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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Rate Dependent Deformation and Strength Analysis of Polymer Matrix Composites

A research program is being undertaken to develop rate dependent deformation and failure models for the analysis of polymer matrix composite materials. In previous work in this program, strain-rate dependent inelastic constitutive equations used to analyze polymers have been implemented into a mechanics of materials based composite micromechanics method. In the current work, modifications to the micromechanics model have been implemented to improve the calculation of the effective inelastic strain. Additionally, modifications to the polymer constitutive model are discussed in which pressure dependence is incorporated into the equations in order to improve the calculation of constituent and composite shear stresses. The Hashin failure criterion is implemented into the analysis method to allow for the calculation of ply level failure stresses. The deformation response and failure stresses for two representative uniaxial polymer matrix composites, IM7/977-2 and AS4-PEEK, are predicted for varying strain rates and fiber orientations. The predicted results compare favorably to experimentally obtained values.

Goldberg, Robert K.↗
DOE OSTI2026

Performing Numerical Analysis of Cybersecurity Options Using Dynamic Risk Analysis Tool EMRALD

Cyberattacks can have many different attack paths, durations, and goals. There are also many different mitigation options involving hardware, software, and/or humans. Considering a cyber threat should involve defense-in-depth methods and a quantitative or numerical evaluation of overall effectiveness against dynamic, time-dependent attacks to make cost and risk-informed decisions. Typical cyberattack modeling methods only provide a qualitative evaluation. The main areas of cybersecurity are confidentiality, integrity, and availability. For companies with cyber-physical systems such as advanced nuclear reactors, cyber-related safety is a requirement set by North American Electric Reliability and the U.S. Nuclear Regulatory Commission. They are also concerned about availability or reliability as a business case. As cyber threats are evolving to a business-for-hire structure, more attacks may focus on disrupting business success and reliability, causing financial and economic stability risk. Companies want to know business reliability and recovery from those threats, and that requires modeling physical behavior of the targets. Dynamic-state-based and Markov-based modeling provides a method for better cyber scenario modeling with different tools having issues such as state-base explosion. Dynamic modeling enables time and conditional features not found in other numerical evaluation methods. EMRALD (Event Modeling Risk Assessment using Lined Diagrams) is a dynamic risk analysis modeling and simulation tool and has features that reduce modeling issues. It has been used to model different time-dependent events including plant behavior and operator procedures. As a general modeling tool, EMRALD can also be used to model cyberattack scenarios with varying mitigation options and quantify effectiveness, producing numerical data for risk-informed decisions. This paper uses EMRALD to demonstrate that dynamic numerical risk analysis can be used for cyber threat modeling to provide insights for design decision-making and optimize defense strategies. Keywords: cyber modeling; cyber-physical systems; numerical cyber modeling

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Comparative Multi-System Approach to Characterizing Bioactivity of Commonly Occurring Chemicals

A 2019 retrospective study analyzed wristband personal samplers from fourteen different communities across three different continents for over 1530 organic chemicals. Investigators identified fourteen chemicals (G14) detected in over 50% of personal samplers. The G14 represent a group of chemicals that individuals are commonly exposed to, and are mainly associated with consumer products including plasticizers, fragrances, flame retardants, and pesticides. The high frequency of exposure to these chemicals raises questions of their potential adverse human health effects. Additionally, the possibility of exposure to mixtures of these chemicals is likely due to their co-occurrence; thus, the potential for mixtures to induce differential bioactivity warrants further investigation. This study describes a novel approach to broadly evaluate the hazards of personal chemical exposures by coupling data from personal sampling devices with high-throughput bioactivity screenings using in vitro and non-mammalian in vivo models. To account for species and sensitivity differences, screening was conducted using primary normal human bronchial epithelial (NHBE) cells and early life-stage zebrafish. Mixtures of the G14 and most potent G14 chemicals were created to assess potential mixture effects. Chemical bioactivity was dependent on the model system, with five and eleven chemicals deemed bioactive in NHBE and zebrafish, respectively, supporting the use of a multi-system approach for bioactivity testing and highlighting sensitivity differences between the models. In both NHBE and zebrafish, mixture effects were observed when screening mixtures of the most potent chemicals. Observations of BMC-based mixtures in NHBE (NHBE BMC Mix) and zebrafish (ZF BMC Mix) suggested antagonistic effects. In this study, consumer product-related chemicals were prioritized for bioactivity screening using personal exposure data. High-throughput high-content screening was utilized to assess the chemical bioactivity and mixture effects of the most potent chemicals.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1982

