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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Search for heavy particles in the b -tagged dijet mass distribution with additional b -tagged jets in proton-proton collisions at $\sqrt{s}$ = 13 TeV with the ATLAS experiment

A search optimized for new heavy particles decaying to two b-quarks and produced in association with additional b-quarks is reported. The sensitivity is improved by b-tagging at least one lower-p T jet in addition to the two highest-p T jets. The data used in this search correspond to an integrated luminosity of 103 fb –1 collected with a dedicated trijet trigger during the 2017 and 2018 √s = 13 TeV proton–proton collision runs with the ATLAS detector at the LHC. The search looks for resonant peaks in the b-tagged dijet invariant mass spectrum over a smoothly falling background. The background is estimated with an innovative data-driven method based on orthonormal functions. The observed b-tagged dijet invariant mass spectrum is compatible with the background-only hypothesis. Upper limits at 95% confidence level on a heavy vector-boson production cross section times branching ratio to a pair of b-quarks are derived.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Measurements of differential cross-sections in top-quark pair events with a high transverse momentum top quark and limits on beyond the Standard Model contributions to top-quark pair production with the ATLAS detector at $ \sqrt{s} $ = 13 TeV

Cross-section measurements of top-quark pair production where the hadronically decaying top quark has transverse momentum greater than 355 GeV and the other top quark decays into ℓνb are presented using 139 fb –1 of data collected by the ATLAS experiment during proton-proton collisions at the LHC. The fiducial cross-section at √s = 13 TeV is measured to be σ = 1.267 ± 0.005 ± 0.053 pb, where the uncertainties reflect the limited number of data events and the systematic uncertainties, giving a total uncertainty of 4.2%. The cross-section is measured differentially as a function of variables characterizing the tt¯ system and additional radiation in the events. The results are compared with various Monte Carlo generators, including comparisons where the generators are reweighted to match a parton-level calculation at next-to-next-to-leading order. The reweighting improves the agreement between data and theory. The measured distribution of the top-quark transverse momentum is used to search for new physics in the context of the effective field theory framework. No significant deviation from the Standard Model is observed and limits are set on the Wilson coefficients of the dimension-six operators O tG and $O$ $^{(8)}_{tq}$, where the limits on the latter are the most stringent to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Measurement of beauty production via non-prompt charm hadrons in p–Pb collisions at $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV

The production cross sections of D 0 , D + , and Λ$^{+}_{c}$ hadrons originating from beauty-hadron decays (i.e. non-prompt) were measured for the first time at midrapidity in proton–lead (p–Pb) collisions at the center-of-mass energy per nucleon pair of $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV. Nuclear modification factors (R pPb ) of non-prompt D 0 , D + , and Λ$^{+}_{c}$ are calculated as a function of the transverse momentum (p T ) to investigate the modification of the momentum spectra measured in p–Pb collisions with respect to those measured in proton–proton (pp) collisions at the same energy. The R pPb measurements are compatible with unity and with the measurements in the prompt charm sector, and do not show a significant p T dependence. The p T -integrated cross sections and p T -integrated R pPb of non-prompt D 0 and D + mesons are also computed by extrapolating the visible cross sections down to p T = 0. The non-prompt D-meson R pPb integrated over p T is compatible with unity and with model calculations implementing modification of the parton distribution functions of nucleons bound in nuclei with respect to free nucleons. The non-prompt Λ$^{+}_{c}$/D 0 and D + /D 0 production ratios are computed to investigate hadronisation mechanisms of beauty quarks into mesons and baryons. The measured ratios as a function of p T display a similar trend to that measured for charm hadrons in the same collision system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Search for Higgs boson pair production in the $ \textrm{b}\overline{\textrm{b}}{\textrm{W}}^{+}{\textrm{W}}^{-} $ decay mode in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search for Higgs boson pair (HH) production with one Higgs boson decaying to two bottom quarks and the other to two W bosons are presented. The search is done using proton-proton collisions data at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb$^{−1}$ recorded by the CMS detector at the LHC from 2016 to 2018. The final states considered include at least one leptonically decaying W boson. No evidence for the presence of a signal is observed and corresponding upper limits on the HH production cross section are derived. The limit on the inclusive cross section of the nonresonant HH production, assuming that the distributions of kinematic observables are as expected in the standard model (SM), is observed (expected) to be 14 (18) times the value predicted by the SM, at 95% confidence level. The limits on the cross section are also presented as functions of various Higgs boson coupling modifiers, and anomalous Higgs boson coupling scenarios. In addition, limits are set on the resonant HH production via spin-0 and spin-2 resonances within the mass range 250–900 GeV.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Pauli energy contribution to the nucleus-nucleus interaction

