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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Advancements in frequency-domain methods for rotorcraft system identification

A new method for frequency-domain identification of rotorcraft dynamics is presented. Nonparametric frequency-response identification and parametric tranfer-function modeling methods are extended to allow the extraction of state-space (stability and control derivative) representations. An interactive computer program DERIVID is described for the iterative solution of the multi-input/multi-output frequency-response matching approach used in the identification. Theoretical accuracy methods are used to determine the appropriate model structure and degree-of-confidence in the identified parameters. The method is applied to XV-15 tilt-rotor aircraft data in hover. Bare-airframe stability and control derivatives for the lateral/directional dynamics are shown to compare favorably with models previously obtained using time-domain identification methods and the XV-15 simulation program.

Tischler, Mark B.↗
NASA NTRS1989

Advancements in frequency-domain methods for rotorcraft system identification

A new method for frequency-domain identification of rotorcraft dynamics is presented. Nonparametric frequency-response identification and parametric transfer-function modeling methods are extended to allow the extraction of state-space (stability and control derivative) representations. An interactive computer program DERIVID is described for the iterative solution of the multi-input/multi-output frequency-response matching approach used in the identification. Theoretical accuracy methods are used to determine the appropriate model structure and degree-of-confidence in the identified parameters. The method is applied to XV-15 tilt-rotor aircraft data in hover. Bare-airframe stability and control derivatives for the lateral/directional dynamics are shown to compare favorably with models previously obtained using time-domain identification methods and the XV-15 simulation program.

Tischler, Mark B.↗
NASA NTRS1989

On the identification of formaldehyde in Halley's comet

The v1 and v5 infrared bands of formaldehyde in Halley's comet have been synthesized, using a line-by-line model for solar infrared fluorescence from low-temperature H2CO. Fully resolved spectra were convolved to spectral resolutions comparable with those used on the IKS spectrometer on the Vega 1 spacecraft. Excellent agreement is obtained between the observed and modeled spectra, permitting a definite identification of H2CO in Halley's comet. The retrieved production rate is 4.5 + or - 0.5 x 10 to the 28th molecules/s, and the rotational temperature is probably less than 150 K, with a best-fit value of about 50 K. Production rates (or upper limits) are also retrieved from ground-based spectra of Comets Halley and Wilson (1986), and it is shown that the production rate of H2CO exhibits significant temporal variability, relative to H2O, in Comet Halley.

Mumma, Michael J.↗
DOE OSTI2016

Results of Modeling and Simulation Support to Specia Nuclear Material Handling Facility Operations - 16053

Newport News Shipbuilding (NNS) is the sole designer and provider of nuclear powered aircraft carriers and one of only two companies in the United States to build nuclear powered submarines. As part of the upkeep of aircraft carriers, the ships return to NNS once in their lifetime for a complex overhaul and to be refueled. In support of overhaul operations NNS maintains a state of the art Special Nuclear Material (SNM) handling facility. Due to the complex nature of the operations that occur within this facility, during the design and initial operation of the building NNS developed a facility simulation model to provide decision support during the project planning and operational phases. This tool allows users to experiment with process times, process order, equipment utilization, personnel utilization and spatial utilization. By capturing the planned operations, time distributions for operations, equipment sizes and uses and personnel requirements, the tool accurately reflects the planned use of the facility. This realism allows the user to experiment with any aspect of the facility, in a controlled and cost effective space, and determine how changes or potential delays may impact overall facility operations. Thus the model allows for rapid exploration of multiple scenarios to determine likely outcomes, allowing a user to identify risks well ahead of their realization and explore mitigation strategies in a controlled space, to determine the ideal path forward. The tool was successful during the initial operation of the facility in helping to identify and mitigate risks related to the complex operations occurring during SNM handling. The tool is now in use to support planning for the next series of operations that will occur within the facility. The initial operations the model supported occurred during the deactivation of the USS Enterprise, and future operation will focus on the overhaul of Nimitz class aircraft carriers. The NNS planning team is currently using the tool to assess potential risks and challenges that are identified as potentially impacting the schedule and timelines for these overhaul processes. In addition, the NNS development team is working to add new operational steps to the model, capturing work that is occurring near the facility, but which directly impacts the facilities operational abilities. In conjuncture with the engineering planning division, the NNS development team has run over 20 complex scenarios through the tool. The team has provided output from these scenarios to both NNS personnel and government representatives. To date the model has successfully supported the identification of several feasible paths to incorporate new processes, dictated by the work to support a overhaul vs a deactivation. The model also provides a spatial arrangement component that allows users to experiment with different equipment placement within the facility. Due to the fidelity of the model, arranging equipment with the spatial component allows a user to set up the facility in an experimental layout and run the processes inside the facility to determine if the layout will be feasible, or if it would impact operational capabilities. Additionally, the spatial component allows for visual collaboration between stakeholders to ensure all operational personnel are aware of the current and planned layout, and that they do not locate equipment or work stations in locations that would interfere with facility operations. The spatial component, in combination with the simulation component, has resulted in several documented improvements in process. These include: the identification of additional equipment which could be stored outside the facility, without impacting operations, to increase space; confirmation of the ideal placement of a large water tank; and identification of several risks related to planned equipment storage area, allowing the team to develop new plans and avoid realizing the risk. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Comprehensive experimental investigation on biomass-glass beads binary fluidization: A data set for CFD model validation

