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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiments

We consider estimation and statistical hypothesis testing on classification images obtained from the two-alternative forced-choice experimental paradigm. We begin with a probabilistic model of task performance for simple forced-choice detection and discrimination tasks. Particular attention is paid to general linear filter models because these models lead to a direct interpretation of the classification image as an estimate of the filter weights. We then describe an estimation procedure for obtaining classification images from observer data. A number of statistical tests are presented for testing various hypotheses from classification images based on some more compact set of features derived from them. As an example of how the methods we describe can be used, we present a case study investigating detection of a Gaussian bump profile.

Non-NASA Center↗
DOE OSTI2021

Environmental predictors of pulmonary nontuberculous mycobacteria (NTM) sputum positivity among persons with cystic fibrosis in the state of Florida

Nontuberculous mycobacteria (NTM) are opportunistic human pathogens that are commonly found in soil and water, and exposure to these organisms may cause pulmonary nontuberculous mycobacterial disease. Persons with cystic fibrosis (CF) are at high risk for developing pulmonary NTM infections, and studies have shown that prolonged exposure to certain environments can increase the risk of pulmonary NTM. It is therefore important to determine the risk associated with different geographic areas. Using annualized registry data obtained from the Cystic Fibrosis Foundation Patient Registry for 2010 through 2017, we conducted a geospatial analysis of NTM infections among persons with CF in Florida. A Bernoulli model in SaTScan was used to identify clustering of ZIP codes with higher than expected numbers of NTM culture positive individuals. Generalized linear mixed models with a binomial distribution were used to test the association of environmental variables and NTM culture positivity. We identified a significant cluster of M . abscessus and predictors of NTM sputum positivity, including annual precipitation and soil mineral levels.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2024

Summary and Annotated Bibliography of Measurement Error Corrections with Potential Application in Future Quesst Mission Community Noise Studies

This document is motivated by likely needs of the Quesst mission community response tests, which will culminate in data collection and estimation of dose-response regression relationships for consideration by domestic and international aviation regulators. Furthermore, basic research questions evaluating interactions between rates of community annoyance, dose levels, and indicators of the presence of rattle, vibration, and startle hinge on hypothesis testing in the context of regression models. For a variety of reasons, noise doses may be known only imprecisely and may not reflect the actual level experienced by responding subjects. These differences between true dose and estimated dose, be they systematic or random, constitute covariate measurement error. Available statistics literature speaks to the impacts of measurement error on regression models, both in terms of bias in estimated coefficients and predicted values, and in terms of the loss of statistical power for hypothesis testing. Given the particulars of a categorical annoyance response variable and a continuous noise dose predictor variable subject to measurement error during testing, the emphasis of this report is on findings and methods pertinent to generalized linear (and mixed) models likely to be employed during the Quesst mission community tests. We reach the following conclusions: 1. Of four reviewed methods, structural Bayesian measurement error models and simulation extrapolation (SIMEX) may be the most readily applicable to Quesst mission community noise study objectives. 2. If warranted, a linear measurement model can help model systematic sources of measurement error that the classical measurement error does not. 3. For its ready implementation and small additional input requirements, simulation extrapolation may be ideally suited for addressing secondary research questions involving interactions between annoyance, noise dose, and other factors through hypothesis testing. 4. For their flexibility and ability to propagate uncertainty, structural Bayesian hierarchical models have great appeal for mission purposes; some care may be needed in developing appropriate probability models describing actual noise exposure during testing. An annotated bibliography logs additional papers and resources that may be of value to analysts in other projects and disciplines.

