Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “sampling statistics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36

THREE DISCRETE GROUPS WITH HOMOGENEOUS CHEMISTRY ALONG THE RED GIANT BRANCH IN THE GLOBULAR CLUSTER NGC 2808

We present the homogeneous reanalysis of Mg and Al abundances from high resolution UVES/FLAMES spectra for 31 red giants in the globular cluster NGC 2808. We found a well defined Mg-Al anticorrelation reaching a regime of subsolar Mg abundance ratios, with a spread of about 1.4 dex in [Al/Fe]. The main result from the improved statistics of our sample is that the distribution of stars is not continuous along the anticorrelation because they are neatly clustered into three distinct clumps, each with different chemical compositions. One group (P) shows a primordial composition of field stars of similar metallicity, and the other two (I and E) have increasing abundances of Al and decreasing abundances of Mg. The fraction of stars we found in the three components (P: 68%, I: 19%, E: 13%) is in excellent agreement with the ratios computed for the three distinct main sequences in NGC 2808: for the first time there is a clear correspondence between discrete photometric sequences of dwarfs and distinct groups of giants with homogeneous chemistry. The composition of the I group cannot be reproduced by mixing of matter with extreme processing in hot H-burning and gas with pristine, unprocessed composition, as also found in the recent analysis of three discrete groups in NGC 6752. This finding suggests that different classes of polluters were probably at work in NGC 2808 as well.

79 ASTRONOMY AND ASTROPHYSICS↗

Micro on a macroscale: relating microbial-scale soil processes to global ecosystem function

ABSTRACT Soil microorganisms play a key role in driving major biogeochemical cycles and in global responses to climate change. However, understanding and predicting the behavior and function of these microorganisms remains a grand challenge for soil ecology due in part to the microscale complexity of soils. It is becoming increasingly clear that understanding the microbial perspective is vital to accurately predicting global processes. Here, we discuss the microbial perspective including the microbial habitat as it relates to measurement and modeling of ecosystem processes. We argue that clearly defining and quantifying the size, distribution and sphere of influence of microhabitats is crucial to managing microbial activity at the ecosystem scale. This can be achieved using controlled and hierarchical sampling designs. Model microbial systems can provide key data needed to integrate microhabitats into ecosystem models, while adapting soil sampling schemes and statistical methods can allow us to collect microbially-focused data. Quantifying soil processes, like biogeochemical cycles, from a microbial perspective will allow us to more accurately predict soil functions and address long-standing unknowns in soil ecology.

59 BASIC BIOLOGICAL SCIENCES↗

Quantitative Particle Analysis of Neptunium-237 Oxides: Optimization of MAMA Analysis for Modified Direct Denitration Products

The production of plutonium-238 through irradiation of neptunium-237 ( 237 Np) target materials for the use in radioisotope thermoelectric generators is paramount for continued deep space exploration. This work employs scanning electron microscopy to analyze 237 Np materials coupled with a well-developed image analysis framework (Morphological Analysis for Material Attribution, or MAMA) to determine the degree of micron-scale homogeneity in the materials. This work demonstrated how the quantification of particle characteristics can validate production materials and affirm the qualitative similarities observed in micrographs. The 237 Np oxide particle analysis determined that the materials from five production runs were quantitatively homogenous (significant at α = 0.05) in particle area, circularity, equivalent circular diameter, and ellipse aspect ratio, with two of the sampling dates having statistically significant different means for one of the four characteristics. Furthermore, these metrics not only confirm general homogeneity of the material but also expand the application of MAMA workflows to 237 Np materials, demonstrating the utility of MAMA analysis for a wider breadth of nuclear materials than previously reported. In the open literature, this study is the first time that these microanalytical techniques were applied to 237 Np materials to this degree.

MAMA↗

Testing hadronic-model predictions of depth of maximum of air-shower profiles and ground-particle signals using hybrid data of the Pierre Auger Observatory

We test the predictions of hadronic interaction models regarding the depth of maximum of air-shower profiles, X max , and ground-particle signals in water-Cherenkov detectors at 1000 m from the shower core, S ( 1000 ) , using the data from the fluorescence and surface detectors of the Pierre Auger Observatory. The test consists of fitting the measured two-dimensional ( S ( 1000 ) , X max ) distributions using templates for simulated air showers produced with hadronic interaction models pos-, et--04, 2.3d and leaving the scales of predicted X max and the signals from hadronic component at ground as free-fit parameters. The method relies on the assumption that the mass composition remains the same at all zenith angles, while the longitudinal shower development and attenuation of ground signal depend on the mass composition in a correlated way. The analysis was applied to 2239 events detected by both the fluorescence and surface detectors of the Pierre Auger Observatory with energies between 10 18.5 eV to 10 19.0 eV and zenith angles below 60°. We found, that within the assumptions of the method, the best description of the data is achieved if the predictions of the hadronic interaction models are shifted to deeper X max values and larger hadronic signals at all zenith angles. Given the magnitude of the shifts and the data sample size, the statistical significance of the improvement of data description using the modifications considered in the paper is larger than 5 σ even for any linear combination of experimental systematic uncertainties. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗

