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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Tissue Doppler Imaging Combined with Advanced 12-Lead ECG Analysis Might Improve Early Diagnosis of Hypertrophic Cardiomyopathy in Childhood

Optimization of early diagnosis of childhood hypertrophic cardiomyopathy (HCM) is essential in lowering the risk of HCM complications. Standard echocardiography (ECHO) has shown to be less sensitive in this regard. In this study, we sought to assess whether spatial QRS-T angle deviation, which has shown to predict HCM in adults with high sensitivity, and myocardial Tissue Doppler Imaging (TDI) could be additional tools in early diagnosis of HCM in childhood. Methods: Children and adolescents with familial HCM (n=10, median age 16, range 5-27 years), and without obvious hypertrophy but with heredity for HCM (n=12, median age 16, range 4-25 years, HCM or sudden death with autopsy-verified HCM in greater than or equal to 1 first-degree relative, HCM-risk) were additionally investigated with TDI and advanced 12-lead ECG analysis using Cardiax(Registered trademark) (IMED Co Ltd, Budapest, Hungary and Houston). Spatial QRS-T angle (SA) was derived from Kors regression-related transformation. Healthy age-matched controls (n=21) were also studied. All participants underwent thorough clinical examination. Results: Spatial QRS-T angle (Figure/ Panel A) and septal E/Ea ratio (Figure/Panel B) were most increased in HCM group as compared to the HCM-risk and control groups (p less than 0.05). Of note, these 2 variables showed a trend toward higher levels in HCM-risk group than in control group (p=0.05 for E/Ea and 0.06 for QRS/T by ANOVA). In a logistic regression model, increased SA and septal E/Ea ratio appeared to significantly predict both the disease (Chi-square in HCM group: 9 and 5, respectively, p less than 0.05 for both) and the risk for HCM (Chi-square in HCM-risk group: 5 and 4 respectively, p less than 0.05 for both), with further increased predictability level when these 2 variables were combined (Chi-square 10 in HCM group, and 7 in HCM-risk group, p less than 0.01 for both). Conclusions: In this small material, Tissue Doppler Imaging and spatial mean QRS-T angle deviation, particularly when combined, appear to be sensitive in predicting the risk for developing childhood HCM. Large-scale, prospective studies are needed to confirm this hypothesis.

Femlund, E.↗
NASA NTRS2012

Interval Management with Spacing to Parallel Dependent Runways (IMSPIDR) Experiment and Results

An area in aviation operations that may offer an increase in efficiency is the use of continuous descent arrivals (CDA), especially during dependent parallel runway operations. However, variations in aircraft descent angle and speed can cause inaccuracies in estimated time of arrival calculations, requiring an increase in the size of the buffer between aircraft. This in turn reduces airport throughput and limits the use of CDAs during high-density operations, particularly to dependent parallel runways. The Interval Management with Spacing to Parallel Dependent Runways (IMSPiDR) concept uses a trajectory-based spacing tool onboard the aircraft to achieve by the runway an air traffic control assigned spacing interval behind the previous aircraft. This paper describes the first ever experiment and results of this concept at NASA Langley. Pilots flew CDAs to the Dallas Fort-Worth airport using airspeed calculations from the spacing tool to achieve either a Required Time of Arrival (RTA) or Interval Management (IM) spacing interval at the runway threshold. Results indicate flight crews were able to land aircraft on the runway with a mean of 2 seconds and less than 4 seconds standard deviation of the air traffic control assigned time, even in the presence of forecast wind error and large time delay. Statistically significant differences in delivery precision and number of speed changes as a function of stream position were observed, however, there was no trend to the difference and the error did not increase during the operation. Two areas the flight crew indicated as not acceptable included the additional number of speed changes required during the wind shear event, and issuing an IM clearance via data link while at low altitude. A number of refinements and future spacing algorithm capabilities were also identified.

