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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

CFD Predictions of Sonic-Boom Characteristics for Unmodified and Modified SR-71 Configurations

Shaped sonic-boom signatures refer to signatures that look something other than the typical N-waves. Shaped sonic-boom signatures such as "flat-top," "ramp-type," or "hybrid-type" waveforms have been shown to reduce the subjective loudness without requiring reductions in overpressure peaks. The shaping of sonic-boom signatures requires increasing the shock rise time and changes in frequency spectra. So far, a flat-top waveform was shown to be achievable in wind tunnels; however, the influence of long propagation distance and real atmosphere on shaped signatures should be addressed using flight tests. Two different approaches have been proposed for sonic-boom minimization flight tests. The first approach, proposed by Eagle Aerospace, is for a flight test using a modified BQM-34 "FIREBEE" remotely piloted vehicle. The 30-foot long FIREBEE has a steady state flight condition at the Mach number and altitude of interest, and it can be recovered by helicopter from the water. As an alternative approach, a modified SR-71 vehicle has been proposed by the McDonnell Douglas Corporation. Benefits of the SR-71 include its variable geometry supersonic inlets, small cockpit bulge, higher Mach number capabilities, slender design, and longer length (105 foot). The present investigation addresses the sonic-boom analysis for the second vehicle.The objective of the current investigation is to assess the feasibility of a modified SR-71 configuration, with McDonnell Douglas-designed fuselage modifications, intended to produce shaped sonic-boom signatures on the ground. The present study describes the use of a higher-order computational fluid dynamics (CFD) method to predict the sonic-boom characteristics for both unmodified and modified SR-71 configurations. An Euler unstructured grid methodology is used to predict the near-field, three-dimensional pressure patterns generated by both SR-71 models. The computed near-field pressure signatures are extrapolated to specified distances below the aircraft down to impingement on the ground using the code MDBOOM. Comparisons of the near-field pressure signatures with available flight-test data are presented in the current paper.

Fouladi, Kamran↗
NASA NTRS2001

Long-Term Reliability of SiGe/Si HBTs From Accelerated Lifetime Testing

Accelerated lifetime tests were performed on double-mesa structure Si(0.7)Ge(0.3)/Si npn heterojunction bipolar transistors, grown by molecular beam epitaxy, in the temperature range of 175 C-275 C. The transistors (with 5x20 sq micron emitter area) have DC current gains approx. 40-50 and f(sub T) and f(sub max) of up to 22 GHz and 25 GHz, respectively. It is found that a gradual degradation in these devices is caused by the recombination enhanced impurity diffusion (REID) of boron atoms from the p-type base region and the associated formation of parasitic energy barriers to electron transport from the emitter to collector layers. This REED has been quantitatively modeled and explained, to the first order of approximation, and the agreement with the measured data is good. The mean time to failure (MTTF) of these devices at room temperature under 1.35 x 10(exp 4) A/sq cm current density operation is estimated from the extrapolation of the Arrhenius plots of device lifetime versus reciprocal temperature. The results of the reliability tests offer valuable feedback for SiGe heterostructure design in order to improve the long-term reliability of the devices and circuits made with them. Hot electron induced degradation of the base-emitter junction was also observed during the accelerated lifetime testing. In order to improve the HBT reliability endangered by the hot electrons, deuterium sintered techniques have been proposed. The preliminary results from this study show that a deuterium-sintered HBT is, indeed, more resistant to hot-electron induced base-emitter junction degradation.

