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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Trainability of ReLU networks and Data-dependent Initialization

Here, in this paper, we study the trainability of rectified linear unit (ReLU) networks at initialization. A ReLU neuron is said to be dead if it only outputs a constant for any input. Two death states of neurons are introduced–tentative and permanent death. A network is then said to be trainable if the number of permanently dead neurons is sufficiently small for a learning task. We refer to the probability of a randomly initialized network being trainable as trainability. We show that a network being trainable is a necessary condition for successful training, and the trainability serves as an upper bound of training success rates. In order to quantify the trainability, we study the probability distribution of the number of active neurons at initialization. In many applications, overspecified or overparameterized neural networks are successfully employed and shown to be trained effectively. With the notion of trainability, we show that overparameterization is both a necessary and a sufficient condition for achieving a zero training loss. Furthermore, we propose a data-dependent initialization method in an overparameterized setting. Numerical examples are provided to demonstrate the effectiveness of the method and our theoretical findings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Cascading Transformer Failure Probability Model Under Geomagnetic Disturbances

This paper develops a probabilistic model to assess the cascading failure of transformers in an electric power grid experiencing geomagnetic disturbances caused by a solar storm. We propose a model in which the probability of failure is a function of the intensity of the solar storm, the physical properties of the transformer, the geographical location of the transformer, and the flow of electrical power. We demonstrate the proposed model using the IEEE 14-bus system and several notional solar storms. The model quickly computes the initial and cascading failure probabilities of the transformers in the system as a first step towards quantifying the risks posed by future solar storms.

Shukla, Pratishtha↗
DOE OSTI2020

Silica nanocluster binding rate coefficients from molecular dynamics trajectory calculations

Oxide nanoparticle growth from vapor phase precursors occurs in high temperature aerosol reactors first via the formation of nanoclusters, which are nanometer-scale condensed-phase species composed of 10 1 -10 2 atoms. The binding rate for nanoclusters, defined as the rate at which two nanoclusters collide with and stick to one another, is hence of interest in predicting nanoparticle size distribution functions in an aerosol. We have utilized molecular dynamics (MD) trajectory calculations to determine the homogeneous (equal-sized) and heterogeneous (disparate-sized) binding rate coefficients of SiO2 (silica) nanoclusters composed of 18, 144, and 333 atoms. MD trajectory calculations incorporated all-atom models of nanoclusters using a combined Born–Huggins–Mayer-Lennard-Jones potential model, which accounts for both short range interactions and electrostatic interactions. MD calculations were utilized to determine the binding probability as a function of both initial relative velocity and impact parameter; integration of the binding probability across impact parameter and relative velocity space yields the binding rate coefficient. MD trajectory calculations reveal that the most common type of encounters between nanoclusters leading to binding are grazing collisions, i.e. instances where collision would not occur without induced dipole potential influences. The resulting binding rate coefficients are found to be extremely weakly dependent on system temperature, which is in contrast to the use of rate coefficient models which are the product of a hard-sphere collision rate coefficient and a constant enhancement factor (leading to a rate coefficient proportional to the square root of temperature). Enhancement factors defined from MD trajectory calculations fall in the range of 3–9 as system temperature decreases from 1500 K to 300 K. Furthermore, such large values suggest that potential interactions need to be considered when modeling oxide nanocluster growth in the gas phase.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Landau-Zener transition between two levels coupled to continuum

We report for a Landau-Zener transition in a two-level system, the probability for a particle, initially in the first level, i, to survive the transition and to remain in the first level, depends exponentially on the square of the tunnel matrix element between the two levels. This result remains valid when the second level, f, is broadened due to e.g. coupling to continuum (Akulin and Schleich (1992) [26]). If the level, i, is also coupled to continuum, albeit much weaker than the level f, a particle, upon surviving the transition, will eventually escape. However, for shorter times, the probability to find the particle in the level i after crossing f is enhanced due to the coupling to continuum. This, as shown in the present paper, is the result of a second-order process, which is an additional coupling between the levels. The underlying mechanism of this additional coupling is virtual tunneling from i into continuum followed by tunneling back into f.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Failure evaluation of neutron-irradiated SiC/SiC composites by underwater acoustic emission

