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NASA NTRS2014

Additive Manufacturing Design Considerations for Liquid Engine Components

The Marshall Space Flight Center's Propulsion Systems Department has gained significant experience in the last year designing, building, and testing liquid engine components using additive manufacturing. The department has developed valve, duct, turbo-machinery, and combustion device components using this technology. Many valuable lessons were learned during this process. These lessons will be the focus of this presentation. We will present criteria for selecting part candidates for additive manufacturing. Some part characteristics are 'tailor made' for this process. Selecting the right parts for the process is the first step to maximizing productivity gains. We will also present specific lessons we learned about feature geometry that can and cannot be produced using additive manufacturing machines. Most liquid engine components were made using a two-step process. The base part was made using additive manufacturing and then traditional machining processes were used to produce the final part. The presentation will describe design accommodations needed to make the base part and lessons we learned about which features could be built directly and which require the final machine process. Tolerance capabilities, surface finish, and material thickness allowances will also be covered. Additive Manufacturing can produce internal passages that cannot be made using traditional approaches. It can also eliminate a significant amount of manpower by reducing part count and leveraging model-based design and analysis techniques. Information will be shared about performance enhancements and design efficiencies we experienced for certain categories of engine parts.

Whitten, Dave↗
NASA NTRS2017

Models of Sector Flows Under Local, Regional and Airport Weather Constraints

Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permits better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools providing assistance would be particularly helpful in effective use of CTOPs. Such DSTs tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of maximum flows in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of flows under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained flow reduction model and then composing these into a single integrated model. A nominal demand model is a flow model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to the location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. In contrast, empirical models do better than theoretical models when there is some data available. The biggest benefit of theoretical models is their general applicability in wider range situations once the degree of accuracy of these has been established.

Kulkarni, Deepak↗
NASA NTRS2017

Background and Lunar Neutron Populations Detected by LEND and Average Concentration of Near-Surface Hydrogen near the Moon's Poles

Neutron flux measurements by the Lunar Exploration Neutron Detector (LEND) on the Lunar Reconnaissance Orbiter (LRO) enable quantifying hydrogen-bearing volatiles in the lunar surface from orbit. Accurately determining hydrogen abundance requires discriminating between the instrument background detection rate and the population of lunar-sourced neutrons that are sensitive to surficial hydrogen. We have investigated the detection rate for lunar and non-lunar (spacecraft-sourced) neutrons in LEND by modeling maps of measured count rate in three LEND detector systems using linear combinations of maps compiled from LEND detectors and from the Lunar Prospector Neutron Spectrometer. We find that 30% of the global-average 24.926 +/- 0.020 neutron counts per second (cps) detected by the LEND STN3 thermal-energy neutron sensor are lunar-sourced neutrons in the thermal energy range (E < 0.4 eV), 65% are lunar-sourced neutrons in the epithermal and fast energy range (E > 0.4 eV), and 5% are from spacecraft-sourced background signal. In the SETN epithermal neutron detector, 90% of the 10.622 +/- 0.002 neutron detections per second are consistent with a lunar source of epithermal and fast neutrons combined (E > 0.4 eV), with 3% due to lunar-sourced thermal neutron leakage into the detector (E < 0.4 eV), and background signal accounting for 7% of total detections. Background signal due to spacecraft-derived neutrons is substantial in the CSETN collimated detector system, accounting for 57% of the global average detection rate of 5.082 +/- 0.001 cps, greater than the 48% estimated from cruise-phase data. Lunar-sourced epithermal and fast neutrons account for 43% of detected neutrons, including neutrons in collimation as well as neutrons that penetrate the collimator wall to reach the detector. We estimate a lower limit of 17% of lunar-sourced neutrons detected by CSETN are epithermal neutrons in collimation (0.37 cps), with an upper limit estimate of 54 +/- 11% of lunar-sourced neutrons received in collimation, or 1.2 +/- 0.2 cps global average. The pole-to-equator contrast ratio in epithermal and high-energy epithermal neutron flux indicates that the average concentration of hydrogen in the polar regolith above 80deg north or south latitude is ∼105 ppmw (parts per million by weight), or 0.095 +/- 0.01 wt% water-equivalent hydrogen. Above 88deg north or south, the concentration increases to ∼140 ppmw, or 0.13 +/- 0.02 wt% water-equivalent hydrogen. The similar pattern of neutron flux suppression at both poles suggests that hydrogen concentration generally increases nearer the pole and is not closely associated with a specific feature such as Shackleton Crater at the lunar south pole that has no northern counterpart. Epithermal neutron flux decreases with increasing latitude outside the polar regions, consistent with surface hydration that increases with latitude if that hydration extends to ∼13-40 cm into the surface.

