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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

JuliaOceanWaves

SAND2023-05107O JuliaOceanWaves is a collection of packages and functions for modeling wave energy converters. The open-source software is designed to be used by the wave energy community to model new concepts, perform design optimization, and more. Capabilities include: • A representation of ocean wave spectra and input/output (e.g. read from National Oceanic and Atmospheric Administration buoys) and post-processing functionalities; • A solver for the linear potential flow radiation and diffraction equations for wave forcing on floating structures. • Solving the floating body linear dynamics in the frequency domain. Future additions to the software will include solving non-linear floating body dynamics in the time-domain through time-marching Ordinary Differential Equation solvers and the pseudo-spectral optimization method. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Michelen Strofer, Carlos↗
DOE OSTI2019

Physics-Informed Machine Learning with Application to Solid Oxide Fuel Cell System Modeling and Optimization

Traditional data-driven machine learning (ML) techniques were combined with the physics-based SOFC-MP model toward improving SOFC system-level performance prediction. Four different physics-informed ML methods were proposed to demonstrate better prediction accuracy compared with traditional ML methods. First, it was preferred that the existing Kriging-based surrogate model not be entirely abandoned, so errors between Kriging regression prediction and true solution are learned using ML. The goal was to find the pattern of the error distribution as a function of model input so discrepancies between the Kriging prediction and true solution could be reduced by adding the additional ML-trained error term to the existing prediction. Second, deep neural networks (DNN) coupled with the mass balance model (MBM) have been developed to significantly decrease the reduced order model (ROM) prediction error with fewer training data compared to the traditional Kriging-based ROM and traditional DNN regression approaches. Third, DNN regression coupled with a neural networks (NN) classifier and MBM was developed. It provides superior performance on classifying the physically operational conditions for natural gas fuel cell (NGFC) than traditional classification approaches. Finally, two kinds of DNN transferring were studied and tested. One was transferring DNN for low-fidelity model data to a high-fidelity model. The second one was transferring DNN from state-of-the-art NGFC to advanced NGFC. These physic-informed ML frameworks can serve as a solid foundation for estimating U.S. Department of Energy-targeted fuel cell performance and exhibit great potential to be employed to other engineering applications.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS1974

A Monte Carlo investigation of experimental data requirements for fitting polynomial functions

This report examines the extent to which sample size affects the accuracy of a low order polynomial approximation of an experimentally observed quantity and establishes a trend toward improvement in the accuracy of the approximation as a function of sample size. The task is made possible through a simulated analysis carried out by the Monte Carlo method, in which data are generated by using several transcendental or algebraic functions as models. Contaminated data of varying amounts are fitted to linear quadratic or cubic polynomials, and the behavior of the mean-squared error of the residual variance is determined as a function of sample size. Results indicate that the effect of the size of the sample is significant only for relatively small sample sizes and diminishes drastically for moderate and large amounts of experimental data.

Canavos, G. C.↗
NASA NTRS1974

An empirical analysis of the quantitative effect of data when fitting quadratic and cubic polynomials

A study is made of the extent to which the size of the sample affects the accuracy of a quadratic or a cubic polynomial approximation of an experimentally observed quantity, and the trend with regard to improvement in the accuracy of the approximation as a function of sample size is established. The task is made possible through a simulated analysis carried out by the Monte Carlo method in which data are simulated by using several transcendental or algebraic functions as models. Contaminated data of varying amounts are fitted to either quadratic or cubic polynomials, and the behavior of the mean-squared error of the residual variance is determined as a function of sample size. Results indicate that the effect of the size of the sample is significant only for relatively small sizes and diminishes drastically for moderate and large amounts of experimental data.

Canavos, G. C.↗
NASA NTRS1990

Application of structured analysis to a telerobotic system

The analysis and evaluation of a multiple arm telerobotic research and demonstration system developed by the NASA Intelligent Systems Research Laboratory (ISRL) is described. Structured analysis techniques were used to develop a detailed requirements model of an existing telerobotic testbed. Performance models generated during this process were used to further evaluate the total system. A commercial CASE tool called Teamwork was used to carry out the structured analysis and development of the functional requirements model. A structured analysis and design process using the ISRL telerobotic system as a model is described. Evaluation of this system focused on the identification of bottlenecks in this implementation. The results demonstrate that the use of structured methods and analysis tools can give useful performance information early in a design cycle. This information can be used to ensure that the proposed system meets its design requirements before it is built.