Here, understanding the statistical properties of mechanical properties of non-irradiated and neutron-irradiated SiC/SiC composites is essential for component design. This study aims to evaluate the detailed damage accumulation behavior of composites focusing on two fracture parameters: proportional limit stress (PLS) and acoustic emission (AE) onset stress. The developmental underwater AE technique, which is benefit in non-contact in-situ failure monitoring method during mechanical testing and in handle of the irradiated material, was first applied to evaluate damage accumulation behavior. Two types of chemical vapor infiltration SiC/SiC composites were used: one reinforced with Hi-Nicalon Type-S SiC fiber and one reinforced with Tyranno-SA3 SiC fiber in the form of satin-woven 2D fabrics with pyrolytic carbon interface. Neutron irradiation in the High Flux Isotope Reactor at Oak Ridge National Laboratory reached a fluence of 30 dpa at a temperature of 620–670°C. Four-point flexural tests were conducted to evaluate post-irradiation strength. Weibull statistics did not suggest marked degradation of composite strength. Detailed failure behavior evaluated by AE demonstrated no irradiation-induced change of the AE onset stress (i.e., crack initiation equivalent stress). Failure probability analysis suggests that increasing the reliability of composites (i.e., the Weibull modulus rather than strength itself) is essential to expanding the design margin and benefiting from a probabilistic design approach.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The effect of annealing on kink band formation in Ag/Fe nanolaminates

Kink banding is a common, though not well understood, failure mechanism in anisotropic materials such as nano metallic laminates (NMLs). In this work, we investigate the effect of annealing on kink band (KB) formation in Ag/Fe NMLs prepared by accumulative roll bonding (ARB) using in situ micropillar compression, scanning/transmission electron microscopy (S/TEM), and transmission Kikuchi diffraction (TKD) analyses. Our results show that annealing increases the KB initiation strain, decreases the probability of KB formation, and decreases the load drop magnitude accompanying kink banding in Ag/Fe NMLs. Post-compression analyses reveal that annealing facilitates more uniform deformation of pillars and affects the formation of geometrically necessary grain boundaries (GNBs) near the kink band boundary (KBB). Compared to its as-rolled counterpart, annealed Ag/Fe has wider KBs with blunter KBBs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Highly excited electron cyclotron for QCD axion and dark-photon detection

We propose using highly excited cyclotron states of a trapped electron to detect meV axion and dark-photon dark matter, marking a significant improvement over our previous proposal and demonstration [One-electron quantum cyclotron as a milli-ev dark-photon detector, .]. When the axion mass matches the cyclotron frequency ω c , the cyclotron state is resonantly excited, with a transition probability proportional to its initial quantum number, n c . The sensitivity is enhanced by taking n c ∼ 10 6 ( 0.1 meV ω c ) 2 . By optimizing key experimental parameters, we minimize the required averaging time for cyclotron detection to t ave ∼ 10 − 6 s, permitting detection of such a highly excited state before its decay. An open–end-cap trap design enables the external photon signal to be directed into the trap, rendering our background-free detector compatible with large focusing cavities, such as the BREAD proposal, while capitalizing on their strong magnetic fields. Furthermore, the axion conversion rate can be coherently enhanced by incorporating layers of dielectrics with alternating refractive indices within the cavity. Collectively, these optimizations enable us to probe the QCD axion parameter space from 0.1 to 2.3 meV (25–560 GHz), covering a substantial portion of the predicted postinflationary QCD axion mass range. This sensitivity corresponds to probing the kinetic mixing parameter of the dark photon down to ε ≈ 2 × 10 − 16 . Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Benchmarking of Probabilistic Fracture Mechanics Models in Grizzly

