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At least 433 records · Page 24

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NASA NTRS2008

The Formation of Filament Threads in a Sheared Magnetic Field

This slide presentation reviews the mechanism that form the filament threads in the sheared magnetic field of the solar photosphere. There are observations of the filaments, a chart showing the magnetic field configuration for the filaments, and charts that show the thermal instability, and thermal conduction. Discussion of the question "How is it possible for a magnetic field to inhibit heat flow in a coronal plasma without simultaneously restricting the mass flow required for the growth of density condensations?" is reviewed. Equations that are used in the model are given. The characteristics of dynamic condensations are reviewed. There are charts that show the density perturbations for principal dynamic condensation mode and 1st harmonic. The characteristics of the kinematic condensations are also discussed. The types of perturbations that were studied are: (1) Generic perturbation with T(sub 0) < T(sub c) (2) Generic perturbation with T(sub 0) = T(sub c) (3) Random perturbation with T(sub 0)< T(sub c).

condensational instability↗

NASA NTRS2008

TPF-C Performance Modeling

This slide presentation reviews the performance modeling of the Terrestrial Planet Finder Coronagraph (TPF-C). Included is a chart of the Error Budget Models, definitions of the static and dynamic terms, a chart showing the aberration sensitivity at 2 lambda/D, charts showing the thermal performance models and analysis, surface requirements, high-level requirements, and calculations for the beam walk model.Also included is a description of the control systems, and a flow for the iterative design and analysis cycle.

terrestrial planet finder↗

NASA NTRS2016

Thermodynamic Spectrum of Solar Flares Based on SDO/EVE Observations: Techniques and First Results

The Solar Dynamics Observatory (SDO)/EUV Variability Experiment (EVE) provides rich information on the thermodynamic processes of solar activities, particularly on solar flares. Here, we develop a method to construct thermodynamic spectrum (TDS) charts based on the EVE spectral lines. This tool could potentially be useful for extreme ultraviolet (EUV) astronomy to learn about the eruptive activities on distant astronomical objects. Through several cases, we illustrate what we can learn from the TDS charts. Furthermore, we apply the TDS method to 74 flares equal to or greater than the M5.0 class, and reach the following statistical results. First, EUV peaks are always behind the soft X-ray (SXR) peaks and stronger flares tend to have faster cooling rates. There is a power-law correlation between the peak delay times and the cooling rates, suggesting a coherent cooling process of flares from SXR to EUV emissions. Second, there are two distinct temperature drift patterns, called Type I and Type II. For Type I flares, the enhanced emission drifts from high to low temperature like a quadrilateral, whereas for Type II flares the drift pattern looks like a triangle. Statistical analysis suggests that Type II flares are more impulsive than Type I flares. Third, for late-phase flares, the peak intensity ratio of the late phase to the main phase is roughly correlated with the flare class, and the flares with a strong late phase are all confined. We believe that the re-deposition of the energy carried by a flux rope, which unsuccessfully erupts out, into thermal emissions is responsible for the strong late phase found in a confined flare. Furthermore, we show the signatures of the flare thermodynamic process in the chromosphere and transition region in the TDS charts. These results provide new clues to advance our understanding of the thermodynamic processes of solar flares and associated solar eruptions, e.g., coronal mass ejections.

Wang, Yuming↗

NASA NTRS2018

System and Method for Providing Visualization Aids for Effective Interval Management Procedure Execution

Methods and apparatus are provided for simulating an interval management (IM) procedure for an ownship aircraft and a target aircraft before the start of the performance of the IM procedure. The method comprises receiving an IM clearance message from air traffic control (ATC), parsing the received IM clearance message into parsed information components identifying the complexity of the IM clearance message based on the number of elements in the information components, generating a flight chart depicting the area over which the proposed IM procedure is to traverse using the mapping information wherein the flight chart includes a vertical view and a plan view, and simulating the IM procedure on the generated flight chart before any steps of the IM procedure are performed.

