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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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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Multi-modal Free-moving Data Fusion (MFDF) v1.0

Multi-modal Free-moving Data Fusion (MFDF) is a python package that implements low and high-level functionality for performing qualitative and quantitative gamma-ray imaging analyses. Such analyses enable the use of gamma-ray spectrometers and/or imagers to estimate the distribution and quantity of radiological materials in an environment. Free-moving 3D imaging requires additional information about the 3D trajectory and orientation of the system, however all of these methods can be applied to 2D static gamma-ray imaging as well. The package includes methods (MLEM and MAP) for distributed source reconstruction, methods (PSL) for point source reconstruction, the ability to ingest and utilize quantitative detector response functions (for absolute analyses), and the ability to perform 3D estimation of dose-rates from quantitative reconstructions.

Joshi, Tenzing↗
DOE OSTI2023

Analysis of ducted fuel injection at high-pressure transcritical conditions using large-eddy simulations

Ducted fuel injection (DFI) is a proposed fuel injection concept for achieving substantial reductions in emissions. In this concept, the fuel is injected through a coannular duct, resulting in increased fuel-air mixing and minimized formation of soot and other unwanted combustion products. Apart from comprehensive experimental investigations on DFI, so far computational studies have been limited to single-point Reynolds-averaged Navier Stokes simulations. Therefore, the objective of this work is to complement these studies by performing large-eddy simulations using a diffuse-interface method to examine the physical mechanisms and combustion processes of DFI, specifically focusing on the mixing process and the effect of fuel-ducting on combustion and pollutant emissions. To this end, finite-rate chemistry simulations are performed of the DFI configuration corresponding to the Engine Combustion Network Spray A injector at transcritical conditions (n-dodecane fuel, 60 bar pressure and 1000 K temperature chamber conditions). A two-equation soot model is employed for the qualitative analysis of soot emissions. Direct comparisons of averaged and instantaneous flow field results with the Spray A configuration are performed to assess the effect of DFI on the first- and second-stage ignition and soot formation. Compared to the free-spray condition, the results show that the DFI case exhibits a combination of (i) increased mass flow rate and entrained air, (ii) larger pressure drop magnitude and flow velocity, and (iii) a closer-to-stoichiometric mixture composition (both globally and locally), each of which is conjectured to contribute toward reduced soot production.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Skyrme-Hartree-Fock-Bogoliubov mass models on a 3D mesh: III. From atomic nuclei to neutron stars

Here, we present BSkG3, the latest entry in the Brussels-Skyrme-on-a-grid series of large-scale models of nuclear structure based on an energy density functional. Compared to its predecessors, the new model offers a more realistic description of nucleonic matter at the extreme densities relevant to neutron stars. This achievement is made possible by incorporating a constraint on the infinite nuclear matter properties at high densities in the parameter adjustment, ensuring in this way that the predictions of BSkG3 for the nuclear Equation of State are compatible with the observational evidence for heavy pulsars with M > 2M ⊙ . Instead of the usual phenomenological pairing terms, we also employ a more microscopically founded treatment of nucleon pairing, resulting in extrapolations to high densities that are in line with the predictions of advanced many-body methods and are hence more suited to the study of superfluidity in neutron stars. By adopting an extended form of the Skyrme functional, we are able to reconcile the description of matter at high densities and at saturation density: the new model further refines the description of atomic nuclei offered by its predecessors. A qualitative improvement is our inclusion of ground state reflection asymmetry, in addition to the spontaneous breaking of rotational, axial, and time-reversal symmetry. Quantitatively, the model offers lowered root-mean-square deviations on 2457 masses (0.631 MeV), 810 charge radii (0.0237 fm) and an unmatched accuracy with respect to 45 primary fission barriers of actinide nuclei (0.33 MeV). Reconciling the complexity of neutron stars with those of atomic nuclei establishes BSkG3 as a tool of choice for applications to nuclear structure, the nuclear equation of state and nuclear astrophysics in general.