Baxley, Brian T.↗
DOE OSTI2025

Using Calibrated Sodium Data for Preliminary Validation of the SRT Code for Advanced Reactors

Various types of non-light water reactors are currently engaged in the U.S. licensing process. Because of inherent differences compared with well-established large light water reactors, appropriate assessment tools are needed. Specifically, source term analysis, which determines environmental dose impacts from potential accident scenarios, is a crucial part of design and licensing. The U.S. Nuclear Regulatory Commission has emphasized the importance of mechanistic source term analysis for advanced reactor deployments. To align with these needs, Argonne National Laboratory has developed the Simplified Radionuclide Transport (SRT) source term analysis code for metal fuel Sodium-cooled Fast Reactors (SFRs) and microreactors. SRT conducts time-dependent radionuclide transport and retention in SFRs for core and ex-core radionuclide source accident sequences. The main objective of SRT is to provide rapid sensitivity and uncertainty analyses, incorporating parametric uncertainties and summarizing probabilistic results. As part of the code validation process, a study focused on the bubble scrubbing module was performed using an experiment recently carried out by the University of Wisconsin-Madison. Based on the analysis, the modeling approach in SRT provides accurate results for small and large aerosols, while slight underprediction of radionuclide aerosol removal are observed for medium sized aerosols. However, the deviation is minor, considering the highly uncertain phenomenon and range of results, and is in the conservative direction. In addition, uncertainty information derived from the experiments is further implemented, reflecting the actual span of parameters, which leads to enhanced agreement with code predictions. The results demonstrate that SRT provides reasonable predictions for the bubble scrubbing process in sodium pool.

Kam, Dong Hoon↗
DOE OSTI2021

Wake steering of multirotor wind turbines

Abstract In this paper, wake steering is applied to multirotor turbines to determine whether it has the potential to reduce wind plant wake losses. Through application of rotor yaw to multirotor turbines, a new degree of freedom is introduced to wind farm control such that wakes can be expanded, channelled or redirected to improve inflow conditions for downstream turbines. Five different yaw configurations are investigated (including a baseline case) by employing large‐eddy simulations (LES) to generate a detailed representation of the velocity field downwind of a multirotor wind turbine. Two lower‐fidelity models from single‐rotor yaw studies (curled‐wake model and analytical Gaussian wake model) are extended to the multirotor case, and their results are compared with the LES data. For each model, the wake is analysed primarily by examining wake cross‐sections at different downwind distances. Further quantitative analysis is carried out through characterisations of wake centroids and widths over a range of streamwise locations and through a brief analysis of power production. Most significantly, it is shown that rotor yaw can have a considerable impact on both the distribution and magnitude of the wake velocity deficit, leading to power gains for downstream turbines. The lower‐fidelity models show small deviation from the LES results for specific configurations; however, both are able to reasonably capture the wake trends over a large streamwise range.

17 WIND ENERGY↗
DOE OSTI2026

Search for new physics in the final state with a single photon and large missing transverse momentum in proton-proton collisions at √𝑠 =13 TeV

A search for new physics in events featuring a single photon and missing transverse momentum is presented, using proton-proton √𝑠 =13 TeV collision data corresponding to an integrated luminosity of 101 fb −1 collected by the CMS experiment at the CERN LHC between 2017 and 2018. This analysis, combined with a previous study of 36 fb −1 of 2016 data (totaling 137 fb −1 ), reveals no significant deviations from standard model expectations. The results are then used to establish 95% confidence level limits on parameters in theoretical models involving dark matter and large extra dimensions. Compared to the 2016-only analysis, this search achieves up to a 14% improvement in exclusion reach for mediator masses in simplified dark matter models, along with 11% and 10% enhancements in the limits on the effective field theory suppression scale and the fundamental Planck scale, respectively. These results are the most stringent constraints on these parameters to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Vacuum stability bounds on Higgs coupling deviations in the absence of new bosons

We analyze the constraints imposed by Higgs vacuum stability on models with new fermions beyond the Standard Model. We focus on the phenomenology of Higgs couplings accessible at the Large Hadron Collider. New fermions that affect Higgs couplings lead to vacuum instability of the Higgs potential. Above the scale of vacuum instability, bosonic states must stabilize the potential, implying a cut-off to the pure fermion model. Conservatively tuning the models to produce the maximal cut-off for a given Higgs coupling effect, we show that observing a deviation in the Htt, H-diphoton, or H-digluon coupling, larger than 20%, would require that new bosons exist in order to stabilize the Higgs potential below about 100 TeV. For generic parameter configurations, and unless the new fermions are made as light as they can possibly be given current experimental constraints, observing a 10% deviation in any of these couplings would suggest an instability cut-off below 10-100 TeV. Similarly, if new bosons are absent up to a high scale, then a deviation in the Hbb or Hττ coupling, larger than about 20%, should be accompanied by a sizable deviation in the Zbb or Zττ couplings that can be conclusively tested with electroweak precision measurements at planned lepton colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Angular analysis of the B o → K *o μ + μ – decay using 3 fb –1 of integrated luminosity