Bhattacharya, Pallab↗
NASA NTRS2003

Rate Constant for the Reaction CH3 + CH3 Yields C2H6 at T = 155 K and Model Calculation of the CH3 Abundance in the Atmospheres of Saturn and Neptune

The column abundances of CH3 observed by the Infrared Space Observatory (ISO) satellite on Saturn and Neptune were lower than predicted by atmospheric photochemical models, especially for Saturn. It has been suggested that the models underestimated the loss of CH3 due to poor knowledge of the rate constant k of the CH3 + CH3 self-reaction at the low temperatures and pressures of these atmospheres. Motivated by this suggestion, we undertook a combined experimental and photochemical modeling study of the CH3 + CH3 reaction and its role in determining planetary CH3 abundances. In a discharge flow-mass spectrometer system, k was measured at T = 155 K and three pressures of He. The results in units of cu cm/molecule/s are k(0.6 Torr) = 6.82 x 10(exp -11), k(1.0 Torr) = 6.98 x 10(exp -11), and k(1.5 Torr) = 6.91 x 10(exp -11). Analytical expressions for k were derived that (1) are consistent with the present laboratory data at T = 155 K, our previous data at T = 202 K and 298 K, and those of other studies in He at T = 296-298 K and (2) have some theoretical basis to provide justification for extrapolation. The derived analytical expressions were then used in atmospheric photochemical models for both Saturn and Neptune. These model results reduced the disparity with observations of Saturn, but not with observations of Neptune. However, the disparity for Neptune is much smaller. The solution to the remaining excess CH3 prediction in the models relative to the ISO observations lies, to a large extent, elsewhere in the CH3 photochemistry or transport, not in the CH3 + CH3 rate.

Cody, Regina J.↗
DOE OSTI2021

Verification of Data-Driven Models of Physical Phenomena using Interpretable Approximation

Machine-learned models, specifically neural networks, are increasingly used as “closures” or “constitutive models” in engineering simulators to represent fine-scale physical phenomena that are too computationally expensive to resolve explicitly. However, these neural net models of unresolved physical phenomena tend to fail unpredictably and are therefore not used in mission-critical simulations. In this report, we describe new methods to authenticate them, i.e., to determine the (physical) information content of their training datasets, qualify the scenarios where they may be used and to verify that the neural net, as trained, adhere to physics theory. We demonstrate these methods with neural net closure of turbulent phenomena used in Reynolds Averaged Navier-Stokes equations. We show the types of turbulent physics extant in our training datasets, and, using a test flow of an impinging jet, identify the exact locations where the neural network would be extrapolating i.e., where it would be used outside the feature-space where it was trained. Using Generalized Linear Mixed Models, we also generate explanations of the neural net (à la Local Interpretable Model agnostic Explanations) at prototypes placed in the training data and compare them with approximate analytical models from turbulence theory. Finally, we verify our findings by reproducing them using two different methods.

42 ENGINEERING↗
DOE OSTI2020

Quantifying uncertainties on fission fragment mass yields with mixture density networks

Probabilistic machine learning techniques can learn both complex relations between input features and output quantities of interest as well as take into account stochasticity or uncertainty within a data set. In this initial work, we explore the use of one such probabilistic network, the mixture density network (MDN), to reproduce fission yields and their uncertainties. In this paper, we study mass yields for the spontaneous fission of 252 Cf, exploring the number of training samples needed for converged predictions, how different levels of uncertainty propagate from the training set to the MDN predictions, and how well physical constraints of the yields—such as normalization and symmetry—are upheld by the algorithm. Finally, we test the ability of the MDN to interpolate between and extrapolate beyond samples in the training set using energy-dependent mass yields for the neutron-induced fission on 235 U. The MDN provides a reliable way to include and predict uncertainties and is a promising path forward for supplementing sparse sets of nuclear data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2009

Improvements in Modeling 90 degree Bleed Holes for Supersonic Inlets

The modeling of porous bleed regions as boundary conditions in computational fluid dynamics (CFD) simulations of supersonic inlet flows has been improved through a scaling of sonic flow coefficient data for 90deg bleed holes. The scaling removed the Mach number as a factor in computing the sonic flow coefficient and allowed the data to be fitted with a quadratic equation, with the only factor being the ratio of the plenum static pressure to the surface static pressure. The implementation of the bleed model into the Wind-US CFD flow solver was simplified by no longer requiring the evaluation of the flow properties at the boundary-layer edge. The quadratic equation can be extrapolated to allow the modeling of small amounts of blowing, which can exist when recirculation of the bleed flow occurs within the bleed region. The improved accuracy of the bleed model was demonstrated through CFD simulations of bleed regions on a flat plate in supersonic flow with and without an impinging oblique shock. The bleed model demonstrated good agreement with experimental data and three-dimensional CFD simulations of bleed holes.