Background: The Pauli exclusion principle plays a crucial role as a building block of many-body quantal systems comprised of fermions. It also induces a “Pauli repulsion” in the interaction between di-nuclear systems. It has been shown in [Phys. Rev. C 95, 031601(R) (2017)] that the Pauli repulsion widens the nucleus-nucleus potential barrier, thus hindering sub-barrier fusion. Purpose: To investigate the proton and neutron contributions to the Pauli repulsion, both in the bare potential neglecting shape polarization and transfer between the reactants, as well as in the dynamical potential obtained by accounting for such dynamical rearrangements. Methods: As the basis of our study we utilize the Pauli kinetic energy (PKE) obtained by studying the nuclear localization function (NLF). Recently this approach has been generalized to incorporate all of the dynamical and time-odd terms present in the nuclear energy density functional. This approach is employed in the density constrained frozen Hartree-Fock (DCFHF) and in the density constrained time-dependent Hartree-Fock (DC- TDHF) microscopic methods. Results: The PKE spatial distribution shows that a repulsion occurs in the neck between the nuclei when they first touch. Inside the barrier, neutrons can contribute significantly more to the Pauli repulsion in neutron-rich systems. Dynamical effects tend to lower the Pauli repulsion near the barrier. Proton and neutron dynamical contributions to the PKE significantly differ inside the barrier for asymmetric collisions, which is interpreted as an effect of multinucleon transfer. Conclusions: The PKE is shown to make a significant contribution to nuclear interaction potentials. Protons and neutrons can play very different roles in both the bare potential and in the dynamical rearrangement. Further microscopic studies are required to better understand the role of transfer and to investigate the effect of pairing and deformation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Across the Scales of the Nucleus: Understanding Short Range Correlations from Medium Modification to Probe Independence

The atomic nucleus presents an intricate system due to the non-linear forces described by Quantum Chromodynamics (QCD) that govern its structure. The range of scales involved is remarkable; the most massive nuclei weigh approximately five orders of magnitude more than the quarks that compose them. The nucleus can be analyzed at various levels, from quarks to hadrons to the nucleus as a whole. Short-Range Correlations (SRCs) within the nucleus play a significant role that spans these diverse scales. At the most fundamental level, SRCs influence the interaction between nucleons. The nucleon-nucleon (NN) interaction, arising from QCD, is crucial in determining nuclear properties. SRCs serve as valuable probes for measuring this NN interaction, as the nucleons within SRCs become effectively decoupled from the rest of the nucleus. Multiple experimental techniques, including electron scattering, have been employed to investigate the NN interaction through SRCs. However, our first project demonstrates that inclusive measurements alone are inadequate to constrain this interaction fully. Moving to the scale of the nucleus, SRCs contribute to the high-momentum tail of the nuclear spectral function. While the low-momentum region is characterized by nucleons exhibiting bulk properties, nucleons begin to pair into SRCs at higher momenta. Our research aims to bridge the understanding between the mean-field portion of the nucleus and its high-momentum SRC components. Additionally, SRCs affect the quark structure of protons, as evidenced by the EMC effect, which indicates that quarks behave differently when protons are embedded within a nucleus—an effect referred to as medium modification. This thesis explores the correlation between SRCs and medium modification across various experimental setups. Finally, we seek to establish an interpretation of the nuclear ground state. Accomplishing this requires demonstrating that our SRC observables are independent of the probe’s scale and scheme. The concluding project of this thesis illustrates how we utilize triple coincidence quasi-elastic scattering across a range of (Q2) values to develop a model-dependent framework for understanding SRC distributions within the nucleus’s ground-state wavefunction.