Integrated and spectral energetics studies of the GLAS general circulation model

Integrated and spectral energetics of the Goddard Laboratory for Atmospheric Sciences (GLAS) general circulation model are compared with observations and examined when subdivided beyond hemispheric integrals. In the monthly mean zonal averages, qualitative improvements are found over previous versions of the model in eddy kinetic energy and barotropic conversions although vertical shear above the subtropical jet remains weak. This paper traces this problem to the erroneous growth of kinetic energy above strong jets, shows that this difficulty is common to all orographic general circulation models, and suggests that this problem has significant effects on upper-level long-wave predictability. In particular, it is considered whether hemispherically integrated kinetic energy or low-wavenumber spectral coefficients retain any skill as the predictability limit. In the time-dependent comparisons, the model shows significant skill in predicting the hemispherically integrated eddy kinetic energy out to two weeks for one of two cases.

Tenenbaum, J.↗
NASA NTRS1972

A model to predict the degradation of a SiGe thermopile.

Discussion of the various phenomena which affect the available output power of a typical radioisotope thermoelectric generator (RTG), including estimates of the magnitude of these effects. Power degradation, as well as the corresponding changes in operating temperature, are calculated by means of a computer code which systematically accounts for the time- and temperature-dependent variables. A model for predicting available output power of an RTG is developed which includes changes in performance due to fuel decay, alteration of bulk thermoelectric properties, changes in electrode contacts, geometry changes due to material sublimation, and degradation of the thermal insulation.

Stapfer, G.↗
DOE OSTI2024

Implementing Ordinary Differential Equation Solvers in Rust Programming Language for Modeling Vehicle Powertrain Systems: Preprint

Efficient and accurate ordinary differential equation (ODE) solvers are necessary for powertrain and vehicle dynamics modeling. However, current commercial ODE solvers can be financially prohibitive, leading to a need for accessible, effective, open-source ODE solvers designed for powertrain modeling. Rust is a compiled programming language that has the potential to be used for fast and easy-to-use powertrain models, given its exceptional computational performance, robust package ecosystem, and short time required for modelers to become proficient. However, of the three commonly used (>3,000 downloads) packages in Rust with ODE solver capabilities, only one has more than four numerical methods implemented, and none are designed specifically for modeling physical systems. Therefore, the goal of the Differential Equation System Solver (DESS) was to implement accurate ODE solvers in Rust designed for the component-based problems often seen in powertrain modeling. DESS is a text-based software package that provides a flexible framework for building and solving systems of ODEs. This allows DESS to be included as a dependency for automotive powertrain models that require a variety of solvers and solver configurations. Seven explicit ODE solver methods have been implemented in DESS: Euler’s, Heun’s, midpoint, Ralston’s, classic Runge-Kutta, Bogacki-Shampine, and Cash-Karp. These represent five fixed-step methods and two adaptive-step methods. This paper shows that the solver implementations increase accuracy and computational efficiency compared to Euler's method when modeling a system of three thermal masses in Rust. DESS also includes features designed for modeling component-based physical systems. Users can define relationships between nodes in their system, which the package then translates into a system of equations, leading to simpler and more intuitive code. In the case of a three-thermal-mass system, the user can specify node thermal properties (e.g., thermal capacitance), how nodes are interconnected, and thermal conductance between nodes rather than providing a system of equations. The core contribution from this work is an open-source, text-based Rust package with ODE solvers for automotive powertrain modeling to support cost-free, fast, and accurate simulation.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Primordial black hole formation by vacuum bubbles. Part II

The discoveries of LIGO/Virgo black holes in recent years have revitalized the study of primordial black holes. In this work we investigate a mechanism where primordial black holes are formed by vacuum bubbles that randomly nucleate during inflation through quantum tunneling. After inflation, these bubbles typically run into the ambient radiation fluid with a large Lorentz factor. In our previous work, we assumed the bubble fields are strongly coupled to the standard model particles so that the bubble wall is impermeable. Here we complete this picture by considering bubbles interacting with the fluid only through gravity. By studying the scenario in several limits, we found that black holes could form in the either subcritical or supercritical regime. Depending on the model parameters, the resulting mass spectrum of the black holes could be wide or narrow, and may develop two peaks separated by a large mass range. Finally, with different spectra, these black holes may account for the LIGO/Virgo black holes, supermassive black holes, and may play an important role in dark matter.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2006