Dose-Response Model↗
NASA NTRSDate not supplied

Statistical Considerations for the Design and Execution of NASA's Community Noise Surveys

The World Health Organization defines community noise as noise emitted from all sources apart from noise at an industrial workplace. Example sources include neighborhood and construction noise, noise from road and rail, and air traffic noise. In particular, overland supersonic flights have been banned in the United States since the 1970s based on data accumulated during the 1960s; the degree of reported annoyance from the resulting sonic booms was a key factor leading to the prohibition. In subsequent years, scientific and engineering understanding has led to the potential to produce low amplitude sonic booms, or ‘sonic thumps’, during supersonic flight through aircraft design choices. Aircraft manufacturers have expressed renewed interest in producing supersonic commercial aircraft, but without appropriate changes to regulation, only overseas routes can be traveled supersonically. The National Aeronautics and Space Administration (NASA) will be flying the X-59 demonstrator aircraft in a series of community tests to begin in the 2024 fiscal year. In this presentation we provide some historical context for the current prohibitions on supersonic commercial flight. Using data collected during earlier NASA risk reduction tests, we demonstrate how generalized linear mixed models can be used to inform the functional dose-response response curve. Finally, we discuss some of the challenges in designing the future community studies and generalizing them to a nationally-representative dose-response curve. The study effort will be of national and international importance as the data and models prepared during the community tests will be provided to the International Civil Aviation Organization (ICAO) in order to help noise regulators determine if supersonic flight will be permitted over land once again and at what demonstrable noise levels.

Nathan B Cruze↗
NASA NTRSDate not supplied

Statistical Engineering Toward Commercial Supersonic Flight: NASA's Quesst Mission

NASA’s Quesst Mission has dual goals of demonstrating low-noise supersonic technology in flight and surveying public reactions to low-noise supersonic overflight. For half a century, commercial aircraft have been required to fly slower than the speed of sound over land to prevent “creating an unacceptable situation” on the ground due to sonic booms. However, aircraft shaping techniques honed through decades of research have dramatically changed the way shockwaves from supersonic flight merge together as they travel to the ground. What used to sound like a boom on the ground will be transformed into a thump. NASA is now building a full-scale, piloted demonstration aircraft called the X-59 to demonstrate low-noise supersonic flight. In 2024, the X-59 aircraft will commence a national series of community overflight surveys to collect data on how people perceive “sonic thumps.” The results will be provided to national and international noise regulators as they consider creating new standards that allow commercial supersonic flight over land at acceptably low noise levels. In this presentation we provide historical context for the current prohibitions on supersonic commercial flight. Using data collected during earlier NASA tests, we demonstrate how generalized linear mixed models can be used to inform the functional dose-response curve. We also illustrate simulation experiments of the variability of sonic thump exposure across the United States. Finally, we discuss some of the challenges in designing the future community studies and generalizing them to a nationally-representative dose-response curve.

Quesst↗
NASA NTRSDate not supplied

Mitigating the Impacts of Measurement Error in the Quesst Mission Community Noise Study

Beginning in 2025, the NASA Quesst mission will conduct a series of community response tests involving flyovers of the X-59 aircraft at select localities across the United States. Several waves of a longitudinal survey will be administered over approximately one month of testing in order to capture perceptual responses to low-amplitude sonic booms, or “sonic thumps”. Simultaneously, noise exposure levels will be estimated by fusing model-based predictions with measurements taken from a sparse network of monitors in the region. As one of the aims of the study is to produce a dose-response curve, a regression model relating perceptual response to noise exposure levels, it is important to acknowledge the potential attenuation bias that results from measurement error in the estimated noise exposure levels. In this presentation we review and compare several methods for dealing with measurement error in generalized linear mixed models. The methods are demonstrated on simulated data and real data collected during past NASA risk reduction studies.

measurement error↗
DOE OSTI2023

Predicting fatigue from heart rate signatures using functional logistic regression

Physical fatigue can have adverse effects on humans in extreme environments. Therefore, being able to predict fatigue using easy to measure metrics such as heart rate (HR) signatures has potential to have an impact in real-life scenarios. We apply a functional logistic regression model that uses HR signatures to predict physical fatigue, where physical fatigue is defined in a data-driven manner. Data were collected using commercially available wearable devices on 47 participants hiking the 20.7-mile Grand Canyon rim-to-rim trail in a single day. Fitted model provides good predictions and interpretable parameters for real-life application.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Wild Isolates of Neurospora crassa Reveal Three Conidiophore Architectural Phenotypes

