Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “process uncertainty”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Multilevel probabilistic approach to evaluate manufacturing defect in composite aircraft structures

In this work it is developed a reliable approach and its feasibility to the design and analysis of a composite structures. The metric is compared the robustness and reliability designs versus the traditional design, to demonstrate the gain that can be achieved with a probabilistic approach. The use of the stochastic approach of the uncertain parameteters in combination with the multi-scale levels analysis is the main objective of this paper. The work is dedicated to analyze the uncertainties in the design, tests, manufacturing process, and key gates such as materials characteristic.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Predictability as a probe of manifest and latent physics: The case of atomic scale structural, chemical, and polarization behaviors in multiferroic Sm-doped BiFeO 3

The predictability of a certain effect or phenomenon is often equated with the knowledge of relevant physical laws, typically understood as a functional or numerically derived relationship between the observations and known states of the system. Correspondingly, observations inconsistent with prior knowledge can be used to derive new knowledge on the nature of the system or indicate the presence of yet unknown mechanisms. In this work, we explore the applicability of Gaussian processes (GP) to establish predictability and uncertainty of local behaviors from multimodal observations, providing an alternative to this classical paradigm. Using atomic resolution scanning transmission electron microscopy (STEM) of multiferroic Sm-doped BiFeO 3 across a broad composition range, we directly visualize the atomic structure and structural, physical, and chemical order parameter fields for the material. GP regression is used to establish the predictability of the local polarization field from different groups of parameters, including the adjacent polarization values and several combinations of physical and chemical descriptors, including lattice parameters, column intensities, etc. We observe that certain elements of microstructure, including charged and uncharged domain walls and interfaces with the substrate, are best predicted with specific combinations of descriptors, and this predictability and associated uncertainties are consistent across the composition series. The associated generative physical mechanisms are discussed. It is also found that certain parameter combinations tend to predict the orthorhombic phase in the cases where rhombohedral phase is observed, suggesting a potential role of clamping and confinement phenomena in phase equilibrium in Sm-BiFeO 3 system close to morphotropic phase boundary. We argue that predictability and uncertainty in observational data offer a new pathway to probe the physics of condensed matter systems from multimodal local observations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2013

THE ROTATION RATES OF MASSIVE STARS: THE ROLE OF BINARY INTERACTION THROUGH TIDES, MASS TRANSFER, AND MERGERS

Rotation is thought to be a major factor in the evolution of massive stars-especially at low metallicity-with consequences for their chemical yields, ionizing flux, and final fate. Deriving the birth spin distribution is of high priority given its importance as a constraint on theories of massive star formation and as input for models of stellar populations in the local universe and at high redshift. Recently, it has become clear that the majority of massive stars interact with a binary companion before they die. We investigate how this affects the distribution of rotation rates, through stellar winds, expansion, tides, mass transfer, and mergers. For this purpose, we simulate a massive binary-star population typical for our Galaxy assuming continuous star formation. We find that, because of binary interaction, 20{sup +5} {sub -10}% of all massive main-sequence stars have projected rotational velocities in excess of 200 km s{sup -1}. We evaluate the effect of uncertain input distributions and physical processes and conclude that the main uncertainties are the mass transfer efficiency and the possible effect of magnetic braking, especially if magnetic fields are generated or amplified during mass accretion and stellar mergers. The fraction of rapid rotators we derive is similar to that observed. If indeed mass transfer and mergers are the main cause for rapid rotation in massive stars, little room remains for rapidly rotating stars that are born single. This implies that spin-down during star formation is even more efficient than previously thought. In addition, this raises questions about the interpretation of the surface abundances of rapidly rotating stars as evidence for rotational mixing. Furthermore, our results allow for the possibility that all early-type Be stars result from binary interactions and suggest that evidence for rotation in explosions, such as long gamma-ray bursts, points to a binary origin.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Foreground contamination in Lyα intensity mapping during the epoch of reionization

