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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Probabilistic Risk Analysis (PRA) of a Mobile Offshore Drilling Unit (MODU) Dynamic Positioning System (DPS)

Probabilistic Risk Assessment (PRA) has been utilized by NASA in a variety of space oriented projects. It has served as one of the primary risk identification and ranking tools. Recent developments in the oil and gas industry have presented opportunities for NASA to lend their PRA expertise to both ongoing and developmental projects within the industry. As a result, NASA has entered into an agreement with Anadarko Petroleum Company (APC) to collaboratively develop PRAs for different aspects of the subsea drilling and completion process of well development. This paper documents how PRA was applied to estimate the probability that a Mobile Offshore Drilling Unit (MODU) equipped with a generically configured Dynamic Positioning System (DPS) loses location and needs to initiate an emergency disconnect. Since this project was in essence a pilot project, the PRA described in this paper is intended to be generic such that the vessel meets the general requirements of an International Maritime Organization (IMO) Maritime Safety Committee (MSC)/Circ. 645 Class 3 dynamically positioned vessel. The results of this analysis are not intended to be applied to any specific drilling vessel, although provisions were made to allow the analysis to be configured to a specific vessel if required.

Thigpen, Eric B.↗
DOE OSTI2016

Adjoint Fokker-Planck equation and runaway electron dynamics

The adjoint Fokker-Planck equation method is applied to study the runaway probability function and the expected slowing-down time for highly relativistic runaway electrons, including the loss of energy due to synchrotron radiation. In direct correspondence to Monte Carlo simulation methods, the runaway probability function has a smooth transition across the runaway separatrix, which can be attributed to effect of the pitch angle scattering term in the kinetic equation. However, for the same numerical accuracy, the adjoint method is more efficient than the Monte Carlo method. The expected slowing-down time gives a novel method to estimate the runaway current decay time in experiments. A new result from this work is that the decay rate of high energy electrons is very slow when E is close to the critical electric field. This effect contributes further to a hysteresis previously found in the runaway electron population.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Single-electron tunneling by using a two-dimensional Corbino nano-scale disk

We investigate a single-electron tunneling effect of two-dimensional electron systems formed in the Corbino nano-scale disk. By controlling bias and gate voltages, the transistor using this effect is able to control electrons one by one. The present study focuses on the electronic transmission probability affected by the charging energy in the Corbino-type single-electron transistor. We reformulated the Schrödinger equation for an electron in the Corbino disk in order to consider the effect of the curvature of the disk, taking into account the charging effect on the performance of the Corbino-type single-electron transistor. We formulated the transmission probability of the electron by applying the Wentzel-Kramers-Brillouin (WKB) method. The electron’s energy in the formula of the transmission probability is then associated to the energy eigenvalue of the Schrödinger equation for an electron in an effective confining potential. We numerically solved the Schrödinger equation to evaluate the transmission probability. Our results show that the transmission probability strongly depends on the charging energy stored in the Corbino disk depending on its size.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

Quantitative assessment of soil CO 2 concentration and stable carbon isotope for leakage detection at geological carbon sequestration sites

This paper presents a quantitative method to evaluate CO 2 concentration ([CO 2 ]) and stable carbon isotope ratio (δ 13 C) as indicators for leakage detection at a geological carbon sequestration site by combining use of field release tests and a numerical modeling approach. A numerical model was developed to simulate CO 2 dynamics by considering diffusion, dissolution in soil water, and soil respiration. The numerical model fits the background dynamics of [CO 2 ] (360 to 550 ppm) and δ 13 C (-16‰ to -6‰) well and reproduces fairly the overall trend observed during the CO 2 release test. The model was further applied to assess detection probability (DP) of [CO 2 ] and δ 13 C for leakage detection in terms of various factors, such as CO 2 leakage rate, background variations, δ 13 C of the CO 2 leaked, and the threshold value of signal-to-noise ratio. Modeling results suggest that δ 13 C may have a higher DP than [CO 2 ]. This study also shows that DP of δ 13 C for the IEA Weyburn project is close to 0, implying δ 13 C is inappropriate to be an indicator for CO 2 leakage at the site. Finally, the quantitative method developed can also be used to design a monitoring plan or strategy in a near-surface environment for geological carbon sequestration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Statistical Strength Analysis of Dissimilar AA2024-T6 and AA6061-T6 Friction Stir Welded Joints

