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All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Digital simulation of hybrid loop operation in RFI backgrounds.

A digital computer model for Monte-Carlo simulation of an imperfect second-order hybrid phase-locked loop (PLL) operating in radio-frequency interference (RFI) and Gaussian noise backgrounds has been developed. Characterization of hybrid loop performance in terms of cycle slipping statistics and phase error variance, through computer simulation, indicates that the hybrid loop has desirable performance characteristics in RFI backgrounds over the conventional PLL or the costas loop.

Ziemer, R. E.↗
NASA NTRS2003

Characterization and Prediction of the SPI Background

The INTEGRAL Spectrometer, like most gamma-ray instruments, is background dominated. Signal-to-background ratios of a few percent are typical. The background is primarily due to interactions of cosmic rays in the instrument and spacecraft. It characteristically varies by +/- 5% on time scales of days. This variation is caused mainly by fluctuations in the interplanetary magnetic field that modulates the cosmic ray intensity. To achieve the maximum performance from SPI it is essential to have a high quality model of this background that can predict its value to a fraction of a percent. In this poster we characterize the background and its variability, explore various models, and evaluate the accuracy of their predictions.

Teegarden, B. J.↗
NASA NTRS1977

Ultrasoft X-rays from the southern galactic hemisphere

Results are reported for sounding-rocket measurements of the X-ray background at ultrasoft energies (90 to 280 eV) in selected regions of the southern galactic hemisphere. The spectrum of the background is found to be extremely soft, being characterized by a kinetic temperature of less than 100 eV in thermal models. A lower limit of about 0.2 per cu pc is set on the space density of stellar sources in a discrete-source model for the background. The results show that the observed background radiation in the southern galactic hemisphere is about 50% less intense than that sampled at corresponding northern latitudes, the intensity at energies less than 150 eV varies along the scan path and is strongest south of -60 deg, there is no evidence for the existence of any ultrasoft pointlike sources, and the background is probably diffuse in origin. A temperature of about 600,000 K and an electron density of the order of 0.007 per cu cm are derived from a simple model where the radiation originates in a hot interstellar plasma interspersed with cold gas along the line of sight.

Levine, A.↗
NASA NTRS1994

The amplitude and spectral index of the large angular scale anisotropy in the cosmic microwave background radiation

In many cosmological models, the large angular scale anisotropy in the cosmic microwave background is parameterized by a spectral index, n, and a quadrupolar amplitude, Q. For a Harrison-Peebles-Zel'dovich spectrum, n = 1. Using data from the Far Infrared Survey (FIRS) and a new statistical measure, a contour plot of the likelihood for cosmological models for which -1 less than n less than 3 and 0 equal to or less than Q equal to or less than 50 micro K is obtained. Depending upon the details of the analysis, the maximum likelihood occurs at n between 0.8 and 1.4 and Q between 18 and 21 micro K. Regardless of Q, the likelihood is always less than half its maximum for n less than -0.4 and for n greater than 2.2, as it is for Q less than 8 micro K and Q greater than 44 micro K.

Ganga, Ken↗
NASA NTRS1985

Cosmic-ray backgrounds in infrared bolometers

Model calculations for the production of cosmic ray events in IR detectors by energy impulses due to fast charged particles' ionization trails are presently compared to the pulse-amplitude spectrum observed from a balloon at an altitude of 38 km. The results are pertinent to the current understanding of cosmic ray backgrounds found in all high sensitivity bolometer applications. The observed signal transients are in all details consistent with the modeling of known cosmic charged particle flux characteristics and with the detector response. Generally, the optics design should minimize detector/substrate cross section.

Nolt, I. G.↗
NASA NTRS1990

The cosmological evolution models of active galaxies and the extragalactic gamma-ray background

The source spectra and angular fluctuations produced by various possible models of AGN evolution derived from observations in other wavelength bands are investigated. It is found that the sizes of the angular fluctuations are roughly constant between 10 and 100 MeV, independent of the models chosen. None of the models produce the spectral 'shelf' observed at a few MeV, and from the simulation, the AGN mechanism is only a minor contributor to the extragalactic gamma-ray background (EGB), with its flux only about 10 percent of what is observed. These evolution-independent effects imply that the EGB is not solely produced by the AGN mechanism.

