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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 73 records · Page 4

Approximation of nearly-periodic symplectic maps via structure-preserving neural networks

A continuous-time dynamical system with parameter ε is nearly-periodic if all its trajectories are periodic with nowhere-vanishing angular frequency as ε approaches 0. Nearly-periodic maps are discrete-time analogues of nearly-periodic systems, defined as parameter-dependent diffeomorphisms that limit to rotations along a circle action, and they admit formal U(1) symmetries to all orders when the limiting rotation is non-resonant. For Hamiltonian nearly-periodic maps on exact presymplectic manifolds, the formal U(1) symmetry gives rise to a discrete-time adiabatic invariant. In this paper, we construct a novel structure-preserving neural network to approximate nearly-periodic symplectic maps. This neural network architecture, which we call symplectic gyroceptron, ensures that the resulting surrogate map is nearly-periodic and symplectic, and that it gives rise to a discrete-time adiabatic invariant and a long-time stability. This new structure-preserving neural network provides a promising architecture for surrogate modeling of non-dissipative dynamical systems that automatically steps over short timescales without introducing spurious instabilities.

97 MATHEMATICS AND COMPUTING↗

Non-contact imaging of terahertz surface currents with aperture-type near-field microscopy

Terahertz (THz) near-field imaging and spectroscopy provide valuable insights into the fundamental physical processes occurring in THz resonators and metasurfaces on the subwavelength scale. However, so far, the mapping of THz surface currents has remained outside the scope of THz near-field techniques. In this study, we demonstrate that aperture-type scanning near-field microscopy enables non-contact imaging of THz surface currents in subwavelength resonators. Through extensive near-field mapping of an asymmetric D-split-ring THz resonator and full electromagnetic simulations of the resonator and the probe, we demonstrate the correlation between the measured near-field images and the THz surface currents. The observed current dynamics in the interval of several picoseconds reveal the interplay between several excited modes, including dark modes, whereas broadband THz near-field spectroscopy analysis enables the characterization of electromagnetic resonances defined by the resonator geometry.

Norman, Sarah↗

The DUNE Near Detector

DUNE is a next-generation experiment aiming to provide precision measurements of neutrino oscillation parameters. It will detect neutrinos produced in the Long-Baseline Neutrino Facility beamline at Fermilab, using a Near Detector situated near the beam target where the neutrinos originate and a Far Detector located 1300 km away in South Dakota. A comparison of the spectra of neutrinos measured at the Far and the Near Detector will allow for the extraction of oscillation probabilities from which the oscillation parameters can be inferred. The specific role of the Near Detector is to serve as the experiment’s control: it will establish the no oscillation null hypothesis, measure and monitor the beam, constrain systematic uncertainties, and provide essential measurements of the neutrino interactions to improve models. The Near Detector complex will include three primary detector components: a liquid argon time projection chamber, a high-pressure gas time projection chamber and an on-axis beam monitor. The three detectors will serve important individual and overlapping functions, with two of them being also able to move transverse to the beam’s axis via the DUNE-PRISM program. The overall mission of the Near Detector, as well as the three sub-detectors’ unique capabilities and physics programs will be discussed in these proceedings.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An Exact and Near-Exact Distribution Approach to the Behrens–Fisher Problem

The Behrens–Fisher problem occurs when testing the equality of means of two normal distributions without the assumption that the two variances are equal. This paper presents approaches based on the exact and near-exact distributions for the test statistic of the Behrens–Fisher problem, depending on different combinations of even or odd sample sizes. We present the exact distribution when both sample sizes are odd and the near-exact distribution when one or both sample sizes are even. The near-exact distributions are based on a finite mixture of generalized integer gamma (GIG) distributions, used as an approximation to the exact distribution, which consists of an infinite series. The proposed tests, based on the exact and the near-exact distributions, are compared with Welch’s t-test through Monte Carlo simulations, in particular for small and unbalanced sample sizes. The results show that the proposed approaches are competent solutions to the Behrens–Fisher problem, exhibiting precise sizes and better powers than Welch’s approach for those cases. Numerical studies show that the Welch’s t-test tends to be a bit more conservative than the test statistics based on the exact or near-exact distribution, in particular when sample sizes are small and unbalanced, situations in which the proposed exact or near-exact distributions obtain higher powers than Welch’s t-test.

