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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
DOE OSTI2018

Constraining the mass and radius of neutron stars in globular clusters

In this paper, we analyse observations of eight quiescent low-mass X-ray binaries in globular clusters and combine them to determine the neutron star mass–radius curve and the equation of state of dense matter. We determine the effect that several uncertainties may have on our results, including uncertainties in the distance, the atmosphere composition, the neutron star maximum mass, the neutron star mass distribution, the possible presence of a hotspot on the neutron star surface, and the prior choice for the equation of state of dense matter. The distance uncertainty is implemented in a new Gaussian blurring method that can be directly applied to the probability distribution over mass and radius. We find that the radius of a 1.4 solar mass neutron star is most likely from 10 to 14 km and that tighter constraints are only possible with stronger assumptions about the nature of the neutron stars, the systematics of the observations, or the nature of dense matter. Finally, strong phase transitions in the equation of state are preferred, and in this case, the radius is likely smaller than 12 km. However, radii larger than 12 km are preferred if the neutron stars have uneven temperature distributions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Corrective Control to Handle Forecast Uncertainty: A Chance Constrained Optimal Power Flow

Higher shares of electricity generation from renewable energy sources and market liberalization is increasing uncertainty in power systems operation. At the same time, operation is becoming more flexible with improved control systems and new technology such as phase shifting transformers (PSTs) and high voltage direct current connections (HVDC). Previous studies have shown that the use of corrective control in response to outages contributes to a reduction in operating cost, while maintaining N-1 security. In this work, we propose a method to extend the use of corrective control of PSTs and HVDCs to react to uncertainty. We characterize the uncertainty as continuous random variables, and define the corrective control actions through affine control policies. This allows us to efficiently model control reactions to a large number of uncertainty sources. The control policies are then included in a chance constrained optimal power flow formulation, which guarantees that the system constraints are enforced with a desired probability. Lastly, by applying an analytical reformulation of the chance constraints, we obtain a second-order cone problem for which we develop an efficient solution algorithm. In a case study for the IEEE 118 bus system, we show that corrective control for uncertainty leads to a decrease in operational cost, while maintaining system security. Further, we demonstrate the scalability of the method by solving the problem for the IEEE 300 bus and the Polish system test cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field

he fourth Fermi Large Area Telescope catalog (4FGL) contains 5064 $\ γ$-ray sources detected at high significance, but 26% of them still lack associations at other wavelengths. The SPT-SZ survey, conducted between 2008 and 2011 with the South Pole Telescope (SPT), covers 2500 deg 2 of the southern sky in three millimeter-wavelength (mm) bands and was used to construct a catalog of nearly 5000 emissive sources. In this study, we introduce a new cross-matching scheme to search for multiwavelength counterparts of extragalactic $\ γ$-ray sources using a mm catalog. We apply a Poissonian probability to evaluate the rate of spurious false associations and compare the multiwavelength associations from the radio, mm, near-infrared, and X-ray with 4FGL $\ γ$-ray sources. In the SPT-SZ survey field, 85% of 4FGL sources are associated with mm counterparts. These mm sources include 94% of previously associated 4FGL sources and 56% of previously unassociated 4FGL sources. The latter group contains 40 4FGL sources for which SPT has provided the first identified counterparts. Nearly all of the SPT-associated 4FGL sources can be described as flat-spectrum radio quasars or blazars. We find that the mm band is the most efficient wavelength for detecting $\ γ$-ray blazars when considering both completeness and purity. We also demonstrate that the mm band correlates better to the $\ γ$-ray band than the radio or X-ray bands. With the next generation of CMB experiments, this technique can be extended to greater sensitivities and more sky area to further complete the identifications of the remaining unknown $\ γ$-ray blazars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Integration of Experimental Hydroprocessing and FCC Data with Process (Aspen Plus) and Refinery Optimization (Aspen PIMS) Models

