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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 1,171 records · Page 65

Machine learning-assisted upscaling analysis of reservoir rock core properties based on micro-computed tomography imagery

Optimum solutions for geologic modeling and reservoir simulation in industries such as oil and gas recovery and carbon capture and storage require accurate characterization of reservoir properties, which are often heterogeneous. In this study, high-quality micro-computed tomography (CT) images (1.475-μm/pixel resolution) of a sandstone core acquired from the Bell Creek oil field, USA, were used to provide nondestructive analysis of pore- and core-scale heterogeneity across measurement scales of 94–566 μm. In addition to characterizing the as-received sample, the core sample was flooded with brine to evaluate the capacity of the core sample to receive injected fluids. The micro-CT images were systematically segmented into pore spaces and grains via machine learning (ML) steps including image preprocessing, label creation using a traditional ML method based on limited manual image annotation, and finally U-Net segmentation. The segmented image stacks were reconstructed into digital cubes of various scales of voxel lengths. The 3D porosity values were calculated for all the digital cubes, and the fractal dimensions of the cubes were estimated using a box-counting method. The results showed that smaller cubes had greater heterogeneity and that the porosity values could be accurately estimated by fractal dimension and voxel lengths using ML models. For the core sample with brine flooding, the ratio of pores filled by brine to the total pore space was related to the porosity and could also be accurately estimated by porosity, fractal dimension, and voxel lengths using ML models. In conclusion, the results of this study demonstrate that the concept of fractal dimension can be a useful vector to perform upscaling analysis of sandstone rock heterogeneity from the pore to core scale and that fractal dimensions can be used to estimate porosity values and pore space-filling capacity across those scales.

58 GEOSCIENCES↗

Zero-truncated Poisson regression for sparse multiway count data corrupted by false zeros

Abstract We propose a novel statistical inference methodology for multiway count data that is corrupted by false zeros that are indistinguishable from true zero counts. Our approach consists of zero-truncating the Poisson distribution to neglect all zero values. This simple truncated approach dispenses with the need to distinguish between true and false zero counts and reduces the amount of data to be processed. Inference is accomplished via tensor completion that imposes low-rank tensor structure on the Poisson parameter space. Our main result shows that an $N$-way rank-$R$ parametric tensor $\boldsymbol{\mathscr{M}}\in (0,\infty )^{I\times \cdots \times I}$ generating Poisson observations can be accurately estimated by zero-truncated Poisson regression from approximately $IR^2\log _2^2(I)$ non-zero counts under the nonnegative canonical polyadic decomposition. Our result also quantifies the error made by zero-truncating the Poisson distribution when the parameter is uniformly bounded from below. Therefore, under a low-rank multiparameter model, we propose an implementable approach guaranteed to achieve accurate regression in under-determined scenarios with substantial corruption by false zeros. Several numerical experiments are presented to explore the theoretical results.

97 MATHEMATICS AND COMPUTING↗

Neutron Coincidence Counting Studies

The efficiency comparison for measured and simulated responses of a 10 B-lined proportional counter and a 3 He proportional counter in a close, symmetrical geometry are presented. The measurement geometry was modeled in MCNPX to validate the methods used for simulating the response of both the 3 He and 10 B-lined tubes. The MCNPX models agree within 1% with the 3 He tube measurements and within 3% for the 10 B-lined tubes when a 0.75-µm boron-metal lining is used.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

False Indications of Dose-Response Nonlinearity in Large Epidemiologic Cancer Radiation Cohort Studies; A Simulation Exercise

This study explores the likely prevalence of false indications of dose-response nonlinearity in large epidemiologic cancer radiation cohort studies (A-bomb survivors, INWORKS, Techa River). Reasons: Increasing numbers of tests of nonlinearity are being made in studies. Hypothesized nonlinear dose-response models have been justified to policy makers by analyses that rely in part on isolated findings that could be statistical fluctuations. After removing dose nonlinearity (linearization) by adjusting person-years of observation at each dose category, indications of nonlinearity, necessarily false, were counted in 5,000 randomized replications of six datasets. The average frequency of any false positive for five indicators of nonlinearity tested against a linear null was roughly 25% in Monte Carlo simulations per study, consistent with binomial calculations, increasing to ~50% within 6 studies assessed. Comparable frequencies were found using Akaike's information criterion (AIC) for model selection or multi-model averaging. False above-zero threshold doses were found more than 50% of the time, averaging to 0.05 Gy, consistent with findings in the 6 studies. Such bias, uncorrected, could distort meta-analyses of multiple studies, because meta-analyses can incorporate high P value findings. AIC-based correction for the extra threshold parameter lowered these false occurrences to 8 to 19%. Given the simulation rates, the possibility of false positives might be noted when isolated findings of nonlinearity are discussed in a regulatory context. When reporting a threshold dose with a P value > 0.05, it would be informative to note the expected high false prevalence rate due to bias.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

