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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Modeling the Redshift Evolution of the Normal Galaxy X-Ray Luminosity Function

Emission from X-ray binaries (XRBs) is a major component of the total X-ray luminosity of normal galaxies, so X-ray studies of high-redshift galaxies allow us to probe the formation and evolution of XRBs on very long timescales (approximately 10 Gyr). In this paper, we present results from large-scale population synthesis models of binary populations in galaxies from z = 0 to approximately 20. We use as input into our modeling the Millennium II Cosmological Simulation and the updated semi-analytic galaxy catalog by Guo et al. to self-consistently account for the star formation history (SFH) and metallicity evolution of each galaxy. We run a grid of 192 models, varying all the parameters known from previous studies to affect the evolution of XRBs. We use our models and observationally derived prescriptions for hot gas emission to create theoretical galaxy X-ray luminosity functions (XLFs) for several redshift bins. Models with low common envelope efficiencies, a 50% twins mass ratio distribution, a steeper initial mass function exponent, and high stellar wind mass-loss rates best match observational results from Tzanavaris & Georgantopoulos, though they significantly underproduce bright early-type and very bright (L(sub x) greater than 10(exp 41)) late-type galaxies. These discrepancies are likely caused by uncertainties in hot gas emission and SFHs, active galactic nucleus contamination, and a lack of dynamically formed low-mass XRBs. In our highest likelihood models, we find that hot gas emission dominates the emission for most bright galaxies. We also find that the evolution of the normal galaxy X-ray luminosity density out to z = 4 is driven largely by XRBs in galaxies with X-ray luminosities between 10(exp 40) and 10(exp 41) erg s(exp −1).

Tremmel, M.↗
NASA NTRS1988

A method for modeling bias in a person's estimates of likelihoods of events

It is of practical importance in decision situations involving risk to train individuals to transform uncertainties into subjective probability estimates that are both accurate and unbiased. We have found that in decision situations involving risk, people often introduce subjective bias in their estimation of the likelihoods of events depending on whether the possible outcomes are perceived as being good or bad. Until now, however, the successful measurement of individual differences in the magnitude of such biases has not been attempted. In this paper we illustrate a modification of a procedure originally outlined by Davidson, Suppes, and Siegel (3) to allow for a quantitatively-based methodology for simultaneously estimating an individual's subjective utility and subjective probability functions. The procedure is now an interactive computer-based algorithm, DSS, that allows for the measurement of biases in probability estimation by obtaining independent measures of two subjective probability functions (S+ and S-) for winning (i.e., good outcomes) and for losing (i.e., bad outcomes) respectively for each individual, and for different experimental conditions within individuals. The algorithm and some recent empirical data are described.

Nygren, Thomas E.↗
NASA NTRS2007

Surveillance and Control of Malaria Transmission in Thailand using Remotely Sensed Meteorological and Environmental Parameters

These slides address the use of remote sensing in a public health application. Specifically, this discussion focuses on the of remote sensing to detect larval habitats to predict current and future endemicity and identify key factors that sustain or promote transmission of malaria in a targeted geographic area (Thailand). In the Malaria Modeling and Surveillance Project, which is part of the NASA Applied Sciences Public Health Applications Program, we have been developing techniques to enhance public health's decision capability for malaria risk assessments and controls. The main objectives are: 1) identification of the potential breeding sites for major vector species; 2) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity; 3) implementation of a dynamic transmission model to identify the key factors that sustain or intensify malaria transmission. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. !> Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment include AVHRR Pathfinder, TRMM, MODIS, NSIPP, and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of the remotely sensed parameters. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Discrete event simulations are used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to the Greater Mekong Subregion. Our models have been applied to malaria in Indonesia, Korea, and other regions in the world with similar success.

Kiang, Richard K.↗
DOE OSTI2026

A Simulator for Neyer Tests of Explosives

Explosives and explosive devices such as detonators are typically tested by applying a range of stimuli such as voltage or mechanical shock, and recording binary “detonated/did not detonate” responses. These are analyzed using maximum likelihood or generalized linear models to provide estimates of quantities such as the all-fire and no-fire points. Given that the true threshold for detonation is unknown a priori , sequential design methods are typically used to optimize the set of test points. One popular method, implemented in commercial software, is Neyer’s algorithm. To support simulation and experimental design, we have developed code in the R programming language to duplicate the functions of the Neyer software. We provide code for the simulator along with a description and examples of usage.