Physics↗
DOE OSTI2025

Quantum stabilization of unexpected ordered phases on the honeycomb lattice

In this work, I discuss and showcase the utility of the method called minimally-augmented spin-wave theory (MAGSWT) as a relatively simple semi-analytical approach to the phase diagrams of quantum magnets. It complements numerical methods by providing physical insight into which states are competitive and by yielding approximate phase boundaries that agree well with much more numerically intensive calculations. This approach enabled me to construct the faithful phase diagrams of two paradigmatic honeycomb-lattice models in the quantum S=1/2 limit, the J 1 –J 3 FM-AF and J 1 –J 2 AF models, for the collinear quantum phases that replace or extend the classical ones. The results are in good qualitative and semi-quantitative agreement with state-of-the-art numerical studies for these models, correctly capturing the emergence of unexpected quantum phases and the suppression of classically favored spiral orders by quantum fluctuations. This study provides a much-needed important guidance to the ongoing theoretical and experimental searches of the unconventional quantum states. This work will be of significant and timely interest to both theorists and experimentalists in the field of quantum magnetism, broadly defined.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Semiclassical shell-structure micro-macroscopic approach for the level density

Level density ρ(E,A) is derived for a one-component nucleon system with a given energy E and particle number A within the mean-field semiclassical periodic-orbit theory beyond the saddle-point method of the Fermi gas model. We obtain ρ∝I ν (S)/S ν , with I ν (S) being the modified Bessel function of the entropy S. Within the micro-macro-canonical approximation (MMA), for a small thermal excitation energy U, with respect to rotational excitations E rot , one obtains ν = 3/2 for ρ(E,A). In the case of excitation energy U larger than E rot but smaller than the neutron separation energy, one finds a larger value of ν = 5/2. A role of the fixed spin variables for rotating nuclei is discussed. The MMA level density ρ reaches the well-known grand-canonical ensemble limit (Fermi gas asymptote) for large S related to large excitation energies, and also reaches the finite micro-canonical limit for small combinatorial entropy S at low excitation energies (the constant “temperature” model). Fitting the ρ(E,A) of the MMA to the experimental data for low excitation energies, taking into account shell and, qualitatively, pairing effects, one obtains for the inverse level density parameter K a value which differs essentially from that parameter derived from data on neutron resonances.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Size-Transferable Prediction of Excited State Properties for Molecular Assemblies with a Machine Learning Exciton Model

Computational modeling of the excited states of molecular aggregates faces significant computational challenges and size heterogeneity. Current machine learning (ML) models, typically trained on specific-sized aggregates, struggle with scalability. We found that the exciton model Hamiltonian of large aggregates can be decomposed into dimer pairs, allowing an ML model trained on dimers to reconstruct Hamiltonians for aggregates of any size. We also proposed a new method to address the phase-correction problem by introducing coupling terms’ approximations. Our model accurately predicted the excitation energies of the trimer and tetramer of perylene and tetracene and estimated S1 oscillator strengths of perylene aggregates. Leveraging our ML model, the optical gaps of nanosized perylene aggregates with up to 50 monomers are analyzed, qualitatively revealing the role of different couplings on their size dependency. Future work will explore transferability across different monomers to predict optical properties in heterogeneous assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Field Test Report Neutron Scintillator Array Dry Storage Cask Scanner FY2024

