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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Statistics of baryon correlation functions in lattice QCD

A systematic analysis of the structure of single-baryon correlation functions calculated with lattice QCD is performed, with a particular focus on characterizing the structure of the noise associated with quantum fluctuations. The signal-to-noise problem in these correlation functions is shown, as long suspected, to result from a sign problem. The log-magnitude and complex phase are found to be approximately described by normal and wrapped normal distributions respectively. Properties of circular statistics are used to understand the emergence of a large time noise region where standard energy measurements are unreliable. Power-law tails in the distribution of baryon correlation functions, associated with stable distributions and “Lévy flights,” are found to play a central role in their time evolution. A new method of analyzing correlation functions is considered for which the signal-to-noise ratio of energy measurements is constant, rather than exponentially degrading, with increasing source-sink separation time. This new method includes an additional systematic uncertainty that can be removed by performing an extrapolation, and the signal-to-noise problem reemerges in the statistics of this extrapolation. It is demonstrated that this new method allows accurate results for the nucleon mass to be extracted from the large-time noise region inaccessible to standard methods. The observations presented here are expected to apply to quantum Monte Carlo calculations more generally. Similar methods to those introduced here may lead to practical improvements in analysis of noisier systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Nucleation of spatiotemporal structures from defect turbulence in the two-dimensional complex Ginzburg-Landau equation

We numerically investigate nucleation processes in the transient dynamics of the two-dimensional complex Ginzburg--Landau equation towards its "frozen'' state with quasi-stationary spiral structures. We study the transition kinetics from either the defect turbulence regime or random initial configurations to the frozen state with a well-defined low density of quasi-stationary topological defects. Nucleation events of spiral structures are monitored using the characteristic length between the emerging shock fronts. We study two distinct situations, namely either when the system is quenched far away from the transition limit or near it. In the former deeply quenched case, the average nucleation time for different system sizes is measured over many independent realizations. We employ an extrapolation method as well as a phenomenological formula to account for and eliminate finite-size effects. The non-zero (dimensionless) barrier for the nucleation of single spiral droplets in the extrapolated infinite system size limit suggests that the transition to the frozen state is discontinuous. Here, we also investigate the nucleation of spirals for systems that are quenched close to but beyond the crossover limit, and of target waves which emerge if a specific spatial inhomogeneity is introduced. In either of these cases, we observe long, "fat'' tails in the distribution of nucleation times, which also supports a discontinuous transition scenario.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Core conditions for alpha heating attained in direct-drive inertial confinement fusion

It is shown that direct-drive implosions on the OMEGA laser have achieved core conditions that would lead to significant alpha heating at incident energies available on the National Ignition Facility (NIF) scale. The extrapolation of the experimental results from OMEGA to NIF energy assumes only that the implosion hydrodynamic efficiency is unchanged at higher energies. This approach is independent of the uncertainties in the physical mechanism that degrade implosions on OMEGA, and relies solely on a volumetric scaling of the experimentally observed core conditions. It is estimated that the current best-performing OMEGA implosion [Regan et al., Phys. Rev. Lett. 117, 025001 (2016)] extrapolated to a 1.9 MJ laser driver with the same illumination configuration and laser-target coupling would produce 125 kJ of fusion energy with similar levels of alpha heating observed in current highest performing indirect-drive NIF implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Precise algorithm to generate random sequential adsorption of hard polygons at saturation

Random sequential adsorption (RSA) is a time-dependent packing process, in which particles of certain shapes are randomly and sequentially placed into an empty space without overlap. In the infinite-time limit, the density approaches a "saturation'' limit. Although this limit has attracted particular research interest, the majority of past studies could only probe this limit by extrapolation. We have previously found an algorithm to reach this limit using finite computational time for spherical particles, and could thus determine the saturation density of spheres with high accuracy. Here in this paper, we generalize this algorithm to generate saturated RSA packings of two-dimensional polygons. We also calculate the saturation density for regular polygons of three to ten sides, and obtain results that are consistent with previous, extrapolation-based studies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