Dashman, Eric↗
NASA NTRS2005

Health Management Applications for International Space Station

Traditional mission and vehicle management involves teams of highly trained specialists monitoring vehicle status and crew activities, responding rapidly to any anomalies encountered during operations. These teams work from the Mission Control Center and have access to engineering support teams with specialized expertise in International Space Station (ISS) subsystems. Integrated System Health Management (ISHM) applications can significantly augment these capabilities by providing enhanced monitoring, prognostic and diagnostic tools for critical decision support and mission management. The Intelligent Systems Division of NASA Ames Research Center is developing many prototype applications using model-based reasoning, data mining and simulation, working with Mission Control through the ISHM Testbed and Prototypes Project. This paper will briefly describe information technology that supports current mission management practice, and will extend this to a vision for future mission control workflow incorporating new ISHM applications. It will describe ISHM applications currently under development at NASA and will define technical approaches for implementing our vision of future human exploration mission management incorporating artificial intelligence and distributed web service architectures using specific examples. Several prototypes are under development, each highlighting a different computational approach. The ISStrider application allows in-depth analysis of Caution and Warning (C&W) events by correlating real-time telemetry with the logical fault trees used to define off-nominal events. The application uses live telemetry data and the Livingstone diagnostic inference engine to display the specific parameters and fault trees that generated the C&W event, allowing a flight controller to identify the root cause of the event from thousands of possibilities by simply navigating animated fault tree models on their workstation. SimStation models the functional power flow for the ISS Electrical Power System and can predict power balance for nominal and off-nominal conditions. SimStation uses realtime telemetry data to keep detailed computational physics models synchronized with actual ISS power system state. In the event of failure, the application can then rapidly diagnose root cause, predict future resource levels and even correlate technical documents relevant to the specific failure. These advanced computational models will allow better insight and more precise control of ISS subsystems, increasing safety margins by speeding up anomaly resolution and reducing,engineering team effort and cost. This technology will make operating ISS more efficient and is directly applicable to next-generation exploration missions and Crew Exploration Vehicles.

Alena, Richard↗
NASA NTRS2017

Model Validation for Propulsion - On the TFNS and LES Subgrid Models for a Bluff Body Stabilized Flame

With advances in computational power and availability of distributed computers, the use of even the most complex of turbulent chemical interaction models in combustors and coupled analysis of combustors and turbines is now possible and more and more affordable for realistic geometries. Recent more stringent emission standards have enticed the development of more fuel-efficient and low-emission combustion system for aircraft gas turbine applications. It is known that the NOx emissions tend to increase dramatically with increasing flame temperature. It is well known that the major difficulty, when modeling the turbulence-chemistry interaction, lies in the high non-linearity of the reaction rate expressed in terms of the temperature and species mass fractions. The transport filtered density function (FDF) model and the linear eddy model (LEM), which both use local instantaneous values of the temperature and mass fractions, have been shown to often provide more accurate results of turbulent combustion. In the present, the time-filtered Navier-Stokes (TFNS) approach capable of capturing unsteady flow structures important for turbulent mixing in the combustion chamber and two different subgrid models, LEM-like and EUPDF-like, capable of emulating the major processes occurring in the turbulence-chemistry interaction will be used to perform reacting flow simulations of a selected test case. The selected test case from the Volvo Validation Rig was documented by Sjunnesson.

bluff body↗
DOE OSTI2013

A PHYSICAL MODEL FOR THE 0 {approx}< z {approx}< 8 REDSHIFT EVOLUTION OF THE GALAXY ULTRAVIOLET LUMINOSITY AND STELLAR MASS FUNCTIONS