An angular analysis of the B o → K *o (→ K + π – )μ + μ – decay is presented. The dataset corresponds to an integrated luminosity of 3.0 fb –1 of pp collision data collected at the LHCb experiment. The complete angular information from the decay is used to determine CP-averaged observables and CP asymmetries, taking account of possible contamination from decays with the K + π – system in an S-wave configuration. The angular observables and their correlations are reported in bins of q 2 , the invariant mass squared of the dimuon system. The observables are determined both from an unbinned maximum likelihood fit and by using the principal moments of the angular distribution. In addition, by fitting for q 2 -dependent decay amplitudes in the region 1.1 < q 2 < 6.0 GeV 2 /c 4 , the zero-crossing points of several angular observables are computed. A global fit is performed to the complete set of CP-averaged observables obtained from the maximum likelihood fit. This fit indicates differences with predictions based on the Standard Model at the level of 3.4 standard deviations. These differences could be explained by contributions from physics beyond the Standard Model, or by an unexpectedly large hadronic effect that is not accounted for in the Standard Model predictions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Extrapolation of thermal conductivity in non-equilibrium molecular dynamics simulations to bulk scale

Predictions of the bulk scale thermal conductivity of solids using non-equilibrium molecular dynamics (MD) simulations have relied on the linear extrapolation of the thermal resistivity versus the reciprocal of the system length in the simulations. Several studies have reported deviation of the extrapolation from linearity near the micro-scale, raising a concern of its applicability to large systems. To investigate this issue, present work conducted extensive MD simulations of silicon with two different potentials (EDIP and Tersoff-II) for unprecedented length scales up to 10.3 μm and simulation times up to 530 ns. For large systems ≥0.35 μm in size the non-linearity of the extrapolation of the reciprocal of the thermal conductivity is mostly due to ignoring the dependence of the thermal conductivity on temperature. To account for such dependence, the present analysis fixes the temperature range for determining the gradient for calculating the thermal conductivity values. However, short systems ≤0.23 μm in size show significant non-linearity in the calculated thermal conductivity values using a temperature window of 500 ± 10 K from the simulations results with the EDIP potential. Since these system sizes are shorter than the mean phonon free path in EDIP (~0.22 μm), the nonlinearity may be attributed to phonon transport. For the MD simulations with the Tersoff-II potential there is no significant non-linearity in the calculated thermal conductivity values for systems ranging in size from 0.05 to 5.4 μm.

42 ENGINEERING↗
DOE OSTI2022

Clean quartz matters for cosmogenic nuclide analyses: An exploration of the importance of sample purity using the CRONUS-N reference material

We report reference materials are key for assessing inter-laboratory variability and measurement quality, and for placing analytical uncertainty bounds on sample analyses. Here, we investigate four years of data resulting from repeated processing of the CRONUS-N reference material for cosmogenic 10 Be and 26 Al analyses. At University of Vermont, we prepared a CRONUS-N aliquot with most of our sample batches from 2013 to 2017; these reference material samples were then distributed to four different accelerator mass spectrometry facilities, yielding 73 10 Be analyses and 58 26 Al analyses. We determine CRONUS-N 10 Be concentrations of (2.26 ± 0.14) x 10 5 atoms g -1 (n = 73, mean, 1 SD) and 26 Al concentrations of (1.00 ± 0.08) x 10 6 atoms g -1 (n = 58, mean, 1 SD). We find a reproducibility of 6.3% for 10 Be and 7.7% for 26 Al (relative standard deviations). We also document highly variable 27 Al and Mg concentrations and a 10 Be dispersion twice as large as the mean AMS analytic uncertainty. Analyses of the CRONUS-N material with and without density separation demonstrate that non-quartz minerals are present in the material and have a large impact on measured concentrations of 27 Al, 10 Be, and impurities; these non-quartz minerals represent only a very small portion of the total mass (0.6–0.8%) but have a disproportionally large effect on the resulting data. Our results highlight the importance of completely removing all non-quartz mineral phases from samples prior to Be/Al extraction for the determination of in situ cosmogenic 10 Be and 26 Al concentrations.