42 ENGINEERING↗
NASA NTRS1985

Extraction of aerodynamic parameters for aircraft at extreme flight conditions

The maximum likelihood estimator has been used to extract stability and control derivatives from flight data for many years. Most of the literature on aircraft estimation concentrates on new developments and applications, assuming familiarity with basic concepts. This paper briefly discusses the maximum likelihood estimator and the aircraft equations of motion that the estimator uses. The current strength and limitations associated with obtaining flight-determined aerodynamic coefficients in extreme flight conditions is assessed. The importance of the careful combining of wind tunnel results (or calculations) and flight results and the thorough evaluation of the mathematical model is emphasized. The basic concepts of minimization and estimation are examined for a simple computed aircraft example, and the cost functions that are to be minimized during estimation are defined and discussed. Graphic representations of the cost functions are given to help illustrate the minimization process. Finally, the basic concepts are generalized, and estimation of stability and control derivatives from flight data is discussed.

Iliff, K. W.↗
NASA NTRS2007

Future Fuel Scenarios and Their Potential Impact to Aviation

In recent years fuel prices have been growing at a rapid pace. Current conservative projections predict that this is only a function of the natural volatility of oil prices, similar to the oil price spikes experienced in the 1970s. However, there is growing concern among analysts that the current price increases may not only be permanent, but that prices may continue to increase into the future before settling down at a much higher level than today. At high enough fuel prices, the aircraft industry would become very sensitive to fuel price. In this paper, the likelihood of fuel price increase is considered in three different price increase scenarios: "low," "medium," and "high." The impact of these scenarios on the aviation industry and alternatives are also addressed.

Hendricks, Robert C.↗
NASA NTRS2011

Future Fuel Scenarios and Their Potential Impact to Aviation

In recent years fuel prices have been growing at a rapid pace. Current conservative projections predict that this is only a function of the natural volatility of oil prices, similar to the oil price spikes experienced in the 1970s. However, there is growing concern among analysts that the current price increases may not only be permanent, but that prices may continue to increase into the future before settling down at a much higher level than today. At high enough fuel prices, the aircraft industry would become very sensitive to fuel price. In this paper, the likelihood of fuel price increase is considered in three different price increase scenarios: "low," "medium," and "high." The impact of these scenarios on the aviation industry and alternatives are also addressed.

Hendricks, Robert C.↗
DOE OSTI2026

The DESI DR1 peculiar velocity survey: growth rate measurements from the maximum likelihood fields method

We present the constraint on the growth rate of structure from the combination of DESI DR1 BGS sample, Fundamental Plane, and Tully-Fisher peculiar velocity catalogues using the maximum likelihood fields method. The combined catalogue contains 415,523 galaxy redshifts and 76,616 peculiar velocity measurements. To handle the large amount of data in the DESI DR1 peculiar velocity catalogue, we significantly improve the computational efficiency by rewriting the algorithm with JAX. After removing outliers and Tully-Fisher galaxies that are affected by systematics, we find fσ 8 = 0.483 -0.043 +0.080 (stat) ± 0.018(sys), consistent within 1σ with the power spectrum and correlation function analysis using the same dataset. Combining all three measurements with appropriate correlations, the consensus measurement is fσ 8 (z eff = 0.07) = 0.450±0.055, consistent with Planck +ΛCDM cosmology (fσ 8 = 0.449±0.008). Combining with the high redshift growth rate of structure measurements from DESI ShapeFit, the constraint on the growth index is γ = 0.58±0.11, consistent with GR.

cosmic flows↗
NASA NTRS2024

Alignment of NASA’s Human System Risks with Technological Capability Gaps to Enable Integrated Research and Technology Development Strategic Planning

BACKGROUND: Radiation, reduced gravity, distance from earth, isolation and confinement, and habitation within artificially created and controlled life support environments are hazards that present risk to human space explorers. NASA’s Human System Risk Board (HSRB) maintains a set of twenty-nine different Human System Risks with subject matter experts from across the agency providing regular updates to the estimated likelihood and consequence associated with each risk. The Human Research Program (HRP) has historically used these risk classifications as a primary basis for identifying and prioritizing human research investments aimed at characterizing and/or mitigating the respective human system risks. In many cases, technology development is required to mature and validate risk mitigation strategies, however, NASA’s primary technology development programs have not typically used Human System Risks as a basis for strategic planning. A primary function of the Environmental Control and Life Support Systems (ECLSS) – Crew Health and Performance (CHP) System Capability Leadership Team (SCLT) is to continually identify, review, and update technological capability gaps and to establish and oversee multiyear strategic roadmaps aimed at guiding NASA’s technology development priorities in these areas. These roadmaps are intended to be agency-wide and independent of any program, directorate, or other organization within NASA. DESCRIPTION: The SCLT and HRP collaborated to establish a set of Human System Capability Gaps, which establish a formal linkage between the capability gaps used to prioritize investments across much of NASA, and the Human System Risks that are primarily used to inform and prioritize human research. This set of twenty-eight gaps was developed by subject matter experts, and each gap mapped to the primary associated Human System Risks. The gaps and risk mapping were then reviewed and approved via the HSRB, thereby formally aligning the research-focused Human System Risks with the technology-focused capability gaps. DISCUSSION: This effort has enabled development of integrated roadmaps and budget coordination with research and technology development activities that are formally linked to agency-recognized capability gaps and Human System Risks. Close and ongoing coordination between the SCLT, HRP, Mars Campaign Office, and the Health & Medical Technical Authority (HMTA) is essential to ensure alignment and prioritization of CHP-related research and technology development to enable NASA’s future exploration missions.

