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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Feasible Perturbations of Control Systems with Pure State Constraints and Applications to Second-Order Optimality Conditions

We propose second-order necessary optimality conditions for optimal control problems with very general state and control constraints which hold true under weak regularity assumptions on the data. In particular the pure state constraints are general closed sets, the optimal control is supposed to be merely measurable and the dynamics may be discontinuous in the time variable as well. These results are obtained by an approach based on local perturbations of the reference process by second-order tangent directions. This method allows direct and quite simple proofs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

RADIAL STELLAR PULSATION AND THREE-DIMENSIONAL CONVECTION. II. TWO-DIMENSIONAL CONVECTION IN FULL AMPLITUDE RADIAL PULSATION

We have developed a three-dimensional radiation hydrodynamics code to simulate the interaction of convection and radial pulsation in classical variable stars. One key goal is the ability to carry these simulations to full amplitude in order to compare them with observed light curves. Previous multi-dimensional calculations were prevented from reaching full amplitude because of drift in the radial coordinate system, due to the algorithm defining radial movement of the coordinate system during the pulsation cycle. We have removed this difficulty by defining our radial coordinate flow algorithm to require that the mass in a spherical shell remain constant for every time step throughout the pulsation cycle. We have used our new code to perform two-dimensional (2D) simulations of the interaction of radial pulsation and convection. We have made comparisons between light curves from our 2D convective simulations with observed light curves and find that our 2D simulated light curves are better able to match the observed light curve shape near the red edge of the RR Lyrae instability strip than light curves from previous one-dimensional time-dependent convective models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Stochastic Dynamic Analysis for Power Systems Under Uncertain Variability

This paper proposes a novel method to analyze impacts of uncertain variability on power system dynamics. There is considerable interest in integrating intermittent renewable energy and plug-in electric vehicles into power systems. Therefore, power systems are in an environment with increasing uncertain variability. In this paper, the uncertain variability is described as a continuous-time stochastic process, and thus, the power system under uncertain variability is modeled by stochastic differential equations. To quantify impacts of uncertain variability on power system dynamics, an intra-region probability index is presented. Based on the stochastic averaging method, an analytical method is proposed to calculate the intra-region probability. Compared to Monte Carlo simulation, the proposed method is many orders of magnitude faster without sacrificing the result accuracy. As a result, several insights are given to improve the power system dynamics under uncertain variability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Uncertainty Quantification in CO 2 Sequestration Using Surrogate Models from Polynomial Chaos Expansion

In this paper, surrogate models are iteratively built using polynomial chaos expansion (PCE) and detailed numerical simulations of a carbon sequestration system. Output variables from a numerical simulator are approximated as polynomial functions of uncertain parameters. Once generated, PCE representations can be used in place of the numerical simulator and often decrease simulation times by several orders of magnitude. However, PCE models are expensive to derive unless the number of terms in the expansion is moderate, which requires a relatively small number of uncertain variables and a low degree of expansion. To cope with this limitation, instead of using a classical full expansion at each step of an iterative PCE construction method, we introduce a mixed-integer programming (MIP) formulation to identify the best subset of basis terms in the expansion. This approach makes it possible to keep the number of terms small in the expansion. Monte Carlo (MC) simulation is then performed by substituting the values of the uncertain parameters into the closed-form polynomial functions. Based on the results of MC simulation, the uncertainties of injecting CO{sub 2} underground are quantified for a saline aquifer. Moreover, based on the PCE model, we formulate an optimization problem to determine the optimal CO{sub 2} injection rate so as to maximize the gas saturation (residual trapping) during injection, and thereby minimize the chance of leakage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Fermi variability study of the candidate pulsar binary 2FGL J0523.3–2530

The Fermi source 2FGL J0523.3–2530 has recently been identified as a candidate millisecond pulsar binary with an orbital period of 16.5 hr. We have carried out detailed studies of the source's emission properties by analyzing data taken with the Fermi Large Area Telescope in the 0.2-300 GeV energy range. Long-term, yearly variability from the source has been found, with a factor of four flux variations in 1-300 GeV. From spectral analysis, we find an extra spectral component at 2-3 GeV that causes the source brightening. While no orbital modulations have been found from the Fermi data over the whole period of 2008-2014, orbital modulation in the source's >2 GeV emission is detected during the last 1.5 yr of the Fermi observation. Our results support the millisecond pulsar binary nature of 2FGL J0523.3–2530. Multi-wavelength observations of the source are warranted in order to find any correlated flux variations and thus help determine the origin of the long-term variability, which currently is not understood.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Continental United States may lose 1.8 petagrams of soil organic carbon under climate change by 2100