NREL's Economic, Sustainability, and Market Analysis (ESMA) team develops process models in Aspen Plus to support techno-economic analysis (TEA) and life-cycle assessment (LCA) of conversion pathways from renewable and circular resources to fuels and chemicals. These tools are being applied to assess probable operational constraints or bottlenecks associated with refinery co-processing and repurposing opportunities. The team also utilizes optimizable refinery models to quantify opportunities for biofuel and bioproduct pathways through integration with existing refining infrastructure. The goals of analysis are to model the transition of refineries to renewable and circular feedstocks and quantify the costs production and CO2 abatement through utilization of existing refineries. At the core of the ESMA team's work is the process data derived from conversion experiments on hydroprocessing and fluid catalytic cracking performed at NREL. The objective of this presentation is to highlight new analysis approaches and capabilities in pathway analysis and refinery optimization modeling with specific emphasis on integration of experimental data.

BIOMASS FUELS,ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

In situ detection of RF breakdown on microfabricated surface ion traps

We report microfabricated surface ion traps are a principal component of many ion-based quantum information science platforms. The operational parameters of these devices are pushed to the edge of their physical capabilities as the experiments strive for increasing performance. When the applied radio-frequency (RF) voltage is increased excessively, the devices can experience damaging electric discharge events known as RF breakdown. We introduce two novel techniques for in situ detection of RF breakdown, which we implemented while characterizing the breakdown threshold of surface ion traps produced at Sandia National Laboratories. In these traps, breakdown did not always occur immediately after increasing the RF voltage, but often minutes or even hours later. This result is surprising in the context of the suggested mechanisms for RF breakdown in vacuum. Additionally, the extent of visible damage caused by breakdown events increased with the applied voltage. To minimize the probability for damage when RF power is first applied to a device, our results strongly suggest that the voltage should be ramped up over the course of several hours and monitored for breakdown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Mapping variations of redshift distributions with probability integral transforms

We present a method for mapping variations between probability distribution functions and apply this method within the context of measuring galaxy redshift distributions from imaging survey data. This method, which we name PITPZ for the probability integral transformations it relies on, uses a difference in curves between distribution functions in an ensemble as a transformation to apply to another distribution function, thus transferring the variation in the ensemble to the latter distribution function. This procedure is broadly applicable to the problem of uncertainty propagation. In the context of redshift distributions, for example, the uncertainty contribution due to certain effects can be studied effectively only in simulations, thus necessitating a transfer of variation measured in simulations to the redshift distributions measured from data. We illustrate the use of PITPZ by using the method to propagate photometric calibration uncertainty to redshift distributions of the Dark Energy Survey Year 3 weak lensing source galaxies. For this test case, we find that PITPZ yields a lensing amplitude uncertainty estimate due to photometric calibration error within 1 per cent of the truth, compared to as much as a 30 per cent underestimate when using traditional methods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Reactivity of heterogeneous surfaces: Modeling precursor–surface interaction using absorbing Markov chains

Heterogeneous reactive surfaces involving a spatial distribution of reactive sites are ubiquitous in thin film growth, from defect nucleation to step flow growth. In this work, the interaction of gas phase species with heterogeneous reactive surfaces was explored using a model combining absorbing Markov chains and local balance equations. Through this model, single particle statistics can be extracted of the adsorption-diffusion-desorption/reaction process even beyond the transport-limited regime, where the surface coverage of adsorbates, and hence adsorbate-adsorbate interaction, is not negligible, and local rates can be connected with macroscopic quantities, such as the sticking probability and desorption rates. In the transport-limited regime, a similarity law was identified for the sticking probability for both step flow growth and nucleation on randomly distributed reactive sites in which the sticking probability is a function of the product of the local diffusion and reaction probabilities. Lastly, the model can be applied to extract local reactivity maps providing the probability that a particle adsorbing on a given site reacts with the surface. This allows one to explore the development of capture zones and the impact of site-blocking and desorption on the local sticking probabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A spatiotemporally explicit and scalable indicator of intact lands across the conterminous United States, 1986–2023

