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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 1,513 records · Page 84

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NASA NTRS2000

Analysis of MIR-18 results for physical and biological dosimetry: radiation shielding effectiveness in LEO

We compare models of radiation transport and biological response to physical and biological dosimetry results from astronauts on the Mir space station. Transport models are shown to be in good agreement with physical measurements and indicate that the ratio of equivalent dose from the Galactic Cosmic Rays (GCR) to protons is about 3/2:1 and that this ratio will increase for exposures to internal organs. Two biological response models are used to compare to the Mir biodosimetry for chromosome aberration in lymphocyte cells; a track-structure model and the linear-quadratic model with linear energy transfer (LET) dependent weighting coefficients. These models are fit to in vitro data for aberration formation in human lymphocytes by photons and charged particles. Both models are found to be in reasonable agreement with data for aberrations in lymphocytes of Mir crew members: however there are differences between the use of LET dependent weighting factors and track structure models for assigning radiation quality factors. The major difference in the models is the increased effectiveness predicted by the track model for low charge and energy ions with LET near 10 keV/micrometers. The results of our calculations indicate that aluminum shielding, although providing important mitigation of the effects of trapped radiation, provides no protective effect from the galactic cosmic rays (GCR) in low-earth orbit (LEO) using either equivalent dose or the number of chromosome aberrations as a measure until about 100 g/cm 2 of material is used.

Flight Experiment↗

NASA NTRS2010

Single Event Test Methodologies and System Error Rate Analysis for Triple Modular Redundant Field Programmable Gate Arrays

We present a test methodology for estimating system error rates of Field Programmable Gate Arrays (FPGAs) mitigated with Triple Modular Redundancy (TMR). The test methodology is founded in a mathematical model, which is also presented. Accelerator data from 90 nm Xilins Military/Aerospace grade FPGA are shown to fit the model. Fault injection (FI) results are discussed and related to the test data. Design implementation and the corresponding impact of multiple bit upset (MBU) are also discussed.

error rate calculations↗

NASA NTRSDate not supplied

Effects of Dose Error and Sample Size on Sonic Boom Dose-response Curves

NASA will soon be collecting noise-annoyance community survey data as the X-59 aircraft flies supersonically over several communities in the USA. Sparse measurements of the X-59 sonic thumps will be used together with physics-based simulations to estimate noise doses at survey participant locations. These dose estimates have associated error that affects the accuracy of modeled dose-response curves, which can result in misestimation of annoyance. The precision in dose-response curves is also a consideration in selecting the number of survey participants. To enable pretest studies of dose error and precision, simulated dose-response data were generated based on NASA’s Quiet Supersonic Flights 2018 test. The data included various degrees of dose error and sample size. Frequentist multilevel logistic regression models were fit to the true and perturbed dose-response data. Simple proportional relationships were identified between the model parameters and the perturbation standard deviation. The summary dose-response curves illustrate the impact on accuracy if dose error is not accounted for in the model. The precision in the dose-response curves is also shown as the number of participants and degree of participation is varied. Finally, sampling variability is illustrated by showing the dose-response curves for several replicates with random draws of participants and errors.

X-59↗

NASA NTRSDate not supplied

Effects of Dose Error and Sample Size on Sonic Boom Dose-Response Curves

X-59↗

DOE OSTI2022

Combining Experimental and Theoretical Techniques to Gain an Atomic Level Understanding of the Defect Binding Mechanism in Hard Carbon Anodes for Sodium Ion Batteries

Sodium ion batteries (NIBs) are an attractive alternative to lithium–ion batteries in applications that require large–scale energy storage due to sodium's high natural abundance and low cost. Hard carbon (HC) is the most promising anode material for NIBs; however, there is a knowledge gap in the understanding of the sodium binding mechanism that prevents a rational design of HC. This study tunes sucrose–derived HC via synthesis temperature then evaluates the structural, physical, and electrochemical properties. Neutron total scattering is used to generate structural models by fitting pair distribution functions (PDF) with a combination of molecular dynamics and reverse Monte Carlo methods. From this model, the number and type of structural features are identified, quantified, and correlated to the galvanostatic charge/discharge. A method of PDF “fingerprinting” binding sites using Na probe atoms is developed and analyzing these PDFs reveals an atomistic view of ion binding sites responsible for “defect” storage mechanisms. Combining these techniques results in an atomic–level study that provides a big picture of the Na–binding mechanism in NIBs, which allows for more precise tuning of the structure–property relationships in the future. Finally, the methodologies developed will also enable new strategies for the analysis of amorphous functional materials.

