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NASA NTRS2023

Using Regionalized Air Quality Model Performance and Bayesian Maximum Entropy Data Fusion to Map Global Surface Ozone Concentration and Associated Uncertainty

Estimates of ground-level ozone concentrations have been improved through data fusion of observations and atmospheric chemistry models. Our previous global ozone estimates for the Global Burden of Disease study corrected for bias uniformly across continents and then corrected near monitoring stations using the Bayesian Maximum Entropy (BME) framework for data fusion. Here, we use the Regionalized Air Quality Model Performance (RAMP) framework to correct model bias over a much larger spatial range than BME can, accounting for the spatial inhomogeneity of bias and nonlinearity as a function of modeled ozone. RAMP bias correction is applied to a composite of 9 global chemistry-climate models, based on the nearest set of monitors. These estimates are then fused with observations using BME, which matches observations at measurement stations, with the influence of observations declining with distance in space and time. We create global ozone maps for each year from 1990 to 2017 at fine spatial resolution. RAMP is shown to create unrealistic discontinuities due to the spatial clustering of ozone monitors, which we overcome by applying a weighting for RAMP based on the number of monitors nearby. Incorporating RAMP before BME has little effect on model performance near stations, but strongly increases R 2 by 0.15 at locations farther from stations, shown through a checkerboard cross-validation. Corrections to estimates differ based on location in space and time, confirming heterogeneity. We quantify the likelihood of exceeding selected ozone levels, finding that parts of the Middle East, India, and China are most likely to exceed 55 parts per billion (ppb) in 2017. About 96% of the global population was exposed to ozone levels above the World Health Organization guideline of 60 µg m −3 (30 ppb) in 2017. Our annual fine-resolution ozone estimates may be useful for several applications including epidemiology and assessments of impacts on health, agriculture, and ecosystems.

Ozone↗

DOE OSTI2024

Assessing observational constraints on dark energy

Observational constraints on time-varying dark energy (e.g., quintessence) are commonly presented on a w 0 –w a plot that assumes the equation of state of dark energy strictly satisfies w(z) = w 0 + w a z/(1 + z) as a function of the redshift z. Recent observations favor a sector of the w 0 –w a plane in which w 0 > –1 and w 0 + w a < –1, suggesting that the equation of state underwent a transition from violating the null energy condition (NEC) at large z to obeying it at small z. In this paper, we demonstrate that this impression is misleading by showing that simple quintessence models satisfying the NEC for all z predict an observational preference for the same sector. We also find that quintessence models that best fit observational data can predict a value for the dark energy equation of state at present that is significantly different from the best-fit value of w 0 obtained assuming the parameterization above. In addition, the analysis reveals an approximate degeneracy of the w 0 –w a parameterization that explains the eccentricity and orientation of the likelihood contours presented in recent observational studies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Numerical Codes for the DESC-LSST Analysis Pipeline: Core Cosmology Library Standard Modules and Beyond wCDM Modules (Final Technical Report)