Kashi, Rajanikanth Nagaraj↗

NASA NTRS2019

Statistical Process Control and Capability Study on the Water Content Measurements in NASA Glenn's Icing Research Tunnel

The Icing Research Tunnel (IRT) at NASA Glenn Research Center follows the recommended practice for icing tunnel calibration outlined in SAE's ARP5905 document. The calibration team has followed the schedule of a full calibration every five years with a check calibration done every six months following. The liquid water content of the IRT has maintained stability within in the specifications presented to customers that the variation is within +/- 10% of the calibrated, target measurement. With recent measurements and instrumentation errors, a more thorough assessment of error source was desired. By constructing statistical process control charts, the ability to determine how the instrument varies in the short term, mid term, and long term was gained. The control charts offer a view of instrument error, facility error, or installation changes. It was discovered that there was a shift from target to mean baseline thus leading to the study of the overall capability indices of the liquid water content measuring instrument to perform within specifications defined in the IRT. This presentation describes data processing procedures for the Multi-Element Sensor in the IRT, including collision efficiency corrections, canonical correlation analysis, Chauvenet's Criterion for rejection of data, distribution check of data, and mean, median and mode for construction of control charts. Further data is presented to describe the repeatability of the IRT with the Multi-Element Sensor and the ability to maintain a stable process for the defined calibration schedule.

Timko, Emily N.↗

NASA NTRSDate not supplied

The Sufficient Component Cause Model Explaining Low-Dose Radiobiology through an Epidemiologic Lens

One of the major challenges in understanding space radiation-induced carcinogenesis is the uncertainty from translating radiobiological research in cellular and animal models to humans, especially at doses below 100 mSv. Biological studies have shown a host of potential outcomes at low doses in animal and cellular models. The existence of non-targeted effects as bystander and abscopal effects is well-documented from clinical research and basic science1,2,3. While some studies have shown increased effects at low doses, others have shown evidence of hormetic bystander effects, where radiation exposure may be beneficial4,5,6. Despite these varied and diverse findings, epidemiologic studies largely support the linear-no threshold (LNT) assumption used by radiation protection guidance7,8. Translational animal-to-human models have predominantly considered ratio values such as the relative biological effectiveness (RBE) and dose and dose-rate effectiveness factor (DDREF) that rely on the assumption of LNT rather than implementing specific dose-response shapes in the low-dose region, and translational cell-to-human models are uncommon. The sufficient component cause model presents an opportunity to examine biological findings at low doses from an epidemiological lens9. In this model, exposures “sufficient” to cause an outcome of interest are presented in pie charts, such that when all slices of a pie chart are fulfilled, the outcome will occur. Multiple pie charts may exist for a single outcome, illustrating individual differences9. In 1988,Greenland and Poole adapted the sufficient component cause model to incorporate interaction with other exposures (such as genetics or lifestyle factors)10. They show that a range of biological processes are possible in a population, but that an epidemiologic study will only reveal the mean outcome from the population at large10,11. Using this construct, the multiple outcomes presented in radiobiological models to date can be explained in the context of epidemiologic studies. This presentation aims to demonstrate a causal framework that can integrate radiobiological and epidemiological models to date. It is intended as a conversation starter to spur future research.

C M Milder↗

NASA NTRSDate not supplied

The Potential Outcome Model: Explaining Low-Dose Radiobiology through an Epidemiologic Lens

One of the major challenges in understanding space radiation-induced carcinogenesis is the uncertainty from translating radiobiological research in cellular and animal models to humans, especially at doses below 100 mSv. Biological studies have shown a host of potential outcomes at lowdoses in animal and cellular models. The existence of non-targeted effects as bystander and abscopal effects is well-documented from clinical research and basic science1,2,3. While some studies have shown increased effects at low doses, others have shown evidence of hormetic bystander effects, where radiation exposure may be beneficial4,5,6. Despite these varied and diverse findings, epidemiologic studies largely support the linear-no threshold (LNT) assumption used by radiation protection guidance7,8. Translational animal-to-human models have predominantly considered ratio values such as the relative biological effectiveness (RBE) and dose and dose-rate effectiveness factor (DDREF) that rely on the assumption of LNT rather than implementing specific dose-response shapes in the low-dose region, and translational cell-to-human models are uncommon. The sufficient component cause model presents an opportunity to examine biological findings at low doses from an epidemiological lens9. In this model, exposures “sufficient” to cause an outcome of interest are presented in pie charts, such that when all slices of a pie chart are fulfilled, the outcome will occur. Multiple pie charts may exist for a single outcome, illustrating individual differences9. In 1988,Greenland and Poole adapted the sufficient component cause model to incorporate interaction with other exposures (such as genetics or lifestyle factors)10. They show that a range of biological processes are possible in a population, but that an epidemiologic study will only reveal the mean outcome from the population at large10,11. Using this construct, the multiple outcomes presented in radiobiological models to date can be explained in the context of epidemiologic studies. This presentation aims to demonstrate a causal framework that can integrate radiobiological and epidemiological models to date. It is intended as a conversation starter to spur future research.