First Direct Measurement of C 12 ( C 12 , n ) Mg 23 at Stellar Energies

Neutrons produced by the carbon fusion reaction 12 C( 12 C,n) 23 Mg play an important role in stellar nucleosynthesis. However, past studies have shown large discrepancies between experimental data and theory, leading to an uncertain cross section extrapolation at astrophysical energies. Here in this paper, we present the first direct measurement that extends deep into the astrophysical energy range along with a new and improved extrapolation technique based on experimental data from the mirror reaction 12 C( 12 C,p) 23 Na . The new reaction rate has been determined with a well-defined uncertainty that exceeds the precision required by astrophysics models. Using our constrained rate, we find that 12 C ( 12 C,n) 23 Mg is crucial to the production of Na and Al in pop-III pair instability supernovae. It also plays a nonnegligible role in the production of weak s -process elements, as well as in the production of the important galactic γ-ray emitter 60 Fe.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Is a Trineutron Resonance Lower in Energy than a Tetraneutron Resonance?

Here, we present quantum Monte Carlo calculations of few-neutron systems confined in external potentials based on local chiral interactions at next-to-next-to-leading order in chiral effective field theory. The energy and radial densities for these systems are calculated in different external Woods-Saxon potentials. We assume that their extrapolation to zero external-potential depth provides a quantitative estimate of three- and four-neutron resonances. The validity of this assumption is demonstrated by benchmarking with an exact diagonalization in the two-body case. We find that the extrapolated trineutron resonance, as well as the energy for shallow well depths, is lower than the tetraneutron resonance energy. This suggests that a three-neutron resonance exists below a four-neutron resonance in nature and is potentially measurable. To confirm that the relative ordering of three- and four-neutron resonances is not an artifact of the external confinement, we test that the odd-even staggering in the helium isotopic chain is reproduced within this approach. Finally, we discuss similarities between our results and ultracold Fermi gases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

High-Precision Mass Measurement of Cu 56 and the Redirection of the r p -Process Flow

We report the mass measurement of 56 Cu, using the LEBIT 9.4 T Penning trap mass spectrometer at the National Superconducting Cyclotron Laboratory at Michigan State University. The mass of 56 Cu is critical for constraining the reaction rates of the 55 Ni(p,y), 56 Cu(p,y), 57 Zn(β + ) 57 Cu bypass around the 56 Ni waiting point. Previous recommended mass excess values have disagreed by several hundred keV. Our new value, ME = -38626.7(7.1) keV, is a factor of 30 more precise than the extrapolated value suggested in the 2012 atomic mass evaluation [Chin. Phys. C 36, 1603 (2012)], and more than a factor of 12 more precise than values calculated using local mass extrapolations, while agreeing with the newest 2016 atomic mass evaluation value [Chin. Phys. C 41, 030003 (2017)]. The new experimental average, using our new mass and the value from AME2016, is used to calculate the astrophysical 55 Ni(p,y) and 56 Cu(p,y) forward and reverse rates and perform reaction network calculations of the rp process. These show that the rp-process flow redirects around the 56 Ni waiting point through the 55 Ni(p,y) route, allowing it to proceed to higher masses more quickly and resulting in a reduction in ashes around this waiting point and an enhancement to higher mass ashes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Neutron Drip Line in the Ca Region from Bayesian Model Averaging

The region of heavy calcium isotopes forms the frontier of experimental and theoretical nuclear structure research where the basic concepts of nuclear physics are put to stringent test. The recent discovery of the extremely neutron-rich nuclei around 60 Ca and the experimental determination of masses for 55-57 Ca provide unique information about the binding energy surface in this region. To assess the impact of these experimental discoveries on the nuclear landscape’s extent, we use global mass models and statistical machine learning to make predictions, with quantified levels of certainty, for bound nuclides between Si and Ti. Using a Bayesian model averaging analysis based on Gaussian-process-based extrapolations we introduce the posterior probability for each nucleus to be bound to neutron emission. We discover that extrapolations for drip-line locations, at which the nuclear binding ends, are consistent across the global mass models used, in spite of significant variations between their raw predictions. In particular, considering the current experimental information and current global mass models, we suggest that 68 Ca has an average posterior probability p ex ≈ 76 % to be bound to two-neutron emission while the nucleus 61 Ca is likely to decay by emitting a neutron (p ex ≈ 46 % ).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Rapid Initial-State Preparation for the Quantum Simulation of Strongly Correlated Molecules