25 ENERGY STORAGE↗

DOE OSTI2015

AN IMAGE-PLANE ALGORITHM FOR JWST'S NON-REDUNDANT APERTURE MASK DATA

The high angular resolution technique of non-redundant masking (NRM) or aperture masking interferometry (AMI) has yielded images of faint protoplanetary companions of nearby stars from the ground. AMI on James Webb Space Telescope (JWST)'s Near Infrared Imager and Slitless Spectrograph (NIRISS) has a lower thermal background than ground-based facilities and does not suffer from atmospheric instability. NIRISS AMI images are likely to have 90%-95% Strehl ratio between 2.77 and 4.8 μm. In this paper we quantify factors that limit the raw point source contrast of JWST NRM. We develop an analytic model of the NRM point spread function which includes different optical path delays (pistons) between mask holes and fit the model parameters with image plane data. It enables a straightforward way to exclude bad pixels, is suited to limited fields of view, and can incorporate effects such as intra-pixel sensitivity variations. We simulate various sources of noise to estimate their effect on the standard deviation of closure phase, σ{sub CP} (a proxy for binary point source contrast). If σ{sub CP} < 10{sup –4} radians—a contrast ratio of 10 mag—young accreting gas giant planets (e.g., in the nearby Taurus star-forming region) could be imaged with JWST NIRISS. We show the feasibility of using NIRISS' NRM with the sub-Nyquist sampled F277W, which would enable some exoplanet chemistry characterization. In the presence of small piston errors, the dominant sources of closure phase error (depending on pixel sampling, and filter bandwidth) are flat field errors and unmodeled variations in intra-pixel sensitivity. The in-flight stability of NIRISS will determine how well these errors can be calibrated by observing a point source. Our results help develop efficient observing strategies for space-based NRM.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Dynamics of the diffusive DM-DE interaction – Dynamical system approach

We discuss dynamics of a model of an energy transfer between dark energy (DE) and dark matter (DM) . The energy transfer is determined by a non-conservation law resulting from a diffusion of dark matter in an environment of dark energy. The relativistic invariance defines the diffusion in a unique way. The system can contain baryonic matter and radiation which do not interact with the dark sector. We treat the Friedman equation and the conservation laws as a closed dynamical system. The dynamics of the model is examined using the dynamical systems methods for demonstration how solutions depend on initial conditions. We also fit the model parameters using astronomical observation: SNIa, H ( z ), BAO and Alcock-Paczynski test. We show that the model with diffuse DM-DE is consistent with the data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Modeling the sharp deuterium release from beryllium co-deposits

Many studies have shown a sharp deuterium desorption from beryllium at around 450 K. In an attempt to model this sharp release, a new model was developed, describing the formation and decomposition of beryllium deuteride. Such a model was found to reproduce the sharp desorption peak in the thermal desorption spectrum. Moreover, in contrast to other models, the new model was able to reproduce the constant deuterium desorption from beryllium held at a constant elevated temperature. Further, fitting the modeling results to experimental data allowed us to determine the deuterium solubility limit in beryllium, which indicated an endothermic formation of beryllium deuteride. New values of the deuterium surface recombination coefficient were also obtained, differing from the ones found in the literature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Forward modeling approach to nuclear reaction cross sections: Applications in neutron inelastic scattering

