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At least 109 records · Page 6

Electron Heat Flux in Pressure Balance Structures at Ulysses

Pressure balance structures (PBSs) are a common feature in the high-latitude solar wind near solar minimum. Rom previous studies, PBSs are believed to be remnants of coronal plumes and be related to network activity such as magnetic reconnection in the photosphere. We investigated the magnetic structures of the PBSs, applying a minimum variance analysis to Ulysses/Magnetometer data. At 2001 AGU Spring meeting, we reported that PBSs have structures like current sheets or plasmoids, and suggested that they are associated with network activity at the base of polar plumes. In this paper, we have analyzed high-energy electron data at Ulysses/SWOOPS to see whether bi-directional electron flow exists and confirm the conclusions more precisely. As a result, although most events show a typical flux directed away from the Sun, we have obtained evidence that some PBSs show bi-directional electron flux and others show an isotropic distribution of electron pitch angles. The evidence shows that plasmoids are flowing away from the Sun, changing their flow direction dynamically in a way not caused by Alfven waves. From this, we have concluded that PBSs are generated due to network activity at the base of polar plumes and their magnetic structures axe current sheets or plasmoids.

Yamauchi, Yohei↗

Obtaining Reliable Predictions of Terrestrial Energy Coupling From Real-Time Solar Wind Measurements

Measurements of the interplanetary magnetic field (IMF) from the ACE (Advanced Composition Explorer), Wind, IMP-8 (Interplanetary Monitoring Platform), and Geotail spacecraft have revealed that the IMF variations are contained in phase planes that are tilted with respect to the propagation direction, resulting in continuously variable changes in propagation times between spacecraft, and therefore, to the Earth. Techniques for using 'minimum variance analysis' have been developed in order to be able to measure the phase front tilt angles, and better predict the actual propagation times from the L1 orbit to the Earth, using only the real-time IMF measurements from one spacecraft. The use of empirical models with the IMF measurements at L1 from ACE (or future satellites) for predicting 'space weather' effects has also been demonstrated.

Weimer, Daniel R.↗

Electron Pitch-Angle Distribution in Pressure Balance Structures Measured by Ulysses/SWOOPS

Pressure balance structures (PBSs) are a common feature in the high-latitude solar wind near solar minimum. From previous studies, PBSs are believed to be remnants of coronal plumes. Yamauchi et al [2002] investigated the magnetic structures of the PBSs, applying a minimum variance analysis to Ulysses/Magnetometer data. They found that PBSs contain structures like current sheets or plasmoids, and suggested that PBSs are associated with network activity such as magnetic reconnection in the photosphere at the base of polar plumes. We have investigated energetic electron data from Ulysses/SWOOPS to see whether bi-directional electron flow exists and we have found evidence supporting the earlier conclusions. We find that 45 ot of 53 PBSs show local bi-directional or isotopic electron flux or flux associated with current-sheet structure. Only five events show the pitch-angle distribution expected for Alfvenic fluctuations. We conclude that PBSs do contain magnetic structures such as current sheets or plasmoids that are expected as a result of network activity at the base of polar plumes.

Yamauchi, Yohei↗

Differential Velocity Between Solar Wind Protons and Alpha Particles in Pressure Balance Structures

Pressure balance structures (PBSs) are a common high plasma beta feature in high latitude, high speed solar wind. They have been proposed as remnants of coronal plumes. If true, they should reflect the observation that plumes are rooted in unipolar magnetic flux concentrations in the photosphere and are heated as oppositely directed flux is advected into and reconnects with the flux concentration. A minimum variance analysis (MVA) of magnetic discontinuities in PBSs showed there is a larger proportion of tangential discontinuities than in the surrounding high speed wind, supporting the hypothesis that plasmoids or extended current sheets are formed during reconnection at the base of plumes. To further evaluate the character of magnetic field discontinuities in PBSs, differential streaming between alpha particles and protons is analyzed here for the same sample of PBSs used in the MVA. Alpha particles in high speed wind generally have a higher radial flow speed than protons. However, if the magnetic field is folded back on itself, as in a large amplitude Alfven wave, alpha particles will locally have a radial flow speed less than protons. This characteristic is used here to distinguish between folded back magnetic fields (which would contain rotational discontinuities) and tangential discontinuities using Ulysses high latitude, high speed solar wind data. The analysis indicates that almost all reversals in the radial magnetic field in PBSs are folded back field lines. This is found to also be true outside PBSs, supporting existing results for typical high speed, high latitude wind. There remains a small number of cases that appear not to be folds in the magnetic field and which may be flux tubes with both ends rooted in the Sun. The distinct difference in MVA results inside and outside PBSs remains unexplained.