The vegetative life cycle in the model filamentous fungus, Neurospora crassa, relies on the development of conidiophores to produce new spores. Environmental, temporal, and genetic components of conidiophore development have been well characterized; however, little is known about their morphological variation. We explored conidiophore architectural variation in a natural population using a wild population collection of 21 strains from Louisiana, United States of America (USA). Our work reveals three novel architectural phenotypes, Wild Type, Bulky, and Wrap, and shows their maintenance throughout the duration of conidiophore development. Furthermore, we present a novel image-classifier using a convolutional neural network specifically developed to assign conidiophore architectural phenotypes in a high-throughput manner. To estimate an inheritance model for this discrete complex trait, crosses between strains of each phenotype were conducted, and conidiophores of subsequent progeny were characterized using the trained classifier. Our model suggests that conidiophore architecture is controlled by at least two genes and has a heritability of 0.23. Additionally, we quantified the number of conidia produced by each conidiophore type and their dispersion distance, suggesting that conidiophore architectural phenotype may impact N. crassa colonization capacity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Resident and transient coyotes exhibit differential patterns of movement behavior across heterogeneous landscapes in the southeastern United States

Coyotes (Canis latrans) are a highly adaptable canid species whose behavioral plasticity has allowed them to persist in a wide array of habitats throughout North America. As generalists, coyotes can alter movement patterns and change territorial strategies between residency (high site fidelity) and transiency (low site fidelity) to maximize fitness. Uncertainty remains about resident and transient coyote movement patterns and habitat use because research has reached conflicting conclusions regarding patterns of habitat use by both groups. We quantified effects of habitat on resident and transient coyote movement behavior using first passage time (FPT) analysis, which assesses recursive movement along an individual's movement path to delineate where they exhibit area-restricted search (ARS) behaviors relative to habitat attributes. We quantified monthly movement rates for 171 coyotes (76 residents and 53 transients) and then used estimated FPT values in generalized linear mixed models to quantify monthly habitat use for resident and transient coyotes. Transients had greater movement rates than residents across all months except January. Resident FPT values were positively correlated with agricultural land cover during fall and winter, but negatively correlated with agriculture during spring. Resident FPT values were also negatively correlated with developed habitats during May–August, deciduous land cover during June–August, and wetlands during September–January except November. FPT values of transient coyotes were positively correlated with developed areas throughout much of the year and near wetlands during July–September. Transient FPT values were negatively correlated with agriculture during all months except June and July. High FPT values (ARS behavior) of residents and transients were generally correlated with greater densities of edge habitat. Although we observed high individual variation in space use, our study found substantive differences in habitat use between residents and transients, providing further evidence that complexity and plasticity of coyote habitat use is influenced by territorial strategy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

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

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

42 ENGINEERING↗
DOE OSTI2021

The toughest animals of the Earth versus global warming: Effects of long‐term experimental warming on tardigrade community structure of a temperate deciduous forest

Abstract Understanding how different taxa respond to global warming is essential for predicting future changes and elaborating strategies to buffer them. Tardigrades are well known for their ability to survive environmental stressors, such as drying and freezing, by undergoing cryptobiosis and rapidly recovering their metabolic function after stressors cease. Determining the extent to which animals that undergo cryptobiosis are affected by environmental warming will help to understand the real magnitude climate change will have on these organisms. Here, we report on the responses of tardigrades within a five‐year‐long, field‐based artificial warming experiment, which consisted of 12 open‐top chambers heated to simulate the projected effects of global warming (ranging from 0 to 5.5°C above ambient temperature) in a temperate deciduous forest of North Carolina (USA). To elucidate the effects of warming on the tardigrade community inhabiting the soil litter, three community diversity indices (abundance, species richness, and Shannon diversity) and the abundance of the three most abundant species ( Diphascon pingue , Adropion scoticum , and Mesobiotus sp.) were determined. Their relationships with air temperature, soil moisture, and the interaction between air temperature and soil moisture were tested using Bayesian generalized linear mixed models. Despite observed negative effects of warming on other ground invertebrates in previous studies at this site, long‐term warming did not affect the abundance, richness, or diversity of tardigrades in this experiment. These results are in line with previous experimental studies, indicating that tardigrades may not be directly affected by ongoing global warming, possibly due to their thermotolerance and cryptobiotic abilities to avoid negative effects of stressful temperatures, and the buffering effect on temperature of the soil litter substrate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Personal and environmental predictors of polycyclic aromatic hydrocarbon exposure identified through repeated silicone wristband sampling

