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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

The Schottky barrier modulation at PtSi/Si interface by strain and structural deformation

We show, using density functional theory (DFT) calculations, that the Schottky barrier height (SBH) at the PtSi/Si interface can be lowered by uniaxial strain applied not only on Si but also on PtSi. The strain was applied to the (001) direction of Si and PtSi, which is normal for the interface. The SBH of the hole is lowered by 0.08 eV under 2% of tensile strain on Si and by 0.09 eV under 4 % of compressive strain on PtSi. Because the SBH at PtSi/Si contact is approximately 0.2 eV, this amount of reduction can significantly lower the resistance of the PtSi/Si contact; thus applying uniaxial strain on both PtSi and Si possibly enhances the performance of Schottky barrier field effect transistors. Theoretical models of SB formation and conventional structure model are evaluated. It is found that Pt penetration into Si stabilizes the interface and lowers the SBH by approximately 0.1 eV from the bulk-terminated interface model, which implies that conventionally used bulk-terminated interface models have significant errors. Among the theoretical models of SB formation, the model of strong Fermi level pining adequately explains the electron transfer phenomena and SBH, but it has limited ability to explain SBH changes induced by changes of interface structure.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Symmetry Breaking and Error Correction in Open Quantum Systems

Symmetry-breaking transitions are a well-understood phenomenon of closed quantum systems in quantum optics, condensed matter, and high energy physics. However, symmetry breaking in open systems is less thoroughly understood, in part due to the richer steady-state and symmetry structure that such systems possess. For the prototypical open system—a Lindbladian—a unitary symmetry can be imposed in a “weak” or a “strong” way. We characterize the possible $\mathbb{Z}_n$ symmetry-breaking transitions for both cases. In the case of $\mathbb{Z}_2$, a weak-symmetry-broken phase guarantees at most a classical bit steady-state structure, while a strong-symmetry-broken phase admits a partially protected steady-state qubit. Viewing photonic cat qubits through the lens of strong-symmetry breaking, we show how to dynamically recover the logical information after any gap-preserving strong-symmetric error; such recovery becomes perfect exponentially quickly in the number of photons. Further, our study forges a connection between driven-dissipative phase transitions and error correction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Structured sequences emerge from random pool when replicated by templated ligation

The central question in the origin of life is to understand how structure can emerge from randomness. The Eigen theory of replication states, for sequences that are copied one base at a time, that the replication fidelity has to surpass an error threshold to avoid that replicated specific sequences become random because of the incorporated replication errors [M. Eigen, Naturwissenschaften 58 (10), 465–523 (1971)]. Here, we showed that linking short oligomers from a random sequence pool in a templated ligation reaction reduced the sequence space of product strands. We started from 12-mer oligonucleotides with two bases in all possible combinations and triggered enzymatic ligation under temperature cycles. Surprisingly, we found the robust creation of long, highly structured sequences with low entropy. At the ligation site, complementary and alternating sequence patterns developed. However, between the ligation sites, we found either an A-rich or a T-rich sequence within a single oligonucleotide. Our modeling suggests that avoidance of hairpins was the likely cause for these two complementary sequence pools. What emerged was a network of complementary sequences that acted both as templates and substrates of the reaction. This self-selecting ligation reaction could be restarted by only a few majority sequences. The findings showed that replication by random templated ligation from a random sequence input will lead to a highly structured, long, and nonrandom sequence pool. This is a favorable starting point for a subsequent Darwinian evolution searching for higher catalytic functions in an RNA world scenario.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Broadband distortion modeling in Lyman-α forest BAO fitting