We present a model to understand the redshift evolution of the UV luminosity and stellar mass functions of Lyman break galaxies. Our approach is based on the assumption that the luminosity and stellar mass of a galaxy is related to its dark-matter (DM) halo assembly and gas infall rate. Specifically, galaxies experience a burst of star formation at the halo assembly time, followed by a constant star formation rate, representing a secular star formation activity sustained by steady gas accretion. Star formation from steady gas accretion is the dominant contribution to the galaxy UV luminosity at all redshifts. The model is calibrated by constructing a galaxy luminosity versus halo mass relation at z = 4 via abundance matching. After this luminosity calibration, the model naturally fits the z = 4 stellar mass function, and correctly predicts the evolution of both luminosity and stellar mass functions from z = 0 to z = 8. While the details of star formation efficiency and feedback are hidden within our calibrated luminosity versus halo mass relation, our study highlights that the primary driver of galaxy evolution across cosmic time is the buildup of DM halos, without the need to invoke a redshift-dependent efficiency in converting gas into stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Alkylation of monomeric, dimeric, and polymeric lignin models through carbon-hydrogen activation using Ru-catalyzed Murai reaction

In this study, we have assessed directed carbon-hydrogen activation (CHA) for alkylation of monomeric, dimeric, and polymeric lignin models using Murai's catalyst [RuH 2 (CO)(PPh 3 ) 3 ]. Based on related work from our laboratory showing that isolated organosolv lignin bears benzylic directing groups ideal for CHA reactions, this approach could offer new methodology for the valorization of biorefinery lignin. Monomeric and dimeric models bearing a keto group at the benzylic position undergo Ru-catalyzed alkylation in good to excellent yield. Similarly, models bearing a benzylic OH group also undergo alkylation via a tandem oxidation/alkylation process enabled by the Ru catalyst. Polymeric models show low levels of functionalization as a result of the poor solubility of the starting polymer. With unsymmetrical models, functionalization occurs first at the least sterically hindered ortho-site, but a subsequent alkylation, leading to disubstituted products can occur at the more sterically hindered site, leading to hexasubstituted arenes. The reaction shows sensitivity to free phenolic OH groups, which appears to reduce the yield in some reactions, and is also a contributing factor to the low yields observed with polymeric lignin models. Finally, combining CHA methodology with lignin isolation technology able to introduce appropriate directing groups for catalytic functionalization will form the basis for improved conversion of lignin to high value chemical products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Ultrafast dynamics of the dielectric functions of ZnO and BaTiO{sub 3} thin films after intense femtosecond laser excitation

The ultrafast carrier dynamics of epitaxial ZnO and BaTiO{sub 3} thin films after intense excitation at 3.10 eV and 4.66 eV photon energy has been studied by femtosecond absorption spectroscopy. Modelling the transient transmission changes on the basis of spectroscopic ellipsometry data and pertinent equilibrium model dielectric functions extended by additional terms for the effects at high carrier density (P-band luminescence and stimulated emission from electron-hole-plasma), a self-consistent parameterized description was obtained for both materials. Excited carrier lifetimes in the range of ≈2 to ≈60 ps and long-lived thermal effects after several hundred ps have been identified in both materials. These findings form a reliable basis to quantitatively describe future femtosecond studies on ZnO/BaTiO{sub 3} heterolayer systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

The Partition Function of the Four-Vertex Model in a Special External Field

The exactly solvable four-vertex model on a square grid with the fixed boundary conditions in a presence of a special external field is considered. Namely, we study a system in a linear field acting on the central column of the grid. The partition function of the model is calculated by the quantum inverse scattering method. The answer is written in determinantal form.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