In 2020, as part of contract/task order 31310019N0006/31310020F0060, the Nuclear Regulatory Commission tasked Idaho National Laboratory (INL) with benchmarking the MOOSE/GRIZZLY code against the NRC’s Fracture Analysis of Vessels - Oak Ridge (FAVOR), version 16.1 code. Both codes can predict large light-water reactor vessel integrity deterministically and probabilistically. In fact, such predictions are the primary purpose of the FAVOR code, and are a main focus of the GRIZZLY code, although GRIZZLY is capable of modeling a wider range of geometries and problems. The vessel integrity modeling capabilities of the GRIZZLY code are still under development and being gradually expanded, and the capability to model vessel fracture by crack growth has not yet been integrated into GRIZZLY (although it does exist in pre-release versions). Thus, the present benchmark study focused on comparing predictions for the conditional probability of crack growth initiation (CPI) between GRIZZLY and FAVOR v16.1. The present benchmarking study expands on a previous study completed in 2020, which focused on single plate regions, various flaw types, and full vessel studies. The previous study was limited in scope and revealed some relatively large discrepancies, particularly in the case of weld regions. In the present study, detailed investigations into the sources of discrepancies between GRIZZLY and FAVOR were performed, with a focus on weld regions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Modeling Clustered DNA Damage by Ionizing Radiation Using Multinomial Damage Probabilities and Energy Imparted Spectra

Simple and complex clustered DNA damage represent the critical initial damage caused by radiation. In this paper, a multinomial probability model of clustered damage is developed with probabilities dependent on the energy imparted to DNA and surrounding water molecules. The model consists of four probabilities: (A) direct damage of sugar-phosphate moieties leading to SSB, (B) OH− radical formation with subsequent SSB and BD formation, (C) direct damage to DNA bases, and (D) energy imparted to histone proteins and other molecules in a volume not leading to SSB or BD. These probabilities are augmented by introducing probabilities for the relative location of SSB using a ≤10 bp criteria for a double-strand break (DSB) and for the possible success of a radical attack that leads to SSB or BD. Model predictions for electrons, 4He, and 12C ions are compared to the experimental data and show good agreement. Thus, the developed model allows an accurate and rapid computational method to predict simple and complex clustered DNA damage as a function of radiation quality and to explore the resulting challenges to DNA repair.

Biochemistry & Molecular Biology↗
DOE OSTI2022

Modified Brink-Axel hypothesis for astrophysical Gamow-Teller transitions

Weak interaction charged current transition strengths from highly excited nuclear states are fundamental ingredients for accurate modeling of compact object composition and dynamics, but are difficult to obtain either from experiment or theory. For lack of alternatives, calculations have often fallen back upon a generalized Brink-Axel hypothesis, that is, assuming the strength function (transition probability) is independent of the initial nuclear state but depends only upon the transition energy and the weak interaction properties of the parent nucleus ground state. Here we present numerical evidence for a modified “local” Brink-Axel hypothesis for Gamow-Teller transitions for pf-shell nuclei relevant to astrophysical applications. Specifically, while the original Brink-Axel hypothesis does not hold globally, strength functions from initial states nearby in energy are similar within statistical fluctuations. This agrees with previous work on strength function moments. Using this modified hypothesis, we can tackle strength functions at previously intractable initial energies, using semiconverged initial states at arbitrary excitation energy. Our work provides a well-founded method for computing accurate thermal weak transition rates for medium-mass nuclei at temperatures occurring in stellar cores near collapse. We finish by comparing results to previous calculations of astrophysical rates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Demonstration of the rodeo algorithm on a quantum computer

The rodeo algorithm is an efficient algorithm for eigenstate preparation and eigenvalue estimation for any observable on a quantum computer. This makes it a promising tool for studying the spectrum and structure of atomic nuclei as well as other fields of quantum many-body physics. The only requirement is that the initial state has sufficient overlap probability with the desired eigenstate. While it is exponentially faster than well-known algorithms such as phase estimation and adiabatic evolution for eigenstate preparation, it has yet to be implemented on an actual quantum device. In this work, we apply the rodeo algorithm to determine the energy levels of a random one-qubit Hamiltonian, resulting in a relative error of 0.08% using mid-circuit measurements on the IBM Q device Casablanca. This surpasses the accuracy of directly-prepared eigenvector expectation values using the same quantum device. We take advantage of the high-accuracy energy determination and use the Hellmann-Feynman theorem to compute eigenvector expectation values for a different random one-qubit observable. For the Hellmann-Feynman calculations, we find a relative error of 0.7%. Here, we conclude by discussing possible future applications of the rodeo algorithm for multi-qubit Hamiltonians.