Globally, ecologically intact areas are increasingly scarce. Agricultural expansion into previously uncultivated areas drives the loss of intact lands that might otherwise exhibit high levels of ecological integrity. Thus, the absence of cultivation can be an indicator of intact lands as measured from remote sensing data and thematic maps. Our objective for this study was to develop and compare tractable approaches based on remotely sensed satellite data to map spatial patterns of potentially intact lands across the conterminous U.S. (CONUS). Using annual cultivation probabilities derived from satellite observations, we classified and mapped potentially intact lands across CONUS from 1986 to 2023 at 30 m resolution. We created three maps, first by applying a constant cultivation probability threshold across CONUS, second by varying the threshold state-by-state to maximize state-level overall accuracies, and third by equalizing the state-level user's and producer's accuracies to minimize classification bias. Validation against 800,000+ independent ground samples resulted in CONUS-level overall accuracies ≥85% for the roughly 660 million ha of potentially intact land. Map accuracy varied with the proportion of potentially intact lands across regions, with the Pacific-Mountain and Great Plains regions exhibiting the highest accuracies, while Eastern CONUS exhibited a greater mix of potentially intact and non-intact lands and more moderate map accuracies. These novel maps and approaches can be adapted to different spatiotemporal extents to support conservation and production decisions ranging from species and ecosystems protection to reducing land conversion and climate mitigation.

agriculture↗
DOE OSTI2023

A Machine Learning–Based Tire Life Prediction Framework for Increasing Life of Commercial Vehicle Tires

In the commercial freight industry, tire retreading decisions are often conservative due to limited knowledge of a tire’s remaining service life. This practice leads to increased costs and material waste. This paper proposes a machine learning–based approach for estimating tire casing life and retreadability, focusing on usage data rather than wear information. This approach could extend the tire’s lifespan and reduce landfill waste. Data integration from diverse tire casing measurement sources presents challenges, including imbalanced removal data. Our methodology addresses these challenges by using historical inspection, telematics, and finite element modeling (FEM) datasets. We introduce “Tire Casing Energy” as a comprehensive usage input and apply a Variance-Reduction Synthetic Minority Oversampling Technique (VR-SMOTE) for data imbalance rectification. A random forest model is used to estimate the state of the tire casing and the casing removal probability, with Bayesian optimization applied for hyperparameter tuning, enhancing model accuracy. Here, the proposed prediction framework is able to differentiate different truck fleets and tire locations based on their usage parameters. With the aid of this machine learning model, the importance and sensitivity of different tire usage parameters can be obtained, which is beneficial to maximize tire life.

Data balancing↗
DOE OSTI2017

DYNAMIC PRA WITH COMPONENT AGING AND DEGRADATION MODELED UTILIZING PLANT RISK MONITORING DATA

In the nuclear industry, risk monitors are intended to provide a point-in-time estimate of the system risk given the current plant configuration. Current risk monitors are limited in that they do not properly take into account the deteriorating states of plant systems, structures, and components (SSCs), which are unit-specific. Current approaches to computing risk monitors use probabilistic risk assessment (PRA) techniques, but the assessment is typically a snapshot in time. Living PRA models attempt to address limitations of traditional PRA models in a limited sense by including temporary changes in plant and system configurations. However, information on plant component health are not considered. This often leaves risk monitors using living PRA models incapable of conducting evaluations with dynamic degradation scenarios evolving over time. There is a need to develop enabling approaches to solidify risk monitors to provide time and condition-dependent risk by integrating traditional PRA models with condition monitoring and prognostic techniques [1]. This paper presents a novel hazard-rate based model of incorporating degradation of nuclear SSCs into an existing PRA model. Time-varying instantaneous hazard-rate of component is used to model degradation based on time-varying performance measure. The instantaneous hazard-rate is used to determine and update time-varying probability of failure of the components in their PRA models. The method is applied to estimate evolution of probability of failure of an in-service pump using vibration measurement taken while the pump undergoes degradation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