Studies on quantum algorithms for ground-state energy estimation often assume perfect ground-state preparation; however, in reality the initial state will have imperfect overlap with the true ground state. Here, we address that problem in two ways: by faster preparation of matrix-product-state (MPS) approximations and by more efficient filtering of the prepared state to find the ground-state energy. We show how to achieve unitary synthesis with a Toffoli complexity about 7 × lower than that in prior work and use that to derive a more efficient MPS-preparation method. For filtering, we present two different approaches: sampling and binary search. For both, we use the theory of window functions to avoid large phase errors and minimize the complexity. We find that the binary-search approach provides better scaling with the overlap at the cost of a larger constant factor, such that it will be preferred for overlaps less than about 0.003 . Finally, we estimate the total resources to perform ground-state energy estimation of Fe - S cluster systems, including the Fe Mo cofactor by estimating the overlap of different MPS initial states with potential ground states of the Fe Mo cofactor using an extrapolation procedure. With a modest MPS bond dimension of 4000 , our procedure produces an estimate of approximately 0.9 overlap squared with a candidate ground state of the Fe Mo cofactor, producing a total resource estimate of 7.3 × 10 10 Toffoli gates; neglecting the search over candidates and assuming the accuracy of the extrapolation, this validates prior estimates that have used perfect ground-state overlap. This presents an example of a practical path to prepare states of high overlap in a challenging-to-compute chemical system. Published by the American Physical Society 2025

Berry, Dominic W. (ORCID:0000000334461449)↗
DOE OSTI2025

Window Observables for Benchmarking Parton Distribution Functions

Global analysis of collider and fixed-target experimental data and calculations from lattice quantum chromodynamics (QCD) are used to gain complementary information on the structure of hadrons. We propose novel “window observables” that allow for higher precision cross-validation between the different approaches, a critical step for studies that wish to combine the datasets. Global analyses are limited by the kinematic regions accessible to experiment, particularly in a range of Bjorken-𝑥, and lattice QCD calculations also have limitations requiring extrapolations to obtain the parton distributions. We provide two different window observables that can be defined within a region of 𝑥 where extrapolations and interpolations in global analyses remain reliable and where lattice QCD results retain sensitivity and precision.

lattice QCD↗
DOE OSTI2026

Moments of parton distribution functions of the pion from lattice QCD using gradient flow

We present a nonperturbative determination of the pion valence parton distribution function (PDF) moment ratios ⟨𝑥 𝑛−1 ⟩/⟨𝑥⟩ up to 𝑛 = 6, using the gradient flow in lattice quantum chromodynamics (QCD). As a testing ground, we employ SU(3) isosymmetric gauge configurations generated by the OpenLat initiative with a pseudoscalar mass of 𝑚 𝜋 ≃ 411 MeV. Our analysis uses four lattice spacings and a nonperturbatively improved action, enabling full control over the continuum extrapolation, and the limit of vanishing flow time, 𝑡 →0. The flowed ratios exhibit O(𝑎 2 ) scaling across the ensembles, and the continuum-extrapolated results, matched to the $\overline{MS}$ scheme at 𝜇 = 2 GeV using next-to-next-to-leading order matching coefficients, show only mild residual flow-time dependence. The resulting ratios, computed with a relatively small number of configurations, are consistent with phenomenological expectations for the pion’s valence distribution, with statistical uncertainties that are competitive with modern global fits. These findings demonstrate that the gradient flow provides an efficient and systematically improvable method to access partonic quantities from first principles. Future extensions of this work will target lighter pion masses toward the physical point, and applications to nucleon structure such as the proton PDFs and the gluon and sea-quark distributions.

lattice QCD↗
DOE OSTI2023

Uncertainty Quantification of Capacitor Switching Transient Location using Machine Learning