58 GEOSCIENCES↗
DOE OSTI2016

Carbon sequestration in the uplands of Eastern China: an analysis with high-resolution model simulations

Using the DeNitrification-DeComposition (DNDC, version 9.5) model, we investigated the soil organic carbon (SOC) changes from 1980 to 2009 in Eastern China's upland-crop fields (3.7% of the land area of China) in northern Jiangsu Province. A currently most detailed high-resolution soil database, containing 17,024 polygons at a scale of 1:50,000, derived from 983 unique upland soil profiles, was used. A coarser county-level soil database was also used for a pair-wise simulation for comparison. We found that SOC changes modeled with the county-level soil database differ significantly from those with high-resolution soil data, with the deviation ranging from -64% to 8.0% in different counties. This implies that coarse soil data may lead to large biases in SOC simulation. With the high-resolution database, the model estimates a SOC increase of 37.89 Tg C in the top soils (0-50 cm) over the study area of 3.93 Mha for the past three decades, with an average rate of 322 kg C ha-1 year-1. The SOC accumulation in the study region accounts for 10.2% of annual national carbon sequestration, underscoring its significance to national climate mitigation. The annual SOC change varied between 61 to 519 kg C ha-1 year-1, mainly driven by the variations in N-fertilizer and manure applications. This study highlights the significance of high-resolution soil databases in quantifying SOC changes. Our high-resolution estimates of SOC will support farming and carbon management in this region.

Zhang, Liming↗
DOE OSTI2016

Drude weight and optical conductivity of a two-dimensional heavy-hole gas with k-cubic spin-orbit interactions

We present a detailed theoretical study on zero-frequency Drude weight and optical conductivity of a two-dimensional heavy-hole gas (2DHG) with k-cubic Rashba and Dresselhaus spin-orbit interactions. The presence of k-cubic spin-orbit couplings strongly modifies the Drude weight in comparison to the electron gas with k-linear spin-orbit couplings. For large hole density and strong k-cubic spin-orbit couplings, the density dependence of Drude weight deviates from the linear behavior. We establish a relation between optical conductivity and the Berry connection. Unlike two-dimensional electron gas with k-linear spin-orbit couplings, we explicitly show that the optical conductivity does not vanish even for equal strength of the two spin-orbit couplings. We attribute this fact to the non-zero Berry phase for equal strength of k-cubic spin-orbit couplings. The least photon energy needed to set in the optical transition in hole gas is one order of magnitude smaller than that of electron gas. Types of two van Hove singularities appear in the optical spectrum are also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Investigation of turbulent inflow specification in Euler–Lagrange simulations of mid-field spray

The process of atomization of a liquid jet by a parallel high-speed gas stream results in a spray, whose downstream development is of considerable interest to several applications. The round jet spray can be spatially divided into (i) a near-field (near-nozzle) region of liquid atomization and (ii) a downstream mid-field region of fully-dispersed droplets. In order to accurately model mid-field droplet dispersion, this work aims at developing a rigorous and robust injection model for Euler–Lagrange spray simulations. Results from experiments are used to obtain the relevant droplet number density, size distribution, and mean and standard deviation velocity distributions of the injection model, systematically in a step-by-step process. Two-phase large eddy simulations are performed by stochastically generating the Lagrangian droplets at the inlet of the mid-field region. Number flux, diameter distribution, mean velocity, and other time-averaged statistics at several downstream locations are shown to agree well with the corresponding experimental data.

42 ENGINEERING↗
DOE OSTI2022

A compendium and meta-analysis of flatband potentials for TiO2, ZnO, and SnO2 semiconductors in aqueous media