The intensity mapping of Lyα emission during the epoch of reionization will be contaminated by foreground emission lines from lower redshifts. We calculate the mean intensity and the power spectrum of Lyα emission at z ∼ 7 and estimate the uncertainties according to the relevant astrophysical processes. We find that the low-redshift emission lines from 6563 Å Hα, 5007 Å [O III], and 3727 Å [O II] will be strong contaminants on the observed Lyα power spectrum. We make use of both the star formation rate and luminosity functions to estimate the mean intensity and power spectra of the three foreground lines at z ∼ 0.5 for Hα, z ∼ 0.9 for [O III], and z ∼ 1.6 for [O II], as they will contaminate the Lyα emission at z ∼ 7. The [O II] line is found to be the strongest. We analyze the masking of the bright survey pixels with a foreground line above some line intensity threshold as a way to reduce the contamination in an intensity mapping survey. We find that the foreground contamination can be neglected if we remove pixels with fluxes above 1.4 × 10{sup –20} W m{sup –2}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

The PDF4LHC report on PDFs and LHC data: Results from Run I and preparation for Run II

The accurate determination of Parton Distribution Functions (PDFs) of the proton is an essential ingredient of the Large Hadron Collider (LHC) program. PDF uncertainties impact a wide range of processes, from Higgs boson characterization and precision Standard Model measurements to New Physics searches. A major recent development in modern PDF analyses has been to exploit the wealth of new information contained in precision measurements from the LHC Run I, as well as progress in tools and methods to include these data in PDF fits. In this report we summarize the information that PDF-sensitive measurements at the LHC have provided so far, and review the prospects for further constraining PDFs with data from the recently started Run II. As a result, this document aims to provide useful input to the LHC collaborations to prioritize their PDF-sensitive measurements at Run II, as well as a comprehensive reference for the PDF-fitting collaborations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Enhanced antineutrino emission from 𝛽 decay in core-collapse supernovae with self-consistent weak decay rates

Nuclear weak-interaction rates are known to exert a prominent effect in the late stages of stellar collapse. Despite their importance, most studies to date on core-collapse supernovae (CCSNe) have focused primarily on the effects of electron captures, neglecting 𝛽 decay contributions. In this work, we present the first CCSNe simulation incorporating global 𝛽 decay rates from a microscopic theory. These are enabled by a large-scale evaluation of both electron capture and 𝛽 decay rates, obtained self-consistently utilizing the relativistic energy density functional theory and finite-temperature quasiparticle random-phase approximation. Including 𝛽 decay leads to a dramatic enhancement of the pre-bounce antineutrino signal as the antineutrino emissivity increases by more than two orders of magnitude and the luminosity by a factor of 50 relative to thermal emission alone, while the average antineutrino energy increases by over 1 MeV. Furthermore, it is expected that these new rates could help us constrain the model uncertainties related to weak-interaction processes, improving the prediction of antineutrino signal during the final stages of stellar death.

Beta decay↗
DOE OSTI2022

Measurement of the Mo 100 ( α , x n ) cross section at weak r -process energies

Here, the weak r process in neutrino-driven winds following a core-collapse supernova is thought to contribute to the cosmic abundances of the first r-process peak elements between Se and Ag. Sensitivity studies have found that the early nucleosynthesis in the weak r process is primarily driven by (α, xn) reactions due to the high temperatures, and that current nuclear physics uncertainties in the (α, xn) rates result in significant uncertainties of the calculated abundances. The weak r-process path proceeds several nuclei away from stability where (α, xn) reaction cross sections have not yet been measured. In this paper we report the 100 Mo (α, xn) cross section (between 8.9 and 13.2 MeV in the center of mass, corresponding to 3.5–6.8 GK) in inverse kinematics using the Multi-Sampling Ionization Chamber (MUSIC) detector at the Argonne Tandem Linac Accelerator System (ATLAS) facility. With this first measurement of the 100 Mo (α, xn) cross section, we have demonstrated the ability of MUSIC to measure (α, xn) cross sections for A up to 100, therefore paving the way for further measurements with radioactive beams at ATLAS or the Facility for Rare Isotope Beams.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Strongly resonating bosons in hot nuclei

When two heavy ions near the Fermi energy collide, a warm and low-density region can form in which fragments appear. This region is mainly dominated by proton (p) and alpha (α) particles. In such an environment, the α particles interact with each other and, especially through strong resonances, form complex systems such as 8 Be and 12 C. Our experiments show that 70(64) Zn( 64 Ni) + 70(64) Zn( 64 Ni) reactions at E/A = 35 MeV/nucleon levels of 8Be appear around relative energies E ij = 0.092 MeV, 3.03 MeV as well as above 10 and 100 MeV. We propose a different method to derive the correlation function based on the relative transverse energy distribution to minimize the experimental uncertainties. For the 3α systems, multiresonance processes give rise to excited levels of 12 C. For instance, the Hoyle state at 7.654 MeV excitation energy shows a decay component through the ground state of 8 Be and also components where two different α couples are at relative energies consistent with the ground state of 8 Be at the same time.