The development of nuclear reaction models for the production of evaluated nuclear data has traditionally been performed by comparing measured cross sections with predictions from reaction model codes whose physical input parameters are adjusted to obtain the best agreement between measured and modeled results. To more directly probe reaction model inputs, this work introduces a forward modeling approach to experimental reaction cross-section determination, where the most important physical input parameters to reaction model calculations are obtained via 𝜒 2 minimization between measured and calculated observables. This was demonstrated using data collected by the Gamma Energy Neutron Energy Spectrometer for Inelastic Scattering (GENESIS) at the 88-inch cyclotron at Lawrence Berkeley National Laboratory, a detection array consisting of organic liquid scintillators and high-purity germanium (HPGe) detectors. Using a broad-spectrum neutron beam and a 99.98%-enriched 56 Fe target, GENESIS was used to perform a simultaneous measurement of 56 Fe 𝛾-ray production cross sections and secondary neutron energy and angle distributions. The results of the forward modeling approach to the determination of energy-differential 𝛾-ray production cross sections for the yrast 4 + → 2 + and 6 + → 4 + transitions, as well as eight other off-yrast transitions, were compared against those obtained using conventional techniques, and the results are in good agreement. In addition to discrete 𝛾-ray yield total scattered neutron energy-angular distributions as a function of incident neutron energy were also obtained using forward modeling and found to agree with evaluated data, with the exception of elastic scattering at small angles. The fitted reaction model parameters obtained through forward modeling were also used to calculate the cross section for the unobserved (𝑛, 2⁢𝑛) reaction; excellent agreement with the current evaluation was obtained, providing a validation of the predictive capabilities of the forward model approach. This work bridges the gap between nuclear data experiment and evaluation by providing a new means for extracting inelastic neutron-scattering cross sections and neutron-induced 𝛾-ray production data while directly probing reaction model physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2014

Scalable Statistical Analysis of Gaussian Models for Petascale Spatiotemporal Data (Final Technical Report)

Gaussian process models for spatial and spatiotemporal data are ubiquitous in scientific and engineering applications. Likelihood-based methods for fitting such models, which includes all Bayesian methods, have desirable statistical properties and are thus the methods of choice when feasible. However, calculating the likelihood function even once can be a challenge for N irregularly sited observations from such a process, requiring O(N 2 ) memory and O(N 3 ) complexity. Thus, there is a need for fast and accurate likelihood approximation even for N on the order of 10 5 , not to mention the 10 15 implied by petascale data. The main objective of this research was to develop computational tools for the statistical analysis of massive spatiotemporal datasets based on Gaussian process models. Another important objective was the development of appropriate statistical models for specific spatiotemporal processes arising in the physical sciences.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Exploring the Whole Set of Accurate Sparse Interpretable Models

In data science applications, there are often many models that fit the data well. This phenomenon was called the Rashomon Effect by Leo Breiman. The set of good models is called the Rashomon Set, and the goal of this project is to locate, store, and study the Rashomon sets for classes of interpretable models, including decision trees and generalized additive models.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1986

Mathematical modelling of solar ultraviolet radiation induced optical degradation in anodized aluminum

In the design of spacecraft for proper thermal balance, accurate information on the long-term optical behavior of the spacecraft outer skin materials is necessary. A phenomenological model for such behavior is given. The underlying principles are explained and some examples are given of the model's fit to actual measurements under simulated Earth-orbit conditions. Comments are given on the applicability of the model to materials testing and thermal modelling.

Ruley, John D.↗

NASA NTRS1974

The electron diffusion coefficient in Jupiter's magnetosphere

A steady-state model of Jupiter's electron radiation belt is developed. The model includes injection from the solar wind, radial diffusion, energy degradation by synchrotron radiation, and absorption at Jupiter's surface. A diffusion coefficient of the form D sub RR/R sub J squared = k times R to the m-th power is assumed, and then observed data on synchrotron radiation are used to fit the model. The free parameters determined from this fit are m = 1.95 plus or minus 0.5, k = 1.7 plus or minus 0.5 x 10 to the 9th power per sec, and the magnetic moment of injected particles equals 770 plus or minus 300 MeV/G. The value of m shows quite clearly that the diffusion is not caused by magnetic pumping by a variable solar wind or by a fluctuating convection electric field. The process might be field line exchange driven by atmospheric-ionospheric winds; our diffusion coefficient has roughly the same radial dependence but is considerably smaller in magnitude than the upper bound diffusion coefficients recently suggested for this process by Brice and McDonough (1973) and Jacques and Davis (1972).

Birmingham, T.↗

DOE OSTI2026

Red Noise–based False Alarm Thresholds for Astrophysical Periodograms via Whittle’s Approximation to the Likelihood