Andrew F J Abercromby↗
NASA NTRS1985

Extraction of aerodynamic parameters for aircraft at extreme flight conditions

The maximum likelihood estimator was used to extract stability and control derivatives from flight data for many years. Most of the literature on aircraft estimation concentrates on new development and applications, assuming familiarity with basic concepts. The maximum likelihood estimator and the aircraft equations of motion that the estimator uses are discussed. The current strength and limitations associated with obtaining flight-determined aerodynamic coefficients in extreme flight conditions are assessed. The importance of the careful combining of wind tunnel results (or calculations) and flight results and the thorough evaluation of the mathematical model is emphasized. The basic concepts of minimization and estimation are examined for a simple computed aircraft example, and the cost functions that are to be minimized during estimation are defined and discussed. Graphic representations of the cost functions are given to help illustrate the minimization process. Finally, the basic concepts are generalized, and estimation of stability and control derivatives from flight data is discussed.

Iliff, K. W.↗
NASA NTRS1988

Cloud classification from satellite data using a fuzzy sets algorithm: A polar example

Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine likely areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.

Key, J. R.↗
NASA NTRS1989

Cloud classification from satellite data using a fuzzy sets algorithm - A polar example

Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine like areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.

Key, J. R.↗
NASA NTRS2000

Estimating Cosmic Ray Spectral Parameters From Simulated Detector Responses With Detector Design Implications

A simple power law model consisting of a single spectral index alpha (sub 1), is believed to be an adequate description of the galactic cosmic ray (GCR) proton flux at energies below 10(exp 13) eV, with a transition at knee energy E(sub k) to a steeper spectral index alpha(sub 2) greater than alpha(sub 1) above E(sub k). The maximum likelihood procedure is developed for estimating these three spectral parameters of the broken power law energy spectrum from simulated detector responses. These estimates and their surrounding statistical uncertainty are being used to derive the requirements in energy resolution, calorimeter size, and energy response of a proposed sampling calorimeter for the Advanced Cosmic ray Composition Experiment for the Space Station (ACCESS). This study thereby permits instrument developers to make important trade studies in design parameters as a function of the science objectives, which is particularly important for space-based detectors where physical parameters, such as dimension and weight, impose rigorous practical limits to the design envelope.

Howell, L. W.↗
NASA NTRSDate not supplied

Velocity and Temperature Measurements in High-speed Flows with Naturally Present Dust Particles Using Rayleigh and Mie Scattering

Dust particles and occasional moisture condensations are unavoidable reality of all wind tunnels. On the path to pursue a goal of velocity and temperature measurements in large transonic and supersonic wind tunnels we have created a tabletop, spectrally resolved, Rayleigh-Mie scattering setup around a small jet fed by ambient and lightly seeded air to determine the viability and accuracy of the technique. The other reality of a wind tunnel setup is the background scattering or the glare at laser frequency, which contaminates the Rayleigh-Mie scattered light. This is simulated by backgrounds with different reflectivity towards the collection optics. Light from a CW laser is delivered via an optical fiber and the scattered light is spectrally resolved using a stabilized Fabry-Perot interferometer, followed by imaging on an EMCCD camera. A model of the of the combined background glare, Mie scattering, and the Rayleigh spectrum was fitted to the camera image using maximum likelihood estimation. Since the background glare occurs at the known frequency of the incident light and the Mie scattering peak corresponds to the Doppler shift from the bulk velocity, both were easily identified, and provided a measure of flow velocity. Preliminary results show that the Rayleigh spectrum can also be resolved, which provides a measure of temperature. It is observed that a slight drift of the laser frequency during data collection affected fitting of the model function leading to larger error. A feedback loop-based stabilization system is on development to take advantage of slight tunability of the laser via a piezo-control. Preliminary results are presented in the abstract. More extensive data from a systematic survey will be presented in the final paper.

