, sensitivity limit of the IR camera. We demonstrate enhancement of PIT imaging capability with unsupervised learning (UL), which enables PIT microscopy of subsurface defects in high strength corrosion resistant stainless steel 316 alloy. PIT images were processed with UL spatial–temporal separation-based clustering segmentation (STSCS) algorithm, refined by morphology image processing methods to enhance visibility of defects. The STSCS algorithm starts with wavelet decomposition to spatially de-noise thermograms, followed by UL principal component analysis (PCA), fine-tuning optimization, and neural learning-based independent component analysis (ICA) algorithms to temporally compress de-noised thermograms. The compressed thermograms were further processed with UL-based graph thresholding K-means clustering algorithm for defects segmentation. The STSCS algorithm also includes online learning feature for efficient re-training of the model with new data. For this study, metallic specimens with calibrated microscopic flat bottom hole defects, with diameters in the range from 203 to 76 µm, were produced using electro discharge machining (EDM) drilling. While the raw thermograms do not show any material defects, using STSCS algorithm to process PIT images reveals defects as small as 101 µm in diameter. To the best of our knowledge, this is the smallest reported size of a sub-surface defect in a metal imaged with PIT, which demonstrates the PIT capability of detecting defects in the size range relevant to quality control requirements of LPBF-printed high-strength metals.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Subsurface Growth of CoSi2 by Deposition of Co on Si-Capped CoSi2 Seed Regions

At a growth temperature of 800 C, Co deposited on Si(111) diffuses through a Si cap and exhibits oriented growth on buried CoSi2 grains, a process referred to as endotaxy. This occurs preferentially to surface nucleation of CoSi2 provided the thickness of the Si cap is less than a critical value between 100 and 200 nm for a deposition rate of 0.01 nm/s. Steady-state endotaxy is modeled under the assumption that the process is controlled by Co diffusion.

Fathauer, R. W.↗
DOE OSTI2025

The rigorous upscaling of advection-dominated transport in heterogeneous porous media via the Method of Finite Averages

Systems involving advection-dominated transport through heterogeneous porous and fractured media are ubiquitous in subsurface engineering applications. However, upscaling such systems continues to challenge rigorous modeling efforts, particularly when advection is stronger than diffusion at fine spatial scales (i.e., when the Péclet number is greater than one at length scales that characterize a system’s unit-cells, representative elementary volumes, or averaging regions). Here, in this work, we propose and validate a strategy for extending the Method of Finite Averages (MoFA), a rigorous upscaling methodology for heterogeneous porous media, to upscale transport systems experiencing stronger advection than diffusion at fine scales (i.e., fine-scale Péclet numbers greater than one). We detail the strategy, the physical conditions under which it can be applied while retaining a priori modeling error guarantees, and implement the strategy to obtain a MoFA model for advective-diffusive transport that accommodates advective physics at fine spatial scales. We then perform two numerical experiments considering systems with system-scale Péclet numbers of 300 and 1000 — which correspond to fine-scale Péclet numbers of 30 and 100, respectively — to verify that the error guarantees are met under the strategy. After, we conduct a numerical study to demonstrate the strategy’s advantages over the original MoFA methodology. The results suggest that rigorously-upscaled transport models for heterogeneous porous media experiencing advective physics at finer spatial scales can be derived through MoFA and resolved orders of magnitude faster than their pore-scale counterparts. The results also suggest that the presented strategy is limited to modeling shallow concentration gradients when there are large differences between the time scales related to advection and a system’s temporally-varying boundary conditions. This limitation hinders the strategy’s practicality in modeling more advective systems, and as such, opportunity exists for developing additional strategies that accommodate rapidly-varying boundary conditions — and consequentially, steeper concentration gradients — while modeling advective systems with MoFA.

36 MATERIALS SCIENCE↗
NASA NTRS1983

Radar and infrared remote sensing of terrain, water resources, arctic sea ice, and agriculture

Radar range measurements, basic waveforms of radar systems, and radar displays are initially described. These are followed by backscatter from several types of terrain and vegetation as a function of frequency and grazing angle. Analytical models for this backscatter include the facet models of radar return, with range-angle, velocity-range, velocity-angle, range, velocity, and angular only discriminations. Several side-looking airborne radar geometries are presented. Radar images of Arctic sea ice, fresh water lake ice, cloud-covered terrain, and related areas are presented to identify applications of radar imagery. Volume scatter models are applied to radar imagery from alpine snowfields. Short pulse ice thickness radar for subsurface probes is discussed in fresh-water ice and sea ice detection. Infrared scanners, including multispectral, are described. Diffusion of cold water into a river, Arctic sea ice, power plant discharges, volcanic heat, and related areas are presented in thermal imagery. Multispectral radar and infrared imagery are discussed, with comparisons of photographic, infrared, and radar imagery of the same terrain or subjects.