Fluidization behavior of biomass and glass beads binary mixtures in a bubbling fluidized bed was experimentally investigated. Mixtures containing different mass fraction of Loblolly Pine white wood and glass beads were fluidized at different fluidization velocities. The particle properties were characterized in a QICPIC that uses a dynamic image processing method to measure both particle size and sphericity. The minimum fluidization velocity was determined using the pressure drop method. An image processing method was developed to capture the dynamic expanded bed height at a very high frequency. The effect of biomass mass fraction and inlet gas velocity on mixing and segregation behavior was studied and analyzed through pressure drop measurements. Pressure drop fluctuations and expanded bed height fluctuations via fast Fourier transform were analyzed and compared. Here, the complete and accurate experimental data reported in this study could provide a benchmark data set for various computational fluid dynamics models validation, calibration, and identification.

42 ENGINEERING↗
DOE OSTI2019

Spatially explicit network analysis reveals multi‐species annual cycle movement patterns of sea ducks

Abstract Conservation of long‐distance migratory species poses unique challenges. Migratory connectivity, that is, the extent to which groupings of individuals at breeding sites are maintained in wintering areas, is frequently used to evaluate population structure and assess use of key habitat areas. However, for species with complex or variable annual cycle movements, this traditional bimodal framework of migratory connectivity may be overly simplistic. Like many other waterfowl, sea ducks often travel to specific pre‐ and post‐breeding sites outside their nesting and wintering areas to prepare for migration by feeding extensively and, in some cases, molting their flight feathers. These additional migrations may play a key role in population structure, but are not included in traditional models of migratory connectivity. Network analysis, which applies graph theory to assess linkages between discrete locations or entities, offers a powerful tool for quantitatively assessing the contributions of different sites used throughout the annual cycle to complex spatial networks. We collected satellite telemetry data on annual cycle movements of 672 individual sea ducks of five species from throughout eastern North America and the Great Lakes. From these data, we constructed a multi‐species network model of migratory patterns and site use over the course of breeding, molting, wintering, and migratory staging. Our results highlight inter‐ and intra‐specific differences in the patterns and complexity of annual cycle movement patterns, including the central importance of staging and molting sites in James Bay, the St. Lawrence River, and southern New England to multi‐species annual cycle habitat linkages, and highlight the value of Long‐tailed Ducks ( Calengula haemalis ) as an umbrella species to represent the movement patterns of multiple sea duck species. We also discuss potential applications of network migration models to conservation prioritization, identification of population units, and integrating different data streams.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Influence of Ag metal dispersion on the thermal conversion of ethanol to butadiene over Ag-ZrO 2 /SiO 2 catalysts