Abstract Aims High‐resolution information on soils’ vulnerability to climate‐induced soil organic carbon (SOC) loss can enable environmental scientists, land managers, and policy makers to develop targeted mitigation strategies. This study aims to estimate baseline and decadal changes in continental US surface SOC stocks under future emission scenarios. Location Continental United States. Time period 2014–2100. Methods We used recent SOC field observations ( n = 6,213 sites), environmental factors ( n = 32), and an ensemble machine learning (ML) approach to estimate baseline SOC stocks in surface soils across the continental United States at 100‐m spatial resolution, and decadal changes under the projected climate scenarios of Coupled Model Intercomparison Project Phase Six (CMIP6) earth system models (ESMs). Results Baseline SOC projections from ML approaches captured more than 50% of variability in SOC observations, whereas ESMs represented only 6–16% of observed SOC variability. ML estimates showed a mean total loss of 1.8 Pg C from US surface soils under the high‐emission scenario by 2100, whereas ESMs showed no significant change in SOC stocks with wide variation among ESMs. Both ML and ESM predictions agree on the direction of SOC change (net emissions or sequestration) across 46–51% of continental US land area. These differences are attributable to the high‐resolution site‐specific data used in the ML models compared to the relatively coarse grid represented in CMIP6 ESMs. Main conclusions Our high‐resolution estimates of baseline SOC stocks, identification of key environmental controllers, and projection of SOC changes from US land cover types under future climate scenarios suggest the need for high‐resolution simulations of SOC in ESMs to represent the heterogeneity of SOC. We found that the SOC change is sensitive to key soil related factors (e.g. soil drainage and soil order) that have not been historically considered as input parameters in ESMs, because currently more than 95% variability in the SOC of CMIP6 ESMs is controlled by net primary productivity, temperature, and precipitation. Using additional environmental factors to estimate the baseline SOC stocks and predict the future trajectory of SOC change can provide more accurate results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Neural chaos: A spectral stochastic neural operator

Building surrogate models for operators with uncertainty quantification capabilities is essential for many engineering applications where randomness–such as variability in material properties, boundary conditions, and initial conditions–is unavoidable. Polynomial Chaos Expansion (PCE) is widely recognized as a go-to method for constructing stochastic surrogates in both intrusive and non-intrusive ways, and it has recently been used in the context of operator learning. However, its application becomes challenging for complex or high-dimensional processes, as achieving accuracy requires higher-order polynomials, which can increase computational demand and/or the risk of overfitting. Furthermore, PCE requires specialized treatments to manage random variables that are not independent, and these treatments may be problem-dependent or may fail with increasing complexity. Here, in this work, we adopt the same formalism as the spectral expansion used in PCE; however, we replace the classical polynomial basis functions with neural network (NN) basis functions to leverage their expressivity. To achieve this, we propose an algorithm that identifies NN-parameterized basis functions in a purely data-driven manner, without any prior assumptions about the joint distribution of the random variables involved, whether independent or dependent, or about their marginal distributions. The proposed algorithm identifies each NN-parameterized basis function sequentially, ensuring they are orthogonal with respect to the data distribution. The basis functions are constructed directly on the joint stochastic variables without requiring a tensor product structure or assuming independence of the random variables. This approach may offer greater flexibility for complex stochastic models, while simplifying implementation compared to the tensor product structures typically used in PCE to handle random vectors. This is particularly advantageous given the current state of open-source packages, where building and training neural networks can be done with just a few lines of code and extensive community support. We demonstrate the effectiveness of the proposed scheme through several numerical examples of varying complexity and provide comparisons with classical PCE.

Polynomial chaos expansion↗
DOE OSTI2025

Precision DIS thrust predictions for HERA and EIC

We present predictions for the DIS 1-jettiness event shape $τ^b_1$, or DIS thrust, using the framework of Soft Collinear Effective Theory (SCET) for factorization, resummation of large logarithms, and rigorous treatment of nonperturbative power corrections, matched to fixed-order QCD away from the resummation region. Our predictions reach next-to-next-to-next-to-leading-logarithmic (N 3 LL) accuracy in resummed perturbation theory, matched to $\mathcal{O}(α^2_s)$ fixed-order QCD calculations obtained using the program NLOJet++. We include a rigorous treatment of hadronization corrections, which are universal across different event shapes and kinematic variables x and Q at leading power, and supplement them with a systematic scheme to remove $\mathcal{O}$(Λ QCD ) renormalon ambiguities in their definition. The framework of SCET allows us to connect smoothly the nonperturbative, resummation, and fixed-order regions, whose relative importance varies with x and Q, and to rigorously estimate theoretical uncertainties, across a broad range of x and Q covering existing experimental results from HERA as well as expected new measurements from the upcoming Electron- Ion-Collider (EIC). Our predictions will serve as an important benchmark for the EIC program, enabling the precise determination of the QCD strong coupling α s and the universal nonperturbative first moment parameter Ω 1 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Annotations on the virtual element method for second-order elliptic problems