On the validity of the perturbative description of axions during inflation

Axions play a central role in many realizations of large field models of inflation and in recent alternative mechanisms for generating primordial tensor modes in small field models. If these axions couple to gauge fields, the coupling produces a tachyonic instability that leads to an exponential enhancement of the gauge fields, which in turn can decay into observable scalar or tensor curvature perturbations. Thus, a fully self-consistent treatment of axions during inflation is important, and in this work we discuss the perturbative constraints on axions coupled to gauge fields. We show how the recent proposal of generating tensor modes through these alternative mechanisms is in tension with perturbation theory in the in-in formalism. Interestingly, we point out that the constraints are parametrically weaker than one would estimate based on naive power counting of propagators of the gauge field. In the case of non-Abelian gauge fields, we derive new constraints on the size of the gauge coupling, which apply also in certain models of natural large field inflation, such as alignment mechanisms.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spline function approximation for velocimeter Doppler frequency measurement

A spline function approximation approach for measuring the Doppler spectral peak frequency in a laser Doppler velocimeter system is presented. The processor is designed for signal bursts with mean Doppler shift frequencies up to 100 MHz, input turbulence up to 20 percent, and photon counts as low as 300. The frequency-domain processor uses a bank of digital bandpass filters for the capture of the energy spectrum of each signal burst. The average values of the filter output energies, as a function of normalized frequency, are modeled as deterministic spline functions which are linearly weighted to evaluate the spectral peak location associated with the Doppler shift. The weighting coefficients are chosen to minimize the mean square error. Performance evaluation by simulation yields average errors in estimating mean Doppler frequencies within 0.5 percent for poor signal-to-noise conditions associated with a low photon count of 300 photons/burst.

Savakis, Andreas E.↗

Localization of a radioactive source in an urban environment using Bayesian Metropolis methods [Bayesian Metropolis methods for source localization in an urban environment]

Here, we present a method for localizing an unknown source of radiation in an urban environment using a distributed detector network. This method employs statistical parameter estimation techniques, relying on an approximation for the response of a detector to the source based on a simplified model of the underlying transport phenomena, combined with a Metropolis-type sampler that is modified to propagate the effect of fixed epistemic uncertainties in the material macroscopic cross sections of objects in the scene. We apply this technique to data collected during a measurement campaign conducted in a realistic analog for an urban scene using a network of six mobile detectors. Our initial results are able to localize the source to within approximately 8 m over a scene of size 300 m 200 m in two independent trials with 30 min count times, including a characterization of the uncertainty associated with the poorly known macroscopic cross sections of objects in the scene. In these measurements, the nearest detectors were between 20 m to 30 m from the source, and recorded count rates between approximately 3 and 13 times background. A few detectors had line-of-sight to the source, while the majority were obscured by objects present in the scene. After extending our model to account for the orientation of the detectors and correcting for anomalies in the measurement data we were able to further improve the localization accuracy to approximately 2 m in both trials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Comparison of manually produced and automated cross country movement maps using digital image processing techniques

The Image-Based Information System (IBIS) was used to automate the cross country movement (CCM) mapping model developed by the Defense Mapping Agency (DMA). Existing terrain factor overlays and a CCM map, produced by DMA for the Fort Lewis, Washington area, were digitized and reformatted into geometrically registered images. Terrain factor data from Slope, Soils, and Vegetation overlays were entered into IBIS, and were then combined utilizing IBIS-programmed equations to implement the DMA CCM model. The resulting IBIS-generated CCM map was then compared with the digitized manually produced map to test similarity. The numbers of pixels comprising each CCM region were compared between the two map images, and percent agreement between each two regional counts was computed. The mean percent agreement equalled 86.21%, with an areally weighted standard deviation of 11.11%. Calculation of Pearson's correlation coefficient yielded +9.997. In some cases, the IBIS-calculated map code differed from the DMA codes: analysis revealed that IBIS had calculated the codes correctly. These highly positive results demonstrate the power and accuracy of IBIS in automating models which synthesize a variety of thematic geographic data.