Identification of capacitor switching transient location provides valuable insight into the state of the associated equipment. Machine learning (ML) models, and convolutional neural networks (CNNs) in particular, have demonstrated remarkable performance in signal location. However, ML models are data driven whose predictions are affected by noise in data and may also suffer from large extrapolation errors when applied to new conditions. Uncertainty quantification (UQ) is necessary to ensure model trustworthiness and avoid overconfident predictions in extrapolation. Here, in this work, we propose a novel UQ method, called PI3NN, to quantify prediction uncertainty of ML models and integrate the method with CNNs for transient source location. PI3NN calculates Prediction Intervals by training 3 Neural Networks and uses root-finding methods to determine the interval precisely. Additionally, PI3NN can identify out-of-distribution (OOD) data in a nonstationary condition to avoid overconfident prediction. Results indicate that with PI3NN, transient signals are not only correctly identified, but when said signals are subject to corruptions characteristic of an actual power monitoring system (e.g. non-ideal sensors), the model recognizes when it is uncertain about its predictions, effectively letting the user know when to accept or discard the results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Advancing global change biology through experimental manipulations: Where have we been and where might we go?

Abstract This commentary summarizes the publication history of Global Change Biology for works on experimental manipulations over the past 25 years and highlights a number of key publications. The retrospective summary is then followed by some thoughts on the future of experimental work as it relates to mechanistic understanding and methodological needs. Experiments for elevated CO 2 atmospheres and anticipated warming scenarios which take us beyond historical analogs are suggested as future priorities. Disturbance is also highlighted as a key agent of global change. Because experiments are demanding of both personnel effort and limited fiscal resources, the allocation of experimental investments across Earth's biomes should be done in ecosystems of key importance. Uncertainty analysis and broad community consultation should be used to identify research questions and target biomes that will yield substantial gains in predictive confidence and societal relevance. A full range of methodological approaches covering small to large spatial scales will continue to be justified as a source of mechanistic understanding. Nevertheless, experiments operating at larger spatial scales encompassing organismal, edaphic, and environmental diversity of target ecosystems are favored, as they allow for the assessment of long‐term biogeochemical feedbacks enabling a full range of questions to be addressed. Such studies must also include adequate investment in measurements of key interacting variables (e.g., water and nutrient availability and budgets) to enable mechanistic understanding of responses and to interpret context dependency. Integration of ecosystem‐scale manipulations with focused process‐based manipulations, networks, and large‐scale observations will aid more complete understanding of ecosystem responses, context dependence, and the extrapolation of results. From the outset, these studies must be informed by and integrated with ecosystem models that provide quantitative predictions from their embedded mechanistic hypotheses. A true two‐way interaction between experiments and models will simultaneously increase the rate and robustness of Global Change research.

Hanson, Paul J.↗
DOE OSTI2019

Thermodynamic assessment of the hollandite high‐level radioactive waste form

Abstract Hollandite has been studied as a candidate ceramic waste form for the disposal of high‐level radioactive waste due to its inherent leach resistance and ability to immobilize alkaline‐earth metals such as Cs and Ba at defined lattice sites in the crystallographic structure. The chemical and structural complexity of hollandite‐type phases developed for high‐level waste immobilization limits the systematic experimental research that is required to understand phase development due to the large number of potential additives and compositional ranges that must be evaluated. Modeling the equilibrium behavior of the complex hollandite‐forming oxide waste system would aid in the design and processing of hollandite waste forms by predicting their thermodynamic stability. Thus, a BaO–Cs 2 O–TiO 2 –Cr 2 O 3 –Al 2 O 3 –Fe 2 O 3 –FeO–Ga 2 O 3 thermodynamic database was developed in this work according to the CALPHAD methodology. The compound energy formalism was used to model solid solution phases such as hollandite while the two‐sublattice partially ionic liquid model characterized the oxide melt. Results of model optimizations are presented and discussed including a 1473 K isothermal BaO–Cs 2 O–TiO 2 pseudo‐ternary diagram that extrapolates phase equilibrium behavior to regions not experimentally explored.