Recently, the Lyman-α absorption observed in the spectra of high-redshift quasars has been used as a tracer of large-scale structure by means of the three-dimensional Lyman-α forest auto-correlation function at redshift z≃ 2.3, but the need to fit the quasar continuum in every absorption spectrum introduces a broadband distortion that is difficult to correct and causes a systematic error for measuring any broadband properties. Here, we describe a k-space model for this broadband distortion based on a multiplicative correction to the power spectrum of the transmitted flux fraction that suppresses power on scales corresponding to the typical length of a Lyman-α forest spectrum. In implementing the distortion model in fits for the baryon acoustic oscillation (BAO) peak position in the Lyman-α forest auto-correlation, we find that the fitting method recovers the input values of the linear bias parameter b F and the redshift-space distortion parameter β F for mock data sets with a systematic error of less than 0.5%. Applied to the auto-correlation measured for BOSS Data Release 11, our method improves on the previous treatment of broadband distortions in BAO fitting by providing a better fit to the data using fewer parameters and reducing the statistical errors on βF and the combination b F (1+β F ) by more than a factor of seven. The measured values at redshift z=2.3 are βF=1.39 +0.11 +0.24 +0.38 -0.10 -0.19 -0.28 and bF(1+βF)=-0.374 +0.007 +0.013 +0.020 -0.007 -0.014 -0.022 (1σ, 2σ and 3σ statistical errors). Our fitting software and the input files needed to reproduce our main results are publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SU-C-209-02: 3D Fluoroscopic Image Generation From Patient-Specific 4DCBCT-Based Motion Models Derived From Clinical Patient Images

Purpose: We develop a method to generate time varying volumetric images (3D fluoroscopic images) using patient-specific motion models derived from four-dimensional cone-beam CT (4DCBCT). Methods: Motion models are derived by selecting one 4DCBCT phase as a reference image, and registering the remaining images to it. Principal component analysis (PCA) is performed on the resultant displacement vector fields (DVFs) to create a reduced set of PCA eigenvectors that capture the majority of respiratory motion. 3D fluoroscopic images are generated by optimizing the weights of the PCA eigenvectors iteratively through comparison of measured cone-beam projections and simulated projections generated from the motion model. This method was applied to images from five lung-cancer patients. The spatial accuracy of this method is evaluated by comparing landmark positions in the 3D fluoroscopic images to manually defined ground truth positions in the patient cone-beam projections. Results: 4DCBCT motion models were shown to accurately generate 3D fluoroscopic images when the patient cone-beam projections contained clearly visible structures moving with respiration (e.g., the diaphragm). When no moving anatomical structure was clearly visible in the projections, the 3D fluoroscopic images generated did not capture breathing deformations, and reverted to the reference image. For the subset of 3D fluoroscopic images generated from projections with visibly moving anatomy, the average tumor localization error and the 95th percentile were 1.6 mm and 3.1 mm respectively. Conclusion: This study showed that 4DCBCT-based 3D fluoroscopic images can accurately capture respiratory deformations in a patient dataset, so long as the cone-beam projections used contain visible structures that move with respiration. For clinical implementation of 3D fluoroscopic imaging for treatment verification, an imaging field of view (FOV) that contains visible structures moving with respiration should be selected. If no other appropriate structures are visible, the images should include the diaphragm. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc, Palo Alto, CA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Single-shot X-ray absorption spectroscopy at X-ray free electron lasers

X-ray Absorption Spectroscopy (XAS) is a widely used X-ray diagnostic method for studying electronic and structural properties of matter. At first glance, the relatively narrow bandwidth and the highly fluctuating spectral structure of X-ray Free Electron Lasers (XFEL) sources seem to require accumulation over many shots to achieve high data quality. To date the best approach to implementing XAS at XFEL facilities has been using monochromators to scan the photon energy across the desired spectral range. While this is possible for easily reproducible samples such as liquids, it is incompatible with many important systems. Here, we demonstrate collection of single-shot XAS spectra over 10s of eV using an XFEL source, with error bars of only a few percent. We additionally show how to extend this technique over wider spectral ranges towards Extended X-ray Absorption Fine Structure measurements, by concatenating a few tens of single-shot measurements. Our results pave the way for future XAS studies at XFELs, in particular those in the femtosecond regime. This advance is envisioned to be especially important for many transient processes that can only be initiated at lower repetition rates, for difficult to reproduce excitation conditions, or for rare samples, such as those encountered in high-energy density physics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Hyperconjugation-controlled molecular conformation weakens lithium-ion solvation and stabilizes lithium metal anodes