Friction stir welding has been emerged as one of the most reliable processes for joining aerospace-grade aluminum alloys. However, limited studies have been focused so far on the reliability of these joint types. In this study, the effect of welding parameters (traverse and rotation speeds) on the fracture strength of dissimilar AA2024-T6 and AA6061-T6 friction stir welded joints was statistically analyzed by the Weibull approach. Based on the results, the Weibull approach was found to be much more accurate than widely used standard deviation for evaluating the scatter of the fracture strength data. The improper selection of the process parameters not only decreased the average fracture strengths of the joints, but also scattered them around the mean value, and increased the failure probability under the same applied tension. According to the microscopic and macroscopic examinations and microhardness measurements, although the microstructural inhomogeneities caused by the improper setting of the welding parameters negatively affected the joints hardness and fracture strength, the welding defects were likely to be the most responsible factor affecting the fracture strength and its reliability.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Conditional Point Sampling: A Monte Carlo Method for Radiation Transport in Stochastic Media.

Current methods for stochastic media transport are either computationally expensive or, by nature, approximate. Moreover, none of the well-developed, benchmarked approximate methods can compute the variance caused by the stochastic mixing, a quantity especially important to safety calculations. Therefore, we derive and apply a new conditional probability function (CPF) for use in the recently developed stochastic media transport algorithm Conditional Point Sampling (CoPS), which 1) leverages the full intra-particle memory of CoPS to yield errorless computation of stochastic media outputs in 1D, binary, Markovian-mixed media, and 2) leverages the full inter-particle memory of CoPS and the recently developed Embedded Variance Deconvolution method to yield computation of the variance in transport outputs caused by stochastic material mixing. Numerical results demonstrate errorless stochastic media transport as compared to reference benchmark solutions with the new CPF for this class of stochastic mixing as well as the ability to compute the variance caused by the stochastic mixing via CoPS. Using previously derived, non-errorless CPFs, CoPS is further found to be more accurate than the atomic mix approximation, Chord Length Sampling (CLS), and most of memory-enhanced versions of CLS surveyed. In addition, we study the compounding behavior of CPF error as a function of cohort size (where a cohort is a group of histories that share intra-particle memory) and recommend that small cohorts be used when computing the variance in transport outputs caused by stochastic mixing.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

De novo design of protein structure and function with RFdiffusion

Abstract There has been considerable recent progress in designing new proteins using deep-learning methods 1–9 . Despite this progress, a general deep-learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher-order symmetric architectures, has yet to be described. Diffusion models 10,11 have had considerable success in image and language generative modelling but limited success when applied to protein modelling, probably due to the complexity of protein backbone geometry and sequence–structure relationships. Here we show that by fine-tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal-binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryogenic electron microscopy structure of a designed binder in complex with influenza haemagglutinin that is nearly identical to the design model. In a manner analogous to networks that produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.

Science & Technology - Other Topics↗
DOE OSTI2025

Calculation of ion–ion mutual neutralization rate constants using Landau–Zener theory coupled with trajectory simulations for Ar + –Cl − , Br − , I −