This study integrates quantitative data on personal exposure to polycyclic aromatic hydrocarbons (PAHs) in 162 silicone wristbands with demographics, behavioral information, and housing characteristics to explore contributions to residential exposure in a superfund-adjacent community over the course of a year. Forty-six residents completed questionnaires and wore silicone wristbands as personal passive samplers for seven consecutive days on up to four separate occasions in alternating months between November 2022 and June 2023. It was hypothesized that individual behaviors and housing characteristics are sources of dependence and correlation between personal PAH exposures. 50 PAHs were detected at least once, 17 of which were alkylated PAHs. Exposure to PAHs of similar molecular weight was often correlated, notably between naphthalenes (2-rings) and higher molecular weight PAHs (3 or more rings). Generalized linear mixed models identified flooring type, participant age, and sampling month as important predictors of increased PAH exposure, and flooring type, and use of wood stoves or heavy machinery as predictors of increased naphthalene exposure relative to higher molecular weight PAHs. Individual chemical models based on concentration data and detection frequencies corroborated these findings across multiple PAHs. We demonstrate that personal exposure is not static and the degree of variability in personal exposure is individual. Hence, identification of influential exposure factors through repeated measures of chemical exposure and characterization of variability in personal exposure as performed in this study, is important in the development of exposure mitigation strategies.

Bonner, Emily↗
DOE OSTI2022

Determining the bubble nucleation efficiency of low-energy nuclear recoils in superheated C 3 F 8 dark matter detectors

The bubble nucleation efficiency of low-energy nuclear recoils in superheated liquids plays a crucial role in interpreting results from direct searches for weakly interacting massive particle (WIMP) dark matter. Here, the PICO collaboration presents the results of the efficiencies for bubble nucleation from carbon and fluorine recoils in superheated C 3 F 8 from calibration data taken with five distinct neutron spectra at various thermodynamic thresholds ranging from 2.1 to 3.9 keV. Instead of assuming any particular functional forms for the nuclear recoil efficiency, a generalized piecewise linear model is proposed with systematic errors included as nuisance parameters to minimize model-introduced uncertainties. A Markov chain Monte Carlo routine is applied to sample the nuclear recoil efficiency for fluorine and carbon at 2.45 and 3.29 keV thermodynamic thresholds simultaneously. The nucleation efficiency for fluorine was found to be ≥ 50% for nuclear recoils of 3.3 keV (3.7 keV) at a thermodynamic Seitz threshold of 2.45 keV (3.29 keV), and for carbon the efficiency was found to be ≥ 50% for recoils of 10.6 keV (11.1 keV) at a threshold of 2.45 keV (3.29 keV). Simulated datasets are used to calculate a p value for the fit, confirming that the model used is compatible with the data. The fit paradigm is also assessed for potential systematic biases, which although small, are corrected for. Additional steps are performed to calculate the expected interaction rates of WIMPs in the PICO-60 detector, a requirement for calculating WIMP exclusion limits.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1977

Stability and control of maneuvering high-performance aircraft

The stability and control of a high-performance aircraft was analyzed, and a design methodology for a departure prevention stability augmentation system (DPSAS) was developed. A general linear aircraft model was derived which includes maneuvering flight effects and trim calculation procedures for investigating highly dynamic trajectories. The stability and control analysis systematically explored the effects of flight condition and angular motion, as well as the stability of typical air combat trajectories. The effects of configuration variation also were examined.