Tuning the solvation structure of lithium ions via electrolyte engineering has proven effective for lithium metal (Li) anodes. Further advancement that bypasses the trial-and-error practice relies on the establishment of molecular design principles. Expanding the scope of our previous work on solvent fluorination, we report here an alternative design principle for non-fluorinated solvents, which potentially have reduced cost, environmental impact, and toxicity. By studying non-fluorinated ethers systematically, we found that the short-chain acetals favor the [gauche, gauche] molecular conformation due to hyperconjugation, which leads to weakened monodentate coordination with Li + . The dimethoxymethane electrolyte showed fast activation to >99% coulombic efficiency (CE) and high ionic conductivity of 8.03 mS cm -1 . The electrolyte performance was demonstrated in anode-free Cu$∥$LFP pouch cells at current densities up to 4 mA cm -2 (70 to 100 cycles) and thin-Li$∥$high-loading-LFP coin cells (200–300 cycles). Overall, we demonstrated and rationalized the improvement in Li metal cyclability by the acetal structure compared to ethylene glycol ethers. We expect further improvement in performance by tuning the acetal structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Characterizing and Mitigating Intraday Variability: Reconstructing Source Structure in Accreting Black Holes with mm-VLBI

The extraordinary physical resolution afforded by the Event Horizon Telescope has opened a window onto the astrophysical phenomena unfolding on horizon scales in two known black holes, M87* and Sgr A*. However, with this leap in resolution has come a new set of practical complications. Sgr A* exhibits intraday variability that violates the assumptions underlying Earth aperture synthesis, limiting traditional image reconstruction methods to short timescales and data sets with very sparse (u, v) coverage. We present a new set of tools to detect and mitigate this variability. We develop a data-driven, model-agnostic procedure to detect and characterize the spatial structure of intraday variability. This method is calibrated against a large set of mock data sets, producing an empirical estimator of the spatial power spectrum of the brightness fluctuations. We present a novel Bayesian noise modeling algorithm that simultaneously reconstructs an average image and statistical measure of the fluctuations about it using a parameterized form for the excess variance in the complex visibilities not otherwise explained by the statistical errors. These methods are validated using a variety of simulated data, including general relativistic magnetohydrodynamic simulations appropriate for Sgr A* and M87*. We find that the reconstructed source structure and variability are robust to changes in the underlying image model. We apply these methods to the 2017 EHT observations of M87*, finding evidence for variability across the EHT observing campaign. The variability mitigation strategies presented are widely applicable to very long baseline interferometry observations of variable sources generally, for which they provide a data-informed averaging procedure and natural characterization of inter-epoch image consistency.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Enabling Large-Scale Condensed-Phase Hybrid Density Functional Theory Based Ab Initio Molecular Dynamics. 1. Theory, Algorithm, and Performance

By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semilocal density functional theory (DFT) and thereby furnish a more accurate and reliable description of the underlying electronic structure in systems throughout biology, chemistry, physics, and materials science. However, the high computational cost associated with the evaluation of all required EXX quantities has limited the applicability of hybrid DFT in the treatment of large molecules and complex condensed-phase materials. To overcome this limitation, we describe a linear-scaling approach that utilizes a local representation of the occupied orbitals (e.g., maximally localized Wannier functions (MLWFs)) to exploit the sparsity in the real-space evaluation of the quantum mechanical exchange interaction in finite-gap systems. In this work, we present a detailed description of the theoretical and algorithmic advances required to perform MLWF-based ab initio molecular dynamics (AIMD) simulations of large-scale condensed-phase systems of interest at the hybrid DFT level. We focus our theoretical discussion on the integration of this approach into the framework of Car–Parrinello AIMD, and highlight the central role played by the MLWF-product potential (i.e., the solution of Poisson’s equation for each corresponding MLWF-product density) in the evaluation of the EXX energy and wave function forces. We then provide a comprehensive description of the exx algorithm implemented in the open-source Quantum ESPRESSO program, which employs a hybrid MPI/OpenMP parallelization scheme to efficiently utilize the high-performance computing (HPC) resources available on current- and next-generation supercomputer architectures. Furthermore, this is followed by a critical assessment of the accuracy and parallel performance (e.g., strong and weak scaling) of this approach when AIMD simulations of liquid water are performed in the canonical (NVT) ensemble. With access to HPC resources, we demonstrate that exx enables hybrid DFT-based AIMD simulations of condensed-phase systems containing 500–1000 atoms (e.g., (H₂O)₂₅₆) with a wall time cost that is comparable to that of semilocal DFT. In doing so, exx takes us one step closer to routinely performing AIMD simulations of complex and large-scale condensed-phase systems for sufficiently long time scales at the hybrid DFT level of theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Adaptive optical correction for in vivo two-photon fluorescence microscopy with neural fields