Gao, Yi-Tian↗
DOE OSTI2025

Searching for Neutrino Tridents in the NOvA Near Detector

This dissertation presents a search for neutrino trident production in the NOvA near detector through the coherent ``dimuon" channel: $\nu_\mu +\hspace{1pt}\text{X} \rightarrow \nu_\mu + \mu^- + \mu^+ +\hspace{1pt}\text{X}$. Trident production is a rare, purely electroweak process with sensitivity to physics beyond the Standard Model. The theoretical background, motivation for studying the process, and previous experimental measurements are reviewed. The analysis uses data collected by the NOvA near detector (ND) from Fermilab's Neutrinos at the Main Injector (NuMI) beam between November 2014 and February 2024, corresponding to an exposure of $25.5\times 10^{20}$ protons on target. The ND is a segmented tracking calorimeter located 800~m from the beam target, receiving neutrinos with a mean energy of 2~GeV. A multi-pass background reduction strategy is implemented, including the development of a novel dimuon-specific tracking technique. Trident candidates are identified using a boost ed decision tree classifier trained on simulated signal and background events. Limited background Monte Carlo statistics necessitate the use of functional fits to sideband data, which are extrapolated to estimate backgrounds in the signal region. The unblinded data contain 9 trident-like events, with an estimated background of 5.66 $\pm$ 5.15 events. This yields a best fit estimate of 3.34 tridents compared to the Standard Model prediction of 4.66. A profiled Feldman-Cousins method is used to determine a 90\% confidence interval of [0,9.1] on the number of signal events, corresponding to an upper limit of 1.95$\times$ the Standard Model prediction. This result represents the lowest energy search for trident events to date, and the first experimental contribution to the process in 27 years.

Bowles, Reed Scott [Indiana U.]↗
DOE OSTI2023

Observation of four-top-quark production in the multilepton final state with the ATLAS detector

This paper presents the observation of four-top-quark ($t$$\overline{t}$$t$$\overline{t}$) production in proton-proton collisions at the LHC. The analysis is performed using an integrated luminosity of 140 fb -1 at a centre-of-mass energy of 13 TeV collected using the ATLAS detector. Events containing two leptons with the same electric charge or at least three leptons (electrons or muons) are selected. Event kinematics are used to separate signal from background through a multivariate discriminant, and dedicated control regions are used to constrain the dominant backgrounds. The observed (expected) significance of the measured $t$$\overline{t}$$t$$\overline{t}$ signal with respect to the standard model (SM) background-only hypothesis is 6.1 (4.3) standard deviations. The $t$$\overline{t}$$t$$\overline{t}$ production cross section is measured to be ${22.5}^{+6.6}_{-5.5}$, consistent with the SM prediction of 12.0 ± 2.4 fb within 1.8 standard deviations. Data are also used to set limits on the three-top-quark production cross section, being an irreducible background not measured previously, and to constrain the top-Higgs Yukawa coupling and effective field theory operator coefficients that affect $t$$\overline{t}$$t$$\overline{t}$ production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1980

Analysis and interpretation of lidar observations of the stratospheric aerosol

Data obtained with a 48 in. telescope lidar system are compared with results obtained using a one-dimensional stratospheric aerosol model to analyze various microphysical processes influencing the formation of this aerosol. Special attention is given to the following problems: (1) how lidar data can help determine the composition of the aerosol particles and (2) how the layer corresponds to temperature profile variations. The lidar record during the period 1974 to 1979 shows a considerable decrease of the peak value of the backscatter ratio. Seasonal variations in the aerosol layer and a gradual decrease in stratospheric loading are observed. The aerosol model simulates a background stratospheric aerosol layer, and it predicts stratospheric aerosol concentrations and compositions. Numerical experiments are carried out by using the model and by comparing the theoretical results with the experimentally obtained lidar record. Comparisons show that the backscatter profile is consistent with the composition when the particles are sulfuric acid and water; it is not consistent with an ammonium sulfate composition. It is shown that the backscatter ratio is not sensitive to the composition or stratospheric loading of condensation nuclei such as meteoritic debris.

Hamill, P.↗
NASA NTRS1995

On the uncertainty in single molecule fluorescent lifetime and energy emission measurements