Phase-space methods for neutrino oscillations: Extension to multibeams

The phase-space approach (PSA), which was originally introduced in Lacroix [] to describe neutrino flavor oscillations for interacting neutrinos emitted from stellar objects is extended to describe arbitrary numbers of neutrino beams. The PSA is based on mapping the quantum fluctuations into a statistical treatment by sampling initial conditions followed by independent mean-field evolution. A new method is proposed to perform this sampling that allows treating an arbitrary number of neutrinos in each neutrino beams. We validate the technique successfully and confirm its predictive power on several examples where a reference exact calculation is possible. We show that it can describe many-body effects, such as entanglement and dissipation induced by the interaction between neutrinos. Due to the complexity of the problem, exact solutions can only be calculated for rather limited cases, with a limited number of beams and/or neutrinos in each beam. The PSA approach considerably reduces the numerical cost and provides an efficient technique to accurately simulate arbitrary numbers of beams. Examples of PSA results are given here, including up to 200 beams with time-independent or time-dependent Hamiltonians. We anticipate that this approach will be useful to bridge exact microscopic techniques with more traditional transport theories used in neutrino oscillations. It will also provide important reference calculations for future quantum computer applications where other techniques are not applicable to classical computers. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Delta Modulation Technique for Improving the Sensitivity of Monobit Subsamplers in Radar and Coherent Receiver Applications

This paper introduces a technique for improving the sensitivity of RF subsamplers in radar and coherent receiver applications. The technique, referred to herein as “delta modulation” (DM), feeds the time-average output of a monobit analog-to-digital converter (ADC) back to the ADC input, but with opposite polarity. Assuming pseudo-stationary modulation statistics on the sampled RF waveform, the feedback signal corrects for aggregate DC offsets present in the ADC that otherwise degrade ADC sensitivity. Two RF integrated circuits (RFICs) are designed to demonstrate the approach. One uses analog DM to create the feedback signal; the other uses digital DM to achieve the same result. A series of tests validates the designs. The dynamic time-domain response confirms the feedback loop’s basic operation. Measured output quantization imbalance, under noise-only input drive, significantly improves with the use of the DM circuit, even for large, deliberately induced DC offsets and wide temperature variation from -55°C to +85 °C. Examination of the corrected vs. uncorrected baseband spectrum under swept input signal-tonoise ratio (SNR) conditions demonstrates the effectiveness of this approach for realistic radar and coherent receiver applications. In conclusion, two-tone testing shows no impact of the DM technique on ADC linearity.

47 OTHER INSTRUMENTATION↗

Robust Design Under Uncertainty in Quantum Error Mitigation

Error mitigation techniques are crucial to achieving near-term quantum advantage. Classical postprocessing of quantum computation outcomes is a popular approach for error mitigation, which includes methods, such as zero noise extrapolation, virtual distillation, and learning-based error mitigation. However, these techniques have limitations due to the propagation of uncertainty resulting from the finite shot number of a quantum measurement. In this work, we introduce general and unbiased methods for quantifying the uncertainty and error of error-mitigated observables based on the strategic sampling of error mitigation outcomes. We then extend our approach to demonstrate the optimization of performance and robustness of error mitigation under uncertainty. To illustrate our methods, we apply them to zero noise extrapolation and Clifford date regression in the ground state of the XY model simulated using depolarizing and International Business Machines Corporation (IBM) Toronto noise models, respectively. In particular, we optimize the choice of noise levels and the allocation of shots for zero noise extrapolation and the distribution of the training circuits for Clifford data regression. While our methods are readily applicable to any postprocessing-based error mitigation approach, in practice they must not be prohibitively expensive—even though they perform optimizations of the error mitigation hyperparameters requiring sampling of a statistical distribution of error mitigation outcomes. By leveraging surrogate-based optimization, we show that our methods can efficiently perform optimal design for a zero noise extrapolation implementation. We then further demonstrate the transferability of learned zero noise extrapolation hyperparameters to other similar circuits.