The overall objective of the project is to investigate and develop specific software modules and analysis components for the software pipeline of LSST Dark Energy Science Collaboration (DESC). Following the key projects of DESC Science Roadmap (SRM), we will write and test computer codes for the Core Cosmology Library (CCL) in order to complete its modules, functionalities, and interface to work with the analysis pipelines from the five science probes of DESC (parts of SRM deliverables CX4.2TJP, CX6.2CS). We will also code modules for CCL to test models beyond w-Cold-Dark-Matter (wCDM) and modification to gravity (MG). Interfaces for MG models will also be developed for the TJPCOSMO software which is the main pipeline of the Theory and Joint Probe (TJP) working group (deliverable TJP2.3). In order to use the full power of LSST data to constrain MG models, we will also work on constraints from nonlinear regime by running and analyzing MG N-Body simulations using a Parameterized-Post-Friedmann framework into the Gadget-2 simulation package (deliverable TJP2.2). Preliminary results for the simulations were obtained in the past. In collaboration with other DESC groups, we plan to make these simulations feedable to cosmic emulators that are practical for likelihood analyzes (deliverable TJP2.2, parts of CX6.2CS). We will also modify and integrate our current codes for consistency tests between data sets and probes into the pipeline (parts of deliverables CX8.2TJP, TJP2.3). We understand that other groups will contribute to some of these objectives but our team will focus and collaborate with others on the particular part of testing MG and models beyond wCDM and refine the DESC pipeline for this purpose. PI has been coordinating his work with the TJP and CS working groups and the DESC management team. PI is a full member of DESC since June 2013. He and his students have been contributing to LSST-DESC activities and work including TJP telecons, collaboration meetings, hack-weeks, and workshops. PI chaired or co-chaired sessions at collaboration meetings and hack-weeks about testing gravity and models beyond wCDM using LSST. He is coordinating the TJP2 projects for testing models beyond wCDM including the writing of DESC-research-note, development of code for pipeline, and N-Body simulations for MG and beyond wCDM models testable with LSST analyses. As stressed in the DESC white paper, SRM, and P5 report, one of the important questions in understanding cosmic acceleration and dark energy is to be able to distinguish whether the acceleration is due to a dark energy component in the universe or a modification to gravity. Answering these questions will have a significant impact on the question of cosmic acceleration and dark energy. The methods that we will use include analytical work, numerical code, and N-Body simulations. A first approach that that we will use consists of using growth rate parameters that enter the perturbed dynamics equations. These parameters take distinctive values for distinct gravity theories and have potential to distinguish between Dark Energy and Modified Gravity. The second method is to look for inconsistencies in Dark Energy parameter spaces using specific combinations of cosmological data sets. Our investigation addresses the Dark Energy problem that is relevant to the mission of the HEP program to understand how our universe works at its most fundamental level. It will allow us to make progress on the HEP mission to explore the nature of Dark Energy and the basic nature of space and time using future surveys such as LSST. The investigation supports the DOE HEP program Cosmic Frontier as it will contribute to the study and understanding of dark energy and fundamental properties of the universe. The investigation contributes directly to LSST-DESC key projects and their deliverables as described in the Science Road-map document to build analysis pipeline and to test dark energy and beyond wCDM models using LSST.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2016

High Resolution Image Reconstruction from Projection of Low Resolution Images DIffering in Subpixel Shifts

In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

0↗

DOE OSTI2024

Constraining Galaxy-Halo connection using machine learning

We investigate the potential of machine learning (ML) methods to model small-scale galaxy clustering for constraining Halo Occupation Distribution (HOD) parameters. Our analysis reveals that while many ML algorithms report good statistical fits, they often yield likelihood contours that are significantly biased in both mean values and variances relative to the true model parameters. This highlights the importance of careful data processing and algorithm selection in ML applications for galaxy clustering, as even seemingly robust methods can lead to biased results if not applied correctly. ML tools offer a promising approach to exploring the HOD parameter space with significantly reduced computational costs compared to traditional brute-force methods if their robustness is established. Using our ANN-based pipeline, we successfully recreate some standard results from recent literature. Properly restricting the HOD parameter space, transforming the training data, and carefully selecting ML algorithms are essential for achieving unbiased and robust predictions. Among the methods tested, artificial neural networks (ANNs) outperform random forests (RF) and ridge regression in predicting clustering statistics, when the HOD prior space is appropriately restricted. We demonstrate these findings using the projected two-point correlation function (w p (r p )), angular multipoles of the correlation function (ξ ℓ (r)), and the void probability function (VPF) of Luminous Red Galaxies from Dark Energy Spectroscopic Instrument mocks. Our results show that while combining w p (r p ) and VPF improves parameter constraints, adding the multipoles ξ 0 , ξ 2 , and ξ 4 to w p (r p ) does not significantly improve the constraints.

cosmology↗

NASA NTRS2011

The Extravehicular Suit Impact Load Attenuation Study for Use in Astronaut Bone Fracture Prediction