Adaptive optics restore ideal imaging performance in complex samples by measuring and correcting optical aberrations but often require custom-built microscopes with carefully aligned wavefront sensing/shaping devices and can be susceptible to sample motion. Here we describe NeAT, a computational framework using neural fields for adaptive optics two-photon fluorescence microscopy. NeAT estimates wavefront aberration and recovers sample structure from a 3D image stack without requiring external datasets for training. Incorporating motion correction in learning and correcting conjugation errors commonly found in commercial microscopes, NeAT is designed for deployment in biological laboratories for in vivo imaging. We validate NeAT’s performance using a custom-built microscope with a wavefront sensor under varying signal-to-noise ratios, aberration and motion conditions. With a commercial microscope, we demonstrate real-time aberration correction for in vivo morphological and functional imaging in the living mouse brain, with NeAT improving the signal and accuracy of glutamate and calcium imaging of synapses and neurons.

Kang, Iksung↗
DOE OSTI2018

Gaussian process based optimization of molecular geometries using statistically sampled energy surfaces from quantum Monte Carlo

Optimization of atomic coordinates and lattice parameters remains a significant challenge to the wide use of stochastic electronic structure methods such as quantum Monte Carlo (QMC). Measurements of the forces and stress tensor by these methods contain statistical errors, challenging conventional gradient-based numerical optimization methods that assume deterministic results. Additionally, forces are not yet available for some methods, wavefunctions, and basis sets and when available may be expensive to compute to sufficiently high statistical accuracy near energy minima, where the energy surfaces are flat. Here, we explore the use of Gaussian process based techniques to sample the energy surfaces and reduce sensitivity to the statistical nature of the problem. We utilize Latin hypercube sampling, with the number of sampled energy points scaling quadratically with the number of optimized parameters. Furthermore, we show these techniques may be successfully applied to systems consisting of tens of parameters, demonstrating QMC optimization of a benzene molecule starting from a randomly perturbed, broken symmetry geometry.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Ab initio electron-phonon interactions using atomic orbital wave functions

The interaction among electrons and lattice vibrations determines key physical properties of materials, including their electrical and heat transport, excited electron dynamics, phase transitions, and superconductivity. We present an ab initio method that employs atomic orbital (AO) wave functions to compute the electron-phonon (e-ph) interactions in materials and interpolate the e-ph coupling matrix elements to fine Brillouin zone grids. We illustrate the numerical implementation of such AO-based e-ph calculations, and benchmark them against direct density functional theory calculations and Wannier function (WF) interpolation. The prime advantages of AOs over WFs for e-ph calculations are outlined. Since AOs are fixed basis functions associated with the atoms, they circumvent the need to generate a material-specific localized basis set with a trial-and-error approach, as is needed in WFs. Therefore, AOs are ideal to compute e-ph interactions in chemically and structurally complex materials for which WFs are challenging to generate, and are also promising for high-throughput materials discovery. Although our findings focus on AOs, the formalism we present generalizes e-ph calculations to arbitrary localized basis sets, with WFs recovered as a special case.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

