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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Upper bounds on the error probabilities and asymptotic error exponents in quantum multiple state discrimination

We consider the multiple hypothesis testing problem for symmetric quantum state discrimination between r given states σ₁, …, σ{sub r}. By splitting up the overall test into multiple binary tests in various ways we obtain a number of upper bounds on the optimal error probability in terms of the binary error probabilities. These upper bounds allow us to deduce various bounds on the asymptotic error rate, for which it has been hypothesized that it is given by the multi-hypothesis quantum Chernoff bound (or Chernoff divergence) C(σ₁, …, σ{sub r}), as recently introduced by Nussbaum and Szkoła in analogy with Salikhov's classical multi-hypothesis Chernoff bound. This quantity is defined as the minimum of the pairwise binary Chernoff divergences min{sub j<k}C(σ{sub j},σ). It was known already that the optimal asymptotic rate must lie between C/3 and C, and that for certain classes of sets of states the bound is actually achieved. It was known to be achieved, in particular, when the state pair that is closest together in Chernoff divergence is more than 6 times closer than the next closest pair. Our results improve on this in two ways. First, we show that the optimal asymptotic rate must lie between C/2 and C. Second, we show that the Chernoff bound is already achieved when the closest state pair is more than 2 times closer than the next closest pair. We also show that the Chernoff bound is achieved when at least r - 2 of the states are pure, improving on a previous result by Nussbaum and Szkoła. Finally, we indicate a number of potential pathways along which a proof (or disproof) may eventually be found that the multi-hypothesis quantum Chernoff bound is always achieved.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Addressing Angular Single-Event Effects in the Estimation of On-Orbit Error Rates

Our study describes complications introduced by angular direct ionization events on space error rate predictions. In particular, prevalence of multiple-cell upsets and a breakdown in the application of effective linear energy transfer in modern-scale devices can skew error rates approximated from currently available estimation models. Moreover, this paper highlights the importance of angular testing and proposes a methodology to extend existing error estimation tools to properly consider angular strikes in modern-scale devices. Finally, these techniques are illustrated with test data provided from a modern 28 nm SRAM-based device.

42 ENGINEERING↗
DOE OSTI2014

A High-Precision Instrument for Mapping of Rotational Errors in Rotary Stages

A rotational stage is a key component of every X-ray instrument capable of providing tomographic or diffraction measurements. To perform accurate three-dimensional reconstructions, runout errors due to imperfect rotation (e.g. circle of confusion) must be quantified and corrected. A dedicated instrument capable of full characterization and circle of confusion mapping in rotary stages down to the sub-10 nm level has been developed. A high-stability design, with an array of five capacitive sensors, allows simultaneous measurements of wobble, radial and axial displacements. The developed instrument has been used for characterization of two mechanical stages which are part of an X-ray microscope.

36 MATERIALS SCIENCE↗
DOE OSTI2014

A Bayesian method for using simulator data to enhance human error probabilities assigned by existing HRA methods

In the past several years, several international organizations have begun to collect data on human performance in nuclear power plant simulators. The data collected provide a valuable opportunity to improve human reliability analysis (HRA), but these improvements will not be realized without implementation of Bayesian methods. Bayesian methods are widely used to incorporate sparse data into models in many parts of probabilistic risk assessment (PRA), but Bayesian methods have not been adopted by the HRA community. In this paper, we provide a Bayesian methodology to formally use simulator data to refine the human error probabilities (HEPs) assigned by existing HRA methods. We demonstrate the methodology with a case study, wherein we use simulator data from the Halden Reactor Project to update the probability assignments from the SPAR-H method. The case study demonstrates the ability to use performance data, even sparse data, to improve existing HRA methods. Furthermore, this paper also serves as a demonstration of the value of Bayesian methods to improve the technical basis of HRA.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Mechanism of error-free DNA synthesis across N1-methyl-deoxyadenosine by human DNA polymerase-$\iota$

N1-methyl-deoxyadenosine (1-MeA) is formed by methylation of deoxyadenosine at the N1 atom. 1-MeA presents a block to replicative DNA polymerases due to its inability to participate in Watson-Crick (W-C) base pairing. Here we determine how human DNA polymerase-ι (Pol$\iota$) promotes error-free replication across 1-MeA. Steady state kinetic analyses indicate that Pol$\iota$ is ~100 fold more efficient in incorporating the correct nucleotide T versus the incorrect nucleotide C opposite 1-MeA. To understand the basis of this selectivity, we determined ternary structures of Polι bound to template 1-MeA and incoming dTTP or dCTP. In both structures, template 1-MeA rotates to the syn conformation but pairs differently with dTTP versus dCTP. Thus, whereas dTTP partakes in stable Hoogsteen base pairing with 1-MeA, dCTP fails to gain a “foothold” and is largely disordered. Together, our kinetic and structural studies show how Polι maintains discrimination between correct and incorrect incoming nucleotide opposite 1-MeA in preserving genome integrity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Evaluation of magnetic field error in ExtendedEBIS

The upgrade of the EBIS, called ExtendedEBIS, is now in progress in Brookhaven National Laboratory. Two 5T-superconducting solenoids have been placed in series with 200 mm distance from each other for higher trap capacity and production of polarized 3He ions. Since the two superconducting solenoids are used, the field error is expected to be larger. In this research, the field error is estimated based on simulation. It was found that the magnetic field line can be 17 mm off from the center axis at the entrance of the collector, and this offset can be adjusted by three types of correction coils. Additionally, mismatch of the spin direction of polarized 3He due to the misalignment was estimated to be small.