Atomistic scale models were developed and coupled with experimental investigation to deliver a functional understanding of catalytic activity and selectivity in the conversion of ethanol to 1,3-butadiene over Ag/ZrO 2 /SiO 2 . A detailed evaluation of the structural and electronic properties of the resultant catalyst models led to the identification of critical active sites of the catalyst. More importantly, the extent of Ag dispersion on the SiO 2 support and relative proximity to ZrO 2 were found to vary with the oxidation state of Ag and local coordination environment (Ag-O SiO2 ) allowing for critical control of ethanol conversion towards butadiene or ethylene. Simulations revealed that less dispersed or clustered Ag contain predominantly Ag 0 charge state and promote conversion of ethanol to ethylene. The well-dispersed Ag/ZrO 2 /SiO 2 catalyst instead contain a larger fraction of cationic Ag δ+ , and predominantly promote ethanol dehydrogenation and subsequent production of butadiene. The theoretical insights drawn were validated and confirmed experimentally using TEM, XRD and reactivity measurements demonstrating the effect of Ag dispersion on the selectivity of ethanol conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Identifying arbitrary parameter zonation using multiple level set functions

In this paper, we extended the analytical level set method [1, 2] for identifying a piece-wisely heterogeneous (zonation) binary system to the case with an arbitrary number of materials with unknown material properties. In the developed level set approach, starting from an initial guess, the material interfaces are propagated through iterations such that the residuals between the simulated and observed state variables (hydraulic head) is minimized. We derived an expression for the propagation velocity of the interface between any two materials, which is related to the permeability contrast between the materials on two sides of the interface, the sensitivity of the head to permeability, and the head residual. We also formulated an expression for updating the permeability of all materials, which is consistent with the steepest descent of the objective function. The developed approach has been demonstrated through many examples, ranging from totally synthetic cases to a case where the flow conditions are representative of a groundwater contaminant site at the Los Alamos National Laboratory. These examples indicate that the level set method can successfully identify zonation structures, even if the number of materials in the model domain is not exactly known in advance. Although the evolution of the material zonation depends on the initial guess field, inverse modeling runs starting with different initial guesses fields may converge to the similar final zonation structure. These examples also suggest that identifying interfaces of spatially distributed heterogeneities is more important than estimating their permeability values.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

E-waste collection in Italy: Results from an exploratory analysis

Highlights: • The performance of the Italian household collection system for E-waste is analysed in a panel data regression analysis. • N. of Collection points, % of female, % of waste separately collected are positively correlated with kg of E-waste collected. • Population density is negatively correlated with kg of E-waste collected. • The Stochastic Frontier Model identifies the optimal production function. • Tuscany, Sardinia and Sicily are the best performing regions. - Abstract: This study looks at the performance of household electrical and electronic waste (WEEE) collection in 20 Italian regions from 2008 to 2015. The impact of several explicative variables on the results of e-waste collection is evaluated. The independent variables are socio-economic and demographic ones (age, gender, household size, education level, migration and income) along with technical-organisational variables (population density, presence of metropoles, macro regions, characteristics of the territory, percentage of household waste collected separately and number of e-waste collection points). The results show that the presence of collection points, the percentage of household waste collected separately and the percentage of females are positively correlated with the kg collected per inhabitant per year. For example, a variation of 1% of input (presence of collection points) corresponds to a 0.25% variation in the output (collection results) while 1% difference in the percentage of females in the population corresponds to a 7.549% difference in the collection rate. Population density, instead, is negatively correlated. It is interesting to note that there is a discrepancy between the Southern regions and the Centre regions (the former have an outcome 0.66 times lower than the latter) while the Northern regions perform similarly to the Centre ones. Moreover, the first year (2008) had a very low performance compared to the following years when the scheme constantly improved, mainly due to the additional collection points available. The Stochastic Frontier Model allows for the identification of the optimal production function among the 20 Italian regions. The best performing region is Tuscany (in the Centre), followed by Sardinia and Sicily (in the South).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Dynamic Process Intensification via Data-Driven Dynamic Optimization: Concept and Application to Ternary Distillation

Process intensification is a design philosophy aimed at making chemical processes safer and more efficient. Its implementation often results in significant modifications to the design and structure of the process, with several conventional unit operations occurring in the same physical device. Traditionally, process intensification has focused on steady-state operation. In our previous works, we introduced dynamic process intensification (DPI) as a new intensification paradigm based on operational changes for conventional or intensified units. DPI is predicated on switching operation between two auxiliary steady states selected via a steady-state optimization calculation that ensures that the system generates, on average and over time, the same products as in nominal steady-state operation, but with favorable economics. This paper extends the DPI concept and introduces a novel dynamic optimization-based DPI strategy (Do-DPI) that involves imposing a true cyclic operation rather than switching between two discrete states. We discuss its implementation using surrogate dynamic models learned via system identification. Here, an extensive case study concerning a ternary distillation column separating a canonical hydrocarbon mixture shows that Do-DPI can reduce energy use by more than 4% relative to steady-state operation, with no significant deviations in product quality and production rate.