Denniston, A. W. Denniston [University of Tel Aviv↗
DOE OSTI2024

Theory and modeling of molecular modes in the NMR relaxation of fluids

Traditional theories of the nuclear magnetic resonance (NMR) autocorrelation function for intra-molecular dipole pairs assume a single-exponential decay, yet the calculated autocorrelation of realistic systems displays a rich, multi-exponential behavior, resulting in anomalous NMR relaxation dispersion (i.e., frequency dependence). We develop an approach to model and interpret the multi-exponential intra-molecular autocorrelation using simple, physical models within a rigorous statistical mechanical development that encompasses both rotational diffusion and translational diffusion in the same framework. Here, we recast the problem of evaluating the autocorrelation in terms of averaging over a diffusion propagator whose evolution is described by a Fokker–Planck equation. The time-independent part admits an eigenfunction expansion, allowing us to write the propagator as a sum over modes. Each mode has a spatial part that depends on the specified eigenfunction and a temporal part that depends on the corresponding eigenvalue (i.e., correlation time) with a simple, exponential decay. The spatial part is a probability distribution of the dipole pair, analogous to the stationary states of a quantum harmonic oscillator. Drawing inspiration from the idea of inherent structures in liquids, we interpret each of the spatial contributions as a specific molecular mode. These modes can be used to model and predict the NMR dipole–dipole relaxation dispersion of fluids by incorporating phenomena on the molecular level. We validate our statistical mechanical description of the distribution in molecular modes with molecular dynamics simulations interpreted without any relaxation models or adjustable parameters: the most important poles in the Padé–Laplace transform of the simulated autocorrelation agree with the eigenvalues predicted by the theory

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Slow scrambling and hidden integrability in a random rotor model

In this work, we analyze the out-of-time-order correlation functions of a solvable model of a large number $\textit{N}$ of $\textit{M}$-component quantum rotors coupled by Gaussian-distributed random, infinite-range exchange interactions. We focus on the growth of commutators of operators at a temperature $\textit{T}$ above the zero temperature quantum critical point separating the spin-glass and paramagnetic phases. In the large $\textit{N, M}$ limit, the squared commutators of the rotor fields do not display any exponential growth of commutators, in spite of the absence of any sharp quasiparticlelike excitations in the disorder-averaged theory. We show that in this limit, the problem is integrable and points out interesting connections to random-matrix theory. At leading order in 1/$\textit{M}$, there are no modifications to the critical behavior but an irrelevant term in the fixed-point action leads to a small exponential growth of the squared commutator. We also introduce and comment on a generalized model involving $\textit{p}$-pair rotor interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Elevation distributed micro-climatology data in a coastal glaciated watershed

Air temperature, ground temperature and relative humidity data were collected in a longitudinal transect of the Nooksack watershed at varying elevations from 500 to 1800 m above sea level. Data were collected by anchoring sensors from trees above winter snow levels and shaded from direct solar radiation. Paired sensors were also buried 3 cm under ground near each air temperature sensor to determine snow absence or presence. Select sites included relative humidity sensors to indicate whether precipitation was occurring. Data were collected every 3-4 h from December 2015 to Sept 2018 (with ongoing collection). Code for analysis of daily mean, minimum, maximum, and temperature change with elevation (lapse rates) are available on Github (https://doi.org/10.5281/zenodo.3239539). The sensor download and intermediate data products are available on HydroShare at (http://www.hydroshare.org/resource/222e832d3df24dea9bae9bbeb6f4219d) with publicly accessible visualization available from the Nooksack Observatory at data.cuahsi.org. Hydrologic models are generally structured with a single annual average lapse rate parameter which assumes a linear temperature gradient with elevation. The daily data (2016-2018) is used as part of ongoing studies on the non-linear dynamics and temporal variability of temperature with elevation to improve assessments of watershed function and salmon habitat.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Probing Heterogeneous Charge Distributions at the α-Al 2 O 3 (0001)/H 2 O Interface