T A Livengood↗
NASA NTRS2018

Background and Lunar Neutron Populations Detected by LEND and Average Concentration of Near-Surface Hydrogen near the Moon's Poles

Neutron flux measurements by the Lunar Exploration Neutron Detector (LEND) on the Lunar Reconnaissance Orbiter (LRO) enable quantifying hydrogen-bearing volatiles in the lunar surface from orbit. Accurately determining hydrogen abundance requires discriminating between the instrument background detection rate and the population of lunar-sourced neutrons that are sensitive to surficial hydrogen. We have investigated the detection rate for lunar and non-lunar (spacecraft-sourced) neutrons in LEND by modeling maps of measured count rate in three LEND detector systems using linear combinations of maps compiled from LEND detectors and from the Lunar Prospector Neutron Spectrometer. We find that 30% of the global-average 24.926 0.020 neutron counts per second (cps) detected by the LEND STN3 thermal-energy neutron sensor are lunar-sourced neutrons in the thermal energy range (E < 0.4 eV), 65% are lunar-sourced neutrons in the epithermal and fast energy range (E > 0.4 eV), and 5% are from spacecraft-sourced background signal. In the SETN epithermal neutron detector, 90% of the 10.622 0.002 neutron detections per second are consistent with a lunar source of epithermal and fast neutrons combined (E > 0.4 eV), with 3% due to lunar-sourced thermal neutron leakage into the detector (E < 0.4 eV), and background signal accounting for 7% of total detections. Background signal due to spacecraft-derived neutrons is substantial in the CSETN collimated detector system, accounting for 57% of the global average detection rate of 5.082 0.001 cps, greater than the 48% estimated from cruise-phase data. Lunar-sourced epithermal and fast neutrons account for 43% of detected neutrons, including neutrons in collimation as well as neutrons that penetrate the collimator wall to reach the detector. We estimate a lower limit of 17% of lunar-sourced neutrons detected by CSETN are epithermal neutrons in collimation (0.37 cps), with an upper limit estimate of 54 11% of lunar-sourced neutrons received in collimation, or 1.2 0.2 cps global average. The pole-to-equator contrast ratio inepithermal and high-energy epithermal neutron flux indicates that the average concentration of hydrogen in the polar regolith above 80 north or south latitude is ~105 ppmw (parts per million by weight), or 0.095 0.01 wt% water-equivalent hydrogen. Above 88 north or south, the concentration increases to ~140 ppmw, or 0.13 0.02 wt% water-equivalent hydrogen. The similar pattern of neutron flux suppression at both poles suggests that hydrogen concentration generally increases nearer the pole and is not closely associated with a specific feature such as Shackleton Crater at the lunar south pole that has no northern counterpart. Epithermal neutron flux decreases with increasing latitude outside the polar regions, consistent with surface hydration that increases with latitude if that hydration extends to ~13-40 cm into the surface.

Livengood, Timothy A.↗
NASA NTRS1986

Star counts and galactic structure

Star counts are discussed as an aid in studies of galactic structure. Iterative computations using a method-of-color-bins to match numerical models with observational data are described. The star counts provide bounds for the luminosity function and the color-magnitude diagram and allow spheroid normalization in a copycat Galaxy model which posits a galaxy with a Population I disk and a Population II spheroid. Good agreement has been obtained between star counts predicted by the model and observed distributions, including color and magnitude ranges and direction. Modifications being considered for the model include consideration of the halo, a galactic bulge and a thick disk. Several galactic structural features which have yet to be modeled and which may be tractable to the copycat model corrected with star counts are identified.