In this computational study, we self-consistently calculate the rate constants of mutual neutralization reactions by incorporating the electron transfer probability, using Landau–Zener state transition theory with inputs derived from ab initio quantum chemistry calculations, into classical trajectory simulations. Electronic structure calculations are done using correlation consistent basis sets with multi-reference configuration interaction to map all the molecular electronic states below the ion-dissociation limit as a function of the distance between the reacting species. Our electronic structure calculations have been significantly improved from our previous work through improved selection of molecular electronic configurations maintaining a fine grid of 1a 0 over a wide range of bond lengths and accurate treatment of spin–orbit couplings. Non-adiabatic coupling matrix elements are calculated with the three-point central difference method near each avoided crossing to estimate the exact crossing point R x and coupling parameter H if , which are inputs to the multi-channel Landau–Zener theory to calculate the electron transition probability. Our approach is applied to estimate the mutual neutralization rate constants for the following ion pairs: Ar + –Cl − , Ar + –Br − , Ar + –I − at ∼133 Pa. Furthermore, our predictions are compared against the experimental data reported. It is seen that the improvement in the electronic structure calculation results in excellent agreement between the simulation results and the available experimental data to within a factor of ∼2 or ∼±50%.

Complete-active space self-consistent field↗
DOE OSTI2025

Probabilistic flux limiters

The stable numerical integration of shocks in compressible flow simulations relies on the reduction or elimination of Gibbs phenomena (unstable, spurious oscillations). A popular method to virtually eliminate Gibbs oscillations caused by numerical discretization in under-resolved simulations is to use a flux limiter. A wide range of flux limiters have been studied in the literature, with recent interest in their optimization via machine learning methods trained on high-resolution datasets. The common use of flux limiters in numerical codes as plug-and-play blackbox components makes them key targets for design improvement. Even for deterministic dynamical models, numerical uncertainty is introduced via coarse-graining required by insufficient computational power to solve all scales of motion. Conventional flux limiters are deterministic and lack the capacity to address uncertainties, both aleatoric (inherent randomness) and epistemic (modeling uncertainty due to limited knowledge), which arise in coarse-grained numerical simulations. Here, we introduce a conceptually distinct type of flux limiter that is designed to handle the effects of randomness in the model and uncertainty in model parameters. Unlike traditional single-function flux limiters, these new probabilistic flux limiters incorporate multiple flux limiting functions, each applied with a learned probability drawn from high-resolution data to mitigate the effects of uncertainty in numerical simulations. This approach departs from traditional single-function limiters by explicitly modeling and incorporating uncertainty into the shock capturing process. Using the example of Burgers' equation as a testbed, we show that a machine learned, probabilistic flux limiter may be used in a shock capturing code to more accurately capture shock profiles. In particular, we show that our probabilistic flux limiter outperforms standard limiters and can be successively improved upon (up to a point) by expanding the set of probabilistically chosen flux limiting functions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Correcting for fibre assignment incompleteness in the DESI Bright Galaxy Survey

The Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) will be a survey of bright, low-redshift galaxies, which is planned to cover an area of ~14000 square degrees in three passes. Each pass will cover the survey area with ~2000 pointings, each of area ~8 square degrees. The BGS is currently proposed to consist of a bright high priority sample to an r-band magnitude limit r ~ 19.5, with a fainter low priority sample to r ~ 20. The geometry of the DESI fibre positioners in the focal plane of the telescope affects the completeness of the survey and has a non-trivial impact on clustering measurements. Using a BGS mock catalogue, we demonstrate that completeness due to fibre assignment primarily depends on the surface density of galaxies. Completeness is high (>95 per cent) in low-density regions, but very low (<10 per cent) in the centre of massive clusters. We apply the pair inverse probability (PIP) weighting correction to clustering measurements from a BGS mock which has been through the fibre assignment algorithm. This method is only unbiased if it is possible to observe every galaxy pair. To expedite this, we randomly promote a small fraction of the fainter sample to be high priority, and dither the set of tile positions by a small angle. We show that inverse pair weighting combined with angular upweighting provides an unbiased correction to galaxy clustering measurements for the complete three pass survey, and also after one pass, which is highly incomplete.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Wildfire Risk Mapping over the State of Mississippi: Land Surface Modeling Approach