42 ENGINEERING↗
DOE OSTI2019

Prediction of Transition-State Energies of Hydrodeoxygenation Reactions on Transition-Metal Surfaces Based on Machine Learning

Computational catalyst discovery involves identification of a meaningful model and suitable descriptors that determine the catalyst properties. We study the impact of combining various descriptors (e.g., reaction energies, metal descriptors, and bond counts) for modeling transition-state energies (TS) based on a database of adsorption and TS energies across transition-metal surfaces for the decarboxylation and decarbonylation of propionic acid, a chemistry characteristic for biomass conversion. Results of different machine learning models for more than 1572 descriptor combinations suggest that there is no statistically significant difference between linear and nonlinear models when using the right combination of reactant energies, metal descriptors, and bond counts. However, linear models are inferior when not including bond count and metal descriptors. In conclusion, when there are missing data for reaction steps on all metals, conventional linear scaling is inferior to linear and nonlinear models with proper choice of descriptors that are surprisingly robust.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Central diffraction in proton-proton collisions at {radical}(s) = 7TeV with ALICE at LHC

A double-gap topology is used for filtering central-diffractive events from a protonproton minimum-bias data sample at a centre-of-mass energy Central diffraction in proton-proton collisions at {radical}(s) = 7TeV. This topology is defined by particle activity in the ALICE central barrel and absence of particle activity outside. The fraction of events satisfying the double-gap requirement R{sub DG} is found to be 7.63{+-}0.02(st at.){+-}0.87(syst.) Multiplication-Sign 10{sup -4}. The background of this double-gap fraction is estimated by studying the contributions of non-diffractive, single-and double-diffractive dissociation processes as modelled by Monte Carlo event generators, and is found to be about 10%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Diffractive production of charm quark/antiquark pairs at RHIC and LHC

We have discussed single and central diffractive production of c(bar sign)c pairs in the Ingelman-Schlein model. In these calculations we have included diffractive parton distributions obtained by the H1 collaboration at HERA and absorption effects neglected in some early calculations in the literature. The absorption effects which are responsible for the naive Regge factorization breaking cause that the cross section for diffractive processes is much smaller than that for the fully inclusive case, but could be measured at RHIC and LHC by imposing special condition on rapidity gaps. We discuss also different approaches to diffractive production of heavy quark/antiquark [1, 2, 3]. The particular mechanism is similar to the diffractive dissociation of virtual photons into quarks, which drives diffractive deep inelastic production of charm in the low-mass diffraction, or large {beta}-region.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Robust predictions of specialized metabolism genes through machine learning

Plant specialized metabolism (SM) enzymes produce lineage-specific metabolites with important ecological, evolutionary, and biotechnological implications. Using Arabidopsis thaliana as a model, we identified distinguishing characteristics of SM and GM (general metabolism, traditionally referred to as primary metabolism) genes through a detailed study of features including duplication pattern, sequence conservation, transcription, protein domain content, and gene network properties. Analysis of multiple sets of benchmark genes revealed that SM genes tend to be tandemly duplicated, coexpressed with their paralogs, narrowly expressed at lower levels, less conserved, and less well connected in gene networks relative to GM genes. Although the values of each of these features significantly differed between SM and GM genes, any single feature was ineffective at predicting SM from GM genes. Using machine learning methods to integrate all features, a prediction model was established with a true positive rate of 87% and a true negative rate of 71%. In addition, 86% of known SM genes not used to create the machine learning model were predicted. We also demonstrated that the model could be further improved when we distinguished between SM, GM, and junction genes responsible for reactions shared by SM and GM pathways, indicating that topological considerations may further improve the SM prediction model. Application of the prediction model led to the identification of 1,220 A. thaliana genes with previously unknown functions, each assigned a confidence measure called an SM score, providing a global estimate of SM gene content in a plant genome.