Hong, Serim↗

Plasmonic Hybridization and Near-Field Localization in Gold “Dog Bone” Nanoparticles

Gold nanoparticles with complex anisotropic geometries offer unique opportunities for tailoring plasmonic near-fields beyond the limits of conventional nanorods. Here we combine photon-induced near-field electron microscopy (PINEM) and full-wave simulations to resolve plasmon hybridization and near-field localization in gold dog-bone nanoparticles and their dimers with and without conformal SiO 2 shells. We demonstrate that the dog-bone geometry drives unconventional polarization-dependent field confinement, including pronounced tip-localized near-fields under both longitudinal and transverse excitation. Conformal SiO 2 shells red-shift the plasmon resonances through dielectric screening and prevent charge-transfer coupling in adjacent dimers. Depending on the dimer orientation and excitation polarization, coupled structures exhibit distinct bonding- and antibonding-like hybridized modes as well as interparticle near-field channels. However, weakly interacting dimers retain largely independent particle responses with geometry-governed asymmetries. The close agreement between PINEM measurements and simulations establishes a direct picture of how shape, dielectric environment, and nanoscale coupling together define plasmonic modes in complex anisotropic nanoparticles. These findings provide design principles for engineering localized optical fields in plasmonic nanoscale structures.

hybridization↗

The Hubble Space Telescope's Near-UV and Optical Transmission Spectrum of Earth as an Exoplanet

We observed the 2019 January total lunar eclipse with the Hubble Space Telescope’s STIS spectrograph to obtain the first near-UV (1700–3200 Å) observation of Earth as a transiting exoplanet. The observatories and instruments that will be able to perform transmission spectroscopy of exo-Earths are beginning to be planned, and characterizing the transmission spectrum of Earth is vital to ensuring that key spectral features (e.g., ozone, or O{sub 3}) are appropriately captured in mission concept studies. O{sub 3} is photochemically produced from O{sub 2}, a product of the dominant metabolism on Earth today, and it will be sought in future observations as critical evidence for life on exoplanets. Ground-based observations of lunar eclipses have provided the Earth’s transmission spectrum at optical and near-IR wavelengths, but the strongest O{sub 3} signatures are in the near-UV. We describe the observations and methods used to extract a transmission spectrum from Hubble lunar eclipse spectra, and identify spectral features of O{sub 3} and Rayleigh scattering in the 3000–5500 Å region in Earth’s transmission spectrum by comparing to Earth models that include refraction effects in the terrestrial atmosphere during a lunar eclipse. Our near-UV spectra are featureless, a consequence of missing the narrow time span during the eclipse when near-UV sunlight is not completely attenuated through Earth’s atmosphere due to extremely strong O{sub 3} absorption and when sunlight is transmitted to the lunar surface at altitudes where it passes through the O{sub 3} layer rather than above it.

79 ASTRONOMY AND ASTROPHYSICS↗

The Near-infrared Spectrum of the Nuclear Star Cluster: Looking below the Tip of the Iceberg, and Comparisons with Extragalactic Nuclei

Long-slit near-infrared (NIR) spectra of the Galactic nuclear star cluster (NSC) are discussed. The spectra sample the major axis of the NSC out to its half-light radius. The absorption spectrum of the central regions of the NSC is averaged over angular scales of tens of arc seconds in order to sample globular cluster-like total luminosities, and the results are compared with model spectra. The equivalent widths of Na i2.21 μm and Ca 2.26 μm outside of the center of the NSC, where light from nuclear bulge stars contributes a large fraction to the total flux, are consistent with solar chemical mixtures. In contrast, the equivalent widths of Na i2.21 μm and Ca i2.26 μm near the center of the NSC are larger than expected from models with solar chemical mixtures, even after light from the brightest evolved stars is removed. The depths of spectroscopic features changing along the major axis of the NSC are consistent with imaging studies that have found evidence of population gradients in the NSC. That Na i2.21 μm and Ca i2.26 μm are deeper than predicted for solar chemical mixtures over a range of evolutionary states is consistent with previous studies that find that the majority of stars near the center of the NSC formed from material that had nonsolar chemical mixtures. The depths of the Na i2.21 μm and Ca i2.26 μm features in the central regions of the NSC are comparable to those in the nuclear spectrum of the early-type Virgo disk galaxy NGC 4491, and are deeper than in the central spectra of NGC 253 and 7793. A spectrum of nebular emission and the youngest stars near the galactic center is also extracted. The equivalent widths of emission features in the extracted NIR spectrum are similar to those in the nuclear spectrum of NGC 253, and it is argued that this agreement is best achieved if the current episode of star formation near the center of the NSC has been in progress for at least a few megayears.