Rayleigh scattering↗
NASA NTRS2000

Estimating Cosmic Ray Spectral Parameters from Simulated Detector Responses

A simple power law model consisting of a single spectral index al is believed to be an adequate description of the galactic cosmic ray (GCR) proton flux at energies below 100 TeV, with a transition at kink energy Ek to a steeper spectral index a2>al above Ek. The maximum likelihood procedure is developed for estimating these three spectral parameters of the broken power law energy spectrum from simulated detector responses. These estimates and their surrounding statistical uncertainty are being used to derive the requirements in energy resolution, calorimeter size, and energy response of a proposed sampling calorimeter for the Advanced Cosmic-ray Composition Experiment for the Space Station (ACCESS). This study thereby permits instrument developers to make important trade studies in design parameters as a function of the science objectives, which is particularly important for space-based detectors where physical parameters, such as dimension and weight, impose rigorous practical limits to the design envelope.

Howell, Leonard↗
NASA NTRS2001

Estimating Cosmic-Ray Spectral Parameters from Simulated Detector Responses with Detector Design Implications

A simple power law model consisting of a single spectral index (alpha-1) is believed to be an adequate description of the galactic cosmic-ray (GCR) proton flux at energies below 10(exp 13) eV, with a transition at knee energy (E(sub k)) to a steeper spectral index alpha-2 > alpha-1 above E(sub k). The maximum likelihood procedure is developed for estimating these three spectral parameters of the broken power law energy spectrum from simulated detector responses. These estimates and their surrounding statistical uncertainty are being used to derive the requirements in energy resolution, calorimeter size, and energy response of a proposed sampling calorimeter for the Advanced Cosmic-ray Composition Experiment for the Space Station (ACCESS). This study thereby permits instrument developers to make important trade studies in design parameters as a function of the science objectives, which is particularly important for space-based detectors where physical parameters, such as dimension and weight, impose rigorous practical limits to the design envelope.

Howell, L. W.↗
DOE OSTI2026

Dark Energy Survey: DESI-independent angular BAO measurement

In this work, we present a measurement of the angular baryon acoustic oscillation (BAO) scale from the completed Dark Energy Survey (DES) dataset excluding the area of overlap with the Dark Energy Spectroscopic Instrument (DESI). We follow the same methodology and validation process as in the DES Y6 BAO analysis. We interpret the impact of this measurement in the context of the statistical preference for 𝑤 0 ⁢𝑤 𝑎 cold dark matter (CDM) over Λ⁢CDM when combined with DES Y5 Type Ia supernovae (SN), Planck CMB, and DESI BAO. Based on our previous work, using the full Y6 DES BAO sample, in combination with SN, CMB and DESI data release 1 (DR1) BAO, added 0.3⁢𝜎 in this preference (from 3.7⁢𝜎 to 4.0⁢𝜎), but this ignored possible correlations between datasets. Using our new DESI-independent DES BAO likelihood instead, we find a smaller increase in the statistical preference for 𝑤 0 ⁢𝑤 𝑎 ⁢CDM, from 3.7⁢𝜎 to 3.8⁢𝜎 when using DESI DR1 BAO, and from 4.0⁢𝜎 to 4.1⁢𝜎 when updating to the more recent DESI data release 2 (DR2) BAO. These significances reduce to 3.1⁢𝜎 when using the new calibrated DES SN-Dovekie. Alongside this work, we publicly release baofit_wtheta, the BAO fitting code for the angular correlation function used in the DES Y6 BAO analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

Ceramics Analysis and Reliability Evaluation of Structures (CARES). Users and programmers manual

This manual describes how to use the Ceramics Analysis and Reliability Evaluation of Structures (CARES) computer program. The primary function of the code is to calculate the fast fracture reliability or failure probability of macroscopically isotropic ceramic components. These components may be subjected to complex thermomechanical loadings, such as those found in heat engine applications. The program uses results from MSC/NASTRAN or ANSYS finite element analysis programs to evaluate component reliability due to inherent surface and/or volume type flaws. CARES utilizes the Batdorf model and the two-parameter Weibull cumulative distribution function to describe the effect of multiaxial stress states on material strength. The principle of independent action (PIA) and the Weibull normal stress averaging models are also included. Weibull material strength parameters, the Batdorf crack density coefficient, and other related statistical quantities are estimated from four-point bend bar or unifrom uniaxial tensile specimen fracture strength data. Parameter estimation can be performed for single or multiple failure modes by using the least-square analysis or the maximum likelihood method. Kolmogorov-Smirnov and Anderson-Darling goodness-of-fit tests, ninety percent confidence intervals on the Weibull parameters, and Kanofsky-Srinivasan ninety percent confidence band values are also provided. The probabilistic fast-fracture theories used in CARES, along with the input and output for CARES, are described. Example problems to demonstrate various feature of the program are also included. This manual describes the MSC/NASTRAN version of the CARES program.

Nemeth, Noel N.↗