Utlak, Stephen A.↗
DOE OSTI2022

Mechanistic modeling of lifetime distribution of SiC/SiC composite claddings

Silicon carbide (SiC) fiber-reinforced SiC matrix (SiC/SiC) composites have emerged as a new material candidate for fuel claddings in light water reactors. Recent studies showed that the load capacity of SiC/SiC materials exhibits a considerable statistical variation. Therefore, reliability analysis plays a critical role in design of SiC/SiC composite claddings. Here, this paper presents a probabilistic model for the lifetime distribution of SiC/SiC composites. The model is anchored by a multiaxial stress-based failure criterion and subcritical damage accumulation mechanism. Based on the kinetics of subcritical damage growth, the lifetime distribution of a laboratory test specimen for any given loading history can be calculated. A finite weakest-link model is used to extrapolate the lifetime distribution of test specimens to full-length claddings. It is shown that the damage accumulation mechanism has a strong influence on the lifetime distribution of the cladding. This finding highlights the importance of understanding the static fatigue behavior of SiC/SiC composites. The present analysis also demonstrates an intricate length effect on the failure probability of the cladding, which is expected to play a crucial role in design extrapolation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unveiling the transferability of PLSR models for leaf trait estimation: lessons from a comprehensive analysis with a novel global dataset

Leaf traits are essential for understanding many physiological and ecological processes. Partial least squares regression (PLSR) models with leaf spectroscopy are widely applied for trait estimation, but their transferability across space, time, and plant functional types (PFTs) remains unclear. We compiled a novel dataset of paired leaf traits and spectra, with 47 393 records for >700 species and eight PFTs at 101 globally distributed locations across multiple seasons. Using this dataset, we conducted an unprecedented comprehensive analysis to assess the transferability of PLSR models in estimating leaf traits. While PLSR models demonstrate commendable performance in predicting chlorophyll content, carotenoid, leaf water, and leaf mass per area prediction within their training data space, their efficacy diminishes when extrapolating to new contexts. Specifically, extrapolating to locations, seasons, and PFTs beyond the training data leads to reduced R 2 (0.12–0.49, 0.15–0.42, and 0.25–0.56) and increased NRMSE (3.58–18.24%, 6.27–11.55%, and 7.0–33.12%) compared with nonspatial random cross-validation. The results underscore the importance of incorporating greater spectral diversity in model training to boost its transferability. These findings highlight potential errors in estimating leaf traits across large spatial domains, diverse PFTs, and time due to biased validation schemes, and provide guidance for future field sampling strategies and remote sensing applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Model Form Error Correction for a Black-Box Thermal Battery Heat Transfer Simulation

Thermal batteries are crucial for supplying power to high-consequence engineering applications such as rockets. Computational simulations have been developed to predict thermal battery behavior, but these simulations often suffer from modeling errors, including model form uncertainty. Addressing this uncertainty can be achieved by quantifying either the model discrepancy in the output or the model form error (MFE) in the governing equation. MFE is particularly valuable as it can be better extrapolated beyond observed outputs, which is essential for predictions involving changes in external system loading, system configuration and geometry, or output quantities. This paper employs a state estimation approach to estimate MFE using experimental data and then utilizes machine learning (ML) to model its relationship with state variables. A nonintrusive technique is used to estimate MFE in a black-box thermal battery heat transfer simulation. The trained machine learning model for MFE is then applied to correct simulation predictions under extrapolated initial conditions and battery configurations. In conclusion, the methodology's performance is evaluated using additional experimental data, demonstrating its effectiveness in improving prediction accuracy.

Batteries↗
DOE OSTI2019

Assessment of passively actuated in-situ cyclic surveillance test specimens for advanced non-light water reactors

The use of surveillance specimens was identified in a roadmap (Sims, 2010, ASME HTGR Code Development Roadmap, STP-NU-045, American Society of Mechanical Engineers, New York, NY) developed for the U.S. Nuclear Regulatory Commission for non-light water reactors that are intended to have very long design lives on the order of 500,000 hours. Creep rupture, long term strain accumulation, creep-fatigue damage, and their interaction with environmental effects require significant extrapolation from shorter term tests. Surveillance specimens provide a means for confirmation of these extrapolations in-situ. The effects of cyclic service on creep-fatigue damage would be particularly challenging based on conventional mechanical testing. Proposed herein is a passive cyclic testing methodology that lends itself well to in-situ surveillance applications. The concept is based on utilizing the difference in the thermal expansion coefficient of candidate materials to generate cyclic loading based on operational thermal transients. Prototypical specimen designs are proposed and their in-situ response to representative plant operation are evaluated.

Messner, M. C.↗