C M Milder↗

DOE OSTI2022

Utah FORGE: Well 16A(78)-32 Stimulation Tracer Test Results

This archive contains data from the tracer test performed during the Utah FORGE well 16A(78)-32 stimulation. This includes: 1. the raw data file from Pason in the csv format; 2. a one-page Word document from Pason that explains the headers and units used in their data file; 3. an Excel spreadsheet with concentration data and relevant Pason flow data; 4. a Word document with jpg versions of concentration charts (Figs. 1-3) and a tracer mass recovery chart (Fig. 4).

15 GEOTHERMAL ENERGY↗

NASA NTRS1944

Compressibility Effects on Heat Transfer and Pressure Drop in Smooth Cylindrical Tubes

An analysis is made to simplify pressure-drop calculations for nonadiabatic and adiabatic friction flow of air in smooth cylindrical tubes when the density changes due to heat transfer and pressure drop are appreciable. Solutions of the equation of motion are obtained by the use of Reynolds' analogy between heat transfer and skin friction. Charts of the solutions are presented for making pressure-drop calculations. A technique of using the charts to determine the position of a normal shock in a tube is described.

AIR FLOW - TUBES, CYLINDRICAL↗

NASA NTRS2004

The HiVy tool set

Our aim is to validate mission-specific components of spacecraft flight software designs that are specified using state-charts and translated automatically to the final flight code for the mission. We established an automatic translation tool set from state-charts to SPIN for the validation of such mission-specific components.

translation↗

DOE OSTI2020

Solar cell efficiency tables (version 57)

Abstract Consolidated tables showing an extensive listing of the highest independently confirmed efficiencies for solar cells and modules are presented. Guidelines for inclusion of results into these tables are outlined, and new entries since June 2020 are reviewed. In this issue, charts showing efficiency improvements since 1993 are included as well as cell and module area definitions and an updated list of recognized test centres.

Green, Martin↗

DOE OSTI2024

Monitoring covariance in multivariate time series: Comparing machine learning and statistical approaches

Abstract In complex systems with multiple variables monitored at high‐frequency, variables are not only temporally autocorrelated, but they may also be nonlinearly related or exhibit nonstationarity as the inputs or operation changes. One approach to handling such variables is to detrend them prior to monitoring and then apply control charts that assume independence and stationarity to the residuals. Monitoring controlled systems is even more challenging because the control strategy seeks to maintain variables at prespecified mean levels, and to compensate, correlations among variables may change, making monitoring the covariance essential. In this paper, a vector autoregressive model (VAR) is compared with a multivariate random forest (MRF) and a neural network (NN) for detrending multivariate time series prior to monitoring the covariance of the residuals using a multivariate exponentially weighted moving average (MEWMA) control chart. Machine learning models have an advantage when the data's structure is unknown or may change. We design a novel simulation study with nonlinear, nonstationary, and autocorrelated data to compare the different detrending models and subsequent covariance monitoring. The machine learning models have superior performance for nonlinear and strongly autocorrelated data and similar performance for linear data. An illustration with data from a reverse osmosis process is given.