Unlike metal or semiconductor electrodes, the surface charge resulting from the protonation or deprotonation of insulating mineral oxides is highly localized and heterogeneous in nature. In this work the Stark active C≡N stretch of potassium thiocyanate is used as a molecular probe of the heterogeneity of the interfacial electrostatic potential at the α-Al 2 O 3 (0001)/H 2 O interface. Vibrational sum frequency generation (vSFG) measurements performed in the OH stretching region suggest that thiocyanate species organize interfacial water similarly to halide ions. Changes in the electrostatic potential are then tracked via Stark shifts of the vibrational frequency of the thiocyanate stretch. Our vSFG measurements show that we can simultaneously measure the vSFG response of SCN – ions experiencing charged and neutral surface sites. We assign local potentials of +308 and -154 mV to positively and negatively charged aluminol groups that are present at pH = 4 and pH = 10, respectively. Thiocyanate anions at positively charged surface sites and negatively charged surface sites and those participating in contact ion pairing adopt similar orientations and are oppositely oriented relative to thiocyanate ions near neutral surface sites. All four species followed Langmuir adsorption isotherms. Density functional theory–molecular dynamics (DFT-MD) simulations of SCN – near the neutral α-Al 2 O 3 (0001)/H 2 O interface show that the vSFG response in the C≡N stretch region originates from a SCN–H–O–Al complex, suggesting the surface site specificity of these experiments. To our knowledge this is the first spectroscopic measurement of local potentials associated with a heterogeneously charged surface. The ability to probe the evolution of local charges in situ could provide vital insight into many industrial, electrochemical, and geochemically relevant interfaces.

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

eDNAjoint: An R package for interpreting paired or semi‐paired environmental DNA and traditional survey data in a Bayesian framework

Abstract Environmental DNA (eDNA) sampling is increasingly used in surveys of species distribution as a potentially sensitive and efficient monitoring method. Yet access to modelling tools designed specifically for interpreting this new data type lags behind its ubiquity. While occupancy modelling software has dominated the analytical landscape for eDNA data analysis of single species, this type of model may not always be the most appropriate. The rate of eDNA detection often corresponds to species density, rather than just occupancy, and researchers often have access to observations from non‐genetic sampling methods at the same sites. To provide users access to a modelling framework designed to maximize the use of all available data, we developed an R package, eDNAjoint . The package provides an easy‐to‐use interface for fitting a ‘joint’ model that integrates data from paired or semi‐paired eDNA and traditional surveys in a Bayesian framework. The model can be used to estimate parameters like the probability of a false positive eDNA detection and mean catch rate at a site, and the package allows access to multiple model variations and Bayesian prior customization. Additional functionality can be used for model selection, summarising posteriors and comparing the relative sensitivities of the two survey methods. We demonstrate the use of eDNAjoint by fitting a variation of the model with site‐level covariates that scale the sensitivity of eDNA sampling relative to traditional sampling. The example workflow uses binary eDNA and seine count data for the endangered tidewater goby ( Eucyclogobius newberryi ) from a study by Schmelzle and Kinziger (2016). This use case includes a prior sensitivity analysis and an evaluation of the relationship between detection rates and environmental variables. eDNAjoint has the potential to greatly increase the range of users who will be able to rigorously analyse eDNA and traditional survey data in a Bayesian framework, understand if and how eDNA can improve monitoring practices, and gain confidence in the interpretability of eDNA data.

Keller, Abigail G. [Department of Environment Scie↗
DOE OSTI2021

Scaling of magnetic dissipation and particle acceleration in ABC fields

Using particle-in-cell numerical simulations with electron–positron pair plasma, we study how the efficiencies of magnetic dissipation and particle acceleration scale with the initial coherence length λ 0 in relation to the system size L of the two-dimensional ‘Arnold–Beltrami–Childress’ (ABC) magnetic field configurations. Topological constraints on the distribution of magnetic helicity in two-dimensional systems, identified earlier in relativistic force-free simulations, that prevent the high-(L/λ 0 ) configurations from reaching the Taylor state, limit the magnetic dissipation efficiency to about ϵ diss ≃60% . Here we find that the peak growth time scale of the electric energy τ E,peak scales with the characteristic value of initial Alfvén velocity β A,ini like τ E,peak ∝(λ 0 /L)β$^{–3}_{A,ini}$ . The particle energy change is decomposed into non-thermal and thermal parts, with non-thermal energy gain dominant only for high initial magnetisation. The most robust description of the non-thermal high-energy part of the particle distribution is that the power-law index is a linear function of the initial magnetic energy fraction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Sizing and Location Selection of Medium‐Voltage Back‐to‐Back Converters for DER‐Dominated Distribution Systems

