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NASA NTRS1967

Design of Liquid Propellant Rocket Engines Second Edition

This book intends to build a bridge for the student and the young engineer: to link the rocket propulsion fundamentals and elements (which are well covered in the literature) with the actual rocket engine design and development work as it is carried out in industry (which is very little, if at all covered in literature). The book attempts to further the understanding of the realistic application of liquid rocket propulsion theories, and to help avoid or at least reduce time and money consuming errors and disappointments. In so doing, it also attempts to digest and consolidate numerous closely related subjects, hitherto often treated as separate, bringing them up to date at the same time. The book was written "on the job" for use by those active in all phases of engine systems design, development, and application, in industry as well as government agencies. Since it addresses itself to human beings set out to create new machines, rather than describing machines about to dominate man, the language chosen may not always be "functional" in the strict sense of the word. The book presents sufficient detail to familiarize and educate thoroughly those responsible for various aspects of liquid propellant rocketry, including engine systems design, engine development, and flight vehicle application. It should enable the rocket engineer to conduct, independently, complete or partial engine systems preliminary detail designs and to understand and judge the activities in, and the problems, limitations, and "facts of life~ of the various subsystems making up a complete engine system. It also attempts to educate those ultimately interested in specialized subsystems and component design (thrust chamber, turbopump, control valves, etc.) about their own as well as neighboring subsystems and about the complete engine system. This should enable the student to prepare realistic analytical calculations and design layouts with a long headstart toward the final specialized designs for subsystem production release. Special emphasis has been placed on engine flight application to stimulate engine systems and subsystem designers to think in these terms from the outset. The book is intended as a textbook, with specific consideration of the teacher without industry experience. We hope it will stimulate those desiring to specialize in the area of a rocket engine subsystem by supplying adequate information to enable them to benefit fully from the specialized literature. Thus, it provides a realistic expert introduction for those joining the liquid propellant rocket engine field.

Dieter K Huzel↗

NASA NTRS1979

Martian seismicity

During the Viking mission to Mars, the seismometer on Lander II collected approximately 0.24 earth years of observational data, excluding periods of time dominated by wind-induced Lander vibration. The 'quiet-time' data set contains no confirmed seismic events. A proper assessment of the significance of this fact requires quantitative estimates of the expected detection rate of the Viking seismometer. The first step is to calculate the minimum magnitude event detectable at a given distance, including the effects of geometric spreading, anelastic attenuation, seismic signal duration, seismometer frequency response, and possible poor ground coupling. Assuming various numerical quantities and a Martian seismic activity comparable to that of intraplate earthquakes, the appropriate integral gives an expected annual detection rate of 10 events, nearly all of which are local. Thus only two to three events would be expected in the observational period presently on hand and the lack of observed events is not in gross contradiction to reasonable expectations. Given the same assumptions, a seismometer 20 times more sensitive than the present instrument would be expected to detect about 120 events annually.

Goins, N. R.↗

NASA NTRS1983

On the role of the seasonal cycle

The definition of the seasonal cycle as the projection of an atmospheric time series onto a suitably defined subset of orthogonal basis functions guarantees that any atmospheric covariance may be expressed as the sum of a seasonal cycle part and a transient part (where transient refers to departures from the seasonal cycle rather than the time mean). Results are presented for the seasonal cycle contribution to the zonally averaged fluxes of momentum and heat, and for the zonally averaged height variance, in data for: the winter season, the winter season with the Fourier basis set appropriate for the seven-year time series, and the seven-year mean. The Fourier basis set calculation indicates that the interannual variability of the momentum flux is dominated by the interactions between the seasonal cycle and the meteorologically low frequency flow.