Weix, Derek↗

DOE OSTI2020

Cooperation or Rivalry? Impact of alternative development pathways on India's long-term electricity generation and associated water demands

The world has witnessed a significant shift in the last decade in the way countries interact with each other. A cooperation based international paradigm is being challenged by countries engaging in rivalry with each other in the name of their national interests. What developmental pathway the world charts in the future is going to be path defining for global energy and emissions use. India, expected to play a critical role in the emissions mitigation debate, would contribute to and would be impacted by these pathways. In India specific literature, however, little attention has been paid to development pathways related uncertainties and their impact on energy futures. We seek to address this gap by modelling India's electricity futures and associated water demands under different development pathways. Our analysis shows that alternative development pathways would have significantly different implications for the energy access, electricity generation mix, associated water withdrawals, and carbon dioxide emissions in India. We conclude by arguing that energy, emissions and water policies should be conceived with an explicit understanding of uncertainties related to potential development pathways that the world and India can chart.

India, Electricity-Water Nexus, Development Pathwa↗

DOE OSTI2020

Experimental studies of the two-step scheme with an intense radioactive 132 Sn beam for next-generation production of very neutron-rich nuclei

The study of nuclei in the yet-unexplored, very neutron-rich, mid- to heavy-mass region of the nuclear chart, comprising perhaps half of all nuclei predicted to exist, is leading to new and/or upgraded facilities, as well as to research into the underlying production processes. In the present study, the usefulness of the two-step scheme, an alternate method to produce very neutron-rich nuclei, by a combination of an isotope-separation online (ISOL) system as a first step, and in-beam fragmentation of re-accelerated radioactive isotopes (RIs) as a second step, was investigated with a 132 Sn beam. In this work, very neutron-rich RIs around the neutron-rich neutron number N = 82 region were produced from the 278-MeV/nucleon 132 Sn beam impinging on a 5.97-mm Be target, and their production cross sections were measured. Yields were then estimated for the two-step scheme with the 132 Sn beam relative to the ones by a one-step scheme, in-flight fission of a 238 U beam, for 1-MW proton and 238 U beams at respective RI-beam facilities. This comparison suggests that the two-step scheme with the 132 Sn beam provides yields >40-times higher than those with the one-step scheme for the very neutron-rich N = 82 region. Moreover, by using various RI beams over the nuclear chart from ISOL, certain kinds of very neutron-rich RIs around the supernova r-process path can be produced with greater yields than by the one-step approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Hyperheavy spherical and toroidal nuclei: The role of shell structure

The properties of toroidal hyperheavy even-even nuclei and the role of toroidal shell structure are extensively studied within covariant density functional theory. The general trends in the evolution of toroidal shapes in the Z ≈ 130–180 region of the nuclear chart are established for the first time. These nuclei are stable with respect to breathing deformations. The most compact fat toroidal nuclei are located in the Z ≈ 136, N ≈ 206 region of the nuclear chart, but thin toroidal nuclei become dominant with increasing proton number and toward proton and neutron drip lines. The roles of toroidal shell structure, its regularity, supershell structure, and shell gaps as well as the role of different groups of the pairs of the orbitals in its formation are investigated in detail. The lowest in energy solutions at axial symmetry are characterized either by large shell gaps or low density of the single-particle states in the vicinity of the Fermi level in at least one of the subsystems (proton or neutron). Related quantum shell effects are expected to act against the instabilities in breathing and sausage deformations for these subsystems. The investigation with a large set of covariant energy density functionals reveals that substantial proton Z = 154 and 186 and neutron N = 228, 308, and 406 spherical shell gaps exist in all functionals. The nuclei in the vicinity of the combination of these particle numbers form the islands of stability of spherical hyperheavy nuclei. Furthermore, the study suggests that the N = 210 toroidal shell gap plays a substantial role in the stabilization of fat toroidal nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Charge radii in covariant density functional theory: A global view