FROM DUST TO PLANETESIMALS: AN IMPROVED MODEL FOR COLLISIONAL GROWTH IN PROTOPLANETARY DISKS

Planet formation occurs within the gas- and dust-rich environments of protoplanetary disks. Observations of these objects show that the growth of primordial submicron-sized particles into larger aggregates occurs at the earliest evolutionary stages of the disks. However, theoretical models of particle growth that use the Smoluchowski equation to describe collisional coagulation and fragmentation have so far failed to produce large particles while maintaining a significant population of small grains. This has generally been attributed to the existence of two barriers impeding growth due to bouncing and fragmentation of colliding particles. In this paper, we demonstrate that the importance of these barriers has been artificially inflated through the use of simplified models that do not take into account the stochastic nature of the particle motions within the gas disk. We present a new approach in which the relative velocities between two particles are described by a probability distribution function that models both deterministic motion (from the vertical settling, radial drift, and azimuthal drift) and stochastic motion (from Brownian motion and turbulence). Taking both into account can give quite different results to what has been considered recently in other studies. We demonstrate the vital effect of two 'ingredients' for particle growth: the proper implementation of a velocity distribution function that overcomes the bouncing barrier and, in combination with mass transfer in high-mass-ratio collisions, boosts the growth of larger particles beyond the fragmentation barrier. A robust result of our simulations is the emergence of two particle populations (small and large), potentially explaining simultaneously a number of longstanding problems in protoplanetary disks, including planetesimal formation close to the central star, the presence of millimeter- to centimeter-sized particles far out in the disk, and the persistence of {mu}m-sized grains for millions of years.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Finding Liebig’s law of the minimum

Abstract Liebig’s law of the minimum (LLM) is often used to interpret empirical biological growth data and model multiple substrates co‐limited growth. However, its mechanistic foundation is rarely discussed, even though its validity has been questioned since its introduction in the 1820s. Here we first show that LLM is a crude approximation of the law of mass action, the state of art theory of biochemical reactions, and the LLM model is less accurate than two other approximations of the law of mass action: the synthesizing unit model and the additive model. We corroborate this conclusion using empirical data sets of algae and plants grown under two co‐limiting substrates. Based on our analysis, we show that when growth is modeled directly as a function of substrate uptake, the LLM model improperly restricts the organism to be of fixed elemental stoichiometry, making it incapable of consistently resolving biological adaptation, ecological evolution, and community assembly. When growth is modeled as a function of the cellular nutrient quota, the LLM model may obtain good results at the risk of incorrect model parameters as compared to those inferred from the more accurate synthesizing unit model. However, biogeochemical models that implement these three formulations are needed to evaluate which formulation is acceptably accurate and their impacts on predicted long‐term ecosystem dynamics. In particular, studies are needed that explore the extent to which parameter calibration can rescue model performance when the mechanistic representation of a biogeochemical process is known to be deficient.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Atomistic modeling of energy band alignment in CdTe(1 0 0) and CdTe(1 1 1) surfaces

An atomic-scale perspective of energy band alignment in CdTe surfaces has not been spatially studied despite the major role surfaces play in forming interfaces within CdTe-based thin film photovoltaic devices. Atomistic modeling based on density functional theory coupled with surface Green’s function is used for calculating energy band alignment of CdTe surfaces. The CdTe(1 0 0) ((1×1) and c(2×2) reconstruction) and CdTe(1 1 1) ((1×1) and (2×2) reconstruction) facets without and with surface relaxation provide insightful band bending characteristics that influence charge carrier transport. Results show that unrelaxed (1×1) CdTe(1 0 0) and CdTe(1 1 1) surfaces bend the valence band downward with surface polarity dictating the surface potential magnitude. The reconstructed CdTe(1 0 0) c(2×2) and CdTe(1 1 1) (2×2) surfaces result in favorable surface electronic features in relation to their unreconstructed variants. In addition, the structurally relaxed CdTe(1 1 1) surfaces develop an internal energy cusp potential that may enhance hole charge transport toward the back of CdTe solar cell devices. In conclusion, energy band alignments calculated within the study lead to a detailed understanding of how CdTe surfaces may affect CdTe-based thin film photovoltaic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Learning Optimal Power Flow Solutions using Linearized Models in Power Distribution Systems

Solving nonlinear optimal power flow (OPF) problem is computationally expensive, and poses scalability challenges for power distribution networks. An alternative to solving the original nonlinear OPF is the linear approximated OPF models. Although, these linear approximated OPF models are fast, the resulting solutions may result in significant optimality gap. Lately, the application of machine learning (ML) methods in successfully solving the nonlinear OPF has been reported. These methods learn and estimate the nonlinear control policies using a purely data-driven approach. In this paper, we propose an approach to complements the ML based approach to solving OPF using solutions from known linearized OPF model. Specifically, we use supervised learning to map the solutions of linear OPF to nonlinear control variables. Unlike, the traditional ML based methods for OPF that approximate the full distribution feeder model using function approximation, our approach uses a two-node approximation of radial networks. The proposed approach is validated using IEEE 123 bus test system for OPF solutions obtained using the nonlinear OPF models.