Straus, D. M.↗

NASA NTRS1983

Observations of neutral hydrogen in radio-loud and interacting galaxies

The results of a survey of H I in radio-loud and interacting galaxies is presented. Four cases of H I absorption and five of emission are reported. The interesting features found for individual galaxies are described, and the systematic properties are discussed. Column densities of absorbing gas generally exceed those expected for a 'Milky Way' H I disk by more than an order of magnitude. The absorbing gas must have a flattened, disklike morphology oriented roughly parallel to the optical disk of the galaxy. Turbulent noncircular gas motions are evidently present, which are shown to be almost certainly induced by galaxy-galaxy interactions. The set of galaxies in which H I absorption has been detected is dominated by morphologically peculiar objects. It is concluded that the detection of H I seen in absorption against a nuclear radio source permits direct determination of the sense of radial flow of extranuclear material, and is direct evidence that potential 'food' for a compact object in the nucleus exists in the galaxy.

Heckman, T. M.↗

NASA NTRS1990

Cirrus cloud spectra and layers observed during the FIRE and GASP projects

A general characterization is developed for cirrus clouds in terms of their spectra, shapes, optical thicknesses, and radiative properties for use in numerical models. Data sets from the Global Atmospheric Sampling Project (GASP) of the upper troposphere and the First ISCCP Regional Experiment (FIRE) are combined and analyzed to study general traits of cirrus clouds. A definition is given for 2D turbulence, and the GASP and FIRE data sets are examined with respect to cirrus layers and entrainment and to dominant turbulent scales. The approach employs conditional sampling in cloudy and clear air, power-spectral analysis, and mixing-line-type diagrams. Evidence is given for a well mixed cloud deck and for the tendency of cirrus to be formed in multilayer structures. The results are of use in mesoscale and global circulation models which predict cirrus, in small-scale cirrus modeling, and in studying the role of gravity waves in the horizontal structure of upper tropospheric clouds.

Flatau, Piotr J.↗

NASA NTRS1992

Studies of the charging of a thin dust layer in a plasma

When an infinite plane layer of dust having a number-density profile normal to the plane is exposed to an ambient e(sup -), p(sup +) plasma, one can imagine the features of the charging process near the layer boundary. If the e(sup -), p(sup +) temperatures are equal, and the B field is normal to the dust layer, the controlling factor is the large electron relative to proton speeds. Since the collision rate between plasma particles of number density n and speed v and an uncharged dust grain of radius a is estimated as the product n v pi a(exp 2), electrons dominate the charging process. The outer edge of the layer charges negatively, setting up an electrical potential that inhibits penetration of electrons into the layer and at the same time accelerates protons inward. Interior to the outer negative region then, one would expect many energetic protons compared to a reduced number of electrons from the ambient plasma. Charge imbalances are bound to arise, but the details are not so easy to deduce from simple arguments. These details are the subject of the present study.

Peterson, Lennart R.↗

NASA NTRS1994

Surface property variations in Venusian fluidized ejecta blanket craters

A comprehensive study of Magellan Cycles 1 and 2 radar data from Venus reveals surface roughness and dielectric variations associated with fluidized ejecta blanket (FEB) craters that help illuminate styles of flow ejecta emplacement. This study develops new procedures of digital unit mapping and polygon-filling algorithms using Magellan synthetic aperture radar (SAR), altimetry, and radiometry data. These techniques allow the extraction of radiophysical information for FEB crater materials, nearby plains, and lava flows. Backscatter curve slopes of the FEBs studied here are consistent with surface textures that are transitional between a'a and pahoehoe-like. Average surface property values of ejecta units are relatively similar for a given crater, but are discernibly different from other craters. Individual crater ejecta reflectivity and emissivity values are relatively similar to those for the surrounding plains, which may suggest a link between plains material and ejecta dielectric properties. Increasing FEB roughness downflow are interpreted to be associated with more lava-like flows, while decreasing roughness are more similar to trends typical of gravity (pyroclastic-like or debris-like) flows. Most commonly, FEB crater flow materials exhibit transitions from proximal, lava/melt-like flow styles to distal, gravity flow-like styles. Some FEBs show more complicated behavior, however, or appear to be more dominated by dielectric differences downflow, as inferred from correlations between the data sets. Such transitions may result from changes in local topography or from overlapping of flow lobes during FEB emplacement.

