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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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Remote multiplexer/demultiplexer digital instrumentation system, which is suitable to both airborne and ground-based data acquisition/process control applications, can be employed in a variety of research and flight test applications where great flexibility to accommodate changes in number of parameters, data sampling rates, and signal conditioning is required.
A unique mechanism developed for conducting friction and wear experiments in orbit is described. The device is capable of testing twelve material samples simultaneously. Parameters considered critical include: power, weight, volume, mounting, cleanliness, and thermal designs. The device performed flawlessly in orbit over an eighteen month period and demonstrated the usefulness of this design for future unmanned spacecraft or shuttle applications.
Fabrication on p-type GaAs of MOS structures in which the quality of the oxide is such that the surface can be driven into deep inversion by a voltage pulse is reported. The capacitance transients in such MOS capacitors as a function of step amplitude and temperature were measured and the transients were analyzed by an extension of a method for silicon. The oxides were produced by plasma oxidation on an LPE-grown p-type GaAs specimen with N sub A of 3x10 to the 17th power/cu cm. The capacitors were produced by depositing 50 microns-diameter gold dots over the native oxide and, therefore, the lifetime is localized to the area under the dot. The method permits extraction of both the bulk lifetime and the interface recombination velocity. These parameters on samples with different N sub A were measured and a correlation between tau sub g and N sub A was found.
Programs for frequently-used mathematical procedures save time. Package contains 16 subroutines. Each separately documented with descriptions of invoking subroutine call, its required parameters, and sample test program. Package written in FORTRAN 77.
This report documents the Benson Diesel Engine Simulation Program and explains how it can be used to predict the performance of diesel engines. The program was obtained from the Garrett Turbine Engine Company but has been extensively modified since. The program is a thermodynamic simulation of the diesel engine cycle which uses a single zone combustion model. It can be used to predict the effect of changes in engine design and operating parameters such as valve timing, speed and boost pressure. The most significan change made to this program is the addition of a more detailed heat transfer model to predict metal part temperatures. This report contains a description of the sub-models used in the Benson program, a description of the input parameters and sample program runs.
Dielectric constants of microwave substrates are required in the design of superconducting microwave circuits at various temperatures. In this paper, the results are reported of a study of the complex permittivity of the newly developed lanthanum aluminate (LaAlO3) substrate, in the 20 to 300 K temperature range at frequencies from 26.5 to 40.0 GHz. The value of the complex permittivity was obtained by measuring the sample scattering parameters using a microwave waveguide technique. It is observed that, while the dielectric constant did not change appreciably with frequency, its value decreased by approximately 14 percent from room temperature to 20 K.
The problem of baffles for control of singly reflected (and nonreflected) ghost rays is considered. The theory of baffle design for Wolter Type I grazing incidence optics is reviewed, and a set of sample baffle parameters is obtained subject to the assumptions of nominal mirror figures and perfect manufacture and alignment of baffles. It is found that baffles forward of the optics (in the thermal precollimator) and between the mirror elements (at the CAP) are sufficient to allow the simultaneous ghost image and vignetting requirements to be satisfied for HRMA shells P1H1, P3H3, and P4H4. However, these baffles are not sufficient for the innermost shell P6H6; at best the requirements are slightly violated and there is no margin for tolerances. The addition of a baffle interior to the P6 space at an axial station about one third of the way forward from the aft end of the paraboloid will allow the ghost ray and vignetting requirements to be met. The minimum ghost ray angles and the vignetting angles are sensitive functions of the baffle positions and radii; tolerances of considerably better than 1 mm will be required. The sensitivities are coupled and correlated; further investigations should be undertaken in order to obtain baffle parameters which, combined with likely achievable tolerances, will minimize the risk of the vignetting/ghost ray requirements not being met. The lightweight carbon-epoxy composite used for thermal baffles has insufficient X-ray opacity to be a suitable material for construction of the controlling X-ray baffles; further study is needed to determine an appropriate material and to investigate its thermal and mechanical implications.
We compare the combined distribution of 31 group and 25 cluster velocity dispersions with the ensemble of 32 models for the formation and evolution of large-scale structure examined by Weinberg & Cole (1992). The models include Gaussian and non-Gaussian initial fluctuations, different power law spectra (n = -1, n = 0, n = -2, 'pancake'), flat (Omega = 1) and open (Omega = 0.2) cosmologies, and unbiased (b(sub 8) = 1) and biased (b(sub 8) = 2) galaxy formation. The set of initial conditions we test, although limited, samples enough parameter space to indicate which general classes of models are consistent with the data. The two Gaussian, n = -1 models which best approximate the standard and open Cold Dark Matter (CDM) models do not match the observed distribution of velocity dispersions; models with b(sub 8) = 2 and Omega = 1 ('standard') or b(sub 8) = 1 and Omega = 0.2 ('open') predict too large a ratio of low to high velocity dispersion systems. A 'COBE-normalized' CDM model with b(sub 8) = 1 and Omega = 1 produces clusters with velocity dispersions higher than those measured. All three models overestimate the total abundance of systems.