Biggs, A. W.↗
DOE OSTI2021

Effect of CO 2 -brine-rock reactions on pore architecture and permeability in dolostone: Implications for CO 2 storage and EOR

Geologic carbon sequestration (GCS) is considered a feasible technology for storing substantive volumes of greenhouse gases in subsurface geological formations. In the reservoir, far from carbon dioxide (CO 2 ) injection wells or in post-injection scenarios, diffusion dominates over advection. This condition conjoins with spatially distributed geochemical reactions to induce heterogeneous changes in pore architecture, i.e. pore body and throat sizes or surface roughness. These changes can affect CO 2 transport properties and storage capacity. In this work, we investigated mineral dissolution and precipitation in dolomite samples saturated with a CO 2 -saturated brine at 93 °C and 34.5 MPa, aged without flow. Two rock types samples, i.e. intergranular- and vuggy-dominant, were selected to investigate changes in pore size, porosity and permeability under reactive conditions. Mineral dissolution and precipitation were characterized using scanning electron microscopy. Changes in pore size were quantified via time-domain nuclear magnetic resonance (TD-NMR) transverse relaxation time (T 2 ) and diffusion coefficient (D) distributions. We show that mineral dissolution likely occurs in highly permeable pathways. These observations are confirmed through analysis of (T 2 ) and diffusion coefficient (D) distributions. In contrast to results during CO 2 -enriched brine continuous injection, mineral precipitation was observed in micropores. The leftward shift of the T 2 peaks, corresponding to micropores, also evidenced mineral precipitation in lowpermeability zones. However, microscale alterations resulted only in a subtle increase in porosity and permeability. Results in this study shed light on effects of geochemical reactions on alteration of rock properties in diffusion-dominated regions during CO 2 storage.

58 GEOSCIENCES↗
DOE OSTI2023

Automated Symbolic Upscaling: 1. Model Generation for Extended Applicability Regimes

Abstract In porous media theory, upscaling techniques are fundamental to deriving rigorous Darcy‐scale models for flow and reactive transport in subsurface systems. Due to limitations in classical techniques, a number of ad hoc approaches have been proposed to address physical regimes in which reactive time scales are similar to, or faster than, diffusive time scales. In Part 1 of this two part series, we present a strategy for expanding the applicability of classical homogenization theory by generalizing the assumed closure form. We detail the implementation of this strategy on two reactive mass transport problems with moderately reactive physics. The strategy produces nontrivial homogenized models with emergent terms and effective parameters that couple reactive, diffusive, and advective transport. The differences in equation forms between the macroscopic and pore‐scale descriptions advise caution to further studies where the forms of macroscopic equations are assumed, as opposed to rigorously derived. Numerical validation is provided for each problem to show that the error estimates of homogenization theory are satisfied, and to justify the implemented strategy. In Part 2, the presented strategy is automated using symbolic computing to expedite its implementation.

Pietrzyk, Kyle↗
DOE OSTI2026

Regularization by denoising diffusion models for solving inverse PDE problems with application to full waveform inversion

Partial differential equation (PDE)-governed inverse problems are fundamental across various scientific and engineering applications; yet they face significant challenges due to nonlinearity, ill-posedness, and sensitivity to noise. Here, we introduce a computational framework, regularization by denoising using diffusion models for partial differential equations (RED-DiffEq), by integrating physics-driven inversion and data-driven learning. RED-DiffEq leverages pretrained diffusion models as a regularization mechanism for PDE-governed inverse problems. We apply RED-DiffEq to solve the full waveform inversion problem in geophysics, a challenging seismic imaging technique that seeks to reconstruct high-resolution subsurface velocity models from seismic measurement data. Our method shows enhanced accuracy and robustness compared to benchmark methods. Additionally, it exhibits strong generalization and domain decomposition capacity, enabling the inversion of more complex velocity models with larger domains than those used in training the diffusion model. Our framework can also be directly applied to diverse PDE-governed inverse problems.