This document contains working annotations on the Virtual Element Method (VEM) for the approximate solution of diffusion problems with variable coefficients. To read this document you are assumed to have familiarity with concepts from the numerical discretization of Partial Differential Equations (PDEs) and, in particular, the Finite Element Method (FEM). This document is not an introduction to the FEM, for which many textbooks (also free on the internet) are available. Eventually, this document is intended to evolve into a tutorial introduction to the VEM (but this is really a long-term goal).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Antiferroelectric Phase Transition in a Proton-Transfer Salt of Squaric Acid and 2,3-Dimethylpyrazine

A proton-transfer reaction between squaric acid (H 2 sq) and 2,3-dimethylpyrazine (2,3-Me 2 pyz) results in crystallization of a new organic antiferroelectric (AFE), (2,3-Me 2 pyzH + )(Hsq – )·H 2 O ( 1 ), which possesses a layered structure. The structure of each layer can be described as partitioned into strips lined with methyl groups of the Me 2 pyzH + cations and strips featuring extensive hydrogen bonding between the Hsq – anions and water molecules. Variable-temperature dielectric measurements and crystal structures determined through a combination of single-crystal X-ray and neutron diffraction reveal an AFE ordering at 104 K. The phase transition is driven by ordering of protons within the hydrogen-bonded strips. Considering the extent of proton transfer, the paraelectric (PE) state can be formulated as (2,3-Me 2 pyzH + ) 2 (Hsq 2 3– )(H 5 O 2 + ), whereas the AFE phase can be described as (2,3-Me 2 pyzH + )(Hsq – )(H 2 O). The structural transition caused by the localization of protons results in the change in color from yellow in the PE state to colorless in the AFE state. The occurrence and mechanism of the AFE phase transition have been also confirmed by heat capacity measurements and variable-temperature infrared and Raman spectroscopy. This work demonstrates a potentially promising approach to the design of new electrically ordered materials by engineering molecule-based crystal structures in which hydrogen-bonding interactions are intentionally partitioned into quasi-one-dimensional regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Autonomous quantum error correction and fault-tolerant quantum computation with squeezed cat qubits

We propose an autonomous quantum error correction scheme using squeezed cat (SC) code against excitation loss in continuous-variable systems. Through reservoir engineering, we show that a structured dissipation can stabilize a two-component SC while autonomously correcting the errors. The implementation of such dissipation only requires low-order nonlinear couplings among three bosonic modes or between a bosonic mode and a qutrit. While our proposed scheme is device independent, it is readily implementable with current experimental platforms such as superconducting circuits and trapped-ion systems. Compared to the stabilized cat, the stabilized SC has a much lower dominant error rate and a significantly enhanced noise bias. Furthermore, the bias-preserving operations for the SC have much lower error rates. In combination, the stabilized SC leads to substantially better logical performance when concatenating with an outer discrete-variable code. The surface-SC scheme achieves more than one order of magnitude increase in the threshold ratio between the loss rate κ 1 and the engineered dissipation rate κ 2 . Under a practical noise ratio κ 1 /κ 2 = 10 -3 , the repetition-SC scheme can reach a 10 -15 logical error rate even with a small mean excitation number of 4, which already suffices for practically useful quantum algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