This report contains viewgraphs on arc tracking tests in various aerospace environments. It has the following six sections: LeRC arc tracking tests parameters, apparatus, sample description, procedure, arc tracking test results, and discussion.
NASA Marshall Space Flight Center and the University of Alabama Huntsville are collaborating with the 45th Weather Squadron (45WS) to develop improved lightning prediction capabilities for the new C-band dual-polarimetric weather radar being acquired for use by 45WS and launch weather forecasters at Cape Canaveral Air Force Station (CCAFS). In particular, these algorithms will focus on lightning onset, cessation and combined lightning-radar applications for convective winds assessment. Research using radar reflectivity (Z) data for prediction of lightning onset has been extensively discussed in the literature and subsequently applied by launch weather forecasters as it pertains to lightning nowcasting. Currently the forecasters apply a relatively straight forward but effective temperature-Z threshold algorithm for assessing the likelihood of lightning onset in a given storm. In addition, a layered VIL above the freezing level product is used as automated guidance for the onset of lightning. Only limited research and field work has been conducted on lightning cessation using Z and vertically-integrated Z for determining cessation. Though not used operationally vertically-integrated Z (basis for VIL) has recently shown promise as a tool for use in nowcasting lightning cessation. The work discussed herein leverages and expands upon these and similar reflectivity-threshold approaches via the application/addition of over two decades of polarimetric radar research focused on distinct multi-parameter radar signatures of ice/mixed-phase initiation and ice-crystal orientation in highly electrified convective clouds. Specifically, our approach is based on numerous previous studies that have observed repeatable patterns in the behavior of the vertical hydrometeor column as it relates to the temporal evolution of differential reflectivity and depolarization (manifested in either LDR or p(sub hv)), development of in-situ mixed and ice phase microphysics, electric fields, and ensuing lightning in the sub-tropical/tropical convection typical of the southeastern U.S., Maritime Continent, and southwestern Amazon. The polarimetric signatures detected in this setting provide a basis for automated 3-D detection of hydrometeor types in fuzzy logic hydrometeor identification algorithms (HID). Our working hypothesis is that improvement in lightning onset warning lead time and specificity for a given storm, relative to application of a Z-threshold algorithm, should arise as a consequence of the ability of dual-polarimetric radar to unambiguously detect and identify (through HID algorithms) the updraft elevation of rain-water cores above the freezing level and subsequent onset of drop freezing, riming, and robust mixed phase processes leading to significant charge separation and lightning. This type of algorithm, though dependent on the quality of the polarimetric data should be less susceptible to variable Z-calibration that can impact a given Z-threshold approach. To facilitate development of the algorithm while the 45WS dual-pol radar is in its current test stages and to evaluate the impact of polarimetric data quality (e.g., modified scan parameters and sampling) on the ensuing algorithms, we are using the ARMOR C-band dual-pol radar in Huntsville combined with N. Alabama LMA data and ARMOR HID algorithms [NCAR algorithm modified for application at C-band] in a testbed fashion. For lightning cessation we are revisiting the application of differential propagation phase variables for the monitoring of ice crystal alignment driven by in-cloud electric fields combined with metrics of ice water path (i.e., vertically integrated reflectivity). Importantly it should be noted that this approach is still very much a research topic and as such, we will explore operational applications that involve radar frequencies other than C-Band by using the UAH MAX X-band dual-pol radar in slow staring modes.
Sunward-flowing voids above post-coronal mass ejection flare arcades were first discovered using the soft X-ray telescope aboard Yohkoh and have since been observed with TRACE (extreme ultraviolet (EUV)), SOHO/LASCO (white light), SOHO/SUMER (EUV spectra), and Hinode/XRT (soft X-rays). Supra-arcade downflow (SAD) observations suggest that they are the cross-sections of thin flux tubes retracting from a reconnection site high in the corona. Supra-arcade downflowing loops (SADLs) have also been observed under similar circumstances and are theorized to be SADs viewed from a perpendicular angle. Although previous studies have focused on dark flows because they are easier to detect and complementary spectral data analysis reveals their magnetic nature, the signal intensity of the flows actually ranges from dark to bright. This implies that newly reconnected coronal loops can contain a range of hot plasma density. Previous studies have presented detailed SAD observations for a small number of flares. In this paper, we present a substantial SADs and SADLs flare catalog. We have applied semiautomatic detection software to several of these events to detect and track individual downflows thereby providing statistically significant samples of parameters such as velocity, acceleration, area, magnetic flux, shrinkage energy, and reconnection rate. We discuss these measurements (particularly the unexpected result of the speeds being an order of magnitude slower than the assumed Alfven speed), how they were obtained, and potential impact on reconnection models.