Slater, John W.↗
NASA NTRS1972

Small-scale wind shear definition for aerospace vehicle design.

Rawinsonde wind profile data provide adequate wind shear information for vertical height intervals greater than 1 km. To specify wind shears for intervals below 1 km for space vehicle design, detailed wind-profile information like that provided by the FPS-16 Radar/Jimsphere system or an extrapolation procedure is required. This paper is concerned with the latter alternative. It is assumed that any realization from an ensemble of wind profiles can be represented in terms of a Fourier integral. This permits the calculation of the ensemble standard deviation and mean of the corresponding shear ensemble for any altitude and shear interval in terms of the power spectrum of the ensemble of wind profiles. The results of these calculations show that the mean and standard deviation of the wind shear ensemble, as well as the wind shear for any percentile, asymptotically behave like the vertical interval to the 0.7 power. This result is in excellent agreement with shear data from Cape Kennedy, Fla.

Fichtl, G. H.↗
DOE OSTI2023

Connecting suborganismal data to bioenergetic processes: killifish embryos exposed to a dioxin-like compound

A core challenge for ecological risk assessment is to integrate molecular responses into a chain of causality to organismal or population level outcomes. Bioenergetic theory may be a useful approach for integrating suborganismal responses to predict organismal level responses that influence population dynamics. In this work, we describe a novel application of Dynamic Energy Budget (DEB), theory in the context of a toxicity framework (Adverse Outcome Pathways, AOP) to make quantitative predictions of chemical exposures to individuals, starting from suborganismal data. We use early life stage exposure of Fundulus heteroclitus to dioxin-like chemicals (DLCs) and connect AOP Key Events (KEs) to DEB processes through “damage” that is produced at a rate proportional to the internal toxicant concentration. We use transcriptomic data of fish embryos exposed to DLCs to translate molecular indicators of damage into changes in DEB parameters (damage increases somatic maintenance costs) and use DEB models to predict sublethal and lethal effects of young fish. By changing a small subset of model parameters, we predict the evolved tolerance to DLCs in some wild F. heteroclitus populations, a data set not used in model parameterization. The differences in model parameters points to reduced sensitivity and altered damage repair dynamics as contributing to this evolved resistance. Our methodology has potential extrapolation to untested chemicals of ecological concern.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

Chromium-coated cladding analysis under simulated LOCA burst conditions

Of the near-term accident-tolerant fuel concepts identified, chromium coatings have been shown to slow cladding oxidation without altering fuel system geometry or greatly affecting neutronic performance. To identify how coated cladding tubes perform under high-temperature accident conditions, pressurized-tube burst tests were conducted in the Severe Accident Test Station at Oak Ridge National Laboratory. To analyze how the coating affects cladding behavior, coated and uncoated cladding burst tests were simulated by using the BISON fuel performance code. Thermocouple data from these tests were fit into axial and azimuthal profiles and combined to generate 3D cladding surface temperatures, and pressure transducer data were compared until cladding failure. Additionally, the cladding temperatures at failure and the internal gas pressure evolution show relatively good agreement between the simulation and experiment results. Simulations were then extrapolated to demonstrate the coatings effectiveness to increasing the cladding burst temperature by using a parametric evaluation of the initial tube gas pressure. This work demonstrates the possibility of an increased cladding failure margin under transient conditions due to the addition of chromium coating, and more pertinently, an increased cladding failure margin from more accurate experimental characterization.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Thermodynamic properties of ZrCl 4 with LiCl, NaCl, KCl, CsCl, MgCl 2 , and UCl 3 for molten salt reactor applications