Johnson, Jeffrey R.↗

NASA NTRS1993

Stochastic dynamics of baroclinic waves

The maintenance of variance and attendant heat flux in linear, forced dissipative baroclinic shear flows subject to stochastic excitation is examined. The baroclinic problem, is intrinsically nonnormal and its stochastic dynamics is found to differ significantly from the more familiar stochastic dynamics of normal systems. When the shear is sufficiently great in comparison to dissipative effects, stochastic excitation supports highly enhanced variance levels in these nonnormal systems compared to variance levels supproted by the same forcing and dissipation in related normal systems. The eddy variance and associated heat flux are found to arise in response to transient amplification of a subset of forcing functions that obtain energy from the mean flow and project this energy on a distinct subset of response functions (EOFs) that are in turn distinct from the set of normal modes of the system. A method for obtaining the dominant forcing and response functions as well as the distribution of heat flux for a given flow is described.

Farrell, Brian F.↗

NASA NTRS2002

The Millimeter-Wave Properties of Superconducting Microstrip Lines

We have developed a novel technique for making high quality measurements of the millimeter-wave properties of superconducting thin-film microstrip transmission lines. Our experimental technique currently covers the 75-100 GHz band. The method is based on standing wave resonances in an open ended transmission line. We obtain information on the phase velocity and loss of the microstrip. Our data for Nb/SiO/Nb lines, taken at 4.2 K and 1.6 K, can be explained by a single set of physical parameters. Our preliminary conclusion is that the loss is dominated by the SiO dielectric, with a temperature-independent loss tangent of 5.3 +/- 0.5 x 10(exp -3) for our samples.

Vayonakis, A.↗

NASA NTRS2004

Active learning in the presence of unlabelable examples

We propose a new active learning framework where the expert labeler is allowed to decline to label any example. This may be necessary because the true label is unknown or because the example belongs to a class that is not part of the real training problem. We show that within this framework, popular active learning algorithms (such as Simple) may perform worse than random selection because they make so many queries to the unlabelable class. We present a method by which any active learning algorithm can be modified to avoid unlabelable examples by training a second classifier to distinguish between the labelable and unlabelable classes. We also demonstrate the effectiveness of the method on two benchmark data sets and a real-world problem.

active learning↗

NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗

NASA NTRS2011

Developer Tools for Evaluating Multi-Objective Algorithms

Multi-objective algorithms for scheduling offer many advantages over the more conventional single objective approach. By keeping user objectives separate instead of combined, more information is available to the end user to make trade-offs between competing objectives. Unlike single objective algorithms, which produce a single solution, multi-objective algorithms produce a set of solutions, called a Pareto surface, where no solution is strictly dominated by another solution for all objectives. From the end-user perspective a Pareto-surface provides a tool for reasoning about trade-offs between competing objectives. From the perspective of a software developer multi-objective algorithms provide an additional challenge. How can you tell if one multi-objective algorithm is better than another? This paper presents formal and visual tools for evaluating multi-objective algorithms and shows how the developer process of selecting an algorithm parallels the end-user process of selecting a solution for execution out of the Pareto-Surface.

multi-objective optimization↗

NASA NTRS2022

Global Driving of Auroral Precipitation: 1. Balance of Sources

The accurate determination of auroral precipitation in global models has remained a daunting and rather inexplicable obstacle. Understanding the calculation and balance of multiple sources that constitute the aurora, and their eventual conversion into ionospheric electrical conductance, is critical for improved prediction of space weather events. In this study, we present a semi-physical global modeling approach that characterizes contributions by four types of precipitation—monoenergetic, broadband, electron, and ion diffuse—to ionospheric electrodynamics. The model uses a combination of adiabatic kinetic theory and loss parameters derived from historical energy flux patterns to estimate auroral precipitation from magnetohydrodynamic (MHD) quantities. It then converts them into ionospheric conductance that is used to compute the ionospheric feedback to the magnetosphere. The model has been employed to simulate the 5–7 April 2010 Galaxy15 space weather event. Comparison of auroral fluxes show good agreement with observational data sets like NOAA-DMSP and OVATION Prime. The study shows a dominant contribution by electron diffuse precipitation, accounting for ∼74% of the auroral energy flux. However, contributions by monoenergetic and broadband sources dominate during times of active upstream solar conditions, providing for up to 61% of the total hemispheric power. The study also finds a greater role played by broadband precipitation in ionospheric electrodynamics which accounts for ∼31% of the Pedersen conductance.