Astronomers who search for periodic signals using Lomb–Scargle periodograms rely on false alarm level (FAL) estimates to identify statistically significant peaks. Although FALs are often calculated from white noise models, many astronomical time series suffer from red noise. Prewhitening is a statistical technique in which a continuum model is subtracted from the log power spectrum estimate, after which the observer can proceed with a white-noise treatment. Here we present a prewhitening-based method of calculating frequency-dependent FALs. We fit power laws and autoregressive models of order 1 to each Lomb–Scargle periodogram by minimizing the Whittle approximation to the negative log-likelihood (NLL), then calculate FALs based on the best-fit model power spectrum. Our technique is a novel extension of the Whittle NLL to datasets with uneven time sampling. We demonstrate FAL calculations using observations of α Cen B, GJ 581, HD 192310, synthetic data from the radial velocity (RV) fitting challenge, and Kepler observations of a differential rotator. The Kepler data analysis shows that only true rotation signals are detected by red noise FALs, while white noise FALs suggest all spurious peaks in the low-frequency range are significant. A high-frequency sinusoid injected into α Cen B logR$'$ HK observations exceeds the 1% red noise FAL despite having only 8.9% of the power of the dominant rotation signal. In a periodogram of HD 192310 RVs, peaks associated with differential rotation and planets are detected against the 5% red noise FAL without iterative model fitting or subtraction. The software for calculating red noise–based FALs is available on GitHub.

Astrostatistics (1882)↗

DOE OSTI2025

Physics-Driven Construction of Compact Primitive Gaussian Density Fitting Basis Sets

We present a model-assisted density fitting (MADF) basis set generator, an algorithm for generating primitive atomic Gaussian density fitting (DF) basis sets (DFBSs) from a contracted Gaussian orbital basis set (OBS). The MADF algorithm produces DFBSs suitable for accurate robust DF approximation of 2-particle interactions in mean-field and correlated electronic structures. The algorithm is designed to (a) saturate the OBS product space by a large regularized set of primitive solid-harmonic Gaussian shells with nonuniform distribution of exponents, followed by (b) pruning of the shells according to their contributions to the 2- body energy of a correlated atomic ensemble. Building the DFBS generator model almost exclusively on mathematical and physical principles allows one to limit the number of parameters that control the density fitting error to three, with a single set of parameters sufficient for computations with all basis cardinal numbers, with and without correlation of core electrons, with and without scalar and spin-dependent relativistic effects, spanning almost all of the Periodic Table. Performance assessment included basis sets up to quadruple-ζ quality from several major basis set families, using molecules composed of main-group, d-block, and f-block elements. The resulting DF errors in Hartree−Fock and second-order MP2 energies (with relativistic all-electron treatments, when appropriate) were on the order of 20 and 10 μE h per electron, respectively.

Approximation↗

DOE OSTI2023

Spatial Bayesian models project shifts in suitable habitat for Pacific Northwest tree species under climate change

Abstract We developed spatial Bayesian hierarchical models to assess potential climate change impacts on suitable habitat for five important tree species in the Pacific northwestern United States (California, Oregon, and Washington). Individual‐species models were fit with presence–absence data from forest inventory field plots and spatial relationships were specified through a conditional autoregressive model. This modeling approach allowed us to visualize uncertainty in response curves, map current and future prediction uncertainty, and provide interval estimates for change. Upward elevational or northward latitudinal shifts in climatically suitable habitat were projected for all species. Climate change impacts were the most damaging for noble fir ( Abies procera ), for which 79%–100% of the current range was projected to become climatically unsuitable by the 2080s. Although coastal Douglas‐fir ( Pseudotsuga menziesii var. menziesii ) has been projected by others to gain habitat in Canada, within our study area we projected a net loss of climatically suitable habitat (ca. 8000–31,400 km 2 ) under three of four future climate scenarios. A net loss in habitat was also projected for Oregon white oak ( Quercus garryana ) under three of four scenarios, with 40%–60% of the current range becoming unsuitable. Although there was no net loss of habitat for forest land blue oak under any scenario, other factors like competition may inhibit blue oak ( Quercus douglasii ) and white oak from occupying areas projected to increase in climatic suitability. Additionally, between 13% and 32% of blue oak's current range was projected to become unsuitable; some of these areas aligned with dieback following the 2012–2015 California drought, which our data set predates. Unlike the other four species, we projected a 17%–25% increase in climatically suitable habitat for California black oak ( Quercus kelloggii ), although 1%–20% of the current range was still projected to become unsuitable. Our findings indicate that, although some species will face more pressure in tracking climatically suitable habitat than others, climate change will impact the location of suitable habitat for many species.