79 ASTRONOMY AND ASTROPHYSICS↗

Molecular dynamics study of primary damage in the near-surface region in nickel

In this work, we carried out a large-scale molecular dynamics (MD) simulation to elucidate the effect of the free surface on the defect production of displacement cascades in pure nickel. These MD simulations were performed both in the bulk and near-surface regions with primary knock-on atom (PKA) energies of E PKA = 1, 5, or 10 keV and at temperatures T = 300, 425, or 525 K. Additionally, for every (T, E PKA ), near-surface cascade simulations were performed as a function of depth. In the near-surface simulations, assuming isotropic neutron fluence, the PKAs were initiated in random directions, including toward and parallel to the free surface. For both the near-surface and bulk cascades, the effect of E PKA and T on the defect production is similar. In both cases, the defect production increases with E PKA , but the temperature has minimal effect. However, the production and clustering of vacancies are higher for near-surface cascades, and they decrease with increasing depth. In contrast, the production and clustering of self-interstitial atoms are lower and increase with depth. Eventually, the production and clustering of both defect types approach bulk cascade-like behavior, and the depth at which this occurs increases with E PKA , but is independent of temperature.

36 MATERIALS SCIENCE↗

Improving the modeling of near-wall interphase heat transfer in porous media models of Pebble Bed Reactors

Here, this work aims to improve capabilities for modeling localized effects in porous media models of Pebble Bed Reactors. The wall-channeling effect is the primary local phenomenon of interest in a PBR, where the presence of the reflector wall disrupts the pebble packing, causing the pebbles near the wall to pack less efficiently and creating large void regions. Accurate modeling of the near-wall region is important as it will affect core bypass flow and temperature predictions. Porous media models are commonly used for design scoping and plant-level simulations of PBRs. Although these models have some capabilities to model the near-wall region, the correlations that are available in porous media codes are often inaccurate when a multi-region model is used to discretize the near-wall region. This work employs a high-to-low analysis to study the accuracy of available interphase heat transfer closures. NekRS, a spectral element computational fluid dynamics code, is used to perform Large Eddy Simulations. These LES simulation results are compared to porous media model results from the Pronghorn porous media code. The friction term of the KTA drag closure is first improved, reducing the error in the prediction of the near-wall velocity from over 50% to less than 5%. This is combined with improvements to the form term from previous works to produce a drag closure that is capable of accurately modeling the wall-channeling effect across a variety of flow conditions. The Nusselt number predictions of several heat transfer correlations are compared to the high-fidelity results where it is found that the KTA heat transfer correlation is capable of accurately predicting the local Nusselt numbers that were determined in the high-fidelity simulation. Comparison of the radial solid temperature profiles, however, reveal discrepancies between NekRS and Pronghorn. It is discovered that the implementation of the interphase heat transfer coefficient that exists in many current porous media codes is not valid when local porosities are modeled. Instead, it is suggested that the interphase heat transfer coefficient should be dependent on the local porosity, the Nusselt number, and the local solid surface-to-volume ratio. Implementation of this change produces improvement in the agreement between the results obtained by NekRS and Pronghorn while using the KTA heat transfer correlation.