Ikeda, Shunsuke (ORCID:0000000339800577)↗
DOE OSTI2020

Taming the fixed-node error in diffusion Monte Carlo via range separation

By combining density-functional theory (DFT) and wave function theory via the range separation (RS) of the interelectronic Coulomb operator, we obtain accurate fixed-node diffusion Monte Carlo (FN-DMC) energies with compact multi-determinant trial wave functions. In particular, we combine here short-range exchange-correlation functionals with a flavor of selected configuration interaction known as configuration interaction using a perturbative selection made iteratively (CIPSI), a scheme that we label RS-DFT-CIPSI. One of the take-home messages of the present study is that RS-DFT-CIPSI trial wave functions yield lower fixed-node energies with more compact multi-determinant expansions than CIPSI, especially for small basis sets. Indeed, as the CIPSI component of RS-DFT-CIPSI is relieved from describing the short-range part of the correlation hole around the electron-electron coalescence points, the number of determinants in the trial wave function required to reach a given accuracy is significantly reduced as compared to a conventional CIPSI calculation. Importantly, by performing various numerical experiments, we evidence that the RS-DFT scheme essentially plays the role of a simple Jastrow factor by mimicking short-range correlation effects, hence avoiding the burden of performing a stochastic optimization. Considering the 55 atomization energies of the Gaussian-1 benchmark set of molecules, we show that using a fixed value of mu = 0.5 bohr(-1) provides effective error cancellations as well as compact trial wave functions, making the present method a good candidate for the accurate description of large chemical systems.

Scemama, Anthony↗
DOE OSTI2017

Measuring galaxy cluster masses with CMB lensing using a Maximum Likelihood estimator: statistical and systematic error budgets for future experiments

We develop a Maximum Likelihood estimator (MLE) to measure the masses of galaxy clusters through the impact of gravitational lensing on the temperature and polarization anisotropies of the cosmic microwave background (CMB). We show that, at low noise levels in temperature, this optimal estimator outperforms the standard quadratic estimator by a factor of two. For polarization, we show that the Stokes Q/U maps can be used instead of the traditional E- and B-mode maps without losing information. We test and quantify the bias in the recovered lensing mass for a comprehensive list of potential systematic errors. Using realistic simulations, we examine the cluster mass uncertainties from CMB-cluster lensing as a function of an experiment’s beam size and noise level. We predict the cluster mass uncertainties will be 3 - 6% for SPT-3G, AdvACT, and Simons Array experiments with 10,000 clusters and less than 1% for the CMB-S4 experiment with a sample containing 100,000 clusters. The mass constraints from CMB polarization are very sensitive to the experimental beam size and map noise level: for a factor of three reduction in either the beam size or noise level, the lensing signal-to-noise improves by roughly a factor of two.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Understanding scale-dependent soft-error behavior of scientific applications

Analyzing application fault behavior on large-scale systems is time-consuming and resource-demanding. Currently, researchers need to perform fault injection campaigns at full scale to understand the effects of soft errors on applications and whether these faults result in silent data corruption. Both time and resource requirements greatly limit the scope of the resilience studies that can be currently performed. In this work, we propose a methodology to model application fault behavior at large scale based on a reduced set of experiments performed at small scale. We employ machine learning techniques to accurately model application fault behavior using a set of experiments that can be executed in parallel at small scale. Our methodology drastically reduces the set and the scale of the fault injection experiments to be performed and provides a validated methodology to study application fault behavior at large scale. We show that our methodology can accurately model application fault behavior at large scale by using only small scale experiments. In some cases, we can model the fault behavior of a parallel application running on 4,096 cores with about 90% accuracy based on experiments on a single core.