The NASA Integrated Medical Model (IMM) assesses the risk, including likelihood and impact of occurrence, of all credible in-flight medical conditions. Fracture of the proximal femur is a traumatic injury that would likely result in loss of mission if it were to happen during spaceflight. The low gravity exposure causes decreases in bone mineral density which heightens the concern. Researchers at the NASA Glenn Research Center have quantified bone fracture probability during spaceflight with a probabilistic model. It was assumed that a pressurized extravehicular activity (EVA) suit would attenuate load during a fall, but no supporting data was available. The suit impact load attenuation study was performed to collect analogous data. METHODS: A pressurized EVA suit analog test bed was used to study how the offset, defined as the gap between the suit and the astronaut s body, impact load magnitude and suit operating pressure affects the attenuation of impact load. The attenuation data was incorporated into the probabilistic model of bone fracture as a function of these factors, replacing a load attenuation value based on commercial hip protectors. RESULTS: Load attenuation was more dependent on offset than on pressurization or load magnitude, especially at small offsets. Load attenuation factors for offsets between 0.1 - 1.5 cm were 0.69 +/- 0.15, 0.49 +/- 0.22 and 0.35 +/- 0.18 for mean impact forces of 4827, 6400 and 8467 N, respectively. Load attenuation factors for offsets of 2.8 - 5.3 cm were 0.93 +/- 0.2, 0.94 +/- 0.1 and 0.84 +/- 0.5, for the same mean impact forces. Reductions were observed in the 95th percentile confidence interval of the bone fracture probability predictions. CONCLUSIONS: The reduction in uncertainty and improved confidence in bone fracture predictions increased the fidelity and credibility of the fracture risk model and its benefit to mission design and operational decisions.

Lewandowski, Beth E.↗

DOE OSTI2022

Accelerating cosmological inference with Gaussian processes and neural networks – an application to LSST Y1 weak lensing and galaxy clustering

ABSTRACT Studying the impact of systematic effects, optimizing survey strategies, assessing tensions between different probes and exploring synergies of different data sets require a large number of simulated likelihood analyses, each of which cost thousands of CPU hours. In this paper, we present a method to accelerate cosmological inference using emulators based on Gaussian process regression and neural networks. We iteratively acquire training samples in regions of high posterior probability which enables accurate emulation of data vectors even in high dimensional parameter spaces. We showcase the performance of our emulator with a simulated 3×2 point analysis of LSST-Y1 with realistic theoretical and systematics modelling. We show that our emulator leads to high-fidelity posterior contours, with an order of magnitude speed-up. Most importantly, the trained emulator can be re-used for extremely fast impact and optimization studies. We demonstrate this feature by studying baryonic physics effects in LSST-Y1 3×2 point analyses where each one of our MCMC runs takes approximately 5 min. This technique enables future cosmological analyses to map out the science return as a function of analysis choices and survey strategy.

Astronomy & Astrophysics↗

DOE OSTI2020

Super-CMB fluctuations and the Hubble tension

We study the covariance in the angular power spectrum estimates of CMB fluctuations when the primordial fluctuations are non-Gaussian. The non-Gaussian covariance comes from a nonzero connected four-point correlation function -- or the trispectrum in Fourier space -- and can be large when long-wavelength (super-CMB) modes are strongly coupled to short-wavelength modes. The effect of such non-Gaussian covariance can be modeled through additional freedom in the theoretical CMB angular power spectrum and can lead to different inferred values of the standard cosmological parameters relative to those in ΛCDM. Taking the collapsed limit of the primordial trispectrum in the quasi-single field inflation model as an example, we study how the six standard ΛCDM parameters shift when two additional parameters describing the trispectrum are allowed. The reduced statistical significance of the Hubble tension in the extended model allows us to combine the {\it Planck} temperature data and the type Ia supernovae data from Panstarrs with the distance-ladder measurement of the Hubble constant. Here, this combination of data shows strong evidence for a primordial trispectrum-induced non-Gaussian covariance, with a likelihood improvement of Δχ 2 ≈ –15 (with two additional parameters) relative to ΛCDM.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Emerging Tools to Support DILI Assessment in Clinical Trials with Abnormal Baseline Serum Liver Tests or Pre-existing Liver Diseases