Medium‐voltage back‐to‐back (MVB2B) converters can connect two distribution systems and quantifiably transfer power between them. This function can enable the MVB2B converter to exchange distributed energy resource (DER)‐generated power between two systems and bring significant value to enhancing distribution system DER adoption. Our previous work analysed and demonstrated the value MVB2B converter can bring to DER integration. As continuous work, this paper presents a methodology that helps address the MVB2B converter sizing and location selection problem in distribution systems with high DER penetrations. The proposed methodology aims to address three critical problems for MVB2B converter implementation in the real world: (1) which distribution systems are better to be connected, (2) what converter size is appropriate for connecting the distribution systems, and (3) where the optimal connection points are in the systems for connecting the MVB2B converter. The proposed methodology has been demonstrated by case studies that include various scenarios involving distribution systems with different dominated load types and high photovoltaic penetrations. The results demonstrate that selecting the optimal converter size based on net revenue and time of return considerations leads to a balance between maximizing energy savings and minimizing financial payback periods. Furthermore, feeder pair selection based on load profile standard deviation effectively identifies systems that derive the greatest value from MVB2B integration. Finally, an optimized connection point selection approach using a voltage load sensitivity matrix ensures minimal system impact while facilitating efficient power exchange. These findings provide practical insights for the real‐world deployment of MVB2B converters to enhance DER hosting capacity and improve grid resilience.

14 SOLAR ENERGY↗
DOE OSTI2020

Gene expression of functionally-related genes coevolves across fungal species: detecting coevolution of gene expression using phylogenetic comparative methods

Researchers often measure changes in gene expression across conditions to better understand the shared functional roles and regulatory mechanisms of different genes. Analogous to this is comparing gene expression across species, which can improve our understanding of the evolutionary processes shaping the evolution of both individual genes and functional pathways. One area of interest is determining genes showing signals of coevolution, which can also indicate potential functional similarity, analogous to co-expression analysis often performed across conditions for a single species. However, as with any trait, comparing gene expression across species can be confounded by the non-independence of species due to shared ancestry, making standard hypothesis testing inappropriate. We compared RNA-Seq data across 18 fungal species using a multivariate Brownian Motion phylogenetic comparative method (PCM), which allowed us to quantify coevolution between protein pairs while directly accounting for the shared ancestry of the species. Our work indicates proteins which physically-interact show stronger signals of coevolution than randomly-generated pairs. Interactions with stronger empirical and computational evidence also showing stronger signals of coevolution. We examined the effects of number of protein interactions and gene expression levels on coevolution, finding both factors are overall poor predictors of the strength of coevolution between a protein pair. Simulations further demonstrate the potential issues of analyzing gene expression coevolution without accounting for shared ancestry in a standard hypothesis testing framework. Furthermore, our simulations indicate the use of a randomly-generated null distribution as a means of determining statistical significance for detecting coevolving genes with phylogenetically-uncorrected correlations, as has previously been done, is less accurate than PCMs, although is a significant improvement over standard hypothesis testing. These methods are further improved by using a phylogenetically-corrected correlation metric. Our work highlights potential benefits of using PCMs to detect gene expression coevolution from high-throughput omics scale data. This framework can be built upon to investigate other evolutionary hypotheses, such as changes in transcription regulatory mechanisms across species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Modification of Quark-Gluon Distributions in Nuclei by Correlated Nucleon Pairs

We extend the QCD Parton Model analysis using a factorized nuclear structure model incorporating individual nucleons and pairs of correlated nucleons. Our analysis of high-energy data from lepton deep-inelastic scattering, Drell-Yan, and W and Z boson production simultaneously extracts the universal effective distribution of quarks and gluons inside correlated nucleon pairs, and their nucleus-specific fractions. Such successful extraction of these universal distributions marks a significant advance in our understanding of nuclear structure properties connecting nucleon- and parton-level quantities. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Evolution of Charge-Lattice Dynamics across the Kuramoto Synchronization Phase Diagram of Quantum Tunneling Polarons in Cuprate Superconductors