Bahcall, John N.↗
NASA NTRS1994

Two-sample discrimination of Poisson means

This paper presents a statistical test for detecting significant differences between two random count accumulations. The null hypothesis is that the two samples share a common random arrival process with a mean count proportional to each sample's exposure. The model represents the partition of N total events into two counts, A and B, as a sequence of N independent Bernoulli trials whose partition fraction, f, is determined by the ratio of the exposures of A and B. The detection of a significant difference is claimed when the background (null) hypothesis is rejected, which occurs when the observed sample falls in a critical region of (A, B) space. The critical region depends on f and the desired significance level, alpha. The model correctly takes into account the fluctuations in both the signals and the background data, including the important case of small numbers of counts in the signal, the background, or both. The significance can be exactly determined from the cumulative binomial distribution, which in turn can be inverted to determine the critical A(B) or B(A) contour. This paper gives efficient implementations of these tests, based on lookup tables. Applications include the detection of clustering of astronomical objects, the detection of faint emission or absorption lines in photon-limited spectroscopy, the detection of faint emitters or absorbers in photon-limited imaging, and dosimetry.

Lampton, M.↗
NASA NTRS1992

Correction for nonlinear photon counting effects in lidar systems

Photomultiplier tubes (PMT's) employed in the photon counting (PC) mode of operation are widely used as detectors in lidar systems. In our laboratory, we have developed a versatile Nd:YAG lidar which is used for measurement of both the middle atmosphere and the troposphere. With this system, we encounter a very wide range of signal levels ranging from the extremely weak signals from the top of the mesosphere to the very strong returns from low level clouds. Although the system is capable of operating the PMT's in either the analog detection or photon counting mode, we find that often when we use photon counting we have portions of our lidar return which contain very useful information but are not within the linear operating regime of the PC system. We report the results of our efforts to explore the extent to which such high intensity PC signals can be quantitatively analyzed. In particular, a useful model relating the mean 'true' count rate and the observed count rate is presented and it's application to our system demonstrated. This model takes into account the variation in height of the PMT output pulses and the effect of the pulse height discrimination threshold.

Donovan, D. P.↗
NASA NTRS1991

Evolving starburst galaxies, faint number counts, and the 2 keV background

Blue and 60 micron extragalactic number counts and redshift distributions are modeled using evolutionary models in which galaxies periodically undergo transient starburst events. Support is found for the hypothesis that the same starburst phenomenon is responsible for the excess source counts seen at both wavelengths, though observed at lower mean redshift in the far infrared than in the blue. The soft X-ray emission from these evolving starburst events is not likely to exceed the 2 keV background unless the evolutionary rate is greater than (1 + z)-cubed (luminosity or density evolution) and the redshift of galaxy formation is greater than about five.

Lonsdale, C.↗
NASA NTRS2021

Modeling of the Tau and Muon Neutrino-induced Optical Cherenkov Signals from Upward-moving Extensive Air Showers

We present a detailed modeling and computation methodology to determine the optical Cherenkovsignals produced by upward-moving extensive air showers (EASs) induced byτ-leptons and muons,sourced from the interaction of high-energy astrophysical neutrinos interacting in the Earth. Fol-lowing and extending the physics modeling and Cherenkov signal simulations performed in [1], thisscheme encompasses a new, state-of-the-art computation of the muon neutrino propagation insidethe Earth and the contribution to theτ-lepton muon decay channel. The modeling takes into ac-count all possibleτ-lepton decay and muon energy loss channels that feed the optical Cherenkovemission, produced by both tau and muon initiated EASs. The EAS modeling uses the electronenergy, angular, and lateral distributions in the EAS and their evolution as well as the wavelengthdependence of the Cherenkov emission and its atmospheric attenuation. The results presented hereare focused on the detection capabilities of sub-orbital (balloon-borne) and orbital (satellite) basedinstruments. The latter case was calculated for POEMMAato compare to that presented in [1],specifically including the muon-decay channel ofτ-leptons and the muonic EAS Cherenkov signalfrom muon neutrino interactions in the Earth. By detailing all these individual contributions tothe optical Cherenkov emission and detection, we show how the ensemble that includes muonicchannels provides a large detection capability for space-based, high-energy cosmic neutrino detec-tion. Specifically, we show that for neutrino energies∼<10 PeV, the upward-EAS sensitivity due tomuon neutrino interactions in the Earth begin to dominate over that for tau neutrino interactions,effectively extending the neutrino sensitivity to lower energies.