Abstract Based on the late Dr. Hyman Zimmerman’s observation that hepatocellular drug-induced liver injury (DILI) leading to jaundice carries a ≥ 10% fatality risk (coined as Hy’s law by others), evaluation of Drug-Induced Serious Hepatotoxicity (eDISH) continues to play a central role in the assessment of a study drug’s liability for acute hepatocellular DILI. The eDISH identifies drugs in clinical trials with DILI fatality (death or transplant) risk that may be unacceptable in a post-market setting. As a two-dimensional graph that plots peak total bilirubin (TB) versus peak serum aminotransferase levels for each patient during study drug or comparator treatment, eDISH identifies potential cases of acute, modest, and serious hepatocellular DILI for in-depth analysis of liver tests (LT) and clinical course so that the likelihood of causal association with the study drug can be determined. Unfortunately, the generalizable utility of this tool only pertains to trials enrolling patients with normal or near normal (NNN) baseline (BL) serum LTs. The eDISH does not necessarily apply to trials of patients with abnormal baseline (ABN-BL) LTs that often coincide with underlying liver disorders. Because drug development programs being reviewed by the FDA increasingly target liver disorders, we are often challenged to evaluate DILI risk in trials of patients with ABN-BL LTs. Also, the high background prevalence of metabolic dysfunction associated steatotic liver disease (MASLD) means patients with LTs above NNN may need to be enrolled in trials treating non-liver disorders to reflect the target population. Such study populations create challenges for industry and regulators because eDISH may not reliably categorize or identify potential cases of DILI for further analysis, as it so efficiently does in NNN-BL trials. We describe the main functionalities of eDISH in NNN-BL trials to understand what should be emulated by new tools or eDISH modifications. We then discuss non-eDISH–based plots that may be useful in ABN-BL trials.

Amirzadegan, Jasmine↗

NASA NTRS2008

Organizational Considerations for Implementing Systems Engineering and Integration in the Ares Projects Office

Systems Engineering and Integration (SE&I) is a critical discipline in developing new space systems. In 2005, NASA performed an internal study of 24 agency and Department of Defense (DoD) programs to evaluate methods of integrating SE&I practices and determine their effectiveness. The goal of the study was to determine the best SE&I implementation strategy for the Ares Projects Office. The study identified six SE&I organizational structures: 1. Lead systems integrator (LSI) with SE&I responsibility and government technical insight. 2a. Integration contractor with government SE&I responsibility (government insight). 2b. Integration contractor with government SE&I responsibility (government oversight). 3a. Prime contractor with SE&I responsibility (government insight). 3b. Prime contractor with SE&I responsibility (government oversight). 3c. Prime contractor with SE&I responsibility (government/industry partnership). 4a.Prime contractor with government SE&I responsibility (government insight). 4b. Prime contractor with government SE&I responsibility (government oversight). 4d.Prime contractors with total system performance responsibility (TSPR). 5. Prime contractor with government SE&I responsibility and integration products through a Federally Funded Research and Development Center (FFRDC). 6. Government/FFRDC in-house development with SE&I responsibility and function. The organizational structure used most often was number 4, using a prime contractor with government SE&I responsibility and government technical insight. However, data analyses did not establish a positive relationship between program development costs and specific SE&I organizational types, nor did it positively determine the relationship between successful programs or projects and their SE&I structure. The SE&I study reached the following conclusions: (1) Large, long-duration, technically complex programs or projects reach their technical goals, but rarely meet schedule or cost goals. NASA's recent successes have been smaller, short-duration development projects using heritage hardware/software, focused technology development, technical oversight and stable external factors. (2) Programs and projects have failed or been terminated due to lack of technical insight, relaxing of SE&I processes, and unstable external factors. (3) The study did not find a single, clear optimum SE&I organization type to fit all projects. However, while any organizational structure can be made to work, the fewer complexities in the program, the better the likelihood of success. (4) The most common successful SE&I organization structure type in the study was type 4b, where the government maintained integration responsibility, with the prime contractor providing SE&I products and the government providing technical oversight. This study was instrumental in helping the APO select organization structure 4, following the same SE&I and oversight process used during humanlund7s last voyages to the Moon.