Experimental and Computational Analysis of Unidirectional Flow Through Stirling Engine Heater Head

A high efficiency Stirling Radioisotope Generator (SRG) is being developed for possible use in long-duration space science missions. NASA s advanced technology goals for next generation Stirling convertors include increasing the Carnot efficiency and percent of Carnot efficiency. To help achieve these goals, a multi-dimensional Computational Fluid Dynamics (CFD) code is being developed to numerically model unsteady fluid flow and heat transfer phenomena of the oscillating working gas inside Stirling convertors. In the absence of transient pressure drop data for the zero mean oscillating multi-dimensional flows present in the Technology Demonstration Convertors on test at NASA Glenn Research Center, unidirectional flow pressure drop test data is used to compare against 2D and 3D computational solutions. This study focuses on tracking pressure drop and mass flow rate data for unidirectional flow though a Stirling heater head using a commercial CFD code (CFD-ACE). The commercial CFD code uses a porous-media model which is dependent on permeability and the inertial coefficient present in the linear and nonlinear terms of the Darcy-Forchheimer equation. Permeability and inertial coefficient were calculated from unidirectional flow test data. CFD simulations of the unidirectional flow test were validated using the porous-media model input parameters which increased simulation accuracy by 14 percent on average.

Wilson, Scott D.↗
NASA NTRS1997

Model For Dense Molecular Cloud Cores

We present a detailed theoretical model for the thermal balance, chemistry, and radiative transfer within quiescent dense molecular cloud cores that contain a central protostar. In the interior of such cores, we expect the dust and gas temperatures to be well coupled, while in the outer regions CO rotational emissions dominate the gas cooling and the predicted gas temperature lies significantly below the dust temperature. Large spatial variations in the gas temperature are expected to affect the gas phase chemistry dramatically; in particular, the predicted water abundance varies by more than a factor of 1000 within cloud cores that contain luminous protostars. Based upon our predictions for the thermal and chemical structure of cloud cores, we have constructed self-consistent radiative transfer models to compute the line strengths and line profiles for transitions of (12)CO, (13)CO, C(18)O, ortho- and para-H2(16)O, ortho- and para-H2(18)O, and O I. We carried out a general parameter study to determine the dependence of the model predictions upon the parameters assumed for the source. We expect many of the far-infrared and submillimeter rotational transitions of water to be detectable either in emission or absorption with the use of the Infrared Space Observatory (ISO) and the Submillimeter Wave Astronomy Satellite. Quiescent, radiatively heated hot cores are expected to show low-gain maser emission in the 183 GHz 3(sub 13)-2(sub 20) water line, such as has been observed toward several hot core regions using ground-based telescopes. We predict the (3)P(sub l) - (3)P(sub 2) fine-structure transition of atomic oxygen near 63 micron to be in strong absorption against the continuum for many sources. Our model can also account successfully for recent ISO observations of absorption in rovibrational transitions of water toward the source AFGL 2591.

Doty, Steven D.↗
NASA NTRS2012

Kinetic Description of Ionospheric Outflows Based on the Exact Form of Fokker-Planck Collision Operator: Electrons

We present the results of a finite difference implementation of the kinetic Fokker-Planck model with an exact form of the nonlinear collisional operator, The model is time dependent and three-dimensional; one spatial dimension and two in velocity space. The spatial dimension is aligned with the local magnetic field, and the velocity space is defined by the magnitude of the velocity and the cosine of pitch angle. An important new feature of model, the concept of integration along the particle trajectories, is discussed in detail. Integration along the trajectories combined with the operator time splitting technique results in a solution scheme which accurately accounts for both the fast convection of the particles along the magnetic field lines and relatively slow collisional process. We present several tests of the model's performance and also discuss simulation results of the evolution of the plasma distribution for realistic conditions in Earth's plasmasphere under different scenarios.