6 ≤ A ≤ 19↗
DOE OSTI2022

How the Universe postpones the evaporation and curtails the quantum spreading of black holes

Black holes are expected to evaporate through the process of Hawking radiation. This process is expected to cause the uncertainty in a black hole’s position to grow to ~ $M^4/M^3_{pl}$ over the course of it’s lifetime, even as its momentum spreads only by ~ $M_{Pl}$ For the black holes that have been observed, which have M ≥ M ⊙ this greatly exceeds the Hubble volume. However, the decay of black holes and their quantum spreading, are delayed in the Universe while the influx of energy into the black holes exceeds their Hawking luminosity. We show that for these M ≥ M ⊙ black holes, their decay outside galaxies and clusters is prevented far longer than it takes the black holes to be dragged well beyond the Hubble horizon, where their eventual decay occurs away from the prying eyes of any observer who has not hitched a ride with them. Meanwhile, black holes in an observer’s galaxy or cluster are themselves prevented from decaying long past the extinction of the last stars, and at least until their galaxy/cluster is swept clean of dark matter, in $\gg$ 10 25 y. Even then, if the black holes become unbound, then they are dragged beyond the Hubble radius before undergoing significant decay; if not, they remain in bound orbits, spreading at most over a subvolume of the galaxy/cluster, and long localized by scatterings to much smaller volumes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Factors influencing quantum evaporation of helium from polar semiconductors from first principles

While there is much indirect evidence for the existence of dark matter (DM), to date it has evaded detection. Current efforts focus on DM masses over ~GeV—to push the sensitivity of DM searches to lower masses, new DM targets and detection schemes are needed. In this work, we focus on the latter—a novel detection scheme recently proposed to detect 10–100 meV phonons in polar target materials. Previous work showed that well-motivated models of DM can interact with polar semiconductors to produce an athermal population of phonons. This new sensing scheme proposes that these phonons then facilitate quantum evaporation of 3 He from a van der Waals film deposited on the target material. However, a fundamental understanding of the underlying process is still unclear, with several uncertainties related to the precise rate of evaporation and how it can be controlled. In this work, we use ab initio density functional theory calculations to compare the adsorption energies of helium atoms on a polar target material, sodium iodide, to understand the underlying evaporation physics. We explore the role of surface termination, monolayer coverage, and elemental species on the rate of He evaporation from the target material. Using this, we discuss the optimal target features for He-evaporation experiments and their range of tunability through chemical and physical modifications such as applied field and surface termination.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Entropic Energy-Time Uncertainty Relation

We report that energy-time uncertainty plays an important role in quantum foundations and technologies, and it was even discussed by the founders of quantum mechanics. However, standard approaches (e.g., Robertson’s uncertainty relation) do not apply to energy-time uncertainty because, in general, there is no Hermitian operator associated with time. Following previous approaches, we quantify time uncertainty by how well one can read off the time from a quantum clock. We then use entropy to quantify the information-theoretic distinguishability of the various time states of the clock. Our main result is an entropic energy-time uncertainty relation for general time-independent Hamiltonians, stated for both the discrete-time and continuous-time cases. Additionally, our uncertainty relation is strong, in the sense that it allows for a quantum memory to help reduce the uncertainty, and this formulation leads us to reinterpret it as a bound on the relative entropy of asymmetry. Because of the operational relevance of entropy, we anticipate that our uncertainty relation will have information-processing applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A Neural Optimizer With Decision-Focused Learning for Optimal Energy Storage Operation

