Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “graphical models”

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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Scientific visualization in computational aerodynamics at NASA Ames Research Center

The visualization methods used in computational fluid dynamics research at the NASA-Ames Numerical Aerodynamic Simulation facility are examined, including postprocessing, tracking, and steering methods. The visualization requirements of the facility's three-dimensional graphical workstation are outlined and the types hardware and software used to meet these requirements are discussed. The main features of the facility's current and next-generation workstations are listed. Emphasis is given to postprocessing techniques, such as dynamic interactive viewing on the workstation and recording and playback on videodisk, tape, and 16-mm film. Postprocessing software packages are described, including a three-dimensional plotter, a surface modeler, a graphical animation system, a flow analysis software toolkit, and a real-time interactive particle-tracer.

Bancroft, Gordon V.↗
DOE OSTI2023

Understanding How Reservoir Operations Influence Methane Emissions: A Conceptual Model

Because methane is a potent greenhouse gas (GHG), understanding controls on methane emissions from reservoirs is an important goal. Yet, reservoirs are complex ecosystems, and mechanisms by which reservoir operations influence methane emissions are poorly understood. In part, this is because emissions occur in ‘hot spots’ and ‘hot moments’. In this study, we address three research questions, ‘What are the causal pathways through which reservoir operations and resulting water level fluctuations (WLF) influence methane emissions?’; ‘How do influences from WLF differ for seasonal drawdown and diurnal hydropeaking operations?’; and ‘How does understanding causal pathways inform practical options for mitigation?’. A graphical conceptual model is presented that links WLF in reservoirs to methane emissions via four causal pathways: (1) water-column mixing (2) drying–rewetting cycles, (3) sediment delivery and redistribution, and (4) littoral vegetation. We review what is known about linkages for WLF at seasonal and diurnal resolutions generate research questions, and hypothesize strategies for moderating methane emissions by interrupting each causal pathway. Those related to flow management involve basin-scale management of tributary flows, seasonal timing of hydropeaking (pathway #1), timing and rates of drawdown (pathway #2). In addition, we describe how sediment (pathway #3) and vegetation management (pathway #4) could interrupt linkages between WLF and emissions. We demonstrate the strength of conceptual modeling as a tool for generating plausible hypotheses and suggesting mitigation strategies. Future research is needed to develop simpler models at appropriate timescales that can be validated and used to manage flow releases from reservoirs.

13 HYDRO ENERGY↗
DOE OSTI2021

Linking Transient Voltage to Spatially-Resolved Luminescence Imaging to Understand Reliability of Perovskite Photovoltaics

In this work, we present a methodology to separate effects of perovskite device metastability from irreversible degradation, using stress/rest cycling under constant current bias while collecting a series of electroluminescence images and continuously monitoring voltage. We develop a simulation model and procedures for image processing to better understand the effects of ion parameters on the transient nature of voltage and evolving electroluminescence images.

electroluminescence↗
DOE OSTI2019

Approximate inference for constructing astronomical catalogs from images

Here, we present a new, fully generative model for constructing astronomical catalogs from optical telescope image sets. Each pixel intensity is treated as a random variable with parameters that depend on the latent properties of stars and galaxies. These latent properties are themselves modeled as random. We compare two procedures for posterior inference. One procedure is based on Markov chain Monte Carlo (MCMC) while the other is based on variational inference (VI). The MCMC procedure excels at quantifying uncertainty, while the VI procedure is 1000 times faster. On a supercomputer, the VI procedure efficiently uses 665,000 CPU cores to construct an astronomical catalog from 50 terabytes of images in 14.6 minutes, demonstrating the scaling characteristics necessary to construct catalogs for upcoming astronomical surveys.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Learning from Crowds by Modeling Common Confusions

Crowdsourcing provides a practical way to obtain large amounts of labeled data at a low cost. However, the annotation quality of annotators varies considerably, which imposes new challenges in learning a high-quality model from the crowdsourced annotations. In this work, we provide a new perspective to decompose annotation noise into common noise and individual noise and differentiate the source of confusion based on instance difficulty and annotator expertise on a per-instance-annotator basis. We realize this new crowdsourcing model by an end-to-end learning solution with two types of noise adaptation layers: one is shared across annotators to capture their commonly shared confusions, and the other one is pertaining to each annotator to realize individual confusion. To recognize the source of noise in each annotation, we use an auxiliary network to choose from the two noise adaptation layers with respect to both instances and annotators. Extensive experiments on both synthesized and real-world benchmarks demonstrate the effectiveness of our proposed common noise adaptation solution.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS2007