97 MATHEMATICS AND COMPUTING↗

Understanding relative metal prices and availability: Combining physical and economic perspectives

Abstract Scientists typically use physical indicators, such as average crustal abundance, and energy requirements in production, as measures of the availability of mineral resources. Economists, on the other hand, typically rely on measures such as prices, and extraction costs. This study investigates the role of crustal abundance, energy requirements, and other physical indicators in determining relative metal prices. The relationship between prices, and physical indicators is estimated statistically for a sample of 22 chemical elements over the period 1970–2013 using an economic market model. The results suggest that energy requirements in production explain 43% of observed variation in metal prices, crustal abundance 21%, and other physical indicators (toxicity, native metal status, and melting point) combine to explain 12% of the observed differences in metal prices.

Watson, Brett J.↗

Prediction of Probabilistic Shock Initiation Thresholds of Energetic Materials Through Evolution of Thermal-Mechanical Dissipation and Reactive Heating

The ignition threshold of an energetic material (EM) quantifies the macroscopic conditions for the onset of self-sustaining chemical reactions. The threshold is an important theoretical and practical measure of material attributes that relate to safety and reliability. Historically, the thresholds are measured experimentally. In this work, we present a new Lagrangian computational framework for establishing the probabilistic ignition thresholds of heterogeneous EM out of the evolutions of coupled mechanical-thermal-chemical processes using mesoscale simulations. Furthermore, the simulations explicitly account for microstructural heterogeneities, constituent properties, and interfacial processes and capture processes responsible for the development of material damage and the formation of hotspots in which chemical reactions initiate. The specific mechanisms tracked include viscoelasticity, viscoplasticity, fracture, post-fracture contact, frictional heating, heat conduction, reactive chemical heating, gaseous product generation, and convective heat transfer. To determine the ignition threshold, the minimum macroscopic loading required to achieve self-sustaining chemical reactions with a rate of reactive heat generation exceeding the rate of heat loss due to conduction and other dissipative mechanisms is determined. Probabilistic quantification of the processes and the thresholds are obtained via the use of statistically equivalent microstructure sample sets (SEMSS). The predictions are in agreement with available experimental data.

36 MATERIALS SCIENCE↗

Features of the application of the Monte Carlo method to calculations for large RBMK reactors and to model correction on the basis of data from in-core detectors

Statistical errors in sampling neutron fields in physically large systems like an RBMK are analyzed both qualitatively and quantitatively. Recommendations concerning the choice of parameters for calculations are given. A new procedure for Monte Carlo RBMK calculations with model corrections on the basis of data from in-core detectors is proposed. Dedicated software based on the CUDA software and hardware platform is developed for computational research. Results of testing the procedure and software in question via calculations for real RBMK reactors are discussed.

74 ATOMIC AND MOLECULAR PHYSICS↗

COSUBS

COSUBS (COrrelated Sampling Using Batch Statistics) reads MCNP6 output files and propagates the statistical uncertainties of various combinations of tallies using batch statistics, accounting for correlations.

Favorite, Jeffrey↗

CORRLA-RS

The CORRLA-RS package provides a suite of statistical methods for sampling multidimensional distributions and to conduct sensitivity and correlation analysis of large scale data in the Rust programming language. The software provides a unique solution to multidimensional constrained sampling problems utilizing a combination of parallelized Markov Chain Monte Carlo methods and traditional rejection sampling. The sensitivity and correlation analysis methods are backed by a high performance randomized singular value decomposition implementation which enables datasets larger than the random access memory (RAM) size to be analyzed. Additionally, CORRLA-RS implements the active subspace identification method using a KD-Tree and the randomized singular value decomposition acting in concert.

Gurecky, William [Oak Ridge National Laboratory (O↗

Commercial Building Energy Code Field Study (Final Report)

What is the dollar value of increasing compliance with the energy code? Ultimately, this is the question that policy makers, funders, and program implementers care about. With this in mind, Pacific Northwest National Laboratory (PNNL) developed a new methodology capable of determining how much energy cost savings could potentially be gained through better compliance with the code (Rosenberg et al. 2016). On March 2, 2016 DOE issued Funding Opportunity Announcement (FOA) Number DE-FOA-0001532, requesting proposals to develop and test a methodology for identifying the commercial energy code requirements that can provide the maximum cost-effective energy and cost savings through increased compliance. Awarded to the Institute for Market Transformation, this report summarizes the development and testing of a commercial code compliance methodology, including a summary of results, statistical analysis of sample, and best practices for others implementing a commercial energy code compliance field study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Exploring the Nature of Neutrinos with the Deep Underground Neutrino Experiment (DUNE)