During two weeks of Field Testing at the Idaho National Laboratory INTEC Cask Farm in July and August 2024, the LLNL Dry Storage Cask Scanner Array was lifted on top of an MC-10 dry storage fuel cask and operated to acquire neutron and gamma-ray data from the 24 fuel bundle positions. Neutron and gamma-ray data acquisition scans across the top of the cask of varying dwell times were performed July 15-18, 2024 and August 19-22, 2024 to evaluate the ability of the scanner data to reveal asymmetries in the fuel positions that reflect asymmetries in the MC-10 cask fuel bundle loading. The MC-10 cask 24 position fuel bundle loading at the INTEC Cask Farm is well documented, including the locations of six empty fuel bundle positions. This loading presents an opportunity to test the ability of the scanner system to detect diversion of spent fuel bundles as well as to validate the MC-10 cask MCNP modeling. The cask scanner array consists of six Stilbene crystal scintillator detectors and a linear actuator frame that moves the six detectors across the MC-10 dry storage cask to obtain data above each of the 24 fuel bundle positions. The detectors are connected to a pulse-shape discrimination data acquisition system capable of generating separate neutron and gamma-ray spectra for each detector and for each scan position. From the prior single detector Field Test in 2021 and iteration with MCNP modeling, the neutron and gamma-ray data were analyzed in multiple energy regions to identify an analysis method that would provide the strongest and most consistent signature of the asymmetric MC-10 cask fuel loading1 . From both the 2021 Field Test and the current Field Test results, the neutron capture gamma-ray count rate around 2.2 MeV provides the strongest signature of the asymmetric MC-10 cask fuel loading and has qualitative agreement with MCNP calculations. Counting all gamma-rays produces a similar signature. Neutrons emerging from the cask top are moderated and captured by the hydrogen in the polyethylene moderator and scintillator detector, producing a 2.2 MeV gamma ray which is seen in the scintillator gamma-ray spectrum. The count rate in the 2.2 MeV gamma-ray region is ~50 c/s, which is ~1000x higher than the ~0.05 n/s rate in the > 4MeV neutron region, and ~50x greater than the ~1 n/s rate in the neutrons > 500 keV region. Analysis of the 2.2 MeV neutron-capture Compton-scattered gamma-rays produces a statistically significant signature of the INTEC Cask Farm MC-10 asymmetric fuel loading. MCNP simulations indicate that the average neutron energy spectrum offers the potential to detect a large asymmetry from several missing bundles as well as individual missing fuel bundles. Testing this feature will require measurements on a cask with single missing elements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Exciton Binding Energy in Organic Polymers: Experimental Considerations and Tuning Prospects

Discrepancies in reported values of exciton binding energy (E b ) for organic semiconductors (OSs) necessitate a comprehensive study. Traditionally, E b is defined as the difference between the transport gap (E t ) and the optical gap (E opt ). Here, the E b values of PBnDT‐TAZ polymer variants are determined using two commonly employed methods: a combination of ultraviolet photoemission spectroscopy and low‐energy inverse photoemission spectroscopy (UPS‐LEIPS) and solid‐state cyclic voltammetry (CV). E b values obtained by UPS‐LEIPS show low dispersion and no clear correlation with the polymer structure and thedielectric properties. In contrast, CV reveals a larger dispersion (200 meV‐1 eV) and an apparent qualitative E b ‐molecular structure correlation, as the lowest E b values are observed for oligo‐ethylene glycol side chains. This discrepancy is discussed by examining the implications of the traditional definition of E b . Additionally, the impact of both intrinsic and extrinsic factors contributing to the derived experimental values of E t is discussed. The differences in intrinsic and extrinsic factors highlight the context‐dependent nature of measurement when drawing global conclusions. Notably, the observed E b trend derived from CV is not intrinsic to the pure materials but likely linked to electrolyte swelling and associated changes in dielectric environment, suggesting that high‐efficiency single‐material organic photovoltaics with low E b may be possible via high dielectric materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Simulation of mineral dissolution at the pore scale with evolving fluid-solid interfaces: review of approaches and benchmark problem set

This manuscript presents a benchmark problem for the simulation of single-phase flow, reactive transport, and solid geometry evolution at the pore scale. The problem is organized in three parts that focus on specific aspects: flow and reactive transport (part I), dissolution-driven geometry evolution in two dimensions (part II), and an experimental validation of three-dimensional dissolution-driven geometry evolution (part III). Five codes are used to obtain the solution to this benchmark problem, including Chombo-Crunch, OpenFOAM-DBS, a lattice Boltzman code, Vortex, and dissolFoam. These codes cover a good portion of the wide range of approaches typically employed for solving pore-scale problems in the literature, including discretization methods, characterization of the fluid-solid interfaces, and methods to move these interfaces as a result of fluid-solid reactions. A short review of these approaches is given in relation to selected published studies. Results from the simulations performed by the five codes show remarkable agreement both quantitatively--based on upscaled parameters such as surface area, solid volume, and effective reaction rate--and qualitatively--based on comparisons of shape evolution. This outcome is especially notable given the disparity of approaches used by the codes. Therefore, these results establish a strong benchmark for the validation and testing of pore-scale codes developed for the simulation of flow and reactive transport with evolving geometries. They also underscore the significant advances seen in the last decade in tools and approaches for simulating this type of problem.