A systematic global investigation of differential charge radii has been performed within the CDFT framework for the first time. Theoretical results obtained with conventional covariant energy density functionals and the separable pairing interaction of Tian et al. [Phys. Lett. B 676, 44 (2009)] are compared with experimental differential charge radii in the regions of the nuclear chart in which available experimental data crosses the neutron shell closures at N=28,50,82, and 126. The analysis of absolute differential radii of different isotopic chains and their relative properties indicate clearly that such properties are reasonably well described in model calculations in the cases when the mean-field approximation is justified. However, while the observed clusterization of differential charge radii of different isotopic chains is well described above the N=50 and N=126 shell closures, it is more difficult to reproduce it above the N=28 and N=82 shell closures because of possible deficiencies in the underlying single-particle structure. The impact of the latter has been evaluated for spherical shapes and it was shown that the relative energies of the single-particle states and the patterns of their occupation with increasing neutron number have an appreciable impact on the evolution of the δ$\langle$r2$\rangle$N,N' values. These factors also limit the predictive power of model calculations in the regions of high densities of the single-particle states of different origin. It is shown that the kinks in the charge radii at neutron shell closures are due to the underlying single-particle structure and due to weakening or collapse of pairing at these closures. The regions of the nuclear chart in which the correlations beyond mean field are expected to have an impact on charge radii are indicated; the analysis shows that the assignment of a calculated excited prolate minimum to the experimental ground state allows us to understand the trends of the evolution of differential charge radii with neutron number in many cases of shape coexistence even at the mean-field level. It is usually assumed that pairing is a dominant contributor to odd-even staggering (OES) in charge radii. Our analysis paints a more complicated picture. It suggests a new mechanism in which the fragmentation of the single-particle content of the ground state in odd-mass nuclei due to particle-vibration coupling provides a significant contribution to OES in charge radii.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Neural network emulation of spontaneous fission

Large-scale computations of fission properties are an important ingredient for nuclear reaction network calculations simulating rapid neutron-capture process (the 𝑟 process) nucleosynthesis. Due to the large number of fissioning nuclei potentially contributing to the 𝑟 process, a microscopic description of fission based on nuclear density functional theory (DFT) is computationally challenging. Here, we explore the use of neural networks (NNs) to construct DFT emulators capable of predicting potential energy surfaces and collective inertia tensors across the whole nuclear chart, starting from a minimal set of DFT calculations. We use constrained Hartree-Fock-Bogoliubov (HFB) calculations to predict the potential energy and collective inertia tensor in the axial quadrupole and octupole collective coordinates, for a set of nuclei in the 𝑟-process region. We then employ NNs to emulate the HFB energy and collective inertia tensor across the considered region of the nuclear chart. Least-action pathways characterizing spontaneous fission half-lives and fragment yields are then obtained by means of the nudged elastic band method. The potential energy predicted by NNs agrees with the DFT value to within a root-mean-square error of 500 keV, and the collective inertia components agree to within an order of magnitude. These results are largely independent of the NN architecture. The exit points on the outer turning line are found to be well emulated. For the spontaneous fission half-lives the NN emulation provides values that are found to agree with the DFT predictions within a factor of 10 3 across more than 70 orders of magnitude. Neural networks are able to emulate the potential energy and collective inertia well enough to reasonably predict physical observables. Future directions of study, such as the inclusion of additional collective degrees of freedom and active learning, will improve the predictive power of microscopic theory and further enable large-scale fission studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Reaching the prolate-oblate boundary at 𝑁=116 via first fragmentation of a 198 Pt beam: Sharp transition to triaxiality in 189 Ta

High-spin isomers in very-neutron-rich 𝐴≈190 Hf-Ta-W nuclei were populated via the pioneering fragmentation of a 198 Pt primary beam at the National Superconducting Cyclotron Laboratory. The nuclei were implanted in a Si detector stack surrounded by the Gamma-Ray Energy Tracking In-beam Nuclear Array (GRETINA) to detect delayed 𝛾 rays, providing first level schemes using 𝛾−𝛾 coincidence data from isomeric decays in this previously inaccessible region of the nuclear chart. Here, a sudden transition to a strong triaxial shape is observed in the very-neutron-rich 189 Ta (𝑁 = 116) nucleus from axially prolate shapes in lighter Ta isotopes, providing a critical experimental benchmark for competing theoretical predictions of nuclear-shape evolution.

150 ≤ A ≤ 189↗