Here, this article introduces a neural optimizer-based framework for optimizing battery energy storage system (BESS) control for grid services, including demand charge and energy cost reduction. By leveraging decision-focused learning (DFL), the proposed framework ensures seamless integration and adaptation, significantly enhancing control performance. A patch time-series transformer is employed for peak load forecasting, incorporating aleatoric uncertainty quantification to account for forecasting uncertainties within the decision-making process. The framework utilizes a solver-in-the-loop approach to generate optimal BESS actions, which are then used to train the neural optimizer-based agent. By co-optimizing both BESS operational modes and output power within the NN, the system achieves improved performance and robustness. After initial training, the forecasting and control models are jointly fine-tuned to account for forecasting errors, further improving decision precision and efficiency through DFL. Case studies are performed to validate the performance of the framework using multiple real-world datasets, demonstrating superior performance in monthly peak load forecasting compared to state-of-the-art models. In addition, the results are compared against existing decision-making approaches. The results demonstrate a reduction in monthly peak forecasting error by approximately 15% across various performance measures and achieve an optimization gap for BESS operation that is about three times smaller compared to existing methods.

Kim, Hyeonjin [Pacific Northwest National Laborato↗
DOE OSTI2016

NJOY2016

NJOY2016 is used to convert evaluations in the Evaluated Nuclear Data Files (ENDF) format into forms useful for practical applications such as fission and fusion reactor analysis, criticality safety, radiation shielding, nuclear waste management, nuclear medicine procedures, and more. It begins with the generation of pointwise libraries, including reaction and resonance reconstruction, Doppler broadening, radiation heating and damage, thermal scattering data, unresolved resonance data, and gas production. It reviews the production of libraries for the continuous-energy Monte Carlo code MCNP, multigroup neutron, photon, and particle cross sections and matrices, and photon interaction data. Uncertainty information for ENDF data is processed, including the capability for calculating covariances of resonance data, angular distributions, energy distributions, and radioactive nuclide production. NJOY can prepare and process thermal scattering data evaluations into application libraries. It can also plot cross sections, angular distributions and secondary emission spectra.

Kahler III, A. C. (Skip)↗
DOE OSTI2021

Sensitivity-based Similarity Metrics for New Experiment Design Optimization

The nuclear data used in advanced reactor simulations requires validation. Data from nuclear criticality experiments can provide this validation. New nuclear criticality experiment design requires extensive knowledge and expert judgement such that the experimental design parameters are selected in such a way to keep the experiment subcritical. To aide in this experimental design process, professionals can utilize sensitivity and uncertainty analysis. Sensitivity and uncertainty analysis relies on matching new application experiments with currently existing benchmark experiments. Currently, there is functionality in the Whisper 1.1 software package to calculate a similarity metric based on neutron multiplication factor sensitivity coefficients between a new application designed by the user and existing International Criticality Safety Benchmark Experiment Project (ICSBEP) benchmarks. The Whisper 1.1 software package is included in Monte Carlo N-Particle ® Code Version 6.21 (MCNP ® 6.2). This work is geared toward expanding this capability to new similarity metrics based on beta-effective sensitivity coefficients and reactivity coefficient sensitivity coefficients. While the investigation of these sensitivity coefficients is presented in detail in separate works at this same conference, this work will be primarily focused on studying the similarity metrics in more detail. These similarity metrics will then be incorporated into the optimization algorithms used for experiment design in EUCLID (Experiments Underpinned by Computational Learning for Improvements in nuclear Data), which is a Los Alamos National Laboratory (LANL) project designed to constrain nuclear data of interest, such that adjustments can be made to possible inaccuracies. A more detailed optimization can be subsequently performed by breaking down these similarity metrics by isotope, reaction, and energy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