SU-E-J-263: Repeatability of SUV and Texture Parameters in Serial PET Studies

Purpose: Standardized uptake values (SUV) are standard quantitative PET measures of FDG tumor uptake used,and are used as a tool to monitor response to therapy. Textural analysis is emerging as a new tool for assessing intratumoral heterogeneity which may allow better tissue characterization and improved prediction of response and survival rate.Understanding what variations may be expected in these parameters is key in order to make decisions based on how the change throughout the course of treatment. The aim of this study was to assess repeatability in SUV measures and texture parameters,and establish criteria that differentiate changes associated with treatment rather than statistical variability. Methods: Eighty patients,167 random lesions total,were scanned in a GE Discovery STE PET/CT Scanner. One field-of-view was chosen centered on the largest lesion observed in a clinical whole-body FDG PET.Immediately following,a gated 9 min scan was acquired in list mode,without changing the patient’s position between any scans. Data was replayed into 3 time bins,3 min each,in order to insure equivalent noise characteristics in each replicate.Data was reconstructed into 128×128×47 square matrices.One VOI was drawn over each lesion for each patient and used to segment all 3 replicates. The mean.max and peak SUV were calculated for each VOI and replicate. First-order textural features were also calculated (skewness and kurtosis). Repeatability was calculated as the average standard deviation over the mean for the 3 repeated measurements for each lesion. Results: The average percent error in the SUV max,peak and mean were 3.4%(0– 12.9%),1.9% (0–7.5%),2.8% (0–12.2%),respectively.For skewness and kurtosis they were 10.9% and 17.8%. Conclusion: We have shown that there is a large variation in %error in SUV measures across patients. SUVpeak is the least variable and kurtosis and skewness parameters are less reliable thatn SUVs.Higher order textures are be.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Search for transient optical counterparts to high-energy IceCube neutrinos with Pan-STARRS1

In order to identify the sources of the observed diffuse high-energy neutrino flux, it is crucial to discover their electromagnetic counterparts. To increase the sensitivity of detecting counterparts of transient or variable sources by telescopes with a limited field of view, IceCube began releasing alerts for single high-energy ( E ν > 60 TeV) neutrino detections with sky localisation regions of order 1° radius in 2016. We used Pan-STARRS1 to follow-up five of these alerts during 2016–2017 to search for any optical transients that may be related to the neutrinos. Typically 10–20 faint ( m i P1 ≲ 22.5 mag) extragalactic transients are found within the Pan-STARRS1 footprints and are generally consistent with being unrelated field supernovae (SNe) and AGN. We looked for unusual properties of the detected transients, such as temporal coincidence of explosion epoch with the IceCube timestamp, or other peculiar light curve and physical properties. We found only one transient that had properties worthy of a specific follow-up. In the Pan-STARRS1 imaging for IceCube-160427A (probability to be of astrophysical origin of ~50%), we found a SN PS16cgx, located at 10.0' from the nominal IceCube direction. Spectroscopic observations of PS16cgx showed that it was an H-poor SN at redshift z = 0.2895 ± 0.0001. The spectra and light curve resemble some high-energy Type Ic SNe, raising the possibility of a jet driven SN with an explosion epoch temporally coincident with the neutrino detection. However, distinguishing Type Ia and Type Ic SNe at this redshift is notoriously difficult. Based on all available data we conclude that the transient is more likely to be a Type Ia with relatively weak Si II absorption and a fairly normal rest-frame r -band light curve. If, as predicted, there is no high-energy neutrino emission from Type Ia SNe, then PS16cgx must be a random coincidence, and unrelated to the IceCube-160427A. We find no other plausible optical transient for any of the five IceCube events observed down to a 5 σ limiting magnitude of m i P1 ≈ 22 mag, between 1 day and 25 days after detection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Field-induced phase coexistence in an artificial spin ice

Artificial spin-ice systems are magnetic metamaterials consisting of nanomagnet arrays that can be designed to study exotic magnetic states not found in natural materials. Typically, these arrays are modelled as interacting binary macrospins that can only be in an up or down state and are described by the Ising model. These materials have demonstrated ordering transitions, but only via a spontaneous symmetry-breaking mechanism. In this study, we have designed and studied a quadrupole artificial spin-ice system consisting of interacting plaquettes of coupled single-domain nanomagnets that can be interpreted as a composite, ternary variable. After annealing this system in an external magnetic field, we observe both a ferroquadrupolar and an antiferroquadrupolar phase, with an apparent first-order phase boundary and a coexistence regime. The phase diagram of this material is reminiscent of a model used to describe phase coexistence in the superfluid transition of 4 He with 3 He impurities. Finally, these results illustrate how composite magnetic objects realize exotic statistical physics models beyond the Ising model.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Sources of biomass feedstock variability and the potential impact on biofuels production