Three fire risk indexes based on soil moisture estimates were applied to simulate wildfire probability over the southern part of Mississippi using the logistic regression approach. The fire indexes were retrieved from: (1) accumulated difference between daily precipitation and potential evapotranspiration (P-E); (2) top 10 cm soil moisture content simulated by the Mosaic land surface model; and (3) the Keetch-Byram drought index (KBDI). The P-E, KBDI, and soil moisture based indexes were estimated from gridded atmospheric and Mosaic-simulated soil moisture data available from the North American Land Data Assimilation System (NLDAS-2). Normalized deviations of these indexes from the 31-year mean (1980-2010) were fitted into the logistic regression model describing probability of wildfires occurrence as a function of the fire index. It was assumed that such normalization provides more robust and adequate description of temporal dynamics of soil moisture anomalies than the original (not normalized) set of indexes. The logistic model parameters were evaluated for 0.25 x0.25 latitude/longitude cells and for probability representing at least one fire event occurred during 5 consecutive days. A 23-year (1986-2008) forest fires record was used. Two periods were selected and examined (January mid June and mid September December). The application of the logistic model provides an overall good agreement between empirical/observed and model-fitted fire probabilities over the study area during both seasons. The fire risk indexes based on the top 10 cm soil moisture and KBDI have the largest impact on the wildfire odds (increasing it by almost 2 times in response to each unit change of the corresponding fire risk index during January mid June period and by nearly 1.5 times during mid September-December) observed over 0.25 x0.25 cells located along the state of Mississippi Coast line. This result suggests a rather strong control of fire risk indexes on fire occurrence probability over this region.

forest fire risk↗
NASA NTRS1976

Vector wind and vector wind shear models 0 to 27 km altitude for Cape Kennedy, Florida, and Vandenberg AFB, California

The techniques are presented to derive several statistical wind models. The techniques are from the properties of the multivariate normal probability function. Assuming that the winds can be considered as bivariate normally distributed, then (1) the wind components and conditional wind components are univariate normally distributed, (2) the wind speed is Rayleigh distributed, (3) the conditional distribution of wind speed given a wind direction is Rayleigh distributed, and (4) the frequency of wind direction can be derived. All of these distributions are derived from the 5-sample parameter of wind for the bivariate normal distribution. By further assuming that the winds at two altitudes are quadravariate normally distributed, then the vector wind shear is bivariate normally distributed and the modulus of the vector wind shear is Rayleigh distributed. The conditional probability of wind component shears given a wind component is normally distributed. Examples of these and other properties of the multivariate normal probability distribution function as applied to Cape Kennedy, Florida, and Vandenberg AFB, California, wind data samples are given. A technique to develop a synthetic vector wind profile model of interest to aerospace vehicle applications is presented.

Smith, O. E.↗
NASA NTRS1976

Effective defect density for MOS breakdown - Dependence on oxide thickness

A new procedure for measuring effective defect density takes time-dependent primary dielectric breakdown in MOS devices into account. A time-varying breakdown probability is obtained by applying a constant field stress to a statistically sufficient number of MOS capacitors. Effective defects are assumed distributed randomly in two dimensions, hence indistinguishable. The effective defect density is found to vary with oxide thickness; tentative explanations are ventured to account for this (interfacial tensile stress, ion patching enhanced by local trapping, breakdown in the form of filamentary discharges with release of stored electrostatic energy).

Li, S. P.↗
NASA NTRS1990

A 153 day periodicity in the occurrence of solar flares producing energetic interplanetary electrons

The occurrence times of energetic (above 10 MeV) solar flare electron events observed on board the ISEE 3 spacecraft during the years 1978-1982 have been examined; strong evidence is found for a periodicity of 153 + or - 2 days, confirming the discovery of a periodicity in the occurrence of solar flares producing X-rays and gamma rays. The Rayleigh test for periodicity is applied to obtain a probability of less than 10 to the -6th that the times of the electron flares were drawn from a uniform distribution.