Khazanov, George V.↗
NASA NTRS2014

Model-Based Estimation of Sampling-Caused Uncertainty in Aerosol Remote Sensing for Climate Research Applications

To evaluate the effect of sampling frequency on the global monthly mean aerosol optical thickness (AOT), we use 6 years of geographical coordinates of Moderate Resolution Imaging Spectroradiometer (MODIS) L2 aerosol data, daily global aerosol fields generated by the Goddard Institute for Space Studies General Circulation Model and the chemical transport models Global Ozone Chemistry Aerosol Radiation and Transport, Spectral Radiationtransport Model for Aerosol Species and Transport Model 5, at a spatial resolution between 1.125 deg × 1.125 deg and 2 deg × 3◦: the analysis is restricted to 60 deg S-60 deg N geographical latitude. We found that, in general, the MODIS coverage causes an underestimate of the global mean AOT over the ocean. The long-term mean absolute monthly difference between all and dark target (DT) pixels was 0.01-0.02 over the ocean and 0.03-0.09 over the land, depending on the model dataset. Negative DT biases peak during boreal summers, reaching 0.07-0.12 (30-45% of the global long-term mean AOT). Addition of the Deep Blue pixels tempers the seasonal dependence of the DT biases and reduces the mean AOT difference over land by 0.01-0.02. These results provide a quantitative measure of the effect the pixel exclusion due to cloud contamination, ocean sun-glint and land type has on the MODIS estimates of the global monthly mean AOT. We also simulate global monthly mean AOT estimates from measurements provided by pixel-wide along-track instruments such as the Aerosol Polarimetry Sensor and the Cloud-Aerosol LiDAR with Orthogonal Polarization. We estimate the probable range of the global AOT standard error for an along-track sensor to be 0.0005-0.0015 (ocean) and 0.0029-0.01 (land) or 0.5-1.2% and 1.1-4% of the corresponding global means. These estimates represent errors due to sampling only and do not include potential retrieval errors. They are smaller than or comparable to the published estimate of 0.01 as being a climatologically significant change in the global mean AOT, suggesting that sampling density is unlikely to limit the use of such instruments for climate applications at least on a global, monthly scale.

long-term variability↗
NASA NTRS1991

An improved k-epsilon model for near wall turbulence

An improved k-epsilon model for low Reynolds number turbulence near a wall is presented. In the first part of this work, the near-wall asymptotic behavior of the eddy viscosity and the pressure transport term in the turbulent kinetic energy equation are analyzed. Based on these analyses, a modified eddy viscosity model with the correct near-wall behavior is suggested, and a model for the pressure transport term in the k-equation is proposed. In addition, a modeled dissipation rate equation is reformulated, and a boundary condition for the dissipation rate is suggested. In the second part of the work, one of the deficiencies of the existing k-epsilon models, namely, the wall distance dependency of the equations and the damping functions, is examined. An improved model that does not depend on any wall distance is introduced. Fully developed turbulent channel flows and turbulent boundary layers over a flat plate are studied as validations for the proposed new models. Numerical results obtained from the present and other previous k-epsilon models are compared with data from direct numerical simulation. The results show that the present k-epsilon model, with added robustness, performs as well as or better than other existing models in predicting the behavior of near-wall turbulence.

Shih, T. H.↗
NASA NTRS2015

MHD Model Results of Solar Wind Plasma Interaction with Mars and Comparison with MAVEN Observations

The crustal remnant field on Mars rotates constantly with the planet, varying the magnetic field configuration interacting with the solar wind. It has been found that ion loss rates slowly vary with the subsolar longitude, anticorrelating with the intensity of the dayside crustal field source, with some time delay, using a time-dependent multispecies MHD model. In this study, we investigate in detail how plasma properties are influenced locally by the crustal field and its rotation. Model results will be compared in detail with plasma observations from MAVEN.

Crustal↗
DOE OSTI2021

Active learning strategy for high fidelity short-term data-driven building energy forecasting

The quality of a data-driven model is heavily dependent on the quality of data. Data from building operation often have data bias problems, which means that the data sample is collected in a way that some members of the intended data population are less likely to be included than others. Data-driven energy forecasting models built on such data hence are biased and could lead to large forecasting errors. Active learning—an effective method to defying data bias—is rarely studied or applied in the area of data-driven building energy forecasting modeling. This paper attempts to fill this gap and explores the application of active learning in data-driven building energy forecasting. The developed strategy in this paper efficiently generate informative training data within a time budget and uses block design to passively consider weather disturbances. The developed active learning strategy is applied and evaluated in both virtual and real-building testbeds against traditional data-driven methods. Via these virtual and real-building evaluation cases, we have demonstrated that the data bias problem typically exists in building operation data is resolved by applying the developed active learning strategy. Furthermore, building energy forecasting models trained from data generated from the active learning strategy have shown improved performances in both model accuracy and model extendibility perspectives. The effectiveness of the block design module is also validated to effectively consider the impact of weather conditions on active learning design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1986