optimal power flow, power distribution systems, su↗
NASA NTRS2004

A New Approach to Using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Recently Grabowski and Khairoutdinov and Randall have proposed and demonstrated, the feasibility of using 2D CRMs (these did not include detailed land processes and used periodic lateral boundary conditions) as 'super-parameterizations or a multi-scale modeling framework MMF' for cloud processes within atmospheric generation circulation models (GCMs). In the MMF, a fine-resolution 2D CRM takes the place of the single-column parameterization that is used in conventional GCMs. An overview of this approach is given by Randall et al.. Since a CRM can explicitly simulate cloud processes at the natural space and time scales of clouddynamical processes, it's possible to compute statistics of cloud fields, including radiances and radar backscatters, directly simulated/produced by the CRM. A seed fund is available at NASA Goddard to build a MMF based on a 2D GCE model and the Goddard fvGCM. A prototype MMF will be developed at end of 2004. The major objectives are to test and evaluate its performance using the GCE model as the super parameterization and compare its results with other super parameterizations, conventional GCMs and observations. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (WE) model. The GCE model is a CRM and it has been improved and applied to study the precipitation processes in the past two decades. Atmospheric aerosols are also described using number density size-distribution functions. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low 'clean' concentration and a high 'dirty' concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated. In addition, the similarities and differences between bulk- and spectral-bin microphysics will be presented,

Tao, Wei-Kuo↗
DOE OSTI2011

Electrostatic waves in superthermal dusty plasmas: review of recent advancement

Real plasmas are often caracterized by the presence of excess energetic particle populations, resulting in a long-tailed non-Maxwellian distribution. In Space plasma physics, this phenomenon is usually modelled via a kappa-type distribution. This presentation is dedicated to an investigation, from first principles, of the effect of superthermality on the characteristics of dusty plasma modes. We employ a kappa distribution function to model the superthermality of the background components (electrons and/or ions). Background superthermality is shown to modify the charge screening mechanism in dusty plasmas, thus affecting the linear dispersion laws of both low-and higher frequency DP modes substantially. Various experimentally observed effects may thus be interpreted as manifestations of superthermality. Focusing on the features of nonlinear excitations (solitons) as they occur in different dusty plasma modes, we investigate the role of superthermality in their propagation dynamics (existence laws, stability profile) and characteristics (geometry).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2010

K{sup -} absorption at rest in nuclei followed by p{Lambda} emission

p{Lambda} emission in coincidence following K{sup -} absorption at rest in nuclei is studied using quantum-mechanical scattering theory and nuclear wave functions. K{sup -} absorption is assumed to occur on two protons in the nucleus. In the formalism, emphasis is put on the study of the final state interaction (FSI) effects of p and {Lambda} with the recoiling nucleus. We include elastic scattering and single-nucleon knock-out (KO) channels in the FSI. Calculations are presented for the {sup 12}C nucleus, using shell-model wave functions, and without any extra mass modification of the K{sup -}pp system in the nucleus. Calculated results are presented for the angular correlation distribution between p and {Lambda}, their invariant mass distribution, and the momentum spectra of p and {Lambda}. These results are compared with the corresponding experimental measurements of M. Agnello et al., [Phys. Rev. Lett. 94, 212303 (2005)]. With only elastic scattering FSI included, the angular correlation distribution and the momentum spectra are found to be in good accord with the corresponding measurements. With full FSI, the calculated p{Lambda} invariant mass distribution is found to have two peaks, one corresponding to the elastic scattering FSI and another to single-nucleon KO FSI. The KO peak agrees fully, in position and shape, with the peak observed by M. Agnello et al. The peak corresponding to elastic scattering FSI does not seem to exist in the measured distribution. Considering that such a two-peak structure is always seen in the inclusive (p,p{sup '}) and (e,e{sup '}) reactions in nuclei at intermediate energies, absence of the elastic scattering peak in the p{Lambda} reaction is intriguing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