Droge, Wolfgang↗
NASA NTRS1991

Monte Carlo study of vibrational relaxation processes

A new model is proposed for the computation of vibrational nonequilibrium in the direct simulation Monte Carlo method (DSMC). This model permits level to level vibrational transitions for the first time in a Monte Carlo flowfield simulation. The model follows the Landau-Teller theory for a harmonic oscillator in which the rates of transition are related to an experimental correlation for the vibrational relaxation time. The usual method for simulating such processes in the DSMC technique applies a constant exchange probability to each collision and the vibrational energy is treated as a continuum. A comparison of these two methods is made for the flow of nitrogen over a wedge. Significant differences exist for the vibrational temperatures computed. These arise as a consequence of the incorrect application of a constant exchange probability in the old method. It is found that the numerical performances of the two vibrational relaxation models are equal.

Boyd, Iain D.↗
NASA NTRS2001

Dynamic Fatigue of ULE Glass

Ultra Low Expansion (ULE) glass is used in a number of applications which require a low thermal expansion coefficient. One such application is telescope mirror elements. An allowable stress can be calculated for this material based upon modulus of rupture data; however, this does not take into account the problem of delayed failure. Delayed failure, due to stress corrosion can significantly shorten the lifetime of a glass article. Knowledge of the factors governing the rate of subcritical flaw growth in a given environment enables the development of relations between lifetime, applied stress and failure probability for the material under study. Dynamic fatigue is one method of obtaining the necessary information to develop these relationships. In this study, the dynamic fatigue method was used to construct time-to-failure diagrams for both 230/270 ground and optically polished samples. The grinding and polishing process reduces the surface flaw size and subsurface damage, and relieves residual stress by removing materials with successively smaller grinding media. This resulted in an increase in the strength of the optic during the grinding and polishing sequence. There was also an increase in the lifetime due to grinding and polishing. It was found that using the fatigue parameters determined from the 230/270 grit surface are not significantly different from the optically polished values. Although the lower bound of the polished samples is more conservative, neither time-to-failure curves lie beyond the upper or lower bound of the confidence limits. Therefore, designers preferring conservative limits could use samples without residual stress present (polished samples) to determine the fatigue parameters and inert Weibull parameters from samples with the service condition surface, to determine time-to-failure of the optical element.

Tucker, Dennis S.↗
NASA NTRS2003

Lifetime Predictions of a Titanium Silicate Glass with Machined Flaws

A dynamic fatigue study was performed on a Titanium Silicate glass to assess its susceptibility to delayed failure and to compare the results with those of a previous study. Fracture mechanics techniques were used to analyze the results for the purpose of making lifetime predictions. The material strength and lifetime was seen to increase due to the removal of residual stress through grinding and polishing. Influence on time-to-failure is addressed for the case with and without residual stress present. Titanium silicate glass otherwise known as ultra-low expansion (ULE)* glass is a candidate for use in applications requiring low thermal expansion characteristics such as telescope mirrors. The Hubble Space Telescope s primary mirror was manufactured from ULE glass. ULE contains 7.5% titanium dioxide which in combination with silica results in a homogenous glass with a linear expansion coefficient near zero. delayed failure . This previous study was based on a 230/270 grit surface. The grinding and polishing process reduces the surface flaw size and subsurface damage, and relieves residual stress by removing the material with successively smaller grinding media. This results in an increase in strength of the optic during the grinding and polishing sequence. Thus, a second study was undertaken using samples with a surface finish typically achieved for mirror elements, to observe the effects of surface finishing on the time-to-failure predictions. An allowable stress can be calculated for this material based upon modulus of rupture data; however, this does not take into account the problem of delayed failure, most likely due to stress corrosion, which can significantly shorten lifetime. Fortunately, a theory based on fracture mechanics has been developed enabling lifetime predictions to be made for brittle materials susceptible to delayed failure. Knowledge of the factors governing the rate of subcritical flaw growth in a given environment enables the development of relations between lifetime, applied stress and failure probability for the material under study. Dynamic fatigue is one method of obtaining the necessary information to develop these relationships. In this study, the dynamic fatigue method was used to construct a time-to-failure diagram for polished ULE glass.

Tucker, Dennis S.↗