58 GEOSCIENCES↗
DOE OSTI2020

Simulation of mixed-mode fracture using the combined finite–discrete element method

It has been shown experimentally that under mixed tensile and compressive stress states, a corresponding mixed-mode fracture will occur. Here, the formation of mixed-mode fractures is investigated using the combined finite–discrete element method. A series of simulations with confining pressures ranging from 7.5 to 150 MPa generate a spectrum of mixed-mode failure conditions. These stress states at failure span the transition from the tensile to compressive failure. The models reproduce previous experiments on Carrara marble using a dog-bone geometry, and a comparison shows good qualitative agreement with the experimental observations. This paper demonstrates that mixed-mode fracture can be captured via numerical simulations and identifies areas where further research is required to better understand mixed-mode fracture processes.

42 ENGINEERING↗
DOE OSTI2024

Designing Remote Monitoring for Smart Manufacturing Facilities: Hazard Identification and Classification

This study investigates the process of hazard identification in complex manufacturing environments during the design phase, emphasizing the significance of the design process in developing designs that effectively mitigate hazards in contexts with numerous variables, such as a variety of machines, sensors, actuators, and agents. Through a mixed-methods approach, the objective of this work is to understand how the evolution of design outcomes across various stages might influence a designer’s ability to recognize both standard and novel hazards. To achieve this understanding, an experimental design task was conducted with six designers from a national lab specializing in manufacturing technologies. This approach combined qualitative and quantitative data analysis from a one-hour virtual session with participants. Findings suggest that the complexity of identifying hazards in a high-dimensional design space is challenging within a limited time frame and that the identification of hazards is significantly influenced by the stage of the design task and the initial design decisions, indicating the need for extended time and strategic initial planning in the design process to enhance hazard identification.

Ballestas, Caseysimone↗
DOE OSTI2023

Schneider Springs Fire Study 2023 for Ecosystem Respiration Rates: Surface Water Chemistry and Hydrologic Sensor Data across the Yakima River Basin, Washington, USA (v2)

This dataset supports a broader study examining the drivers of spatial variability in wildfire impacts across the Yakima River Basin. Data provided within this dataset were generated from sample collection across 17 total sites (8 sites affected by a recent wildfire, 9 sites unaffected by a recent wildfire) within multiple rivers throughout the Yakima River Basin in Washington, USA from May-July 2023. Fire affected sites are defined as those affected by the 2021 Schneider Springs Fire, based on the drainage area of the streams being within the 2021 Schneider Springs Fire burn perimeter or not (Figure 1, below). The contents include surface water geochemistry data (dissolved organic carbon; total dissolved nitrogen; total suspended solids); short-term sonde data (specific conductivity; turbidity; pH; chlorophyll A; temperature); stream depth data; stream velocity; manual chamber open channel respiration data; sensor time-series data (oxygen; water pressure; barometric pressure); field metadata (including qualitative information on in stream and river corridor characteristics); and environmental context photos taken in the field. The dataset also includes a summary file of the sensor data and plots of the sensor data. Sensors were only recovered at 15 out of the 17 sites, and not all sensors were recovered at all 15 sites (see Methods section for more details), therefore all data does not exist at all sites. Data from a 2022 study at the same sites, as well as additional sites, can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566. The data package was originally published in November 2023. It was updated in June 2025 (v2; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder with field photos and one main data folder with two subfolders. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) field protocol; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) stream depth and averages. The sensor data subfolder consists of (1) sensor installation methods summary; (2) stream velocity; and (3) six subfolders. The BarotrollAtm (barometric pressure; temperature), DepthHOBO (water pressure; temperature), MantaRiver (specific conductivity; turbidity; pH; chlorophyll A; temperature), EXO (specific conductivity; pH; temperature), miniDOT (dissolved oxygen; temperature), and miniDOTManualChamber (dissolved oxygen; temperature) contain time-series data, plots, and summary files. The sample data subfolder consists of (1) total suspended solids (TSS) data; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (3) total dissolved nitrogen (TN) data and averages; and (4) methods codes. All files are .csv, .pdf, .jpg, .jpeg, or .mov.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Explaining word embeddings with perfect fidelity: a case study in predicting research impact