X-ray observations of many clusters of galaxies reveal the presence of edges in surface brightness and temperature, known as "cold fronts". In relaxed clusters with cool cores, these edges have been interpreted as evidence for the "sloshing" of the core gas in the cluster's gravitational potential. The smoothness of these edges has been interpreted as evidence for the stabilizing effect of magnetic fields "draped" around the front surfaces. To check this hypothesis, we perform high-resolution magnetohydrodynamics simulations of magnetized gas sloshing in galaxy clusters initiated by encounters with subclusters. We go beyond previous works on the simulation of cold fronts in a magnetized intracluster medium by simulating their formation in realistic, idealized mergers with high resolution ((Delta)x approx. 2 kpc). Our simulations sample a parameter space of plausible initial magnetic field strengths and field configurations. In the simulations, we observe strong velocity shears associated with the cold fronts amplifying the magnetic field along the cold front surfaces, increasing the magnetic field strength in these layers by up to an order of magnitude, and boosting the magnetic pressure up to near-equipartition with thermal pressure in some cases. In these layers, the magnetic field becomes strong enough to stabilize the cold fronts against Kelvin-Helmholtz instabilities, resulting in sharp, smooth fronts as those seen in observations of real clusters. These magnetic fields also result in strong suppression of mixing of high and low-entropy gas in the cluster, seen in our simulations of mergers in the absence of a magnetic field. As a result, the heating of the core due to sloshing is very modest and is unable to stave off a cooling catastrophe.
Aquarius was launched on June 10, 2011 as part of the Aquarius/SAC-D observatory and the instrument has been operating continuously since being turned on in August of the same year. The initial map of sea surface salinity was released one month later (September) and the quality of the retrieval has continuously improved since then. The Aquarius radiometers include several special features such as measurement of the third Stokes parameter, fast sampling, and careful thermal control, and a combined passive/active instrument. Aquarius is working well and in addition to helping measure salinity, the radiometer special features are generating new results.
The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human-rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30-sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post-processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one-way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.
The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human‐rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30‐sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post‐processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one‐way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.
A new variant of the multilevel Monte Carlo estimator [5, 3, 9, 12] is presented for the estimation of expectation statistics that utilizes sample reuse in specified levels, explicitly removes approximation error bias associated with numerically computed output quantities of interest that have an asymptotic limit behavior, and permits a low variance estimate of the asymptotic rate of convergence to that limit. In addition, it is shown that this new multilevel Monte Carlo variant can yield a computational cost savings. A review of Monte Carlo and multilevel Monte Carlo estimators is presented that includes analysis of expected value, expected mean squared error, and the calculation of optimized multilevel sample size parameters. The multilevel Monte Carlo estimator produces estimates of expectation for numerically approximated output quantities of interest that are biased by approximation error. When the quantity of interest can be modeled as the asymptotic limit of numerically approximated output quantities of interest, it is theoretically possible to remove this approximation error bias in the multilevel Monte Carlo estimator. In actual implementations, however, this procedure is unreliable due to statistical variability and inaccuracy in estimating the needed asymptotic limit. Analysis and numerical experiment show that the proposed variant of the multilevel Monte Carlo method greatly reduces (in some cases eliminates) the statistical variability in this limit estimation.
We present a scalable unsupervised learning-based method for obtaining explicit control policies for model predictive control problems for stochastic linear systems with additive uncertainties subject to nonlinear chance constraints. We call the proposed method stochastic parametric differentiable predictive control (SP-DPC), which extends the recently proposed deterministic DPC policy optimization algorithm. We formulate the SP-DPC as a deterministic approximation to the stochastic parametric constrained optimal control problem via independent sampling of the problem's parameters and uncertainties. This formulation allows us to directly compute the policy gradients via automatic differentiation of the problem's value function, evaluated over sampled parameters and uncertainties. In particular, the computed expectation of the problem's value function is backpropagated through the finite-time closed-loop system rollouts parametrized by a known nominal system dynamics model and neural control policy. We also provide theoretical probabilistic guarantees on closed-loop stability and chance constraints satisfaction for systems controlled by learned neural policies. We demonstrate the computational efficiency and scalability of the proposed policy optimization algorithm in three numerical examples, including systems with a large number of states or subject to nonlinear constraints.
Markov chain Monte Carlo (MCMC) methods have not been broadly adopted in Bayesian neural networks (BNNs). This paper initially reviews the main challenges in sampling from the parameter posterior of a neural network via MCMC. Such challenges culminate to lack of convergence to the parameter posterior. Nevertheless, this paper shows that a nonconverged Markov chain, generated via MCMC sampling from the parameter space of a neural network, can yield via Bayesian marginalization a valuable posterior predictive distribution of the output of the neural network. Further, classification examples based on multilayer perceptrons showcase highly accurate posterior predictive distributions. The postulate of limited scope for MCMC developments in BNNs is partially valid; an asymptotically exact parameter posterior seems less plausible, yet an accurate posterior predictive distribution is a tenable research avenue.