Semiconductor/electrolyte interfaces are of great interest to numerous scientific fields including renewable energy, (photo)electrochemistry, and energy storage. The semiconductor flatband potential is a key parameter in locating the conduction band minimum or valence band maximum of the semiconductor material in electrolyte. Despite its importance for quantifying the energetic location of the semiconductor bands, literature reports for the same material demonstrate significant variability in the flatband potential. In this compendium and meta-analysis, reported flatband potentials of the common semiconductor materials TiO2, SnO2, and ZnO in aqueous electrolyte were compiled and assessed to quantify the spread in literature flatband potentials as well as determine the factors that lead to the significant spread. For TiO2, SnO2, and ZnO, literature flatband potentials referenced to the reversible hydrogen electrode span a range of nearly 2 V each. Flatband potential tabulations were separated by variables such as the solution pH, the crystalline polymorph, the crystal facet, the morphology, and the dimensions or combinations of these variables to assess the factors that contribute to the observed spread. Important and surprising findings from these categorizations are summarized: (1) Even for the narrowest categorizations, the spread in flatband potential is still large. (2) Flatband potentials of TiO2 and SnO2 follow the expected Nernstian dependence with solution pH. ZnO materials deviate from this Nernstian dependence. (3) In the aggregate, there is no statistically significant difference in the reported flatband potentials of anatase and rutile TiO2. Single crystal tabulations were the only distributions to have statistically significant differences in the flatband potential between anatase and rutile TiO2. (4) Anatase TiO2 materials with a nanotube morphology appear to have a +400 mV difference in mean flatband potential compared to all other morphologies, but we argue that this is likely due to widespread misuse of the Mott–Schottky analysis. Other interesting findings are revealed within the spread of literature flatband potentials, and possible explanations are provided to generate discussion. We also briefly review and discuss common techniques that were used to determine the flatband potential and the pitfalls/criticisms of these techniques. Last, we discuss some ways in which future research on the determination of the flatband potential can be performed to improve the reliability of reported values and the quality of the work. In total, the results from this meta-analysis suggest multiple factors can affect the measured flatband potential and that an abundance of caution should be applied when attempting to quantify the flatband potential of complex or nanostructured systems.

Patel, Milan Y. (ORCID:0000000291948141)↗
DOE OSTI2019

Composite fermion Hall conductivity and the half-filled Landau level

We consider the Hall conductivity of composite fermions in the theory of Halperin, Lee, and Read (HLR). We present a fully quantum mechanical numerical calculation that shows, under suitable conditions, the HLR theory exhibits a particle-hole symmetric dc electrical Hall response in the presence of quenched disorder. Remarkably, this response of the HLR theory remains robust even when the disorder range is of the order of the Fermi wavelength. We nd that deviations from particle-hole symmetric response can appear in the ac Hall conductivity at frequencies su ciently large compared to the inverse system size. Our results agree with a recent semi-classical analysis by Wang et al., Phys. Rev. X 7, 031029 (2017) and complement the arguments based on the fully quantum-mechanical model by Kumar et al., Phys. Rev. B 98, 11505 (2018). These results provide further evidence that the HLR theory is compatible with an emergent particle-hole symmetry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

SU-F-T-125: Radial Dose Distributions From Carbon Ions of Therapeutic Energies Calculated with Geant4-DNA

Purpose: Radial dose distribution D(r) is the dose as a function of lateral distance from the path of a heavy charged particle. Its main application is in modelling of biological effects of heavy ions, including applications to hadron therapy. It is the main physical parameter of a broad group of radiobiological models known as the amorphous track models. Our purpose was to calculate D(r) with Monte Carlo for carbon ions of therapeutic energies, find a simple formula for D(r) and fit it to the Monte Carlo data. Methods: All calculations were performed with Geant4-DNA code, for carbon ion energies from 10 to 400 MeV/u (ranges in water: ∼ 0.4 mm to 27 cm). The spatial resolution of dose distribution in the lateral direction was 1 nm. Electron tracking cut off energy was 11 eV (ionization threshold). The maximum lateral distance considered was 10 µm. Over this distance, D(r) decreases with distance by eight orders of magnitude. Results: All calculated radial dose distributions had a similar shape dominated by the well-known inverse square dependence on the distance. Deviations from the inverse square law were observed close to the beam path (r<10 nm) and at large distances (r >1 µm). At small and large distances D(r) decreased, respectively, slower and faster than the inverse square of distance. A formula for D(r) consistent with this behavior was found and fitted to the Monte Carlo data. The accuracy of the fit was better than 10% for all distances considered. Conclusion: We have generated a set of radial dose distributions for carbon ions that covers the entire range of therapeutic energies, for distances from the ion path of up to 10 µm. The latter distance is sufficient for most applications because dose beyond 10 µm is extremely low.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