SubKit

Generating a CTF (thermal-hydraulics subchannel code) model can be time consuming and error prone because of the rigid formatting of the input file and the amount of input requirements. Because of the structured input format, making small changes to a model can require large scale changes to the input file. Furthermore, a user typically has to perform calculations to develop CTF input parameters from actual model geometry. Changing model geometry requires re-calculating input parameters and copying them from wherever the calculation was performed, be it a script, spreadsheet, or piece of paper. This process complicates the quality assurance process for that model and makes changing the model more difficult. CtfDeckBuilder is an object-oriented Python interface to CTF that allows the user to build a CTF model in Python. The user no longer needs to interface with the CTF input file when using the CtfDeckBuilder. The interface reduces the information required of the user by offering defaults for most modeling options provided by CTF. The user can perform calculations directly in Python when building the model so that calculations stay with the model itself.

Salko, Jr., RobertK↗
DOE OSTI2016

Bayesian optimization of the Community Land Model simulated biosphere-atmosphere exchange using CO 2 observations from a dense tower network and aircraft campaigns over Oregon

Here, the vast forests and natural areas of the Pacific Northwest comprise one of the most productive ecosystems in the northern hemisphere. The heterogeneous landscape of Oregon poses a particular challenge to ecosystem models. We present a framework using a scaling factor Bayesian inversion to improve the modeled atmosphere-biosphere exchange of carbon dioxide. Observations from 5 CO/CO 2 towers, eddy covariance towers, and airborne campaigns were used to constrain the Community Land Model CLM4.5 simulated terrestrial CO 2 exchange at a high spatial and temporal resolution (1/24°, 3-hourly). To balance aggregation errors and the degrees of freedom in the inverse modeling system, we applied an unsupervised clustering approach for the spatial structuring of our model domain. Data from flight campaigns were used to quantify the uncertainty introduced by the Lagrangian particle dispersion model that was applied for the inversions. The average annual statewide net ecosystem productivity (NEP) was increased by 32% to 29.7 TgC per year by assimilating the tropospheric mixing ratio data. The associated uncertainty was decreased by 28.4% to 29%, on average over the entire Oregon model domain with the lowest uncertainties of 11% in western Oregon. The largest differences between posterior and prior CO 2 fluxes were found for the Coast Range ecoregion of Oregon that also exhibits the highest availability of atmospheric observations and associated footprints. In this area, covered by highly productive Douglas-fir forest, the differences between the prior and posterior estimate of NEP averaged 3.84 TgC per year during the study period from 2012 through 2014.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

DeepMerge: Studying Distant Merging Galaxies with Deep Neural Networks

The hierarchical merging of galaxies is a probe of the cosmos to test the canonical ?CDM cosmology paradigm. A particularly interesting period is "cosmic high noon" at redshifts z? 2?3, during which star formation rates were the highest, and significant amounts of stellar mass assembled into galaxy-scale bodies. Detecting galaxy mergers in observations by conventional automated methods (which use extracted parameters of galaxy structure - asymmetry, clumpiness, concentration etc.) or by visual inspection has proven to be quite time-consuming and prone to errors. Convolutional Neural Network (CNNs) are a primary representative of deep learning algorithms which are used in computer vision tasks by training to detect features in images. CNNs were already used for classification of low-redshift merging galaxies [1, 2]. Here we will use CNN to to learn directly from images (without the need to extract morphology parameters) of distant merging galaxies in order to distinguish between merging and non-merging objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

X-RAY SPECTRAL AND OPTICAL PROPERTIES OF A ULX IN NGC 4258 (M106)