Thomas, LeAnn↗

DOE OSTI2026

Measurements of three-flavor neutrino oscillations from a PISCES two-detector fit to the NOvA Experiment data

NOvA is a long-baseline neutrino oscillation experiment with two functionally identical detectors: a Near Detector (ND) at Fermilab, placed 1 km from the neutrino source, and a Far Detector (FD) located 810 km away from the ND in Minnesota. NOvA s primary physics goals are to measure the neutrino oscillation parameters $\theta_{23}$ and $\Delta m^2_{32}$ with high precision, determine the neutrino mass hierarchy, and constrain the value of $\delta_{CP}$, primarily via the study of muon neutrino to electron neutrino oscillation. Extracting values for oscillation parameters from fits to data usually relies on treating systematic uncertainties as nuisance parameters, a strategy that suffers from poor scalability as the number of uncertainties becomes larger. This work introduces PISCES (Parameter Inference with Systematic Covariance and Exact Statistics), a novel method that circumvents this scalability problem by encoding systematic uncertainties into a covariance matrix. PISCES utilizes a nested minimization in which optimal systematic pulls are first computed using the covariance matrix in an inner minimization step, then the oscillation parameters are profiled over in the outer minimization. PISCES also uses a Poisson Likelihood term, making it ideal for the inclusion of low-statistic samples in the fits. PISCES is a flexible framework that also supports complex fits, such as a joint Near and Far detector fit. In the standard NOvA analysis, oscillation parameters are extracted using an extrapolation technique in which the ND data indirectly constrain the FD prediction via a ratio method. PISCES, on the other hand, enables a simultaneous ND+FD fit, allowing the high-statistics ND data to directly constrain systematic uncertainties across all samples. This thesis presents the full PISCES joint ND+FD fit for the NOvA three-flavor analysis, details its implementation, and evaluates its performance through extensive robustness tests and fake data studies. It also provides a comparison between the PISCES joint ND+FD results and the standard NOvA extrapolation method using the full NOvA 10-year data set. The results demonstrate that PISCES can successfully fit NOvA data while incorporating the constraints from the ND detectors consistently, using physically motivated systematic uncertainties to account for data/MC discrepancies.

Rajaoalisoa, Miriama [Cincinnati U.]↗

DOE OSTI2022

Comparative Study of Wind Energy Potential Estimation Methods for Wind Sites in Togo and Benin (West Sub-Saharan Africa)

The characterization of wind speed distribution and the optimal assessment of wind energy potential are critical factors in selecting a suitable site for wind power plants (WPP). The Weibull distribution law has been used extensively to analyze the wind characteristics of candidate WPP sites, and to estimate the available and deliverable energy. This paper presents a comparative study of five wind energy resource assessment methods as they applied to the context of wind sites in West Sub-Saharan Africa. We investigated three numerical approaches, namely, the adaptive neuro-fuzzy inference system (ANFIS), the multilayer perceptron method (MLP), and support vector regression (SVR), to derive the distribution law of wind speeds and to optimally quantify the corresponding wind energy potential. Next, we compared these three approaches to two well-known Weibull distribution law-based methods: the empirical method of Justus (EMJ) and the maximum likelihood method (MLM). Case study results indicated that the neural network-based methods, ANFIS and MLP, yielded the most accurate distribution fits and wind energy potential estimates, and consequently, are the most recommended methods for the wind sites in Togo and Benin. The orders of magnitude of the root mean squared error (RMSE) in estimating the recoverable energy using ANFIS were, respectively, 10-4 and 10-5 for Lomé and Cotonou, while MLP achieved an RMSE order of magnitude of 10-3 for both sites.