interphase heat transfer↗

Water Structure and Dynamics Near the Surfaces of Silicalite-1

Zeolites are crystalline microporous aluminosilicates that are commonly used as industrial sorbents and membranes. Solvent structuring and dynamics near zeolite crystal surfaces are thought to influence interfacial transport and molecular recognition processes, as well as fundamental aspects of their crystallization from solution. Here, in this work, we use molecular dynamics (MD) simulations to investigate the behavior of interfacial water near the exposed (010), (100), and (101) crystal faces of silicalite-1, one of the most widely studied zeolites. The MD simulations reveal that water’s translational and orientational order is strongly influenced by the distinct corrugations, pore apertures, and functional group distributions presented on each surface. Specifically, we observe two distinct hydration layers near each surface. Water molecules in the contact layer are hydrogen bonded to two or three exposed surface silanol groups. The relative populations of water molecules that are doubly and triply hydrogen bonded to the surface strongly depend on the distribution of the exposed silanols. The interactions with exposed surface silanols also influence water’s local orientational order and distribution across each surface. We also show that the structuring of the solvent near the different faces of silicalite-1 strongly impacts the interfacial dynamics. The translational and orientational relaxation dynamics of water are slowest in the contact layers and correlate with structural ordering near each face.

42 ENGINEERING↗

Near-Infrared Optical Gain of Colloidal Quantum Wells via Intraband Transitions

Tunable, unipolar, near-infrared intraband optical gain is demonstrated in semiconductor colloidal quantum wells, expanding the form and optical range for potential infrared applications. Atomically flat colloidal quantum wells of cadmium selenide display photoinduced absorption features in the near-infrared assigned to intraband (alternatively intersubband) transitions from the first to second electron subbands of the quantum wells. Under ultraviolet optical excitation, these same transitions from the first to second electron subbands are shown to exhibit stimulated emission, resulting in optical gain covering the near-infrared spectral region. The modal gain, bandwidth, and lifetime of this intraband gain are manipulated by using excitation energy, fluence, temperature, and surface chemistry. Unlike previous demonstrations of intraband optical gain in epitaxial quantum wells (e.g., quantum cascade lasers), the colloidal quantum wells are undoped. As a result, nearly thresholdless gain is in principle possible and limited in practice by the measurement of small optical losses of the samples in the near-infrared. Furthermore, the observations may be understood as a modified "quantum fountain" employing the valence band, a strategy that may be applied to many other materials.

Optical gain↗

High–Resolution Maps of Near–Surface Permafrost for Three Watersheds on the Seward Peninsula, Alaska Derived From Machine Learning

Permafrost soils are a critical component of the global carbon cycle and are locally important because they regulate the hydrologic flux from uplands to rivers. Furthermore, degradation of permafrost soils causes land surface subsidence, damaging infrastructure that is crucial for local communities. Regional and hemispherical maps of permafrost are too coarse to resolve distributions at a scale relevant to assessments of infrastructure stability or to illuminate geomorphic impacts of permafrost thaw. Here we train machine learning models to generate meter–scale maps of near–surface permafrost for three watersheds in the discontinuous permafrost region. The models were trained using ground truth determinations of near–surface permafrost presence from measurements of soil temperature and electrical resistivity. We trained three classifiers: extremely randomized trees (ERTr), support vector machines (SVM), and an artificial neural network (ANN). Model uncertainty was determined using k–fold cross validation, and the modeled extents of near–surface permafrost were compared to the observed extents at each site. At–a–site near–surface permafrost distributions predicted by the ERTr produced the highest accuracy (70%–90%). However, the transferability of the ERTr to the sites outside of the training data set was poor, with accuracies ranging from 50% to 77%. The SVM and ANN models had lower accuracies for at–a–site prediction (70%–83%), yet they had greater accuracy when transferred to the non–training site (62%–78%). These models demonstrate the potential for integrating high–resolution spatial data and machine learning models to develop maps of near–surface permafrost extent at resolutions fine enough to assess infrastructure vulnerability and landscape morphology influenced by permafrost thaw.