We study the X-ray and optical properties of the ultraluminous X-ray source (ULX) X-6 in the nearby galaxy NGC 4258 (M106) based on the archival XMM-Newton , Chandra , Swift , and Hubble Space Telescope (HST) observations. The source has a peak luminosity of L {sub X} ∼ 2 × 10{sup 39} erg s{sup −1} in the XMM-Newton observation of 2004 June. Consideration of the hardness ratios and the spectral model parameters shows that the source seems to exhibit possible spectral variations throughout the X-ray observations. In the images from the HST /Advanced Camera for Surveys, three optical sources have been identified as counterpart candidates within the 1 σ error radius of 0.″3. The brightest one has an absolute magnitude of M {sub V} ≈ −7.0 and shows extended structure. The remaining two sources have absolute magnitudes of M {sub V} ≈ −5.8 and −5.3. The possible spectral types of the candidates from brightest to dimmest were determined as B6–A5, B0–A7, and B2–A3. The counterparts of the X-ray source possibly belong to a young star cluster. Neither the standard disk model nor the slim disk model provides firm evidence to determine the spectral characteristics of ULX X-6. We argue that the mass of the compact object lies in the range 10–15 M {sub ☉}, indicating that the compact source is most likely a stellar-mass black hole.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Progress in Understanding the Origins of Excellent Corrosion Resistance in Metallic Alloys: From Binary Polycrystalline Alloys to Metallic Glasses and High Entropy Alloys

Some of the factors responsible for good corrosion resistance of select polycrystalline and emerging alloys in chloride solutions are discussed with a goal of providing some perspectives on the current status and future directions. Traditional metallic glass alloys, single phase high entropy alloys (HEAs), early metallic glasses, and high entropy metallic glasses are all emerging corrosion-resistant alloys (CRAs) that utilize traditional strategies for improved corrosion resistance as well as take advantage of some other novel beneficial attributes. These materials enjoy many degrees of freedom as far as choice of both composition and structure, providing great flexibility in the pursuit of superior corrosion resistance. The new materials depart from classical solvent-solute type polycrystalline binary or ternary alloys. Thus, such emerging materials provide significant opportunities to achieve even greater improvements in corrosion resistance in harsh environments. Several examples of the unique corrosion properties of selected materials in the context of modern theories of corrosion are discussed herein. Discussion is restricted to solid-solution binary or ternary polycrystalline alloys, several metallic glass alloys, and single phase HEAs. A common feature of many CRAs is that composition and microstructure often affect both passivity and resistance to localized corrosion that can be divided into initiation, stabilization, and propagation stages. Enormous complexities in protective oxide structures and chemistries and the large number of combinatorial possibilities in newer materials such as HEAs preclude trial-and-error approaches and perhaps even combinatorial experimental design. Computational materials methodologies will be required in the search for new corrosion-resistant alloys in these material classes. The search must consider the best scientific insights available regarding how major and minor alloy additions, as well as various microstructural attributes, contribute to corrosion mitigation. Additional scientific insights, as they emerge, will enable choices beyond the reliance on high concentrations of alloying elements that are known to affect passivity breakdown and pit stabilization. A challenge is to connect the “basic attributes” of an alloy with its properties. The strength of this connection will likely require new scientific principles enabling deep multiphysics insights in order to link feature(s) such as composition and metallurgical phases to the desired corrosion properties. Application of data informatics will likely also play a role given the plethora of variables that are important in corrosion and the difficulty in assessing all relationships. Here, the opportunity exists to accelerate the design of emerging materials for high corrosion resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Common Cause Failure Mitigation Experience on Digital I and C System in NPP

CCF is failures of redundant or separate structures, systems, or components due to a shared root cause. The CCF includes those are resulted from severe environments, design errors, calibration and maintenance errors, and consequential failures. In addition, digital I and C systems can be vulnerable to CCF caused by software errors or software developed logic, which could defeat the redundancy achieved by the hardware architecture. Therefore, diversity and defense in-depth (D3) has become an important issue to overcome the CCF of the safety I and C system. The U.S. NRC has established regulatory guidance addressing a method for assessing D3 provided by the safety I and C system architecture at a NPP. This method enables determination of whether vulnerabilities to CCF have been adequately addressed. The guidance is included in BTP 7-19 and Chapter 7 of NUREG-0800. The regulatory guidance provides a methodology for designing diversity. APR1400 establishes the mitigating strategies that consider the characteristics of digital I and C system that contribute to the potential for CCF. The diversity strategies consist of a combination of diversity attributes and associated criteria to address potential CCF vulnerabilities in digital safety I and C system. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