Time-correlated single photon counting has recently been combined with mode-locked picosecond pulsed excitation to measure the fluorescent lifetimes and energy emissions of single molecules in a flow stream. Maximum likelihood (ML) and least square methods agree and are optimal when the number of detected photons is large however, in single molecule fluorescence experiments the number of detected photons can be less than 20, 67% of those can be noise and the detection time is restricted to 10 nanoseconds. Under the assumption that the photon signal and background noise are two independent inhomogeneous poisson processes, we derive the exact joint arrival time probably density of the photons collected in a single counting experiment performed in the presence of background noise. The model obviates the need to bin experimental data for analysis, and makes it possible to analyze formally the effect of background noise on the photon detection experiment using both ML or Bayesian methods. For both methods we derive the joint and marginal probability densities of the fluorescent lifetime and fluorescent emission. the ML and Bayesian methods are compared in an analysis of simulated single molecule fluorescence experiments of Rhodamine 110 using different combinations of expected background nose and expected fluorescence emission. While both the ML or Bayesian procedures perform well for analyzing fluorescence emissions, the Bayesian methods provide more realistic measures of uncertainty in the fluorescent lifetimes. The Bayesian methods would be especially useful for measuring uncertainty in fluorescent lifetime estimates in current single molecule flow stream experiments where the expected fluorescence emission is low. Both the ML and Bayesian algorithms can be automated for applications in molecular biology.

Brown, Emery N.↗
NASA NTRS1996

On the Uncertainty in Single Molecule Fluorescent Lifetime and Energy Emission Measurements

Time-correlated single photon counting has recently been combined with mode-locked picosecond pulsed excitation to measure the fluorescent lifetimes and energy emissions of single molecules in a flow stream. Maximum likelihood (ML) and least squares methods agree and are optimal when the number of detected photons is large, however, in single molecule fluorescence experiments the number of detected photons can be less than 20, 67 percent of those can be noise, and the detection time is restricted to 10 nanoseconds. Under the assumption that the photon signal and background noise are two independent inhomogeneous Poisson processes, we derive the exact joint arrival time probability density of the photons collected in a single counting experiment performed in the presence of background noise. The model obviates the need to bin experimental data for analysis, and makes it possible to analyze formally the effect of background noise on the photon detection experiment using both ML or Bayesian methods. For both methods we derive the joint and marginal probability densities of the fluorescent lifetime and fluorescent emission. The ML and Bayesian methods are compared in an analysis of simulated single molecule fluorescence experiments of Rhodamine 110 using different combinations of expected background noise and expected fluorescence emission. While both the ML or Bayesian procedures perform well for analyzing fluorescence emissions, the Bayesian methods provide more realistic measures of uncertainty in the fluorescent lifetimes. The Bayesian methods would be especially useful for measuring uncertainty in fluorescent lifetime estimates in current single molecule flow stream experiments where the expected fluorescence emission is low. Both the ML and Bayesian algorithms can be automated for applications in molecular biology.

Brown, Emery N.↗
DOE OSTI2022

Modeling of deuterium and carbon radiation transport in MAST-U tokamak advanced divertors

Modest effects of deuterium and carbon radiation opacity in the Super-X and snowflake divertor plasmas are predicted for MAST Upgrade tokamak with core plasma input power 2.5–5 MW and plasma current 1 MA. The radiation transport modeling is based on the SOLPS-EIRENE and UEDGE code divertor plasma predictions. Two radiation transport models are used: one is based on a full radiation transport equation implemented in the radiation transport and collisional-radiative code CRETIN (without feedback on the background plasma), and another is an internal self-consistent UEDGE model with ionization, recombination, and heating rates corrected for Ly α line trapping based on the escape probability model implemented in CRETIN. In MAST-U, the Super-X and snowflake divertor plasmas are predicted to reach detached regimes at lower upstream densities than the standard divertor, and the conclusion still holds with radiation transport effects included. At neutral densities m -3 , modest Ly α deuterium line trapping with optical depths 10–15 is predicted in the Super-X divertor. Divertor plasmas are optically thin to other Lyman and Balmer lines, as well as to strong C III and C IV lines that are responsible for most of divertor radiated power. Insignificant changes (within a few percent) to divertor deuterium ionization and recombination rates are found. Radiation fluxes on outer divertor target are modified within a factor of 2–3 when the radiation transport is accounted for, and a similar variation is found due to the line shape models that define the absorption and emission line profiles in the radiation transport modeling. The predicted Lyman and Balmer spectral intensities are significantly modified due to radiation trapping. A measurement of divertor radiation transport effects is discussed using the Ly β /Ba α line ratio. In the snowflake divertor configuration, divertor plasmas are found to be optically thin to Lyman series lines within a large range of parameter variations that include upstream density, divertor transport coefficients, and magnetic configurations. Finally, modest radiation transport effects are only found in a few cases with strongest divertor transport and magnetic configurations closest to the ideal snowflake configuration, however, the plasma background models that were used are yet to be validated with an experiment.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

A three-dimensional model of terrain-induced updrafts for movement ecology studies