ANALYSIS OF VARIANCE-BASED MIXED MULTISCALE FINITE ELEMENT METHOD AND APPLICATIONS IN STOCHASTIC TWO-PHASE FLOWS

The stochastic partial differential systems have been widely used to model physical processes, where the inputs involve large uncertainties. Flows in random and heterogeneous porous media is one of the cases where the random inputs (e.g., permeability) are often modeled as a stochastic field with high-dimensional random parameters. To treat the high dimensionality and heterogeneity efficiently, model reduction is employed in both stochastic space and physical space. An analysis of variance (ANOVA)-based mixed multiscale finite element method MsFEM) is developed to decompose the high-dimensional stochastic problem into a set of lower-dimensional stochastic subproblems, which require much less computational complexity and significantly reduce the computational cost in stochastic space, and the mixed MsFEM can capture the heterogeneities on a coarse grid to greatly reduce the computational cost in the spatial domain. In addition, to enhance the efficiency of the traditional ANOVA method, an adaptive ANOVA method based on a new adaptive criterion is developed, where the most active dimensions can be selected to greatly reduce the computational cost before conducting ANOVA decomposition. This novel adaptive criterion is based on variance-decomposition method coupled with sparse-grid probabilistic collocation method or multilevel Monte Carlo method. The advantage of this adaptive criterion lies in its much lower computational overhead for identifying the active dimensions and interactions. A number of numerical examples in two-phase stochastic flows are presented and demonstrate the accuracy and performance of the adaptive ANOVA-based mixed Ms-FEM.

Wei, Jia↗
DOE OSTI2024

Seismic Tomography 2024

Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early-career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. Finally, it remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.

58 GEOSCIENCES↗
DOE OSTI2014

Basin-Scale Leakage Risks from Geologic Carbon Sequestration: Impact on Carbon Capture and Storage Energy Market Competitiveness

This three-year project, performed by Princeton University in partnership with the University of Minnesota and Brookhaven National Laboratory, examined geologic carbon sequestration in regard to CO 2 leakage and potential subsurface liabilities. The research resulted in basin-scale analyses of CO 2 and brine leakage in light of uncertainties in the characteristics of leakage processes, and generated frameworks to monetize the risks of leakage interference with competing subsurface resources. The geographic focus was the Michigan sedimentary basin, for which a 3D topographical model was constructed to represent the hydrostratigraphy. Specifically for Ottawa County, a statistical analysis of the hydraulic properties of underlying sedimentary formations was conducted. For plausible scenarios of injection into the Mt. Simon sandstone, leakage rates were estimated and fluxes into shallow drinking-water aquifers were found to be less than natural analogs of CO 2 fluxes. We developed the Leakage Impact Valuation (LIV) model in which we identified stakeholders and estimated costs associated with leakage events. It was found that costs could be incurred even in the absence of legal action or other subsurface interference because there are substantial costs of finding and fixing the leak and from injection interruption. We developed a model framework called RISCS, which can be used to predict monetized risk of interference with subsurface resources by combining basin-scale leakage predictions with the LIV method. The project has also developed a cost calculator called the Economic and Policy Drivers Module (EPDM), which comprehensively calculates the costs of carbon sequestration and leakage, and can be used to examine major drivers for subsurface leakage liabilities in relation to specific injection scenarios and leakage events. Finally, we examined the competiveness of CCS in the energy market. This analysis, though qualitative, shows that financial incentives, such as a carbon tax, are needed for coal combustion with CCS to gain market share. In another part of the project we studied the role of geochemical reactions in affecting the probability of CO 2 leakage. A basin-scale simulation tool was modified to account for changes in leakage rates due to permeability alterations, based on simplified mathematical rules for the important geochemical reactions between acidified brines and caprock minerals. In studies of reactive flows in fractured caprocks, we examined the potential for permeability increases, and the extent to which existing reactive transport models would or would not be able to predict it. Using caprock specimens from the Eau Claire and Amherstburg, we found that substantial increases in permeability are possible for caprocks that have significant carbonate content, but minimal alteration is expected otherwise. We also found that while the permeability increase may be substantial, it is much less than what would be predicted from hydrodynamic models based on mechanical aperture alone because the roughness that is generated tends to inhibit flow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

2015 IC Report: w14_biosurveillance [Slides]

Our primary use of the institutional computing clusters has been for Wikipedia-based disease surveillance and forecasting work. We've expanded breadth: the number of diseases and locations that can be surveilled using internet data. We've expanded forecasting: surprisingly little work towards forecasting disease spread with quantified uncertainty. We've expanded big data processing techniques: the Wikipedia access logs are 5TB of compressed text; we're working on efficient ways to process and store time series. Our work received significant media coverage and was highlighted as LANL's best science story of 2014.

59 BASIC BIOLOGICAL SCIENCES↗