Agnit Mukhopadhyay↗

NASA NTRS2010

Multiphysics Modeling for Dimensional Analysis of a Self-Heated Molten Regolith Electrolysis Reactor for Oxygen and Metals Production on the Moon and Mars

The technology of direct electrolysis of molten lunar regolith to produce oxygen and molten metal alloys has progressed greatly in the last few years. The development of long-lasting inert anodes and cathode designs as well as techniques for the removal of molten products from the reactor has been demonstrated. The containment of chemically aggressive oxide and metal melts is very difficult at the operating temperatures ca 1600 C. Containing the molten oxides in a regolith shell can solve this technical issue and can be achieved by designing a self-heating reactor in which the electrolytic currents generate enough Joule heat to create a molten bath. In a first phase, a thermal analysis model was built to study the formation of a melt of lunar basaltic regolith irradiated by a focused solar beam This mode of heating was selected because it relies on radiative heat transfer, which is the dominant mode of transfer of energy in melts at 1600 C. Knowing and setting the Gaussian-type heat flux from the concentrated solar beam and the phase and temperature dependent thermal properties, the model predicts the dimensions and temperature profile of the melt. A validation of the model is presented in this paper through the experimental formation of a spherical cap melt realized by others. The Orbitec/PSI experimental setup uses an 3.6-cm diameter concentrated solar beam to create a hemispheric melt in a bed of lunar regolith simulant contained in a large pot. Upon cooling, the dimensions of the vitrified melt are measured to validate the thermal model. In a second phase, the model is augmented by multiphysics components to compute the passage of electrical currents between electrodes inserted in the molten regolith. The current through the melt generates Joule heating due to the high resistivity of the medium and this energy is transferred into the melt by conduction, convection and primarily by radiation. The model faces challenges in two major areas, the change of phase as temperature increases, and the dominance of radiative heat flux as heat transfer mechanism within the melt the change of phase concerns the regolith itself which is present in states ranging from a fine grain regolith with low thermal conductivity and low density to a vitrified melt with much higher thermal conductivity, and higher density. As the regolith is heated, it starts to soften around 1300 C the melt iS very viscous and evolving gas bubbles out in thick, lava-like fashion. By 1600 C the regolith is completely melted and the viscosity is low The second challenge resides in the proper modeling of the radiative heat flux requiring the addition of the computing-demanding radiative-heat-transfer function to the general heat transfer equation. The model Includes temperature-dependent properties (density, thermal conductivity, heat capacity, and viscosity, and absorption coefficients) and solves the radiative heat flux equation assuming gray (fine grains) and semi-transparent (melt) media and using an absorption coefficient spectral found in the literature for terrestrial minerals similar in composition to those of lunar regolith simulant

Dominguez, Jesus A.↗

NASA NTRS1992

The diffuse interstellar cloud toward HD 179406 (20 Aquilae)

An analysis of the diffuse interstellar cloud complex in front of HD 179406 (20 Aql) is presented. Along this sight line, multispectral absortion- and emission-line studies have uncovered at least three distinct velocity components due to individual clouds. A dominant velocity component is seen in both the absorption and emission-line data sets at 3 +/- 1 km/s. It is argued that the cloud associated with this velocity component is responsible for most of the atomic and all of the molecular gas in front of 20 Aql. The present chemical and physical analysis of the cloud combines the diagnostic tools of radio emission-line data with those of UV and optical absorption data. Using non-LTE models to synthesize the observed absorption profiles, (C-12)O and (C-13)O column densities along this line of sight are determined. The (C-12)O/(C-13)O abundance ratio was found to be 50 +/- 15, similar to that found by Wannier et al. toward Zeta Oph. The physical conditions of the cloud have been investigated using ultraviolet absorption lines. Measurements indicate that the dominant absorption cloud has a gas pressure similar to that found in the local diffuse molecular cloud in Ophiuchus with nT = 20,000/cu cm K.