Imaging radar polarimetry from wave synthesis

It was shown that it is possible to measure the complete scattering matrix of an object using data acquired on a single aircraft pass, and can combine the signals later in the data processor to generate radar images corresponding to any desired combination of transmit and receive polarization. Various scattering models predict different dependence on polarization state of received power from an object. The imaging polarimeter permits determination of this dependence, which is called the polarization signature, of each point in a radar image. Comparison of the theoretical predictions and observational data yield identification of possible scattering mechanisms for each area of interest. It was found that backscatter from the ocean is highly polarized and well-modeled by Bragg scattering, while scattering from trees in a city park possesses a considerable unpolarized component. Urban regions exhibit the characteristics expected from dihedral corner reflectors and their polarization signatures are quite different from the one-bounce Bragg model.

Zebker, Howard A.↗
NASA NTRS1991

Model and observation comparison of the universal time and IMF by dependence of the ionospheric polar hole

The polar ionospheric F-region often exhibits regions of marked density depletion. These depletions have been observed by a variety of polar orbiting ionospheric satellites over a full range of solar cycle, season, magnetic activity, and universal time (UT). An empirical model of these observations has recently been developed to describe the polar depletion dependence on these parameters. Specifically, the dependence has been defined as a function of F10.7 (solar), summer or winter, Kp (magnetic), and UT. Polar cap depletions have also been predicted /1, 2/ and are, hence, present in physical models of the high latitude ionosphere. Using the Utah State University Time Dependent Ionospheric Model (TDIM) the predicted polar depletion characteristics are compared with those described by the above empirical model. In addition, the TDIM is used to predict the IMF By dependence of the polar hole feature.

Sojka, J. J.↗
NASA NTRSDate not supplied

Measurements and Computations of the Turbulent Corner Flow on the NASA Juncture-Flow Model with a Symmetric Wing

The NASA Juncture Flow experiment is designed to acquire high-quality flowfield data deep in the corner of a wing-fuselage junction specifically for the purpose of computational fluid dynamics (CFD) validation and turbulence model improvement. This paper presents and discusses the results of a recent experiment with the juncture-flow model in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The main objective of the test was to expand the existing juncture-flow dataset with a symmetric wing case that displays fully attached, incipient separation, and separated flow in the corner of the wing-fuselage junction, depending on the model angle of incidence. Laser Doppler velocimetry (LDV) measurements were made at three model angles of incidence (0 deg: fully attached, 1 deg: incipient separation, and 5 deg: separated flow) and for each one, mean-flow and Reynolds-stress data were obtained on the fuselage and at several streamwise locations along the corner of the wing-fuselage junction. Supporting measurements were made during the test campaign and included model and tunnel wall static pressures, tunnel wall and ceiling boundary-layer rake data, oil-flow visualizations, and laser-based measurements of the as-built model geometry and model position in the test section. Comparisons between the experimental data on the test article and Reynolds-averaged Navier-Stokes CFD results are presented and discussed.

Juncture Flow↗
NASA NTRS2023

Measurements and Computations of the Turbulent Corner Flow on the NASA Juncture-Flow Model with a Symmetric Wing

The NASA Juncture Flow experiment is designed to acquire high-quality flowfield data deep in the corner of a wing-fuselage junction specifically for the purpose of computational fluid dynamics (CFD) validation and turbulence model improvement. This paper will present and discuss the results of a recent experiment with the juncture-flow model in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The main objective of that test was to expand the existing juncture-flow dataset with a symmetric wing case that displays fully attached, incipient separation, and separated flow in the corner of the wing-fuselage junction, depending on the model pitch angle. Laser Doppler velocimetry (LDV) measurements were made at three model pitch angles (0 deg: fully attached, 1 deg: incipient separation, and 5 deg: separated flow) and for each one, mean-flow and Reynolds-stress data was obtained on the fuselage and at several streamwise locations along the corner of the wing-fuselage junction. Supporting measurements were made during the test campaign and included model and tunnel wall static pressures, tunnel wall and ceiling boundary-layer rake data, oil-flow visualizations, and laser-based measurements of the as-built model geometry and model position in the test section. Comparisons between the experimental data and Reynolds averaged Navier-Stokes CFD results will also be presented and discussed.

Juncture Flow↗