Stengel, R. F.↗
NASA NTRS1988

Analysis of crack-induced-craze in polymers

In this paper, the viscoelastic boundary element method is used to estimate the opening displacement and the envelope stress on the surface of an isolated crack-induced-craze system. To predict the propagation history of both the crack and the craze in a polymer sheet, the material properties of the glassy polymers are represented by a generalized linear viscoelastic model. Results are compared with the theoretical micromechanics predictions. Good agreements are obtained.

Sun, B. N.↗
DOE OSTI2022

Determining the bubble nucleation efficiency of low-energy nuclear recoils in superheated C$_3$F$_8$ dark matter detectors

The bubble nucleation efficiency of low-energy nuclear recoils in superheated liquids plays a crucial role in interpreting results from direct searches for weakly interacting massive particle (WIMP) dark matter. The PICO Collaboration presents the results of the efficiencies for bubble nucleation from carbon and fluorine recoils in superheated C$_3$F$_8$ from calibration data taken with 5 distinct neutron spectra at various thermodynamic thresholds ranging from 2.1 keV to 3.9 keV. Instead of assuming any particular functional forms for the nuclear recoil efficiency, a generalized piecewise linear model is proposed with systematic errors included as nuisance parameters to minimize model-introduced uncertainties. A Markov-Chain Monte-Carlo (MCMC) routine is applied to sample the nuclear recoil efficiency for fluorine and carbon at 2.45 keV and 3.29 keV thermodynamic thresholds simultaneously. The nucleation efficiency for fluorine was found to be $\geq 50\, \%$ for nuclear recoils of 3.3 keV (3.7 keV) at a thermodynamic Seitz threshold of 2.45 keV (3.29 keV), and for carbon the efficiency was found to be $\geq 50\, \%$ for recoils of 10.6 keV (11.1 keV) at a threshold of 2.45 keV (3.29 keV). Simulated data sets are used to calculate a p-value for the fit, confirming that the model used is compatible with the data. The fit paradigm is also assessed for potential systematic biases, which although small, are corrected for. Additional steps are performed to calculate the expected interaction rates of WIMPs in the PICO-60 detector, a requirement for calculating WIMP exclusion limits.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs

Genome-wide association studies (GWAS) at biobank scale are computationally intensive, especially for admixed populations requiring robust statistical models. SAIGE is a widely used method for generalized linear mixed-model GWAS but is limited by its CPU-based implementation, making phenome-wide association studies impractical for many research groups. We developed SAIGE-GPU, a GPU-accelerated version of SAIGE that replaces CPU-intensive matrix operations with GPU-optimized kernels. The core innovation is distributing genetic relationship matrix calculations across GPUs and communication layers. Applied to 2068 phenotypes from 635 969 participants in the Million Veteran Program, including diverse and admixed populations, SAIGE-GPU achieved a 5-fold speedup in mixed model fitting on supercomputing infrastructure and cloud platforms. We further optimized the variant association testing step through multi-core and multi-trait parallelization. Deployed on Google Cloud Platform and Azure, the method provided substantial cost and time savings. Source code and binaries are available for download at https://github.com/saigegit/SAIGE/tree/SAIGE-GPU-1.3.3. A code snapshot is archived at Zenodo for reproducibility (DOI: [10.5281/zenodo.17642591]). SAIGE-GPU is available in a containerized format for use across HPC and cloud environments and is implemented in R/C++ and runs on Linux systems.

Rodriguez, Alex [Argonne National Laboratory (ANL)↗
NASA NTRS1975

Comparison of some biased estimation methods (including ordinary subset regression) in the linear model

Ridge, Marquardt's generalized inverse, shrunken, and principal components estimators are discussed in terms of the objectives of point estimation of parameters, estimation of the predictive regression function, and hypothesis testing. It is found that as the normal equations approach singularity, more consideration must be given to estimable functions of the parameters as opposed to estimation of the full parameter vector; that biased estimators all introduce constraints on the parameter space; that adoption of mean squared error as a criterion of goodness should be independent of the degree of singularity; and that ordinary least-squares subset regression is the best overall method.

Sidik, S. M.↗