In this study, terrestrial lignocellulosic biomass has the potential to be a carbon neutral and domestic source of fuels and chemicals. However, the innate variability of biomass resources, such as herbaceous and woody materials, and the inconsistency within a single resource due to disparate growth and harvesting conditions, presents challenges for downstream processes which often require materials that are physically and chemically consistent. Intrinsic biomass characteristics, including moisture content, carbohydrate and ash compositions, bulk density, and particle size/shape distributions are highly variable and can impact the economics of transforming biomass into value-added products. For instance, ash content increases by an order of magnitude between woody and herbaceous feedstocks (from ~0.5 to 5 %, respectively) while lignin content drops by a factor of two (from ~30 to 15 %, respectively). This increase in ash and reduction in lignin leads to biofuel conversion consequences, such as reduced pyrolysis oil yields for herbaceous products as compared to woody material. In this review, the sources of variability for key biomass characteristics are presented for multiple types of biomass. Additionally, this review investigates the major impacts of the variability in biomass composition on four conversion processes: fermentation, hydrothermal liquefaction, pyrolysis, and direct combustion. Finally, future research processes aimed at reducing the detrimental impacts of biomass variability on conversion to fuels and chemicals are proposed.

09 BIOMASS FUELS↗
DOE OSTI2023

Assessing Multi-Dimensional Impacts of Achieving Sustainability Goals by Projecting the Sustainable Agriculture Matrix Into the Future

The concept of sustainability inherently spans multiple spatial scales, sectors, variables, and time horizons. This study links a recently developed method of assessing present-day agricultural sustainability across environmental, economic, and social dimensions with a process-based integrated assessment model, in order to allow forward-looking analysis of sustainability by region and scenario. The sustainable agriculture matrix estimates present-day agricultural sustainability at the national level using 18 indicator variables, of which this study estimates nine to the year 2100, using an enhanced version of the Global Change Analysis Model. Scenarios include a reference scenario, and scenarios that apply the following measures, both individually and in combination, that are thought to improve sustainability: yield intensification, transition toward more plant-based (“flexitarian”) diets, and economy-wide greenhouse gas emissions mitigation. The scenarios illustrate considerable complexity and tradeoffs inherent to efforts to improve agricultural sustainability in all regions globally. For example, yield intensification typically increases nitrogen pollution, flexitarian diets can reduce agricultural output, and greenhouse gas mitigation efforts may either increase deforestation or crowd out crop and livestock production due to consequent bioenergy demands. However, there is considerable inter-regional heterogeneity in the responses, and the importance of such secondary responses also differs by region. The analysis and post-processing methods developed in this study allow quantification and visualization of the absolute and relative magnitude of the tradeoffs between agricultural sustainability indicator variables across regions, time periods, and scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Higher-order temporal integration for the incompressible Navier–Stokes equations in bounded domains

Here, this paper compares and contrasts higher-order, semi-implicit temporal integration strategies for the incompressible Navier–Stokes methods based on spectral deferred corrections applied to certain gauge or auxiliary variable formulations of the equations. Particular focus is placed on the imposition of boundary conditions in the semi-implicit formulation, the accurate treatment of the pressure term, and the smoothness of the numerical solution for different formulations. The main result presented here is the formulation and numerical validation of a single-step, semi-implicit method called spectral deferred pressure corrections, which can in theory obtain arbitrary formal order of accuracy in time. Lastly, numerical results demonstrate up to eighth-order accuracy, scenarios where optimal temporal accuracy is attained, and scenarios where order reduction is observed due to time-dependent boundary conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Statistical variability of mechanical fields in thermo-poro-elasticity: Multiscale analytical estimations applied to cement-based materials at early-age

Highlights: • Standard deviation of stresses in C-S-H has the order of magnitude of the stresses applied at concrete scale. • Fluctuations increase with the stiffness and contrast of phases. • Fluctuations are dependent of mechanical load. • Transformation fields also cause mechanical fluctuations. - Abstract: Analytical homogenization provides information about the average mechanical fields but can also be used to obtain information about the statistical variability or fluctuations of these fields. Here, we present analytical estimations of the fluctuations of elastic stresses within cement-based materials (CBM). Mori-Tanaka, self-consistent and generalized self-consistent schemes are combined to represent the multiscale character of CBM. The second moment of mechanical fields is derived from the internal energy. The presence of transformation fields and resulting fluctuations are considered. We account for the evolution of the volume fractions of phases due to cement hydration. Scenarios considering or not the ITZ are studied. Our estimations are dependent on load and representation CBM microstructure. The obtained standard deviation of stresses in C-S-H are on the order of the stresses applied at concrete scale. We provide estimations of the compressive strength of a cement paste at early-age using our results of fluctuation of stresses.

36 MATERIALS SCIENCE↗