fPINNs: Fractional Physics-Informed Neural Networks

Physics-informed neural networks (PINNs), introduced, are effective in solving integer-order partial differential equations (PDEs) based on scattered and noisy data. PINNs employ standard feedforward neural networks (NNs) with the PDEs explicitly encoded into the NN using automatic differentiation, while the sum of the mean-squared PDE residuals and the mean-squared error in initial-boundary conditions is minimized with respect to the NN parameters. Here we extend PINNs to fractional PINNs (fPINNs) to solve space-time fractional advection-diffusion equations (fractional ADEs), and we study systematically their convergence, hence explaining both fPINNs and PINNs for the first time. Specifically, we demonstrate their accuracy and effectiveness in solving multidimensional forward and inverse problems with forcing terms whose values are only known at randomly scattered spatio-temporal coordinates (black-box (BB) forcing terms). A novel element of the fPINNs is the hybrid approach that we introduce for constructing the residual in the loss function using both automatic differentiation for the integer-order operators and numerical discretization for the fractional operators. This approach bypasses the difficulties stemming from the fact that automatic differentiation is not applicable to fractional operators because the standard chain rule in integer calculus is not valid in fractional calculus. To discretize the fractional operators, we employ the Grünwald--Letnikov (GL) formula in one-dimensional fractional ADEs and the vector GL formula in conjunction with the directional fractional Laplacian in two- and three-dimensional fractional ADEs. We first consider the one-dimensional fractional Poisson equation and compare the convergence of the fPINNs against the finite difference method (FDM). We present the solution convergence using both the mean L 2 error as well as the standard deviation due to sensitivity to NN parameter initializations. Using different GL formulas we observe first-, second-, and third-order convergence rates for small size training sets but the error saturates for larger training sets. We explain these results by analyzing the four sources of numerical errors due to discretization, sampling, NN approximation, and optimization. The total error decays monotonically (below 10 –5 for a third-order GL formula) but it saturates beyond that point due to the optimization error. We also analyze the relative balance between discretization and sampling errors and observe that the sampling size and the number of discretization points (auxiliary points) should be comparable to achieve the highest accuracy. As we increase the depth of the NN up to certain value, the mean error decreases and the standard deviation increases, whereas the width has essentially no effect unless its value is either too small or too large. We next consider time-dependent fractional ADEs and compare white-box (WB) and BB forcing. We observe that for the WB forcing, our results are similar to the aforementioned cases; however, for the BB forcing fPINNs outperform FDM. Subsequently, we consider multidimensional time-, space-, and space-time-fractional ADEs using the directional fractional Laplacian and we observe relative errors of 10 –3 ~ 10 –4 . Lastly, we solve several inverse problems in one, two, and three dimensions to identify the fractional orders, diffusion coefficients, and transport velocities and obtain accurate results given proper initializations even in the presence of significant noise.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those it is found that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely because of differences in instrumentation, calibration, and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat-dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory), and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but they poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration, or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Finally, data from models and observations should be put on the same spatial and temporal scales before comparison.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Fracture Network Localization Preceding Catastrophic Failure in Triaxial Compression Experiments on Rocks

We quantify the spatial distribution of fracture networks throughout six in situ X-ray tomography triaxial compression experiments on crystalline rocks at confining stresses of 5–35 MPa in order to quantify how fracture development controls the final macroscopic failure of the rock, a process analogous to those that control geohazards such as earthquakes and landslides. Tracking the proportion of the cumulative volume of fractures with volumes >90th percentile to the total fracture volume, ∑ v 90 / v t o t indicates that the fracture networks tend to increase in localization toward these largest fractures for up to 80% of the applied differential stress. The evolution of this metric also matches the evolution of the Gini coefficient, which measures the deviation of a population from uniformity. These results are consistent with observations of localizing low magnitude seismicity before large earthquakes in southern California. In both this analysis and the present work, phases of delocalization interrupt the general increase in localization preceding catastrophic failure, indicating that delocalization does not necessarily indicate a reduction of seismic hazard. However, the proportion of the maximum fracture volume to the total fracture volume does not increase monotonically. Experiments with higher confining stress tend to experience greater localization. To further quantify localization, we compare the geometry of the largest fractures, with volumes >90th percentile, to the best fit plane through these fractures immediately preceding failure. The r 2 scores and the mean distance of the fractures to the plane indicate greater localization in monzonite than in granite. The smaller mean mineral diameter and lower confining stress in the granite experiments may contribute to this result. Tracking these various metrics of localization reveals a close association between macroscopic yielding and the acceleration of fracture network localization. Near yielding, ∑ v 90 / v t o t and the Gini coefficient increase while the mean distance to the final failure plane decreases. Macroscopic yielding thus occurs when the rate of fracture network localization increases.

58 GEOSCIENCES↗