Here, a set of self-consistent Gibbs energy functions has been developed to describe the thermochemical behavior of the major reactive fission product ZrCl 4 with key components in chloride molten salt reactors (MSRs): LiCl–ZrCl 4 , NaCl–ZrCl 4 , KCl–ZrCl 4 , CsCl–ZrCl 4 , MgCl 2 –ZrCl 4 and UCl 3 –ZrCl 4 . Low ZrCl 4 concentration phase equilibria most relevant to MSR applications have been confirmed via differential scanning calorimetry for NaCl–ZrCl 4 , and X-ray diffraction analysis performed on equilibrated samples of NaCl–ZrCl 4 , KCl–ZrCl 4 , MgCl 2 –ZrCl 4 , and UCl 3 –ZrCl 4 . Within the framework of the modified quasi-chemical model in the quadruplet approximation, extrapolations of pseudo-binary models were generated to represent KCl–MgCl 2 –ZrCl 4 , KCl–NaCl–ZrCl 4 , and MgCl 2 –NaCl–ZrCl 4 , which show agreement with phase equilibria data where available without the use of ternary interaction parameters. The optimized thermodynamic descriptions for these systems and others are available in the open-source compendium Molten Salt Thermal Properties Database – Thermochemical (MSTDB–TC).

CALPHAD↗
DOE OSTI2025

Multi-fidelity learning for interatomic potentials: low-level forces and high-level energies are all you need

The promise of machine learning interatomic potentials (MLIPs) has led to an abundance of public quantum mechanical (QM) training datasets. The quality of an MLIP is directly limited by the accuracy of the energies and atomic forces in the training dataset. Unfortunately, most of these datasets are computed with relatively low-accuracy QM methods, e.g. density functional theory with a moderate basis set. Due to the increased computational cost of more accurate QM methods, e.g. coupled-cluster theory with a complete basis set (CBS) extrapolation, most high-accuracy datasets are much smaller and often do not contain atomic forces. The lack of high-accuracy atomic forces is quite troubling, as training with force data greatly improves the stability and quality of the MLIP compared to training to energy alone. Because most datasets are computed with a unique level of theory, traditional single-fidelity (SF) learning is not capable of leveraging the vast amounts of published QM data. In this study, we apply multi-fidelity learning (MFL) to train an MLIP to multiple QM datasets of different levels of accuracy, i.e. levels of fidelity. Specifically, we perform three test cases to demonstrate that MFL with both low-level forces and high-level energies yields an extremely accurate MLIP—far more accurate than a SF MLIP trained solely to high-level energies and almost as accurate as a SF MLIP trained directly to high-level energies and forces. Therefore, MFL greatly alleviates the need for generating large and expensive datasets containing high-accuracy atomic forces and allows for more effective training to existing high-accuracy energy-only datasets. Indeed, low-accuracy atomic forces and high-accuracy energies are all that are needed to achieve a high-accuracy MLIP with MFL.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Constraining Carbon and Nutrient Flows in Soil With Ecological Stoichiometry

Soil organic matter (SOM) is central to soil carbon (C) storage and terrestrial nutrient cycling. New data have upended the traditional model of stabilization, which held that stable SOM was mostly made of undecomposed plant molecules. We now know that microbial by-products and dead cells comprise unexpectedly large amounts of stable SOM because they can become attached to mineral surfaces or physically protected within soil aggregates. SOM models have been built to incorporate the microbial to mineral stabilization of organic matter, but now face a new challenge of accurately capturing microbial productivity and metabolism. Explicitly representing stoichiometry, the relative nutrient requirements for growth and maintenance of organisms, could provide a way forward. Stoichiometry limits SOM formation and turnover in nature, but important nutrients like nitrogen (N), phosphorus (P), and sulfur (S) are often missing from the new generation of SOM models. In this synthesis, we seek to facilitate the addition of these nutrients to SOM models by (1) reviewing the stoichiometric bias—the tendency to favor one element over another—of four key processes in the new framework of SOM cycling and (2) applying this knowledge to build a stoichiometrically explicit budget of C, N, P, and S flow through the major SOM pools. By quantifying the role of stoichiometry in SOM cycling, we discover that constraining the C:N:P:S ratio of microorganisms and SOM to specific values reduces uncertainty in C and nutrient flow as effectively as using microbial C use efficiency (CUE) parameters. We find that the value of additional constraints on stoichiometry vs. CUE varies across ecosystems, depending on how precise the available data are for that ecosystem and which biogeochemical pathways are present. Moreover, because CUE summarizes many different processes, stoichiometric measurements of key soil pools are likely to be more robust when extrapolated from soil incubations to plot or biome scale estimates. Our results suggest that measuring SOM stoichiometry should be a priority for future empirical work and that the inclusion of new nutrients in SOM models may be an effective way to improve precision.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