54 ENVIRONMENTAL SCIENCES↗

First-principles study of hydrogen behavior near W/WC interfaces

Hydrogen (H) solution, migration, and binding to vacancies near the tungsten/tungsten carbide (W/WC) interfaces based on hcp WC or bcc W (W/WCb and Wb/WC) have been studied by first-principles simulations to provide insights into the effect of C on H behavior in W exposed to C deposition in fusion reactors. The H behavior near the W/WC interfaces is related to the tensile or compressive strain due to the lattice match and interfacial effects. Near the W/WCb interface, the H solution energy in hcp WC increases approaching the interface, while it decreases from the W side to the interface. The configuration change of the W slab significantly decreases the H solution energy but has only a modest effect on the H migration energy barrier in comparison with the values in bcc W. The interface enhances the H binding to vacancies in WC layers. Both the interface and configuration adjustment of the W slab reduce the H binding to vacancies on the W side of the interface. Near the Wb/WC interface, H solution energies in both WC and W slabs weakly decrease approaching the interface. The configuration change of the WC slab significantly increases the H solution energy and binding energy to vacancies but decreases the H migration energy barrier in comparison with the values in hcp WC. The H energetics near the W/WC interfaces indicate the likelihood of H localization and diffusion in the W side of the interface, rather than diffusing through the interface into WC layers.

Yang, L. (ORCID:0000000322166071)↗

Normal stability of slow manifolds in nearly periodic Hamiltonian systems

Kruskal [J. Math. Phys. 3, 806 (1962)] showed that each nearly periodic dynamical system admits a formal U(1) symmetry, generated by the so-called roto-rate. We prove that such systems also admit nearly invariant manifolds of each order, near which rapid oscillations are suppressed. We study the nonlinear normal stability of these slow manifolds for nearly periodic Hamiltonian systems on barely symplectic manifolds—manifolds equipped with closed, non-degenerate 2-forms that may be degenerate to leading order. In particular, we establish a sufficient condition for long-term normal stability based on second derivatives of the well-known adiabatic invariant. We use these results to investigate the problem of embedding guiding center dynamics of a magnetized charged particle as a slow manifold in a nearly periodic system. Here, we prove that one previous embedding and two new embeddings enjoy long-term normal stability and thereby strengthen the theoretical justification for these models.

97 MATHEMATICS AND COMPUTING↗

Pressure Drop Correlation Improvement for the Near-Wall Region of Pebble-Bed Reactors

Packed beds play an important role in several engineering fields, with their applications in nuclear energy being driven by the development of next-generation reactors utilizing pebble fuel. The random nature of a packed pebble bed creates a flow field that is complex and difficult to predict. Porous media models are an attractive option for modeling pebble-bed reactors (PBRs), as they provide intermediate fidelity results and are computationally efficient. Porous media models, however, rely on the use of correlations to estimate the effect of complicated flow features on the pressure drop and heat transfer in the system. Existing correlations were developed to predict the average behavior of the bed, but they are inaccurate in the near-wall region where the presence of the wall affects the pebble packing. This work aims to investigate the accuracy of a porous media model using the Kerntechnischer Ausschuss (KTA) correlation, the most common pressure drop correlation for PBRs compared to the high-fidelity large eddy simulation (LES). A bed of 1568 pebbles is investigated at Reynolds numbers from 625 to 10 000. The bed is divided into five concentric subdomains to compare the average velocity, friction losses, and form losses between the porous media and LES codes. The comparison between the LES simulation and the KTA correlation revealed that the KTA correlation largely underpredicts the form losses in the near-wall region, leading to an overprediction of the velocity near the wall by nearly 30%. An investigation of the form losses across the range of Reynolds numbers in the LES results provided additional insight into how the KTA correlation may be improved to better predict these spatial effects in a pebble bed. These data suggest that the form coefficient near the wall must be increased by 48% while decreasing the form coefficient of the inner bulk region of the bed by 15%. The implementation of these improvements to the KTA correlation in a porous media model produced a radial velocity profile that saw significantly improved agreement with the LES results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NEAR: Neural Embeddings for Amino acid Relationships