Designing Rolling-Element Bearings

Bearing Analysis Tool (BAT) is a computer program for designing rolling-element bearings for cryogenic turbomachines. BAT provides a graphical user interface (GUI) that guides the entry of data to develop mathematical models of bearings. The GUI breaks model data into logical subsets that are entered through logic-driven input screens. The software generates a threedimensional graphical model of a bearing as the data are entered. Most dataentry errors become immediately obvious in the graphical model. BAT provides for storage of all the data on a shaft/bearing system, enabling the creation of a library of proven designs. Data from the library can be transferred to subsequent projects by use of simple cut-and-paste routines. BAT includes a library of temperature- dependent cryogenic bearing-material properties for use in the mathematical models. BAT implements algorithms that (1) enable the user to select combinations of design and/or operating-condition parameters, and then (2) automatically optimize the design by performing trade studies over all of the parameter combinations. This feature enables optimization over a large trade space in a fraction of the time taken when using prior bearingmodel software.

Moore, James D., Jr.↗
DOE OSTI2017

Order priors for Bayesian network discovery with an application to malware phylogeny

Here, Bayesian networks have been used extensively to model and discover dependency relationships among sets of random variables. We learn Bayesian network structure with a combination of human knowledge about the partial ordering of variables and statistical inference of conditional dependencies from observed data. Our approach leverages complementary information from human knowledge and inference from observed data to produce networks that reflect human beliefs about the system as well as to fit the observed data. Applying prior beliefs about partial orderings of variables is an approach distinctly different from existing methods that incorporate prior beliefs about direct dependencies (or edges) in a Bayesian network. We provide an efficient implementation of the partial-order prior in a Bayesian structure discovery learning algorithm, as well as an edge prior, showing that both priors meet the local modularity requirement necessary for an efficient Bayesian discovery algorithm. In benchmark studies, the partial-order prior improves the accuracy of Bayesian network structure learning as well as the edge prior, even though order priors are more general. Our primary motivation is in characterizing the evolution of families of malware to aid cyber security analysts. For the problem of malware phylogeny discovery, we find that our algorithm, compared to existing malware phylogeny algorithms, more accurately discovers true dependencies that are missed by other algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A search for the standard model Higgs boson decaying to charm quarks

A direct search for the standard model Higgs boson, H, produced in association with a vector boson, V (W or Z), and decaying to a charm quark pair is presented. The search uses a data set of proton-proton collisions corresponding to an integrated luminosity of 35.9 fb$^{−1}$, collected by the CMS experiment at the LHC in 2016, at a centre-of-mass energy of 13 TeV. The search is carried out in mutually exclusive channels targeting specific decays of the vector bosons: W → ℓν, Z → ℓℓ, and Z → νν, where ℓ is an electron or a muon. To fully exploit the topology of the H boson decay, two strategies are followed. In the first one, targeting lower vector boson transverse momentum, the H boson candidate is reconstructed via two resolved jets arising from the two charm quarks from the H boson decay. A second strategy identifies the case where the two charm quark jets from the H boson decay merge to form a single jet, which generally only occurs when the vector boson has higher transverse momentum. Both strategies make use of novel methods for charm jet identification, while jet substructure techniques are also exploited to suppress the background in the merged-jet topology. The two analyses are combined to yield a 95% confidence level observed (expected) upper limit on the cross section $ \sigma \left(\mathrm{VH}\right)\mathrm{\mathcal{B}}\left(\mathrm{H}\to \mathrm{c}\overline{\mathrm{c}}\right) $ of 4.5 $ \left({2.4}_{-0.7}^{+1.0}\right) $ pb, corresponding to 70 (37) times the standard model prediction.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Measurement of properties of B$^0_\mathrm{s}\to\mu^+\mu^-$ decays and search for B$^0\to\mu^+\mu^-$ with the CMS experiment