A L Cummings↗
NASA NTRS1972

Photon counting and Laguerre detection.

In this correspondence maximum-likelihood binary detection theory is applied to an incoherent optical system model employing photodetectors governed by Laguerre counting statistics. It is shown that a maximum-likelihood Laguerre detector corresponds to a count comparison over each signaling interval. Laguerre error probabilities are presented and compared with those for Poisson counting.

Gagliardi, R. M.↗
NASA NTRS2011

Correlations in the (Sub)Mil1imeter Background from ACT x BLAST

We present measurements of the auto- and cross-frequency correlation power spectra of the cosmic (sub)millimeter background at: 250, 350, and 500 microns (1200, 860, and 600 GHz) from observations made with the Balloon-borne Large Aperture Submillimeter Telescope, BLAST; and at 1380 and 2030 microns (218 and 148 GHz) from observations made with the Atacama Cosmology Telescope, ACT. The overlapping observations cover 8.6 deg(sup 2) in an area relatively free of Galactic dust near the south ecliptic pole (SEP). The ACT bands are sensitive to radiation from the CMB, the Sunyaev-Zel'dovich (SZ) effect from galaxy clusters, and to emission by radio and dusty star-forming galaxies (DSFGs), while the dominant contribution to the BLAST bands is from DSFGs. We confirm and extend the BLAST analysis of clustering with an independent pipeline, and also detect correlations between the ACT and BLAST maps at over 25(sigma) significance, which we interpret as a detection of the DSFGs in the ACT maps. In addition to a Poisson component in the cross-frequency power spectra, we detect a clustered signal at 4(sigma), and using a model for the DSFG evolution and number counts, we successfully fit all our spectra with a linear clustering model and a bias that depends only on red shift and not on scale. Finally, the data are compared to, and generally agree with, phenomenological models for the DSFG population. This study represents a first of its kind, and demonstrates the constraining power of the cross-frequency correlation technique to constrain models for the DSFGs. Similar analyses with more data will impose tight constraints 011 future models.

Hajian, Amir↗
NASA NTRS1980

Star counts as an indicator of galactic structure and quasar evolution

A detailed model of the stellar content of the Galaxy is described briefly. Illustrative applications of the model are made, using existing data, to indicate how star counts can be used to determine some parameters of galactic structure, to detect a massive (stellar) halo, and to constrain models of quasar evolution.

Bahcall, J. N.↗
NASA NTRS1995

The axis ratio distribution of faint galaxies: Evidence for a populatin of dwarfgalaxies at I approximately 20.5

The axis ratio distribution of faint galaxies observed by the Hubble Space Telescope (HST) as part of the Medium Deep Survey (MDS) key project suggests that a very large fraction of the total population at magnitudes I greater than or equal to 20 mag consists of a class of galaxies with luminosity profile, axis ratio distribution, angular size, and color that resemble local dwarfs. We find that galaxies with exponential light profiles and small angular sizes (half-light radius less than 0.6 sec) have an axis ratio distribution that is incompatible with their being intrinsically flattened objects and is instead consistent with local elliptical galaxies. We call these objects 'Small Exponential Ellipticals.' They are most likely dwarf galaxies, and they are numerous enough that, together with irregular galaxies, they can account for most if not all of the excess in the number counts at I approximately 20-21 mag with respect to the standard no-evolution models. This may suggest that the excess number counts are best explained by dwarf-rich models with strong luminosity evolution of the dwarf galaxies. Our data also supports a very mild luminosity evolution of the giant galaxy populations, which contributes little to the excess number counts.