Protein language models (PLMs) have recently demonstrated potential to supplant classical protein database search methods based on sequence alignment, but are slower than common alignment-based tools and appear to be prone to a high rate of false labeling. Here, we present NEAR, a method based on neural representation learning that is designed to improve both speed and accuracy of search for likely homologs in a large protein sequence database. NEAR’s ResNet embedding model is trained using contrastive learning guided by trusted sequence alignments. It computes per-residue embeddings for target and query protein sequences, and identifies alignment candidates with a pipeline consisting of residue-level k-NN search and a simple neighbor aggregation scheme. Tests on a benchmark consisting of trusted remote homologs and randomly shuffled decoy sequences reveal that NEAR substantially improves accuracy relative to state-of-the-art PLMs, with lower memory requirements and faster embedding and search speed. While these results suggest that the NEAR model may be useful for standalone homology detection with increased sensitivity over standard alignment-based methods, in this manuscript we focus on a more straightforward analysis of the model’s value as a high-speed pre-filter for sensitive annotation. In that context, NEAR is at least 5x faster than the pre-filter currently used in the widely-used profile hidden Markov model (pHMM) search tool HMMER3, and also outperforms the pre-filter used in our fast pHMM tool, nail.

59 BASIC BIOLOGICAL SCIENCES↗

Near Detector Selection for Neutral Current Disappearance Search at the Short-Baseline Neutrino Program

Various short baseline neutrino experiments observe anomalies that challenge the three-flavor neutrino oscillation model, consistent with a hypothetical “sterile” neutrino that does not interact via the weak force. This poster presents a near detector event selection at the Short-Baseline Near Detector (SBND), developed for the first search for neutral current (NC) disappearance at short-baseline experiments. NC disappearance provides ``smoking gun” insight into the sterile neutrino question because NC interactions are equally sensitive to all three active neutrinos, meaning any change in the NC interaction rate between near and far detectors cannot be explained by oscillations among known flavor states. This analysis focuses on the NC1p topology, the most common NC interaction type at the Short-Baseline Neutrino (SBN) Program. NC topologies are inherently challenging due to their low light yield and the absence of an outgoing charged lepton, which complicates identification and leads to poor energy reconstruction as the outgoing neutrino carries away a large portion of the neutrino’s initial energy. This work presents an NC1p event selection at the near detector, highlighting SBND’s impressive detector capabilities, including trigger efficiency studies. Combined with a novel kinematic energy reconstruction technique leveraging the detector’s outstanding hadronic detail, this analysis establishes a robust near detector foundation to target an NC disappearance measurement consistent with the 3$+$1 sterile neutrino model. This SBND selection will soon be combined with the far detector to conduct an NC disappearance search, providing unique insight and complementary information to traditional charged current searches and advancing the SBN Program’s goal to resolve the sterile neutrino question, including 3$+$1 searches and beyond.

Nicole Pallat, Nicole Pallat [Minnesota U.] (ORCID↗

Machine learning predictions of near-surface permafrost extent at Teller 27, Teller 47, and the Kougarok 64 Hillslope sites on the Seward Peninsula, Alaska: Supporting Data

Geophysical surveys were conducted at the NGEE Arctic Teller mile marker 27 site, Teller mile marker 47 site, and Kougarok mile marker 64 site during the summers of 2018, 2019, and 2021. Additional data was collected at Teller mile marker 47 during September 2021 and August 2022. These surveys were used to identify locations of near-surface permafrost during the period of maximum seasonal thaw depth for ground truth data used in machine learning predictions of near-surface permafrost extent at each site. This dataset contains CSV files of ground truth observations of near-permafrost presence or absence for each site, where PF = 1 indicates permafrost presence and PF = 0 indicates permafrost absence. The dataset also includes 2 sets of binary rasters (WGS84 UTM zone 3) of permafrost extent for each site using 1) all of the training data and 2) the transferred model. For both sets of rasters, 0 = non-permafrost and 1 = permafrost. Included are 6 *.tif files and 5 *.csv files that include a data dictionary (dd.csv) and file-level metadata (flmd.csv). This dataset is in support of the paper "Machine learning-derived high-resolution maps of near-surface permafrost for three watersheds on the Seward Peninsula, Alaska" that is in review (May 2023). The Next-Generation Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