The Deep Underground Neutrino Experiment (DUNE) is a next-generation experimental program designed to study the behaviour of neutrino oscillation. DUNE will utilize a neutrino beam originating at Fermilab, near Chicago, and will leverage a detector at Fermilab (Near Detector) and a detector 1300 km away in South Dakota (Far Detector), south of Saskatchewan. In the first phase of DUNE, its Far Detector will comprise of two 10,000 ton (fiducial) liquid argon (LAr) time-projection chamber (TPC) modules – powerful tracking calorimeter detectors – placed nearly a mile underground. With this large, sensitive, underground detector, DUNE aims to collect a high statistics and pure sample of neutrinos at the Far Detector. This setup also offers the potential to study non-beam physical processes via e.g. neutrinos produced in the atmosphere, supernova neutrino bursts, and/or solar neutrinos, etc. A second phase will aim to add more detector mass and expand the program. The Near Detector will consist of a LAr TPC module as well: critical to constraining systematic uncertainties in the oscillation analysis. However, this LAr TPC will have a novel design using a pixel-based readout instead of the traditional wire-based readout. This and the segmentation of the LAr TPC into multiple units are crucial in mitigating the high multiplicity of neutrino interactions expected in any readout window given its proximity to the beam. The Near Detector will feature additional components and capability beyond the LAr TPC, allowing one to deeply characterize the neutrino flux. Due to the complexity of this experimental program, several smaller-scale prototype detectors have been operating to test, validate, and improve both the technical designs and software for processing and analyzing events. By operating in charged particle test beams or neutrino beams, several of the prototypes are also capable of producing valuable results. Canadian institutions are involved in the realization of the DUNE through efforts with both the Near and Far Detectors and prototypes. DUNE is anticipated to begin operating near the end of this decade/the beginning of the next. This talk will focus on the overall DUNE program, for example its ultimate plans, status, and the efforts with prototypes.

Howard, Bruce [York U., Canada; Fermilab]↗

High-Burnup LOCA Burst Susceptibility BISON Analysis in PWRs and BWRs

Accurately assessing high-burnup fuel behavior during loss-of-coolant accidents (LOCAs) is essential for understanding fuel fragmentation, relocation, and dispersal (FFRD) risks across the US light-water reactor fleet. This work updates previous Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program multiphysics LOCA analyses for a pressurized water reactor (PWR) and a boiling water reactor (BWR) by incorporating recent model and material property advancements in the BISON fuel performance code, including a high-burnup structure (HBS) model, revised cladding burst criteria, and updated thermal–mechanical correlations. This update was needed to support ongoing industry initiatives and upcoming regulatory changes. Full-core, rod-resolved operating histories generated using Virtual Environment for Reactor Analysis (VERA) and system-level LOCA conditions obtained from TRACE were applied to statistically representative rod samples in BISON to evaluate burst behavior and FFRD susceptibility. These calculations used two cladding burst correlations and three fuel pulverization models so that the predictions of these models could be compared. The updated PWR simulations show markedly improved numerical stability as the number of crashed simulations decreased by 95% compared to the previous study, and hence higher confidence in results. The updated PWR simulations predicted cladding bursts exclusively among once-burned, high-power rods, with two different cladding burst models identifying the same burst-susceptible population. Resulting FFRD susceptibility estimates are significantly reduced compared with earlier studies, driven by cooler predicted fuel and plenum temperatures, lower hoop strains, and reduced fission gas release in the updated models. In contrast, none of the BWR rods were predicted to burst under either burst criterion, reaffirming minimal BWR FFRD susceptibility even with updated HBS and material models. Comparisons between the PWR and BWR end-of-cycle predictions are made. Comparison with prior work highlights significant shifts in PWR fuel performance metrics and confirmation of earlier BWR conclusions. Overall, the updated results underscore the importance of having high-resolution detailed modeling capability and continuously integrating evolving material models and physics into high-resolution multiphysics simulations. The unified assessment presented here strengthens confidence in predicting high-burnup LOCA behavior by improving agreement between different cladding burst correlations. These results also provide an improved foundation for future BISON model development, FFRD susceptibility calculations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Ground state energy and magnetization curve of a frustrated magnetic system from real-time evolution on a digital quantum processor