A discussion on the origin of quantum probabilities

We study the origin of quantum probabilities as arising from non-Boolean propositional-operational structures. We apply the method developed by Cox to non distributive lattices and develop an alternative formulation of non-Kolmogorovian probability measures for quantum mechanics. By generalizing the method presented in previous works, we outline a general framework for the deduction of probabilities in general propositional structures represented by lattices (including the non-distributive case). -- Highlights: •Several recent works use a derivation similar to that of R.T. Cox to obtain quantum probabilities. •We apply Cox’s method to the lattice of subspaces of the Hilbert space. •We obtain a derivation of quantum probabilities which includes mixed states. •The method presented in this work is susceptible to generalization. •It includes quantum mechanics and classical mechanics as particular cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Improving Limit Surface Search Algorithms in RAVEN Using Acceleration Schemes: Level II Milestone

The RAVEN code is becoming a comprehensive tool to perform Probabilistic Risk Assessment (PRA); Uncertainty Quantification (UQ) and Propagation; and Verification and Validation (V&V). The RAVEN code is being developed to support the Risk-Informed Safety Margin Characterization (RISMC) pathway by developing an advanced set of methodologies and algorithms for use in advanced risk analysis. The RISMC approach uses system simulator codes applied to stochastic analysis tools. The fundamental idea behind this coupling approach to perturb (by employing sampling strategies) timing and sequencing of events, internal parameters of the system codes (i.e., uncertain parameters of the physics model) and initial conditions to estimate values ranges and associated probabilities of figures of merit of interest for engineering and safety (e.g. core damage probability, etc.). This approach applied to complex systems such as nuclear power plants requires performing a series of computationally expensive simulation runs. The large computational burden is caused by the large set of (uncertain) parameters characterizing those systems. Consequently, exploring the uncertain/parametric domain, with a good level of confidence, is generally not affordable, considering the limited computational resources that are currently available. In addition, the recent tendency to develop newer tools, characterized by higher accuracy and larger computational resources (if compared with the presently used legacy codes, that have been developed decades ago), has made this issue even more compelling. In order to overcome to these limitations, the strategy for the exploration of the uncertain/parametric space needs to use at best the computational resources focusing the computational effort in those regions of the uncertain/parametric space that are “interesting” (e.g., risk-significant regions of the input space) with respect the targeted Figures Of Merit (FOM): for example, the failure of the system, subject of the analysis. These methodologies are named, in the RAVEN environment, adaptive sampling strategies. These methodologies infer system responses from surrogate models constructed from already existing samples (produced using high fidelity simulations) and suggest the most relevant location (coordinate in the input space) of the next sampling point to be explored in the uncertain/parametric domain. When using those methodologies, it is possible to understand features of the system response with a small number of carefully selected samples. This report focuses on the development and improvement of the limit surface search. The limit surface is an important concept in system reliability analysis. Without going into the details, which will be covered later in the report, the limit surface could be briefly described as an hyper-surface in the system uncertainty/parametric space separating the regions leading to a prescribed system outcome. For example, if the uncertainty/parametric space is the one generated by the reactor power level and the duration of the batteries, the system is a nuclear power plant and the system outcome discriminating variable is the clad failure in a station blackout scenario, then the limit surface separates the combinations of reactor power level and battery duration that lead to clad failure from the ones that do not.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Fission Matrix Convergence Diagnostic of the Iterated Fission Probability Method

Monte Carlo methods have been applied to reactor problems in order to solve for adjoint-weighted quantities. The Iterated Fission Probability (IFP) method allows adjoint-weighted tallies to be recorded during a forward Monte-Carlo simulation. A key parameter in the IFP method is the number of generations that must pass before the progeny neutrons of a progenitor neutron are tallied. A convergence diagnostic for the IFP is developed using a deterministic code. In particular, a discrete ordinates code is used as a surrogate to demonstrate the theoretical properties of the proposed Monte Carlo convergence diagnostic. The diagnostic is applied to 1-D slab problems and quantifies the error associated with tallying the neutron progeny before an asymptotic distribution is achieved. The results show that the default value of 10 for the number of generations used in MCNP is acceptable for most classes of problems. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
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↗