The best-performing approaches for scholarly document quality prediction are based on embedding models. In addition to their performance when used in classifiers, embedding models can also provide predictions even for words that were not contained in the labelled training data for the classification model, which is important in the context of the ever-evolving research terminology. Although model-agnostic explanation methods, such as Local interpretable model-agnostic explanations, can be applied to explain machine learning classifiers trained on embedding models, these produce results with questionable correspondence to the model. We introduce a new feature importance method, Self-Model Entities Rated (SMER), for logistic regression-based classification models trained on word embeddings. We show that SMER has theoretically perfect fidelity with the explained model, as the average of logits of SMER scores for individual words (SMER explanation) exactly corresponds to the logit of the prediction of the explained model. Quantitative and qualitative evaluation is performed through five diverse experiments conducted on 50,000 research articles (papers) from the CORD-19 corpus. In conclusion, through an AOPC curve analysis, we experimentally demonstrate that SMER produces better explanations than LIME, SHAP and global tree surrogates.

Coarse-grained models↗
DOE OSTI2020

Inertial dynamics of an interface with interfacial mass flux: Stability and flow fields’ structure, inertial stabilization mechanism, degeneracy of Landau’s solution, effect of energy fluctuations, and chemistry-induced instabilities

This work focuses on the long-standing problem of inertial dynamics of an interface with interfacial mass flux and reports new mechanisms for the interface stabilization and destabilization. The interface is a phase boundary separating fluids of different densities and having interfacial mass flux. To analyze the interface dynamics from a far field, we develop and apply the general matrix method to rigorously solve the boundary value problem involving the governing equations in the fluid bulk and the boundary conditions at the interface and at the outside boundaries of the domain. We find the fundamental solutions for the linearized system of equations and analyze the interplay of interface stability with flow fields’ structure by directly linking rigorous mathematical attributes to physical observables. We find that the interface is stable when the dynamics conserves the fluxes of mass, momentum, and energy; the stabilization is due to an inertial mechanism causing small oscillations of the interface velocity. In the classic Landau’s dynamics, the postulate of perfect constancy of the interface velocity leads to the development of Landau–Darrieus instability. This destabilization is also linked to the imbalance of the perturbed energy at the interface. The classic Landau’s solution is found to have degeneracy; lifting of the degeneracy may lead to singularity and self-similar dynamics. Our results compare well with traditional theories of combustion and propose new experiments to study the dynamics of the interface and the flow fields in combustible systems. We further conduct reactive molecular dynamics simulations to elucidate the complexity of chemical processes, to study the destabilizing effect of energy fluctuations on the interface stability, and to illustrate the chemistry-induced instabilities. In summary, we identify the extreme sensitivity of the interface dynamics to the interfacial boundary conditions, including the formal properties of fundamental solutions and the qualitative and quantitative properties of the flow fields. This provides new opportunities for studies, diagnostics, and control of multiphase flows in a broad range of processes in nature and technology.

42 ENGINEERING↗
DOE OSTI2020

Quantitative assessment of eddy viscosity rans models for turbulent mixed convection in a differentially heated plane channel