ERTS orbit maintenance

Error drift in the ERTS orbit maintenance problem is determined from the actual ground trace errors that the spacecraft experienced over the first 3 1/2 repeat cycles. Actual data are fitted to a parametric model of ground trace error by a least squares method, and initial offsets to these key parameters as well as their rates of change are extrapolated forward analytically to obtain the future ground trace drift in orbital estimates.

Fuchs, A. J.↗
NASA NTRS1973

Space vehicle engine and heat shield environment review. Volume 1: Engineering analysis

Methods for predicting the base heating characteristics of a multiple rocket engine installation are discussed. The environmental data is applied to the design of adequate protection system for the engine components. The methods for predicting the base region thermal environment are categorized as: (1) scale model testing, (2) extrapolation of previous and related flight test results, and (3) semiempirical analytical techniques.

Mcanelly, W. B.↗
NASA NTRS1975

Ultraviolet observations of classical Cepheids by OAO-2

OAO-2 observations of eight bright classical Cepheids in the wavelength region 1910 A to 4250 A are presented. The data for RT Aurigae, alpha Ursa Minoris, delta Cephei, and gamma Ophiuchi show excellent agreement with ground based photometry in the wavelength region of overlap and are consistent with a simple extrapolation of light curve properties from the visible region. However, in the ultraviolet, the light curve of beta Doradus shows two small flux bumps, at phases of 0.75 and 0.85, in addition to the well known bump at phase 0.0. All three bumps should probably be associated with the arrival of shocks at the stellar surface.

Hutchinson, J. L.↗
NASA NTRS1979

Population statistics of faint stellar and non-stellar objects

A disc and halo population model is constructed to fit star counts and color data down to V approximately 23 at absolute value of b = 90 deg. This model is used to predict star counts and colors down to V approximately 30. Deviations from these extrapolated relationships provide constraints on the number of faint quasars and black dwarf stars. It is shown that extra-galactic globular clusters start contributing significantly to star counts at V approximately 25 and are more numerous than stars for V 31. Morphological studies of galaxies with approximately 0.5, were made with the space telescope. Significant constraints on theoretical models that describe the evolution of clusters of galaxies are provided.

Vandenbergh, S.↗
NASA NTRS1981

Investigation of geomagnetic field forecasting and fluid dynamics of the core

The magnetic determination of the depth of the core-mantle boundary using MAGSAT data is discussed. Refinements to the approach of using the pole-strength of Earth to evaluate the radius of the Earth's core-mantle boundary are reported. The downward extrapolation through the electrically conducting mantle was reviewed. Estimates of an upper bound for the time required for Earth's liquid core to overturn completely are presented. High order analytic approximations to the unsigned magnetic flux crossing the Earth's surface are also presented.

Benton, E. R.↗
NASA NTRS1987

Calculating Sonic-Boom Propagation

Nonlinear effects included, enabling more-realistic modeling. Modified Method of Characteristics Sonic Boom Extrapolation Program (MMOC) is computer program for sonic-boom propagation that includes shock coalescence and incorporates effects of asymmetries due to volume and lift. Numerically integrates nonlinear governing equations using data on initial data line approximately one body length from aircraft and yields sonic-boom pressure at ground as function of time or of position at given time. MMOC written in FORTRAN IV.

Darden, C. M.↗