17 WIND ENERGY↗

NASA NTRS2008

Five-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Likelihoods and Parameters from the WMAP Data

The Wilkinson Microwave Anisotropy Probe (WMAP), launched in 2001, has mapped out the Cosmic Microwave Background with unprecedented accuracy over the whole sky. Its observations have led to the establishment of a simple concordance cosmological model for the contents and evolution of the universe, consistent with virtually all other astronomical measurements. The WMAP first-year and three-year data have allowed us to place strong constraints on the parameters describing the ACDM model. a flat universe filled with baryons, cold dark matter, neutrinos. and a cosmological constant. with initial fluctuations described by nearly scale-invariant power law fluctuations, as well as placing limits on extensions to this simple model (Spergel et al. 2003. 2007). With all-sky measurements of the polarization anisotropy (Kogut et al. 2003; Page et al. 2007), two orders of magnitude smaller than the intensity fluctuations. WMAP has not only given us an additional picture of the universe as it transitioned from ionized to neutral at redshift z approx.1100. but also an observation of the later reionization of the universe by the first stars. In this paper we present cosmological constraints from WMAP alone. for both the ACDM model and a set of possible extensions. We also consider tlle consistency of WMAP constraints with other recent astronomical observations. This is one of seven five-year WMAP papers. Hinshaw et al. (2008) describe the data processing and basic results. Hill et al. (2008) present new beam models arid window functions, Gold et al. (2008) describe the emission from Galactic foregrounds, and Wright et al. (2008) the emission from extra-Galactic point sources. The angular power spectra are described in Nolta et al. (2008), and Komatsu et al. (2008) present and interpret cosmological constraints based on combining WMAP with other data. WMAP observations are used to produce full-sky maps of the CMB in five frequency bands centered at 23, 33, 41, 61, and 94 GHz (Hinshaw et al. 2008). With five years of data, we are now able to place better limits on the ACDM model. as well as to move beyond it to test the composition of the universe. details of reionization. sub-dominant components, characteristics of inflation, and primordial fluctuations. We have more than doubled the amount of polarized data used for cosmological analysis. allowing a better measure of the large-scale E-mode signal (Nolta et al. 2008). To this end we describe an alternative way to remove Galactic foregrounds from low resolution polarization maps in which Galactic emission is marginalized over, providing a cross-check of our results. With longer integration we also better probe the second and third acoustic peaks in the temperature angular power spectrum, and have many more year-to-year difference maps available for cross-checking systematic effects (Hinshaw et al. 2008).

Dunkey, J.↗

DOE OSTI2023

DSPS: Differentiable stellar population synthesis

ABSTRACT Models of stellar population synthesis (SPS) are the fundamental tool that relates the physical properties of a galaxy to its spectral energy distribution (SED). In this paper, we present DSPS: a python package for SPS. All of the functionality in DSPS is implemented natively in the JAX library for automatic differentiation, and so our predictions for galaxy photometry are fully differentiable, and directly inherit the performance benefits of JAX, including portability onto GPUs. DSPS also implements several novel features, such as i) a flexible empirical model for stellar metallicity that incorporates correlations with stellar age, ii) support for the Diffstar model that provides a physically-motivated connection between the star formation history of a galaxy (SFH) and the mass assembly of its underlying dark matter halo. We detail a set of theoretical techniques for using autodiff to calculate gradients of predictions for galaxy SEDs with respect to SPS parameters that control a range of physical effects, including SFH, stellar metallicity, nebular emission, and dust attenuation. When forward modelling the colours of a synthetic galaxy population, we find that DSPS can provide a factor of 5 speed-up over standard SPS codes on a CPU, and a factor of 300-400 on a modern GPU. When coupled with gradient-based techniques for optimization and inference, DSPS makes it practical to conduct expansive likelihood analyses of simulation-based models of the galaxy–halo connection that fully forward model galaxy spectra and photometry.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2008