Because of its sensitivity to the instantaneous structure factor, S(Q,t = 0), Extended X-ray Absorption Fine Structure (EXAFS) is a powerful tool for probing the dynamic structure of condensed matter systems in which the charge and lattice dynamics are coupled. When applied to hole-doped cuprate superconductors, EXAFS has revealed the presence of internal quantum tunneling polarons (IQTPs). An IQTP arises in EXAFS as a two-site distribution for certain Cu–O pairs, which is also duplicated in inelastic scattering but not observed in standard diffraction measurements. The Cu–Sr pair distribution has been found to be highly anharmonic and strongly correlated to both the IQTPs and to superconductivity, as, for example, in YSr 2 Cu 2.75 Mo 0.25 O 7.54 (T c =84 K). In order to describe such nontrivial, anharmonic charge-lattice dynamics, we have proposed a model Hamiltonian for a prototype six-atom cluster, in which two Cu-apical-O IQTPs are charge-transfer bridged through Cu atoms by an O atom in the CuO 2 plane and are anharmonically coupled via a Sr atom. By applying an exact diagonalization procedure to this cluster, we have verified that our model indeed produces an intricate interplay between charge and lattice dynamics. Then, by using the Kuramoto model for the synchronization of coupled quantum oscillators, we have found a first-order phase transition for the IQTPs into a synchronized, phase-locked phase. Most importantly, we have shown that this transition results specifically from the anharmonicity. Finally, we have provided a phase diagram showing the onset of the phase-locking of IQTPs as a function of the charge-lattice and anharmonic couplings in our model. We have found that the charge, initially confined to the apical oxygens, is partially pumped into the CuO 2 plane in the synchronized phase, which suggests a possible connection between the synchronized dynamic structure and high-temperature superconductivity (HTSC) in doped cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Generation of random geological models using multi-randomization for machine learning

Generating high-fidelity geological models is essential for advancing machine learning (ML) methods in automated seismic interpretation. For instance, seismic images paired with corresponding fault labels are foundational for ML-based fault detection from seismic migration sections. While several open-access datasets of random geological models exist, open-source tools specifically designed to produce large volumes of such models for ML applications remain scarce. To address this gap, we present RGM (Random Geological Model), an open-source software package for efficiently generating 2D and 3D synthetic geological models tailored for ML workflows. RGM supports the creation of diverse model components, including medium property distributions (P-/S-wave velocities and density), seismic reflectivity images (i.e., synthetic migration sections), relative geological time, and discrete fault attributes such as probability, dip, strike, rake, and displacement. It also accommodates the creation of complex geological features such as salt bodies and unconformities. The model generation algorithm employs a multi-randomization strategy, yielding an effectively infinite-dimensional model space that encompasses a wide range of geological scenarios and associated seismic features. Furthermore, RGM incorporates a method to generate synthetic elastic migration images using analytical elastic reflection coefficients combined with frequency-dependent scaling. This functionality enables the creation of training datasets for ML models that leverage elastic seismic images. RGM is implemented in modern object-oriented Fortran, allowing users to flexibly control statistical parameters governing model variability. We demonstrate the capability, performance, and geological realism of the package through comprehensive 2D and 3D examples.

58 GEOSCIENCES↗
DOE OSTI2026

Soil Water Retention and Hydraulic Conductivity Data and Model at Pump House in East River Watershed, Colorado 2019-2024

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors near Pump House at Mount Crested Butte in the East River Watershed. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format ER-X-Y, where ER refers to East River, X is the location identifier, and Y is the depth identifier at the same X (shallow Y=1). Specifically, ER-PHS, ER-LMC, ER-LMF, and ER-SMN are associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and ER-RBTn (upslope n=1) are sampling transects during the 2019 Rootball Campaign. The sample and location information can be found in metadata.csv. Sampling and Measurements Each sample falls into one of the three sampling methods – (1) intact cores, (2) repacked samples, or (3) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. Both intact cores and repacked samples were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores and in-situ soil sensors could be prioritized because these sampling methods are less destructive. While the repacked samples were packed to the target bulk density (estimated post-sampling, when sample volume was known), these samples had altered pore structures. Nevertheless, intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method also has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

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