Turbulent mixed convection between two vertical, infinite parallel plates at different temperatures is studied using various two-equation turbulence models. The numerical simulations are performed at a turbulent Reynolds number of Re τ = 150 and a Grashof number of Gr = 9.6 × 10 5 . Comparisons are made against the highly trusted DNS results. Consistent with the DNS approach, the current simulations are performed using constant properties and the Boussinesq approximation to predict the influence of buoyancy. Previous studies have provided assessments of two-equation turbulence models for various scenarios, but often rely on a qualitative “eye” test in order to determine the most appropriate model to predict a given flow. This study aims to provide a new form of quantitative assessment that accounts for both the physics captured by the turbulence model as well as the magnitude of the system response quantities (SRQ) using a modified symmetric mean absolute percent error (SMAPE) method. This method is designed to be approachable to researchers at any level and can be applied to system response quantities from multiple research fields. Uncertainty quantification is also performed to determine the discretization error for each turbulence model. Recommendations are made as to which turbulence models best capture the physics – hydrodynamically and thermally – using both local and global validation metrics. Lastly, a sensitivity analysis is performed on the damping functions used in the most accurate models. This underpins the potential of model developments and adjustments most worth pursuing for buoyant flows. Finally, this framework provides a more physics-based comparative analysis of the selected turbulence models.

42 ENGINEERING↗
DOE OSTI2020

Autonomous adaptive data acquisition for scanning hyperspectral imaging

Non-invasive and label-free spectral microscopy (spectromicroscopy) techniques can provide quantitative biochemical information complementary to genomic sequencing, transcriptomic profiling, and proteomic analyses. However, spectromicroscopy techniques generate high-dimensional data; acquisition of a single spectral image can range from tens of minutes to hours, depending on the desired spatial resolution and the image size. This substantially limits the timescales of observable transient biological processes. To address this challenge and move spectromicroscopy towards efficient real-time spatiochemical imaging, we developed a grid-less autonomous adaptive sampling method. Our method substantially decreases image acquisition time while increasing sampling density in regions of steeper physico-chemical gradients. When implemented with scanning Fourier Transform infrared spectromicroscopy experiments, this grid-less adaptive sampling approach outperformed standard uniform grid sampling in a two-component chemical model system and in a complex biological sample, Caenorhabditis elegans. We quantitatively and qualitatively assess the efficiency of data acquisition using performance metrics and multivariate infrared spectral analysis, respectively.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Quantitative Trade-Off in Distributed Secondary Control for Autonomous AC Microgrids

In this paper, we propose to quantify the trade-off between voltage regulation and reactive power sharing in autonomous AC microgrids with distributed secondary control. It is known that voltage regulation and reactive power sharing in droop-controlled autonomous AC microgrids are two conflicting control objectives that present a natural trade-off between voltage regulation towards the voltage magnitude reference and reactive power sharing accuracy. This trade-off is commonly shown qualitatively without sufficient quantification. In this work, to quantify the trade-off between the two objectives, we focus on distributed secondary control and utilize regression and polynomial surface fitting to identify the requisite parameter area to satisfy the predefined error bands for voltage magnitude regulation and reactive power sharing. Extensive case studies are presented to validate the proposed method.

autonomous AC microgrids↗
DOE OSTI2023

Continental Scale Hydrostratigraphy: Comparing Geologically Informed Data Products to Analytical Solutions

Abstract This study synthesizes two different methods for estimating hydraulic conductivity (K) at large scales. We derive analytical approaches that estimate K and apply them to the contiguous United States. We then compare these analytical approaches to three‐dimensional, national gridded K data products and three transmissivity (T) data products developed from publicly available sources. We evaluate these data products using multiple approaches: comparing their statistics qualitatively and quantitatively and with hydrologic model simulations. Some of these datasets were used as inputs for an integrated hydrologic model of the Upper Colorado River Basin and the comparison of the results with observations was used to further evaluate the K data products. Simulated average daily streamflow was compared to daily flow data from 10 USGS stream gages in the domain, and annually averaged simulated groundwater depths are compared to observations from nearly 2000 monitoring wells. We find streamflow predictions from analytically informed simulations to be similar in relative bias and Spearman's rho to the geologically informed simulations. R ‐squared values for groundwater depth predictions are close between the best performing analytically and geologically informed simulations at 0.68 and 0.70 respectively, with RMSE values under 10 m. We also show that the analytical approach derived by this study produces estimates of K that are similar in spatial distribution, standard deviation, mean value, and modeling performance to geologically‐informed estimates. The results of this work are used to inform a follow‐on study that tests additional data‐driven approaches in multiple basins within the contiguous United States.

54 ENVIRONMENTAL SCIENCES↗