Hanson, Margaret M.↗

NASA NTRS2005

The Application of Infrared Thermographic Inspection Techniques to the Space Shuttle Thermal Protection System

The Nondestructive Evaluation Sciences Branch at NASA s Langley Research Center has been actively involved in the development of thermographic inspection techniques for more than 15 years. Since the Space Shuttle Columbia accident, NASA has focused on the improvement of advanced NDE techniques for the Reinforced Carbon-Carbon (RCC) panels that comprise the orbiter s wing leading edge. Various nondestructive inspection techniques have been used in the examination of the RCC, but thermography has emerged as an effective inspection alternative to more traditional methods. Thermography is a non-contact inspection method as compared to ultrasonic techniques which typically require the use of a coupling medium between the transducer and material. Like radiographic techniques, thermography can be used to inspect large areas, but has the advantage of minimal safety concerns and the ability for single-sided measurements. Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. A typical implementation of PCA is when the eigenvectors are generated from the data set being analyzed. Although it is a powerful tool for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the "good" material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued where a fixed set of eigenvectors, generated from an analytic model of the thermal response of the material under examination, is used to process the thermal data from the RCC materials. Details of a one-dimensional analytic model and a two-dimensional finite-element model will be presented. An overview of the PCA process as well as a quantitative signal-to-noise comparison of the results of performing both embodiments of PCA on thermographic data from various RCC specimens will be shown. Finally, a number of different applications of this technology to various RCC components will be presented.

Cramer, K. E.↗

NASA NTRS2006

The Application of Principal Component Analysis Using Fixed Eigenvectors to the Infrared Thermographic Inspection of the Space Shuttle Thermal Protection System

The Nondestructive Evaluation Sciences Branch at NASA s Langley Research Center has been actively involved in the development of thermographic inspection techniques for more than 15 years. Since the Space Shuttle Columbia accident, NASA has focused on the improvement of advanced NDE techniques for the Reinforced Carbon-Carbon (RCC) panels that comprise the orbiter s wing leading edge. Various nondestructive inspection techniques have been used in the examination of the RCC, but thermography has emerged as an effective inspection alternative to more traditional methods. Thermography is a non-contact inspection method as compared to ultrasonic techniques which typically require the use of a coupling medium between the transducer and material. Like radiographic techniques, thermography can be used to inspect large areas, but has the advantage of minimal safety concerns and the ability for single-sided measurements. Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. A typical implementation of PCA is when the eigenvectors are generated from the data set being analyzed. Although it is a powerful tool for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the good material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued when a fixed set of eigenvectors is used to process the thermal data from the RCC materials. These eigen vectors can be generated either from an analytic model of the thermal response of the material under examination, or from a large cross section of experimental data. This paper will provide the details of the analytic model; an overview of the PCA process; as well as a quantitative signal-to-noise comparison of the results of performing both embodiments of PCA on thermographic data from various RCC specimens. Details of a system that has been developed to allow insitu inspection of a majority of shuttle RCC components will be presented along with the acceptance test results for this system. Additionally, the results of applying this technology to the Space Shuttle Discovery after its return from flight will be presented.

Cramer, K. Elliott↗

NASA NTRS2015

Principal Component Analysis of Thermographic Data

Principal Component Analysis (PCA) has been shown effective for reducing thermographic NDE data. While a reliable technique for enhancing the visibility of defects in thermal data, PCA can be computationally intense and time consuming when applied to the large data sets typical in thermography. Additionally, PCA can experience problems when very large defects are present (defects that dominate the field-of-view), since the calculation of the eigenvectors is now governed by the presence of the defect, not the "good" material. To increase the processing speed and to minimize the negative effects of large defects, an alternative method of PCA is being pursued where a fixed set of eigenvectors, generated from an analytic model of the thermal response of the material under examination, is used to process the thermal data from composite materials. This method has been applied for characterization of flaws.

Winfree, William P.↗