Kestor, Gokcen G.↗
DOE OSTI2018

Global Sensitivity Analysis and Estimation of Model Error, Toward Uncertainty Quantification in Scramjet Computations

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However, performing uncertainty quantification for scramjet simulations is challenging due to the large number of uncertain parameters involved and the high computational cost of flow simulations. These difficulties are addressed in this paper by developing practical uncertainty quantification algorithms and computational methods, and deploying them in the current study to large-eddy simulations of a jet in crossflow inside a simplified HIFiRE Direct Connect Rig scramjet combustor. First, global sensitivity analysis is conducted to identify influential uncertain input parameters, which can help reduce the system’s stochastic dimension. Second, because models of different fidelity are used in the overall uncertainty quantification assessment, a framework for quantifying and propagating the uncertainty due to model error is presented. In conclusion, these methods are demonstrated on a nonreacting jet-in-crossflow test problem in a simplified scramjet geometry, with parameter space up to 24 dimensions, using static and dynamic treatments of the turbulence subgrid model, and with two-dimensional and three-dimensional geometries.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Non-Destructive Assay (NDA) Uncertainties Impact on Physical Inventory Difference (ID) and Material Balance Determination: Sources of Error, Precision/Accuracy, and ID/Propagation of Error (POV)

These are slides from a presentation made by a researcher from Los Alamos National Laboratory. The following topics are covered: sources of error for NDA gamma measurements, precision and accuracy are two important characteristics of measurements, four items processed in a material balance area during the inventory time period, inventory difference and propagation of variance, sum in quadrature, and overview of the ID/POV process.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Spectral characteristics of background error covariance and multiscale data assimilation

The spatial resolutions of numerical atmospheric and oceanic circulation models have steadily increased over the past decades. Horizontal grid spacing down to the order of 1 km is now often used to resolve cloud systems in the atmosphere and sub-mesoscale circulation systems in the ocean. These fine resolution models encompass a wide range of temporal and spatial scales, across which dynamical and statistical properties vary. In particular, dynamic flow systems for small scales can become spatially localized and temporarily intermittent. An analysis shows that the background correlation length scale is larger than 75 km for streamfunctions, even for a 2-km resolution model, and larger than 25 km for water vapor mixing ratios. The theoretical analyses suggest that such correlation length scales prevent the currently used data assimilation schemes from constraining spatial scales smaller than 150 km for streamfunctions and 50 km for water vapor mixing ratios. These results highlight the necessity of fundamentally modifying the currently used data assimilation algorithm for assimilating high-resolution observations into the aforementioned fine resolution models. A multiscale methodology based on scale decomposition is suggested, and challenges are discussed.

Li, Zhijin↗
DOE OSTI2018

Shrinking Self-Interaction Errors with the Fermi–Löwdin Orbital Self-Interaction-Corrected Density Functional Approximation

The self-interaction error (SIE) is one of the major drawbacks of practical exchange-correlation functionals for Kohn-Sham density functional theory. Despite this, the use of methods that explicitly remove SIE from approximate density functionals is scarce in the literature due to their relatively high computational cost and lack of consistent improvement over standard modern functionals. Here, we assess the performance of a novel approach recently proposed by Pederson, Ruzsinszky, and Perdew for performing self-interaction free calculations in density functional theory based on Fermi-orbitals. To this end, we employ test sets consisting of reaction energies that are considered particularly sensitive to SIE. We found that the parameter-free Fermi-Löwdin orbital self-interaction correction method combined with standard local spin density approximation (LSDA) and Perdew-Burke-Ernzerhof (PBE) functionals gives a much better estimate of reaction energies compared to their parent LSDA and PBE functionals for most of the reactions in these two sets. They also perform on par with the global PBE0 and range-separated LC-ωPBE hybrids, which partially eliminate the SIE by including Hartree-Fock exchange. This shows the potential of the Fermi-Löwdin orbital self-interaction corrected (FLOSIC) method for practical density functional calculations without SIE.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Impact of error fields and error field correction on heat fluxes in SPARC

Using a single toroidal array of coils to reduce the m,n = 2,1 resonant error field (EF) produced by the misalignment of the axisymmetric coils in SPARC can result in the enhancement of the local divertor heat fluxes. Managing high divertor heat fluxes (q ∥ $\simeq$ 10 GW m -2 ) poses a challenge for compact tokamak devices such as SPARC. The presence of non-axisymmetric magnetic field perturbations adds complexity to the problem by generating intricate 3D edge magnetic topologies that alter the heat flux distributions on the target plates. The aim of this work is to investigate the impact of the EF correction (EFC) on the heat fluxes at the divertor plates in SPARC. The MHD code M3DC1 has been used to simulate the 3D magnetic perturbations generated by the shift and tilt of several axisymmetric coils within specified tolerances, as well as from the array of EFC coils located at the midplane. Using a heuristic model that extends the concept of an axisymmetric heat flux layer to 3D plasmas, the resultant heat flux distributions is derived from magnetic footprints calculated with the MAFOT code. The results show that the EFC could either decrease or further enhance the local heat flux when used to correct the m,n = 2,1 resonant EF to enhance the core plasma performance.

3D fields↗
DOE OSTI2018

Assessing Gaussian Assumption of PMU Measurement Error Using Field Data

Gaussian PMU measurement noise has been assumed for many power system applications, such as state estimation, oscillatory modes monitoring, voltage stability analysis, to cite a few. This letter proposes a simple yet effective approach to validate this assumption by using the stability property of a probability distribution and the concept of redundant measurement. Extensive results using field PMU data from WECC system reveal that the Gaussian assumption is questionable.

Wang, Shaobu (ORCID:0000000236073573)↗