Application of an Elongated Kelvin Model to Space Shuttle Foams

Spray-on foam insulation is applied to the exterior of the Space Shuttle s External Tank to limit propellant boil-off and to prevent ice formation. The Space Shuttle foams are rigid closed-cell polyurethane foams. The two foams used most extensively on the Space Shuttle External Tank are BX-265 and NCFI24-124. Since the catastrophic loss of the Space Shuttle Columbia, numerous studies have been conducted to mitigate the likelihood and the severity of foam shedding during the Shuttle s ascent to space. Due to the foaming and rising process, the foam microstructures are elongated in the rise direction. As a result, these two foams exhibit a non-isotropic mechanical behavior. In this paper, a detailed microstructural characterization of the two foams is presented. The key features of the foam cells are summarized and the average cell dimensions in the two foams are compared. Experimental studies to measure the room temperature mechanical response of the two foams in the two principal material directions (parallel to the rise and perpendicular to the rise) are also reported. The measured elastic modulus, proportional limit stress, ultimate tensile stress and the Poisson s ratios for the two foams are compared. The generalized elongated Kelvin foam model previously developed by the authors is reviewed and the equations which result from this model are presented. The resulting equations show that the ratio of the elastic modulus in the rise direction to that in the perpendicular-to-rise direction as well as the ratio of the strengths in the two material directions is only a function of the microstructural dimensions. Using the measured microstructural dimensions and the measured stiffness ratio, the foam tensile strength ratio and Poisson s ratios are predicted for both foams. The predicted tensile strength ratio is in close agreement with the measured strength ratios for both BX-265 and NCFI24-124. The comparison between the predicted Poisson s ratios and the measured values is not as favorable.

Sullivan, Roy M.↗

NASA NTRS1981

The estimation of genetic divergence

Consideration is given to the criticism of Nei and Tateno (1978) of the REH (random evolutionary hits) theory of genetic divergence in nucleic acids and proteins, and to their proposed alternative estimator of total fixed mutations designated X2. It is argued that the assumption of nonuniform amino acid or nucleotide substitution will necessarily increase REH estimates relative to those made for a model where each locus has an equal likelihood of fixing mutations, thus the resulting value will not be an overestimation. The relative values of X2 and measures calculated on the basis of the PAM and REH theories for the number of nucleotide substitutions necessary to explain a given number of observed amino acid differences between two homologous proteins are compared, and the smaller values of X2 are attributed to (1) a mathematical model based on the incorrect assumption that an entire structural gene is free to fix mutations and (2) the assumptions of different numbers of variable codons for the X2 and REH calculations. Results of a repeat of the computer simulations of Nei and Tateno are presented which, in contrast to the original results, confirm the REH theory. It is pointed out that while a negative correlation is observed between estimations of the fixation intensity per varion and the number of varions for a given pair of sequences, the correlation between the two fixation intensities and varion numbers of two different pairs of sequences need not be negative. Finally, REH theory is used to resolve a paradox concerning the high rate of covarion turnover and the nature of general function sites as permanent covarions.