data integration↗
DOE OSTI2015

EVALUATING THE MORPHOLOGY OF THE LOCAL INTERSTELLAR MEDIUM: USING NEW DATA TO DISTINGUISH BETWEEN MULTIPLE DISCRETE CLOUDS AND A CONTINUOUS MEDIUM

Ultraviolet and optical spectra of interstellar gas along the lines of sight to nearby stars have been interpreted by Redfield and Linsky and previous studies as a set of discrete warm, partially ionized clouds each with a different flow vector, temperature, and metal depletion. Recently, Gry and Jenkins proposed a fundamentally different model consisting of a single cloud with nonrigid flows filling space out to 9 pc from the Sun that they propose better describes the local ISM. Here we test these fundamentally different morphological models against the spatially unbiased Malamut et al. spectroscopic data set, and find that the multiple cloud morphology model provides a better fit to both the new and old data sets. The detection of three or more velocity components along the lines of sight to many nearby stars, the presence of nearby scattering screens, the observed thin elongated structures of warm interstellar gas, and the likely presence of strong interstellar magnetic fields also support the multiple cloud model. The detection and identification of intercloud gas and the measurement of neutral hydrogen density in clouds beyond the Local Interstellar Cloud could provide future morphological tests.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The molecular architecture of the yeast spindle pole body core determined by Bayesian integrative modeling

Microtubule-organizing centers (MTOCs) form, anchor, and stabilize the polarized network of microtubules in a cell. The central MTOC is the centrosome that duplicates during the cell cycle and assembles a bipolar spindle during mitosis to capture and segregate sister chromatids. Yet, despite their importance in cell biology, the physical structure of MTOCs is poorly understood. Here we determine the molecular architecture of the core of the yeast spindle pole body (SPB) by Bayesian integrative structure modeling based on in vivo fluorescence resonance energy transfer (FRET), small-angle x-ray scattering (SAXS), x-ray crystallography, electron microscopy, and two-hybrid analysis. The model is validated by several methods that include a genetic analysis of the conserved PACT domain that recruits Spc110, a protein related to pericentrin, to the SPB. The model suggests that calmodulin can act as a protein cross-linker and Spc29 is an extended, flexible protein. The model led to the identification of a single, essential heptad in the coiled-coil of Spc110 and a minimal PACT domain. It also led to a proposed pathway for the integration of Spc110 into the SPB.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Highly boosted dielectron identification in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A new technique is developed to identify dielectrons (e$^+$e$^-$) with Lorentz boost $γ_\mathrm{L}$$\gt$ 20 that produce one single merged cluster in the electromagnetic calorimeter of the CMS detector. The identification uses two multivariate models: one for the case where both electron tracks are reconstructed, and another where only one of the tracks is reconstructed. The efficiency is determined using proton-proton collision data collected at a center-of-mass energy of 13 TeV. Boosted J/$ψ$ mesons decaying into e$^+$e$^-$ pairs are used to estimate the efficiency of the model with two tracks, yielding an overall efficiency of 80%. The Z $\to$ $μ^+μ^-γ$ events, where the photon converts into a collimated dielectron, are used for the model with a single track, yielding an efficiency of about 60%. A dedicated energy correction for dielectron candidates is also developed using B$^\pm$ $\to$ J/$ψ$K$^\pm$ $\to$ e$^+$e$^-$K$^\pm$ data.

Hayrapetyan, A. [Yerevan Phys. Inst.]↗
DOE OSTI2021

Geometric deep learning of RNA structure

RNA molecules adopt three-dimensional structures that are critical to their function and of interest in drug discovery. Few RNA structures are known, however, and predicting them computationally has proven challenging. We introduce a machine learning approach that enables identification of accurate structural models without assumptions about their defining characteristics, despite being trained with only 18 known RNA structures. The resulting scoring function, the Atomic Rotationally Equivariant Scorer (ARES), substantially outperforms previous methods and consistently produces the best results in community-wide blind RNA structure prediction challenges. By learning effectively even from a small amount of data, our approach overcomes a major limitation of standard deep neural networks. Because it uses only atomic coordinates as inputs and incorporates no RNA-specific information, this approach is applicable to diverse problems in structural biology, chemistry, materials science, and beyond.

Townshend, Raphael J. L.↗