Abstract Background Spatially explicit simulation models of animal movements through the atmosphere necessarily require a representation of the spatial and temporal variation of atmospheric conditions. In particular, for movements of soaring birds that rely extensively on vertical updrafts to avoid flapping flight, accurate and reliable estimation of the vertical component of wind is critical. The interaction between wind and complex terrain shapes both the horizontal and vertical wind fields, highlighting the need to model the coupling between local terrain features and atmospheric conditions at scales relevant to animal movement. Methods In this work, we propose a new empirical model for estimating the orographic updraft field. The model is developed using computational fluid dynamics simulations of canonical atmospheric conditions over moderately complex terrain. To isolate buoyancy and thermal effects, and focus on terrain-induced effects, we use only simulations of a neutrally stratified atmosphere to develop the model. The model, which we name Engineering Vertical Velocity Estimator (EVVE), is simple to implement and is a function of the underlying terrain elevation map, the desired height above ground level (AGL), and wind conditions at a reference height (80 m). We validate the model with data from the Alaiz mountain (Spain) field campaign. Results Compared to observations, the proposed improved model estimates the updrafts at 120 m AGL with a mean error of 0.11 m/s ( $$\sigma =0.28$$ σ = 0.28 m/s), compared to 0.85 m/s ( $$\sigma =0.58$$ σ = 0.58 m/s) for its baseline. For typical land-based wind turbine hub heights of 80 m AGL, the proposed model has a mean error of 0.04 m/s ( $$\sigma =0.25$$ σ = 0.25 m/s), compared to baseline 0.54 m/s ( $$\sigma =0.45$$ σ = 0.45 m/s) estimations. We illustrate an application of the model in movement ecology by comparing simulated tracks and presence maps of golden eagles ( Aquila chrysaetos ) moving across two distinct landscapes. The tracks and presence maps are obtained using a simple heuristic-based movement model, with the updraft field given by the proposed model and a wind vector-based estimation approach that is currently in wide use in movement ecology studies of raptors and other soaring birds. Conclusions We highlight that movement model results can be sensitive to the underlying orographic updraft model, especially in studies of fine-scale movements in regions of complex topography. We suggest adopting the proposed model rather than the wind vector estimation method for studies of soaring bird movements.

17 WIND ENERGY↗
NASA NTRS2018

A First Look at the Evolution of Flight Crew Requirements for Emerging Market Aircraft

This is an exciting time for aviation. New vehicle and airspace technologies promise large increases in the number of aircraft in operation. One critical technology for these emerging markets is the increased use of automated systems to reduce pilot skill, training, and proficiency requirements. While the use of these systems promises to reduce or eliminate pilot functions in the long-term, the technology development for the required functions will necessitate a phased transition. The transition to, and adoption of automated systems will generate new safety challenges. This paper is a first look at a model to help frame flight crew functions for evaluation of future operational requirements. The model is intended to provide required flight crew functions regardless of whether the functions are performed by human or artificial agent. It is hoped that the model will be useful in identifying safety challenges and enabling a safe transition for the new aviation markets. The paper presents some background for a model for framing the flight crew function model and some thoughts about next steps.

safety-critical automation↗
DOE OSTI2024

Assessing the reliability of medical resource demand models in the context of COVID-19

Abstract Background Numerous medical resource demand models have been created as tools for governments or hospitals, aiming to predict the need for crucial resources like ventilators, hospital beds, personal protective equipment (PPE), and diagnostic kits during crises such as the COVID-19 pandemic. However, the reliability of these demand models remains uncertain. Methods Demand models typically consist of two main components: hospital use epidemiological models that predict hospitalizations or daily admissions, and a demand calculator that translates the outputs of the epidemiological model into predictions for resource usage. We conducted separate analyses to evaluate each of these components. In the first analysis, we validated various hospital use epidemiological models using a recent validation framework designed for epidemiological models. This allowed us to quantify the accuracy of the models in predicting critical aspects such as the date and magnitude of local COVID-19 peaks, among other factors. In the second analysis, we evaluated a range of demand calculators for ventilators, medical gowns, and COVID-19 test kits. To achieve this, we decoupled these demand calculators from the underlying epidemiological models and provided ground truth data for their inputs. This approach enabled a direct comparison of the demand calculators, comparing them against each other and actual usage data when available. The code is available athttps://doi.org/10.5281/zenodo.13712387. Results Performance varied greatly across the epidemiological models, with greater variability in COVID-19 hospital use predictions than for COVID-19 deaths as analyzed previously. Some models did not have any peaks. Among those that did, the models under-estimated date of peak approximately as often as they over-estimated, but were more likely to under-estimate magnitude of peak, with typical relative errors around 50%. Regarding demand calculator predictions, there was significant variability, including five-fold differences in predictions for gown models. Validation against actual or surrogate usage data illustrated the potential value of demand models while demonstrating their limitations. Conclusions The emerging field of demand modeling holds promise in averting medical resource shortages during future public health emergencies. However, achieving this potential necessitates focused efforts on standardization, transparency, and rigorous model validation before placing reliance on demand models in critical public health decision-making.