Im, Myungshin↗
NASA NTRS2004

Study of CFD Variation on Transport Configurations from the Second Drag-Prediction Workshop

This paper describes and analyzes a series of nearly 90 CFD test cases performed as a contribution to the second Drag Prediction Workshop, held in association with the AIAA in June 2003. Two configurations are included: DLR-F6 wing-body and wing-body-nacelle-pylon. The ability of CFD to predict the drag, lift, and pitching moment from experiment-including the "delta" arising from the addition of the nacelle and pylon-is assessed. In general, at a fixed angle of attack CFD overpredicts lift, but predicts the delta C (sub L) reasonably well. At low lift levels (C (sub L) less than 0.3)), delta C (sub D) is 20-30 drag counts (30-45%) high. At the target lift coefficient of C(sub L) = 0.5, delta C (sub D) is overpredicted by between 11-16 counts. However, the primary contribution of this paper is mot so much the assessment of CFD against experiment, but rather a detailed assessment and analysis of CFD variation. The series of test cases are designed to determine the sensitivity/variability of CFD to a variety of factors, including grid, turbulence model, transition code, and viscous model. Using medium-level grids (6-11 million points) at the target lift coefficient, the maximum variation in drag due to different grids is 5-11 drag counts, due to code is 5-10 counts, due to turbulence model is 7-15 counts, due to transition is 10-11 counts, and due to viscous model is 4-5 counts. Other specific variations are described in the paper.

Christopher L Rumsey↗
NASA NTRS2013

Characterization of the 2012-044C Briz-M Upper Stage Breakup

The NASA breakup model prediction was close to the observed population for catalog objects. The NASA breakup model predicted a larger population than was observed for objects under 10 cm. The stare technique produces low observation counts, but is readily comparable to model predictions. Customized stare parameters (Az, El, Range) were effective to increase the opportunities for HAX to observe the debris cloud. Other techniques to increase observation count will be considered for future breakup events.

Hamilton, Joseph A.↗
NASA NTRSDate not supplied

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of trained machine-learning models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a Windows app that has been created to deploy trained machine-learning models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of machine-learning application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). Current version of the app focuses on the performance prediction of conventional turbofans. The app gets user input for a turbofan design, preprocesses the input data, and deploys trained machine-learning models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The machine-learning predictive models were built by employing supervised deep-learning algorithm to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these machine-learning models using the app shows that Aero-Engines AI is an easy-to-use and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage.

machine learning↗
NASA NTRS1994

The Galactic far-ultraviolet sky as seen by Faust: Modeling and observations

We test the model of the Galactic point source sky recently extended to the far-ultraviolet by Cohen (1994) against the set of Galactic far-ultraviolet point sources detected by the Far Ultraviolet Space Telescope (FAUST) experiment. We find excellent agreement between the predicted (log N, log S) and the observed source counts for a range of Galactic directions observed by Faust. At low galactic latitudes, we can directly infer the amount of interstellar extinction in a given direction associated with local molecular complexes, based on comparison of model calculations and FAUST star counts. The model can also be used to predict the statistical stellar content of any field. We compare the model predcitions with the observations of Brosch et al. (1994), who have spectroscopically studied an optically identified complete sample of FAUST objects in a region near the north Galactic pole. We have used the model to determine that the contribution of far-ultraviolet stars fainter than 6 x 10(exp -14) ergs/s/sq cm/A (the FAUST detection limit) is less than 1% of the diffuse sky brightness, and less than about 4% of the total point source flux.

Cohen, Martin↗
NASA NTRS2017

Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD): Data and Tools for Dynamic Management and Decision Support

The Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD) is a web-based, open access, decision-support tool designed to assist scientists, non-governmental organizations and policy-makers working to meet the management objectives as set forth by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) and other components of the Antarctic Treaty System (ATS) (that is, Consultative Meetings and the ATS Committee on Environmental Protection). MAPPPD was designed specifically to complement existing efforts such as the CCAMLR Ecosystem Monitoring Program (CEMP) and the ATS site guidelines for visitors. The database underlying MAPPPD includes all publicly available (published and unpublished) count data on emperor, gentoo, Adelie) and chinstrap penguins in Antarctica. Penguin population models are used to assimilate available data into estimates of abundance for each site and year.Results are easily aggregated across multiple sites to obtain abundance estimates over any user-defined area of interest. A front end web interface located at www.penguinmap.com provides free and ready access to the most recent count and modelled data, and can act as a facilitator for data transfer between scientists and Antarctic stakeholders to help inform management decisions for the continent.

Humphries, G. R. W.↗