algorithm↗
DOE OSTI2026

Prioritizing Uncertainties in Hydrogen Contribution to Risk in Post-Crash Outcomes for Rail

This report presents analysis from Sandia National Laboratories predicting contributions to risk associated with the use of hydrogen technology for rail. Event sequence diagrams are used to describe possible accident scenarios and progressions. Initiating event frequencies and branch event probabilities for each scenario are quantified with uncertainty using distributions fit to Federal Railroad Administration and U.S. Department of Transportation Pipeline and Hazardous Materials Safety Administration data on applicable accidents from 2000 to 2020. Uncertainty is propagated through the event sequence diagram to estimate the frequency and conditional probability of accident end states. The analysis identifies four scenarios with significant contributions to risk from hydrogen that are predicted to occur relatively frequently, which may inform priorities for reducing uncertainty. These scenarios are 1) overpressure events resulting from collisions with hydrogen release due to mechanical damage and delayed ignition, 2) jet fire events resulting from collisions with hydrogen release due to mechanical damage and immediate ignition, 3) jet fires resulting from fire or explosion initiating events involving the hydrogen tank and correct operation of the thermally-activated pressure relief device (TPRD) subsequent to the thermal insult, and 4) pressure burst resulting from fire or explosion initiating events involving the hydrogen tank and failure of the TPRD. Delayed and immediate hydrogen ignition probabilities are identified as being highly uncertain and potential candidates for reducing conservatism in the predicted frequencies for these two scenarios.

08 HYDROGEN↗
DOE OSTI2022

Sensitivity analysis applied to SiC failure probability in TRISO modeled with BISON

Here, a sensitivity analysis on the failure probability of the Silicon Carbide (SiC) layer in tristructural isotropic (TRISO) nuclear fuel during transient conditions predicted by the BISON fuel performance code is performed. The principal goal of the analysis is to understand the most important parameters dictating SiC failure behavior in BISON during Reactivity Initiated Accidents (RIAs). SiC brittle fracture probability is modeled using Weibull statistics. A total of seven inputs related to SiC failure has been selected for the analysis, including the Weibull statistics parameters, elastic moduli for SiC and Pyrolitic Carbon (PyC) and SiC stress-free temperature. A 1D TRISO BISON model has been established for various reactivity insertions performed at the Nuclear Safety Research Reactor (NSRR). The principal advantage associated with the 1D TRISO model developed in this work is its computational efficiency. The Sobol variance decomposition method is used, and the sensitivity indices are presented for eight different values of the energy deposition. The results show that the two most important parameters impacting the predicted SiC failure probability are the Weibull modulus and the characteristic stress, and a co-variance amongst these parameters is obtained for low reactivity insertions. An additional new finding of this work is that the relative importance of Weibull parameters depends on the energy deposition, and thus reactivity, regime. For low energy depositions, two parameters are of influence on SiC failure probability, while for high energy depositions only one parameter impacts failure probability results. Moreover, optimization of the Weibull modulus and characteristic stress is performed by minimizing the RMSE between BISON failure probability predictions and experimental failure fractions for each energy deposition. This work also demonstrates the validity of the NSRR tests BISON simulations and of the respective sensitivity analysis results as conservative, yet indicative for slower transients characterized by lower deposited energies. Such verification is achieved through the partial extension of the analysis to a group Control Rod Withdrawal reproduced from a previous study. Another novel result of this analysis is that no single set of Weibull parameters can reproduce all reactivity insertion experimental failure results, which is related to the intrinsic nature of SiC failure properties, and a new range for the parameters is proposed to produce a failure probability envelope that encompasses the experimental fractions. Additionaly, this work proposes a new approach for future failure analysis with BISON, consisting in the use of Weibull parameters ranges, rather than fixed sets, along with failure envelopes generation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Dynamic Restructuring Induced Oxygen Activation on AgCu Near Surface Alloys