Medical Informatics↗
NASA NTRS2018

The Effects of Uncertainty in Initial CME Input Parameters on Deflection, Rotation, Bz, and Arrival Time Predictions

Understanding the effects of coronal mass ejections (CMEs) requires knowing if and when they will impact and their properties upon impact. Of particular importance is the strength of a CME's southward magnetic field component (Bz ). Kay et al. (2013, https://doi:10.1088/0004-637X/775/1/5, 2015, https://doi:10.1088/948 0004-637X/805/2/168) have shown that the simplified analytic model Forecasting a CME's Altered Trajectory (ForeCAT) can reproduce the deflection and rotation of CMEs. Kay, Gopalswamy, Reinard, and Opher (2017, https://doi.org/10.3847/1538-4357/835/2/117) introduced ForeCAT In situ Data Observer, which uses ForeCAT results to simulate magnetic field profiles. ForeCAT In situ Data Observer reproduces the in situ observations on roughly hourly time scales, suggesting that these models could be extremely useful for predictions of Bz . However, as with all models, both models are sensitive to their input parameters, which may not be precisely known for predictions. We explore this sensitivity using ensembles having small changes in the initial latitude, longitude, and orientation of the erupting CME. We explore the effects of different background magnetic field models and find that the changes in deflection and rotation resulting from the uncertainty in the initial parameters tend to exceed the changes from dierent magnetic backgrounds. The range in the in situ proles tends to scale with the range in the deflection and rotation. We also consider a simple arrival time model using ForeCAT results and nd an average absolute error of only 3 hr. We show that an uncertainty in the CME position of 8.1 ± 6.9 leads to variations of 6 hr in the arrival time. This measure depends strongly on the location of impact within the CME with the arrival time changing less for impacts near the nose.

Kay, Christina D.↗
DOE OSTI2023

Predictive models of long COVID

Background: The cause and symptoms of long COVID are poorly understood. It is challenging to predict whether a given COVID-19 patient will develop long COVID in the future. Methods: We used electronic health record (EHR) data from the National COVID Cohort Collaborative to predict the incidence of long COVID. We trained two machine learning (ML) models — logistic regression (LR) and random forest (RF). Features used to train predictors included symptoms and drugs ordered during acute infection, measures of COVID-19 treatment, pre-COVID comorbidities, and demographic information. We assigned the ‘long COVID’ label to patients diagnosed with the U09.9 ICD10-CM code. The cohorts included patients with (a) EHRs reported from data partners using U09.9 ICD10-CM code and (b) at least one EHR in each feature category. We analysed three cohorts: all patients (n = 2,190,579; diagnosed with long COVID = 17,036), inpatients (149,319; 3,295), and outpatients (2,041,260; 13,741). Findings: LR and RF models yielded median AUROC of 0.76 and 0.75, respectively. Ablation study revealed that drugs had the highest influence on the prediction task. The SHAP method identified age, gender, cough, fatigue, albuterol, obesity, diabetes, and chronic lung disease as explanatory features. Models trained on data from one N3C partner and tested on data from the other partners had average AUROC of 0.75. Interpretation: ML-based classification using EHR information from the acute infection period is effective in predicting long COVID. SHAP methods identified important features for prediction. Cross-site analysis demonstrated the generalizability of the proposed methodology.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1990

A model for the distribution of material generating the soft X-ray background

The observational evidence relating to the soft X-ray diffuse background is discussed, and a simple model for its source and spatial structure is presented. In this simple model with one free parameter, the observed 1/4 keV X-ray intensity originates as thermal emission from a uniform hot plasma filling a cavity in the neutral material of the Galactic disk which contains the sun. Variations in the observed X-ray intensity are due to variations in the extent of the emission volume and therefore the emission measure of the plasma. The model reproduces the observed negative correlation between X-ray intensity and H I column density and predicts reasonable values for interstellar medium parameters.

Snowden, S. L.↗