Shan, Siming [Yale University, New Haven, CT (Unit↗
DOE OSTI2021

Rapid Alloy Surface Engineering through Closed-Vessel Reagent Pyrolysis

For rapid surface engineering of Cr-containing alloys by low-temperature nitrocarburization, we introduce a process based on pyrolysis of solid reagents, e.g., urea, performed in an evacuated closed vessel. Upon heating to temperatures high enough for rapid diffusion of interstitial solute, but low enough to avoid second-phase precipitation, the reagent is pyrolyzed to a gas atmosphere containing molecules that (i) activate the alloy surface by stripping away the passivating Cr 2 O 3 -rich surface film (diffusion barrier) and (ii) rapidly infuse carbon and nitrogen into the alloy. We demonstrate quantitatively that this method can generate a subsurface zone with concentrated carbon and nitrogen comparable to what can be accomplished by established (e.g., gas-phase- or plasma-based) methods, but with significantly reduced processing time. As another important difference to established gas-phase processing, the interaction of gas molecules with the alloy surface can have auto-catalytic effects by altering the gas composition in a way that accelerates solute infusion by providing a high activity of HNCO. The new method lends itself to rapid experimentation with a minimum of laboratory equipment.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Gas-phase hydrogen permeation through alpha iron, 4130 steel, and 304 stainless steel from less than 100 C to near 600 C

Gas phase hydrogen permeation studies were conducted on hollow, cylindrical membranes of triply zone-refined alpha iron, AISI 304 austenitic stainless steel, and AISI-SAE 4130 steel in both the normalized (ferrite and carbide) and quenched and tempered (martensite) conditions. Membrane temperature was varied from less than 100 C to near 600 C and hydrogen pressure was varied. For one membrane material, normalized 4130 steel, gas phase hydrogen transport under both steady state and nonsteady state conditions was demonstrated to be controlled by lattice diffusion. Additionally, Sievert's law was shown to be applicable. For all membrane materials, expressions for the coefficients for hydrogen permeation were determined by analysis of steady state transport; the coefficients for diffusion were determined by the lag time technique applied to nonsteady state transport; and through a knowledge of the Sievert's constants, the subsurface equilibrium lattice hydrogen concentrations were determined.

Nelson, H. G.↗
DOE OSTI2025

Drought-induced changes in groundwater-surface water exchange at Lake Mead area

This study focuses on the Lake Mead region in the southwestern United States, a key water reservoir serving over 25 million people and agricultural lands across several states. The area has experienced recurring anthropogenic droughts since the early 2000s. We investigate the hydrological response of the coupled surface-groundwater system to the 2020–2022 drought, one of the most severe on record. To this end, we use Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) data to quantify vertical land motion caused by the elastic response of the crust to water-mass loss in the lake vicinity. Next, we apply an inverse elastic load modeling framework to quantify water loss. We further assess possible hydraulic connectivity between Lake Mead and adjacent groundwater reservoirs. We detect ground uplift of up to 8 mm/yr near the lake center, likely due to crustal rebound from reduced water-mass loading. We estimated the total water storage loss at 3.03 ± 0.25 km 3 /yr across a 3150 km 2 area surrounding Lake Mead. Groundwater accounts for approximately a third of that, being 0.94 ± 0.32 km 3 /yr. In addition, observed time lags of 6–98 days between lake and groundwater level responses, corresponding to a lateral diffusivity of 3.2–86 m 2 /s, suggest spatially variable connectivity between the lake and aquifers. These findings highlight that drought impacts propagate through the subsurface within interconnected systems, resulting in reduced buffering capacity of groundwater resources following droughts, and emphasizing the need for more integrated surface and groundwater management strategies to enhance resilience under climate and anthropogenic stressors.

58 GEOSCIENCES↗
NASA NTRS1984

Macrosegregation in aluminum alloy ingot cast by the semicontinuous direct chill method

A theoretical model of the semicontinuous DC casting method is developed to predict the positive segregation observed at the subsurface and the negative segregation commonly found at the center of large commercial-size aluminum alloy ingot. Qualitative analysis of commercial-size aluminum alloy semicontinuous cast direct chill (DC) ingot is carried out. In the analysis, both positive segregation in the ingot subsurface and negative segregation at the center of the ingot are examined. Ingot subsurface macrosegregation is investigated by considering steady state casting of a circular cross-section binary alloy ingot. Nonequilibrium solidification is assumed with no solid diffusion, constant equilibrium partition ratio, and constant solid density.

Yu, H.↗