Wynn, L. K.↗

Data Files for 'The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure'

This data set includes modeling results from The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure, including region-specific (i.e., national, state, and core-based statistical area cities and towns) electric vehicle supply equipment port count requirements in 2025 and 2030 for multiple scenarios described in the study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An analysis of the Basel star catalog

The standard Bahcall-Soneira (1980) Galaxy model is compared with the data from the 12 fields in the Basel star catalog that are at Galactic latitudes above 20 deg and have E(B-V) of less than 0.1 mag. Good agreement is found between the calculated and observed color distributions, as well as star counts, for all the fields. The globular cluster feature that is observed in the luminosity function of globular clusters near M(v) = +1 to +4 mag is also present in the spheroid field stars. It is possible to assign some of the spheroid stars from the standard two-component Galaxy model (thin disk plus de Vaucouleurs spheroid) to a third stellar component (a thick disk with a spheroid luminosity function) without disturbing the agreement with observations.

Bahcall, J. N.↗

A Scalable Algorithm for Radiative Heat Transfer Using Reverse Monte Carlo Ray Tracing

Radiative heat transfer is an important mechanism in a class of challenging engineering and research problems. A direct all-to-all treatment of these problems is prohibitively expensive on large core counts due to pervasive all- to-all MPI communication. The massive heat transfer problem arising from the next generation of clean coal boilers being modeled by the Uintah framework has radiation as a dominant heat transfer mode. Reverse Monte Carlo ray tracing (RMCRT) can be used to solve for the radiative-flux divergence while accounting for the effects of participating media. The ray tracing approach used here replicates the geometry of the boiler on a multi-core node and then uses an all-to-all communication phase to distribute the results globally. The cost of this all-to-all is reduced by using an adaptive mesh approach in which a fine mesh is only used locally, and a coarse mesh is used elsewhere. Here, a model for communication and computation complexity is used to predict performance of this new method. We show this model is consistent with observed results and demonstrate excellent strong scaling to 262K cores on the DOE Titan system on problem sizes that were previously computationally intractable.

97 MATHEMATICS AND COMPUTING↗

Generalized eikonal identities for charged currents

Abstract We discuss QED radiative corrections to contact operators coupling two heavy fields and one light field. These operators appear ubiquitously in weak interactions with nuclei such as beta decay and neutrino nucleus scattering. New eikonal identities are derived in the static limit (i.e., neglecting nuclear recoil) that allow for manifest power counting of enhancements proportional to the charge of the nucleus. We apply these new identities to nuclear beta decays and find that the “independent particle model” used by Jaus, Rasche, Sirlin & Zucchini is closely related, though not identical, to a model independent effective field theorcalculation.

Physics↗

Energy, power, and infrastructure demands from electrifying airport ground support equipment at United States airports

As the airline industry seeks to reduce costs and transition to clean energy, electric ground support equipment is emerging as a favorable option. The integration of electric ground support equipment into airport operations requires careful planning for vehicle deployment, charging infrastructure, and grid impacts. We develop a flexible, bottom-up modeling framework to assess energy and infrastructure needs across more than 300 U.S. airports. Our analysis estimates site-specific power and energy demand, equipment counts by type, charger requirements, and costs. Here we quantify the magnitude of new electrical loads created by the electrification of airport ground support equipment, finding that peak power demand at the largest airports can reach up to 20 megawatts, with annual electricity consumption approaching 51,000 megawatt-hours. We further show that behind-the-meter battery energy storage systems and solar photovoltaic systems can reduce peak load and lower total system costs by as much as 10 million dollars.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Applications of the associated-particle neutron-time-of-flight interrogation technique - From sheep to unexploded ordnance

The associated-particle technique (APT) will be presented for some diverse applications that include on the one hand, analyzing the body composition of live sheep and on the other, identifying the fillers of unexploded ordnance (UXO). What began with proof-of-concept studies using a large laboratory based 14 MeV neutron generator of the 'associated-particle' type, soon became possible for the first time to measure total body protein, fat and water simultaneously in live sheep using a compact field deployable associated-particle sealed-tube neutron generator (APSTNG). This non-invasive technique offered the animal physiologist a tool to monitor the growth of an animal in response to new genetic, nutritional and pharmacologic methods for livestock improvement. While measurement of carbon (C), nitrogen (N) and oxygen (O) determined protein, fat and water because of the fixed stoichiometric proportions of these elements in these body components, the unique C/N and C/O ratios of high explosives revealed their identity in UXO. The algorithm that was developed and implemented to extract C, N and O counts from an APT generated gamma-ray spectrum will be presented together with the UXO investigations that involved preliminary proofof-concept studies and modeling with Monte Carlo produced synthetic spectra of 57-155 mm projectiles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Screening materials with the XIA UltraLo alpha particle counter at Southern Methodist University