Kralicek, Karin↗

DOE OSTI2013

Estimation of placental and lactational transfer and tissue distribution of atrazine and its main metabolites in rodent dams, fetuses, and neonates with physiologically based pharmacokinetic modeling

Atrazine (ATR) is a widely used chlorotriazine herbicide, a ubiquitous environmental contaminant, and a potential developmental toxicant. To quantitatively evaluate placental/lactational transfer and fetal/neonatal tissue dosimetry of ATR and its major metabolites, physiologically based pharmacokinetic models were developed for rat dams, fetuses and neonates. These models were calibrated using pharmacokinetic data from rat dams repeatedly exposed (oral gavage; 5 mg/kg) to ATR followed by model evaluation against other available rat data. Model simulations corresponded well to the majority of available experimental data and suggest that: (1) the fetus is exposed to both ATR and its major metabolite didealkylatrazine (DACT) at levels similar to maternal plasma levels, (2) the neonate is exposed mostly to DACT at levels two-thirds lower than maternal plasma or fetal levels, while lactational exposure to ATR is minimal, and (3) gestational carryover of DACT greatly affects its neonatal dosimetry up until mid-lactation. To test the model's cross-species extrapolation capability, a pharmacokinetic study was conducted with pregnant C57BL/6 mice exposed (oral gavage; 5 mg/kg) to ATR from gestational day 12 to 18. By using mouse-specific parameters, the model predictions fitted well with the measured data, including placental ATR/DACT levels. However, fetal concentrations of DACT were overestimated by the model (10-fold). This overestimation suggests that only around 10% of the DACT that reaches the fetus is tissue-bound. These rodent models could be used in fetal/neonatal tissue dosimetry predictions to help design/interpret early life toxicity/pharmacokinetic studies with ATR and as a foundation for scaling to humans. - Highlights: • We developed PBPK models for atrazine in rat dams, fetuses, and neonates. • We conducted pharmacokinetic (PK) study with atrazine in pregnant mice. • Model predictions were in good agreement with experimental rat and mouse PK data. • The fetus is exposed to atrazine/its main metabolite at levels similar to the dam. • The nursing neonate is exposed primarily to atrazine's main metabolite DACT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-F-304-05: Cranial TCP/NTCP Modeling Insights and Caveats

Stereotactic Body Radiation Therapy (SBRT) was introduced clinically more than twenty years ago, and many subsequent publications have reported safety and efficacy data. The AAPM Working Group on Biological Effects of Hypofractionated Radiotherapy/SBRT (WGSBRT) extracted published treatment outcomes data from extensive literature searches to summarize and construct tumor control probability (TCP) and normal tissue complication probability (NTCP) models for six anatomical regions: Cranial, Head and Neck, Thoracic, Abdominal, Pelvic, and Spinal. In this session, we present the WGSBRT’s work for cranial sites, and recurrent head and neck cancer. From literature-based data and associated models, guidelines to aid with safe and effective hypofractionated radiotherapy treatment are being determined. Further, the ability of existing and proposed radiobiological models to fit these data is considered as to the ability to distinguish between the linear-quadratic and alternative radiobiological models such as secondary cell death from vascular damage, immunogenic, or bystander effects. Where appropriate, specific model parameters are estimated. As described in “The lessons of QUANTEC,” (1), lack of adequate reporting standards continues to limit the amount of useful quantitative information that can be extracted from peer-reviewed publications. Recommendations regarding reporting standards are considered, to enable such reviews to achieve more complete characterization of clinical outcomes. 1 Jackson A, Marks LB, Bentzen SM, Eisbruch A, Yorke ED, Ten Haken RK, Constine LS, Deasy JO. The lessons of QUANTEC: recommendations for reporting and gathering data on dose-volume dependencies of treatment outcome. Int J Radiat Oncol Biol Phys. 2010 Mar 1;76(3 Suppl):S155–60. Learning Objectives: Describe the techniques, types of cancer and dose schedules used in treating recurrent H&N cancers with SBRT List the radiobiological models that compete with the linear-quadratic model in explaining the results of hypofractionated RT Describe the dose/volume metrics that are considered safe in SBRT treatment of tumors near the optic structures. Discuss the efficacy of hypofractionation and dosing schedules used in treating vestibular schwannomas Identify some difficulties in modeling TCP and NTCP for cranial tumors treated with hypofractionation. One moderator, Dr. Grimm, designed and holds intellectual property rights to the DVH Evaluator software tool which is an FDA-cleared product in commercial use, and can analyze some of this data. No others have relevant conflicts of interest.

60 APPLIED LIFE SCIENCES↗