Models of interacting many-body quantum systems that may realize new exotic phases of matter, notably quantum spin liquids, are challenging to study using even state-of-the-art classical methods such as tensor network simulations. Quantum computing provides a promising route for overcoming these difficulties to find ground states, dynamics, and more. In this paper, we argue that recently developed hybrid quantum-classical algorithms based on real-time evolution are promising methods for solving a particularly important model in the search for spin liquids, the antiferromagnetic Heisenberg model on the two-dimensional kagome lattice. We show how to construct efficient quantum circuits to implement time evolution for the model and to evaluate key observables on the quantum computer, and we argue that the method has favorable scaling with increasing system size. We then restrict to a 12-spin star plaquette from the kagome lattice and a related 8-spin system, and we give an empirical demonstration on these small systems that the hybrid algorithms can efficiently find the ground state energy and the magnetization curve. For these demonstrations, we use four levels of approximation: exact state vectors, exact state vectors with statistical noise from sampling, noisy classical emulators, and (for the 8-spin system only) real quantum hardware, specifically the Quantinuum H1-1 processor; for the noisy simulations and hardware demonstration, we also employ error mitigation strategies based on the symmetries of the Hamiltonian. Our results strongly suggest that these hybrid algorithms present a promising direction for studying quantum spin liquids and more generally for resolving important unsolved problems in condensed matter theory and beyond.

97 MATHEMATICS AND COMPUTING↗

THE BOLOCAM GALACTIC PLANE SURVEY. XIV. PHYSICAL PROPERTIES OF MASSIVE STARLESS AND STAR-FORMING CLUMPS

We sort 4683 molecular clouds between 10° < ℓ < 65° from the Bolocam Galactic Plane Survey based on observational diagnostics of star formation activity: compact 70 μm sources, mid-IR color-selected YSOs, H{sub 2}O and CH{sub 3}OH masers, and UCH ii regions. We also present a combined NH{sub 3}-derived gas kinetic temperature and H{sub 2}O maser catalog for 1788 clumps from our own GBT 100 m observations and from the literature. We identify a subsample of 2223 (47.5%) starless clump candidates (SCCs), the largest and most robust sample identified from a blind survey to date. Distributions of flux density, flux concentration, solid angle, kinetic temperature, column density, radius, and mass show strong (>1 dex) progressions when sorted by star formation indicator. The median SCC is marginally subvirial (α ∼ 0.7) with >75% of clumps with known distance being gravitationally bound (α < 2). These samples show a statistically significant increase in the median clump mass of ΔM ∼ 170–370 M {sub ⊙} from the starless candidates to clumps associated with protostars. This trend could be due to (i) mass growth of the clumps at M-dot ∼200--440 M {sub ⊙} Myr{sup −1} for an average freefall 0.8 Myr timescale, (ii) a systematic factor of two increase in dust opacity from starless to protostellar phases, and/or (iii) a variation in the ratio of starless to protostellar clump lifetime that scales as ∼M {sup −0.4}. By comparing to the observed number of CH{sub 3}OH maser containing clumps, we estimate the phase lifetime of massive (M > 10{sup 3} M {sub ⊙}) starless clumps to be 0.37 ± 0.08 Myr (M/10{sup 3} M {sub ⊙}){sup −1}; the majority (M < 450 M {sub ⊙}) have phase lifetimes longer than their average freefall time.

79 ASTRONOMY AND ASTROPHYSICS↗

A Map of the Local Velocity Substructure in the Milky Way Disk

We confirm, quantify, and provide a table of the coherent velocity substructure of the Milky Way disk within 2 kpc of the Sun toward the Galactic anticenter, with a 0.2 kpc resolution. We use the radial velocities of ∼340,000 F-type stars obtained with the Guoshoujing Telescope (also known as the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, LAMOST), and proper motions derived from the PPMXL catalog. The PPMXL proper motions have been corrected to remove systematic errors by subtracting the average proper motions of galaxies and QSOs that have been confirmed in the LAMOST spectroscopic survey, and that are within 2.°5 of the star’s position. We provide the resulting table of systematic offsets derived from the PPMXL proper motion measurements of extragalactic objects identified in the LAMOST spectroscopic survey. Using the corrected phase-space stellar sample, we find statistically significant deviations in the bulk disk velocity of 20 km s{sup −1} or more in the three-dimensional velocities of Galactic disk stars. The bulk velocity varies significantly over length scales of half a kiloparsec or less. The rotation velocity of the disk increases by 20 km s{sup −1} from the Sun’s position to 1.5 kpc outside the solar circle. Disk stars in the second quadrant, within 1 kpc of the Sun, are moving radially toward the Galactic center and vertically toward a point a few tenths of a kiloparsec above the Galactic plane; looking down on the disk, the stars appear to move in a circular streaming motion with a radius of the order of 1 kpc.

79 ASTRONOMY AND ASTROPHYSICS↗