Results are reported for the $ {\mathrm{B}}_{\mathrm{s}}^0 $→ μ$^{+}$μ$^{−}$ branching fraction and effective lifetime and from a search for the decay B$^{0}$→ μ$^{+}$μ$^{−}$. The analysis uses a data sample of proton-proton collisions accumulated by the CMS experiment in 2011, 2012, and 2016, with center-of-mass energies (integrated luminosities) of 7 TeV (5 fb$^{−1}$), 8 TeV (20 fb$^{−1}$), and 13 TeV (36 fb$^{−1}$). The branching fractions are determined by measuring event yields relative to B$^{+}$→ J/ψK$^{+}$ decays (with J/ψ → μ$^{+}$μ$^{−}$), which results in the reduction of many of the systematic uncertainties. The decay $ {\mathrm{B}}_{\mathrm{s}}^0 $→ μ$^{+}$μ$^{−}$ is observed with a significance of 5.6 standard deviations. The branching fraction is measured to be $ \mathrm{\mathcal{B}}\left({\mathrm{B}}_{\mathrm{s}}^0\to {\upmu}^{+}{\upmu}^{-}\right)=\left[2.9\pm 0.7\left(\exp \right)\pm 0.2\left(\mathrm{frag}\right)\right]\times {10}^{-9} $, where the first uncertainty combines the experimental statistical and systematic contributions, and the second is due to the uncertainty in the ratio of the $ {\mathrm{B}}_{\mathrm{s}}^0 $ and the B$^{+}$ fragmentation functions. No significant excess is observed for the decay B$^{0}$→ μ$^{+}$μ$^{−}$, and an upper limit of ℬ(B$^{0}$ → μ$^{+}$μ$^{−}$) < 3.6 × 10$^{−10}$ is obtained at 95% confidence level. The $ {\mathrm{B}}_{\mathrm{s}}^0 $→ μ+μ− effective lifetime is measured to be $ {\tau}_{\upmu^{+}{\upmu}^{-}}={1.70}_{-0.44}^{+0.61} $ ps. These results are consistent with standard model predictions.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Angular analysis of the decay B$^+$ $\to$ K$^*$(892)$^+\mu^+\mu^-$ in proton-proton collisions at $\sqrt{s} =$ 8 TeV

Angular distributions of the decay B$^{+}$→ K$^{∗}$(892)$^{+}$μ$^{+}$μ$^{−}$ are studied using events collected with the CMS detector in $ \sqrt{\mathrm{s}} $ = 8 TeV proton-proton collisions at the LHC, corresponding to an integrated luminosity of 20.0 fb$^{−1}$. The forward-backward asymmetry of the muons and the longitudinal polarization of the K$^{∗}$(892)$^{+}$ meson are determined as a function of the square of the dimuon invariant mass. These are the first results from this exclusive decay mode and are in agreement with a standard model prediction.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Data-driven reduced order models for effective yield strength and partitioning of strain in multiphase materials

There is a critical need for the development and verification of practically useful multiscale modeling strategies for simulating the mechanical response of multiphase metallic materials with heterogeneous microstructures. In this contribution, we present data-driven reduced order models for effective yield strength and strain partitioning in such microstructures. These models are built employing the recently developed framework of Materials Knowledge Systems that employ 2-point spatial correlations (or 2-point statistics) for the quantification of the heterostructures and principal component analyses for their low-dimensional representation. The models are calibrated to a large collection of finite element (FE) results obtained for a diverse range of microstructures with various sizes, shapes, and volume fractions of the phases. The performance of the models is evaluated by comparing the predictions of yield strength and strain partitioning in two-phase materials with the corresponding predictions from a classical self-consistent model as well as results of full-field FE simulations. The reduced-order models developed in this work show an excellent combination of accuracy and computational efficiency, and therefore present an important advance towards computationally efficient microstructure-sensitive multiscale modeling frameworks. - Graphical abstract:.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Optimum Aggregation and Control of Spatially Distributed Flexible Resources in Smart Grid

This paper presents an algorithm to optimally aggregate spatially distributed flexible resources at strategic microgrid/smart-grid locations. The aggregation reduces a distribution network having thousands of nodes to an equivalent network with a few aggregated nodes, thereby enabling distribution system operators (DSOs) to make faster operational decisions. Moreover, the aggregation enables flexibility from small distributed flexible resources to be traded to different power and energy markets. A hierarchical control architecture comprising a combination of centralized and decentralized control approaches is proposed to practically deploy the aggregated flexibility. The proposed method serves as a great operational tool for DSOs to decide the exact amount of required flexibilities from different network section(s) for solving grid constraint violations. The effectiveness of the proposed method is demonstrated through simulation of three operational scenarios in a real low voltage distribution system having high penetrations of electric vehicles and heat pumps. Finally, the simulation results demonstrated that the aggregation helps DSOs not only in taking faster operational decisions, but also in effectively utilizing the available flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Deep Hierarchical Super Resolution for Scientific Data