Holmquist, R.↗

DOE OSTI2020

Measurement of 3-Flavour Neutrino Oscillation Parameters in the NOvA Experiment

NOvA is a long-baseline neutrino oscillation experiment consisting of two functionally identical tracking calorimeters, a Near and Far Detector, that measure neutrino interactions induced by the Fermi National Accelerator Laboratory’s NuMI beam at baselines of 1 km and 810 km, respectively. The NuMI beam can be configured to produce either a primary ν µ neutrino or $\bar{ν}$ µ anti-neutrino beam. Neutrino oscillations are observed and measured by the analysis of ν µ + $\bar{ν}$ µ disappearance and νe + $\bar{ν}$ e appearance in the beam, comparing the neutrino energy spectra in the Near and Far detectors means that neutrino oscillation parameters sin 2 θ 23 , |Δ$m^2_{32}$|, and δ CP can be constrained. This thesis presents the 2018 NOvA ν µ +$\bar{ν}$ µ disappearance, ν e +$\bar{ν}$ e appearance, and combined analyses using both neutrino and anti-neutrino data, where oscillation fits have been performed, where possible, on an event-by-event basis rather than on a bin-by-bin basis as has conventionally been used in NOvA oscillation analyses. This allows for better precision in applying both neutrino oscillation probabilities and systematic uncertainties. Furthermore, oscillation analyses for the disappearance, appearance, and combined channels are presented using an unbinned likelihood fit and compared with the equivalent binned χ 2 likelihood fit used in the standard analysis. The 14 ktonne detector equivalent beam exposures used for this thesis are 8.85 × 10 20 and 6.91 × 10 20 protons on target for neutrino and antineutrino data respectively, corresponding to 5 years of NOvA data taking. A combined ν µ + $\bar{ν}$ µ disappearance and ν e + $\bar{ν}$ e appearance fit to the Far Detector data, assuming normal mass ordering and using the event-by-event oscillation and unbinned fitting methodologies, produces oscillation parameter constraints of Δ$m^2_{32}$ = (2.50$^{+0.08}_{-0.06}$) × 10 -3 eV 2 , sin 2 θ 23 = 0.59$^{+0.02}_{-0.04}$, and δ CP = 0.72$^{+0.5}_{-0.9}$π.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRSDate not supplied

Validation of Multisystem Countermeasures Protocol for Spaceflight during Antarctica Winter-over at Palmer Station (Palmer Countermeasures)

Stressors associated with spaceflight induce persistent immune compromise in astronauts which increase subclinical latent virus reactivation. In select crews, adverse clinical events have been documented. Antarctica winter-over (AWO) mission most closely reproduces these mission stressors: prolonged deployment, extreme environment, circadian misalignment, isolation, station lifestyle, and personal risk. The US maintains three primary stations in Antarctica: South Pole Station, McMurdo, and Palmer. Previous studies suggest that stations located near the interior of Antarctica (South Pole, McMurdo) have confounding effects on the immune system due to persistent hypobaric hypoxia. We hypothesized that winter-over at a coastal station (Palmer) would be more akin to spaceflight due to its normoxic but still extreme environment. Therefore, AWO at Palmer Station was selected, and validated in a pilot study [2], as the platform for testing and validating the effectiveness of an immune-restorative countermeasure protocol designed for deep space missions. Specifics include diet modifications, nutritional supplementation (vitamin D, probiotic, etc.), prescribed aerobic and resistive exercise, and a protocol of stress relieving virtual reality exercises. A multitude of biological sample types, including blood, saliva, and hair will be collected in tandem with the countermeasures in order to examine the combined effectiveness of the countermeasures. Samples and logs from subjects will be transported from Palmer Station to Johnson Space Center for further processing and distribution to co-investigators at the end of each winter-over. Extracted samples will be analyzed by appropriate testing platforms (Multiplex, qPCR, ELISA, etc.) to monitor alterations in leukocyte distribution, T cell and NK function, cytokine profiles, reactivation of latent herpesviruses, and nutritional factors. The data collected will be compared to a control year in which no countermeasures were deployed to evaluate the overall effectiveness of the analog and to validate the candidate immune countermeasure strategy. AWO 2023 concluded with the 4th in-mission timepoint conducted in September 2023. Samples for 16 subjects, including blood, saliva, hair, surveys, and PCR data, were all successfully returned from Antarctica to NASA/JSC mid-November 2023. Samples have since been distributed to co-investigators for further processing and analysis. With the completion of the first countermeasure year, preliminary data on the effectiveness of the deep-space protocol is being evaluated, however, no conclusions can be drawn yet until the completion of the second AWO countermeasure year, AWO 2024. AWO 2024 commenced in late-March 2024, with 13 subjects consenting and performing their baseline data collections (BDCs). Unique to the 2024 deployment, NSF lifted certain COVID restrictions and rallied the crewmembers in Punta Arenas, Chile. All NSF activities were transferred to this location and NASA was allowed, for the first time, to perform consent briefings, baseline samplings and training in person. This augment greatly increased the likelihood of success for the overwinter activities.

Cody L Gutierrez↗