Recent studies have shown that the addition of Cu to Ag catalysts improves their epoxidation performance by increasing the overall selectivity of the bimetallic catalyst. We have prepared AgCu near-surface alloys and used scanning tunneling microscopy to gain an atomistic picture of O 2 dissociation on the bimetallic system. These data reveal a higher dissociative sticking probability for O 2 on AgCu than Ag(111), and density functional theory (DFT) confirms that the O 2 dissociation barrier is 0.17 eV lower on the alloy. Surprisingly, we find that after a slow initial uptake of O 2 , the sticking probability increases exponentially. Further DFT calculations indicate that surface oxygen reverses the segregation energy for AgCu, stabilizing Cu atoms in the Ag layer. These single Cu atoms in the Ag surface are found to significantly lower the O 2 dissociation barrier. Altogether, these results explain nonlinear effects in the activation of O 2 on this catalytically relevant surface alloy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Quantifying Uncertainty in All-to-All Estimates of Space Object Conjunction Probabilities using U-Statistics

Predicting space object conjunctions is inherently probabilistic due to initial state and orbit model uncertainty. A commonly considered Monte Carlo estimator of the conjunction probability is the ’all-to-all’ estimator. Given independent random samples of the trajectories of both objects, the estimator is the percentage of all pairs of trajectories that result in a conjunction. Intuitively, the all-to-all estimator is the best possible estimator of the conjunction probability since it considers all pairs of Monte Carlo samples. However, its distribution is not available in closed-form, which limits its use in practice and makes this intuition difficult to make rigorous. In this paper, the all-to-all estimator is identified as a U-statistic, which implies that it has several favorable properties. Specifically, the estimator is the minimum variance unbiased estimator of the conjunction probability and is asymptotically Gaussian distributed. An approximate confidence interval for the conjunction probability is obtained from an estimate of the asymptotic Gaussian distribution. We show how to efficiently compute the confidence interval and demonstrate that the interval has the nominal coverage level. The confidence intervals are also seen to be narrower than those based on the commonly-used each-to-each estimator. Furthermore, the all-to-all estimator is shown to allow different Monte Carlo sample sizes, whereas the each-to-each estimator requires equal sample sizes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Comparison of two pressure–temperature equilibration methods

We compare and contrast the traditionally used method of solving the pressure–temperature equilibration problem in hydrodynamics, where specific internal energy and density are considered independent variables, with a different method where pressure and temperature are independent variables. With the goal of examining the robustness of the two methods as the number of components increases, we examine 2-, 4-, 6-, and 8-component systems. After equilibrating more than 10 4 initial conditions for each system using both methods, we demonstrate that the latter method constrains the search space by lowering its dimensionality and forces a better initial guess, resulting in a higher probability of convergence to solution with fewer, cheaper iterations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Path-integral predictions for preasymptotic quantum tunneling

When tunneling occurs out of generic initial states, a significant fraction of probability is lost at early times, during which the dynamics is governed by excited resonance states. However, first-principles analyses based on path-integrals have only captured the leading asymptotic behavior, during which the tunneling rate is dominated by the false vacuum contribution. In this work, we discuss the behavior in the preasymptotic regime from a first-principles path-integral perspective. We demonstrate how the relevant expressions can be evaluated systematically through semiclassical methods in the recently developed steadyon picture. This approach allows one to trace the role of the relevant physical scales, making transparent the underlying assumptions and approximations, and offering a clear path to establishing a systematically improvable framework to evaluate tunneling rates nonperturbatively.

Lin, Joshua↗
DOE OSTI2022

Let’s talk about sex: A biological variable in immune response against melanoma

As science culture gravitates toward a more holistic inclusion of both males and females in research design, the outlining of sex differences and their respective intersections with disease physiology and pathophysiology should see reciprocal expansion. Melanoma skin cancer, for example, has observed a female advantage in incidence, mortality, and overall survival since the early 1970s. The exact biological mechanism of this trend, however, is unclear and further complicated by a layering of clinical variables such as skin phototype, age, and body mass index. In this perspective, we highlight epidemiological evidence of sex differences in melanoma and summarize the landscape of their potential origin. Among several biological hallmarks, we make a note of sex-specific immune profiles—along with divergent hormonal regulation, social practices, DNA damage and oxidative stress responses, body composition, genetic variants, and X-chromosome expression—as probable drivers of disparity in melanoma initiation and progression. This review further focuses the conversation of sex as an influencing factor in melanoma development and its potential implication for disease management and treatment strategies.

59 BASIC BIOLOGICAL SCIENCES↗