We present a novel technique for hierarchical super resolution (SR) with neural networks (NNs), which upscales volumetric data represented with an octree data structure to a high-resolution uniform gridwith minimal seam artifacts on octree node boundaries. Our method uses existing state-of-the-art SR models and adds flexibility to upscale input data with varying levels of detail across the domain, instead of only uniform grid data that are supported in previous approaches.The key is to use a hierarchy of SR NNs, each trained to perform 2x SR between two levels of detail, with a hierarchical SR algorithm that minimizes seam artifacts by starting from the coarsest level of detail and working up.We show that our hierarchical approach outperforms baseline interpolation and hierarchical upscaling methods, and demonstrate the usefulness of our proposed approach across three use cases including data reduction using hierarchical downsampling+SR instead of uniform downsampling+SR, computation savings for hierarchical finite-time Lyapunov exponent field calculation, and super-resolving low-resolution simulation results for a high-resolution approximation visualization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Progress Report on Model Development for Aerosol Transport through Divergent Cracks Paths

This report summarizes the progress in developing a phenomenological model of aerosol transport, deposition, and plugging through microchannels. The purpose of this effort is to introduce to a user community—involving researchers, regulators, and industry—a generic, reliable numerical model for the prediction of aerosol transport while accounting for potential deposition and plugging of the leak paths to model spent nuclear fuel (SNF) release from postulated Stress Corrosion Cracks in canisters under storage or transportation. Current work focuses on expanding the model to predict aerosol (and gas) flow through complex microchannel (nozzle) geometries in addition to the rectangular and cylindrical geometries, as we approach more realistic Stress Corrosion Crack conditions. In this regard, a divergent nozzle geometry, used at Sandia National Laboratories (SNL) for testing aerosol release and retention (Durbin et al. 2021), was added to the model. The model was then validated with blowdown data for the particular microchannel, from experiments conducted at SNL. The report also presents preliminary non-benchmarked aerosol penetration fraction and mass flow rate for a monodisperse 10-micron (AED) particle concentration of 1.7e-08 kg/m 3 being released through the divergent microchannel geometry from the SNL’s aerosol experimental tank setup.Future work will involve validating the aerosol model and updating the model’s Graphical User Interface (GUI) to include the divergent nozzle geometry. This is expected to help stakeholders perform quick and easy first principles calculations without needing to understand the underlying MATLAB script.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1971

Project MAC

On-line programming for the following topics is discussed: (1) artificial intelligence, (2) automata theory, (3) cellular automata, (4) computation structures, (5) computer systems research, (6) dynamic modeling, computer graphics, and computer networks, (7) education, (8) implicit computation, (10) interactive management systems, (11) interactive algebraic manipulation, and (12) programming languages.

Licklider, J. C. R.↗
NASA NTRS1979

Feature extraction applied to agricultural crops as seen by LANDSAT

The physical interpretation of the spectral-temporal structure of LANDSAT data can be conveniently described in terms of a graphic descriptive model called the Tassled Cap. This model has been a source of development not only in crop-related feature extraction, but also for data screening and for haze effects correction. Following its qualitative description and an indication of its applications, the model is used to analyze several feature extraction algorithms.

Kauth, R. J.↗
NASA NTRS1984

Interactive graphics for quick-geometry modeling

The QUICK-geometry system is a method for defining configuration shapes in completely analytical form. It was developed for use when the analytical definition of aircraft geometry is advantageous or necessary for the solution of the flow around it. While the QUICK-geometry system provides a convenient and flexible method for generating configurations with completely analytical definitions, experience showed that it can be difficult to match a previously defined configuration with a QUICK-geometry definition. Therefore, the National Aeronautics and Space Administration (NASA) and other users developed computer programs that aid in the generation of QUICK inputs. A NASA-developed set of such programs which recently were upgraded extensively to improve its usability and portability are described.

Townsend, J. C.↗
NASA NTRS1984

An energy principle for high-latitude electrodynamics

A theoretical model for mid- and high-latitude electric fields and currents is constructed using Fourier analysis methods. A two-dimensional planar ionosphere with an enhanced conductivity auroral belt and field-aligned currents at the edges is employed. The postulate that the electric field and currents adjust self-consistently to minimize the global Joule dissipation rate defines a theoretical relation between the primary and secondary field-aligned currents. This so-called minimal dissipation configuration is examined using several input field-aligned current models, and graphical solutions for the electric field and ionospheric current are shown. A detailed discussion and interpretation of the solutions with relation to diverse observations and high-latitude phenomenology are included.

Barbosa, D. D.↗