Southern Methodist University houses one of five existing commercially available UltraLo 1800 production model alpha counters made by XIA LLC. The instrument has an electron drift chamber with a 707 cm{sup 2} or 1800 cm{sup 2} counting region which is determined by selecting the inner electrode size. The SMU team operating this device is part of the SuperCDMS screening working group, and uses the alpha counter to study the background rates from the decay of radon in materials used to construct the SuperCDMS experiment. We have studied four acrylic samples obtained from the MiniCLEAN direct dark matter search with the XIA instrument demonstrating its utility in low background experiments by investigating the plate-out of {sup 210}Pb and comparing the effectiveness of cleaning procedures in removing {sup 222}Rn progenies from the samples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Tip radius preservation for high resolution imaging in amplitude modulation atomic force microscopy

The acquisition of high resolution images in atomic force microscopy (AFM) is correlated to the cantilever's tip shape, size, and imaging conditions. In this work, relative tip wear is quantified based on the evolution of a direct experimental observable in amplitude modulation atomic force microscopy, i.e., the critical amplitude. We further show that the scanning parameters required to guarantee a maximum compressive stress that is lower than the yield/fracture stress of the tip can be estimated via experimental observables. In both counts, the optimized parameters to acquire AFM images while preserving the tip are discussed. The results are validated experimentally by employing IgG antibodies as a model system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Compare linear-system solver and preconditioner stacks with emphasis on GPU performance and propose phase-2 NGP solver development pathway

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. In this report we evaluated GPU-performance baselines for the linear solvers in the Trilinos and hypre solver stacks using two representative Nalu-Wind simulations: an atmospheric boundary layer precursor simulation on a structured mesh, and a fixed-wing simulation using unstructured overset meshes. Both strong-scaling and weak-scaling experiments were conducted on the OLCF supercomputer Summit and similar proxy clusters. We focused on the performance of multi-threaded Gauss-Seidel and two-stage Gauss-Seidel that are extensions of classical Gauss-Seidel; of one-reduce GMRES, a communication-reducing variant of the Krylov GMRES; and algebraic multigrid methods that incorporate the afore-mentioned methods. The team has established that AMG methods are capable of solving linear systems arising from the fixed-wing overset meshes on CPU, a critical intermediate result for ExaWind FY20 Q3 and Q4 milestones. For the fixed-wing strong-scaling study (model with 3M grid-points), the team identified that Nalu-Wind simulations with the new Trilinos and hypre solvers scale to modest GPU counts, maintaining above 70% efficiency up to 6 GPUs. However, there still remain significant bottlenecks to performance: matrix assembly (hypre), AMG setup (hypre and Trilinos) In the weak-scaling experiments (going from 0.4M to 211M gridpoints), it's shown that the solver apply phases are faster on GPUs, but that Nalu-Wind simulation times grow, primarily due to the multigrid-setup process. Finally, based on the report outcomes, we propose a linear solver path-forward for the remainder of the ExaWind project. Near term, the NREL team will continue their work on GPU-based linear-system assembly. They will also investigate how the use of alternatives to the NVIDIA UVM (unified virtual memory) paradigm affects performance. Longer term, the NREL team will evaluate algorithmic performance on other types of accelerators and merge their improvements back to the main hypre repository branch. Near term, the Trilinos team will address performance bottlenecks identified in this milestone, such as implementing a GPU-based segregated momentum solve and reusing matrix graphs across linear-system assembly phases. Longer term, the Trilinos team will do detailed analysis and optimization of multigrid setup.

17 WIND ENERGY↗

PRIME - A Software Toolkit for the Characterization of Partially Observed Epidemics in a Bayesian Framework

PRIME is a modeling framework designed for the “real-time’” characterization and forecasting of partially observed epidemics. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients. The method is designed to help guide medical resource allocation in the early epoch of the outbreak. The estimation problem is posed as one of Bayesian inference and solved using a Markov Chain Monte Carlo technique. The framework can accommodate multiple epidemic waves and can help identify different disease dynamics at the regional, state, and country levels. We include examples using publicly available COVID-19 data.

97 MATHEMATICS AND COMPUTING↗