Yamauchi, Y.↗

Differential Velocity between Solar Wind Protons and Alpha Particles in Pressure Balance Structures

Pressure balance structures (PBSs) are a common high-plasma beta feature in high-latitude, high-speed solar wind. They have been proposed as remnants of coronal plumes. If true, they should reflect the observation that plumes are rooted in unipolar magnetic flux concentrations in the photosphere and are heated as oppositely directed flux is advected into and reconnects with the flux concentration. A minimum variance analysis (MVA) of magnetic discontinuities in PBSs showed there is a larger proportion of tangential discontinuities than in the surrounding high-speed wind, supporting the hypothesis that plasmoids or extended current sheets are formed during reconnection at the base of plumes. To further evaluate the character of magnetic field discontinuities in PBSs, differential streaming between alpha particles and protons is analyzed here for the same sample of PBSs used in the MVA. Alpha particles in high-speed wind generally have a higher radial flow speed than protons. However, if the magnetic field is folded back on itself, as in a large-amplitude Alfven wave, alpha particles will locally have a radial flow speed less than protons. This characteristic is used here to distinguish between folded back magnetic fields (which would contain rotational discontinuities) and tangential discontinuities using Ulysses high-latitude, high-speed solar wind data. The analysis indicates that almost all reversals in the radial magnetic field in PBSs are folded back field lines. This is found to also be true outside PBSs, supporting existing results for typical high-speed, high-latitude wind. There remains a small number of cases that appear not to be folds in the magnetic field and which may be flux tubes with both ends rooted in the Sun. The distinct difference in MVA results inside and outside PBSs remains unexplained.

Yamauchi, Yohei↗

6DOF Testing of the SLS Inertial Navigation Unit

The Navigation System on the NASA Space Launch System (SLS) Block 1 vehicle performs initial alignment of the Inertial Navigation System (INS) navigation frame through gyrocompass alignment (GCA). In lieu of direct testing of GCA accuracy in support of requirement verification, the SLS Navigation Team proposed and conducted an engineering test to, among other things, validate the GCA performance and overall behavior of the SLS INS model through comparison with test data. This paper will detail dynamic hardware testing of the SLS INS, conducted by the SLS Navigation Team at Marshall Space Flight Center's 6DOF Table Facility, in support of GCA performance characterization and INS model validation. A 6-DOF motion platform was used to produce 6DOF pad twist and sway dynamics while a simulated SLS flight computer communicated with the INS. Tests conducted include an evaluation of GCA algorithm robustness to increasingly dynamic pad environments, an examination of GCA algorithm stability and accuracy over long durations, and a long-duration static test to gather enough data for Allan Variance analysis. Test setup, execution, and data analysis will be discussed, including analysis performed in support of SLS INS model validation.

Geohagan, Kevin W.↗

Statistical Study of the Properties of Magnetosheath Lion Roars

Lion roars are narrowband whistler wave emissions that have been observed in several environments, such as planetary magnetosheaths, the Earth's magnetosphere, the solar wind, downstream of interplanetary shocks, and the cusp region. We present measurements of more than 30,000 such emissions observed by the Magnetospheric Multiscale spacecraft with high‐cadence (8,192 samples/s) search coil magnetometer data. A semiautomatic algorithm was used to identify the emissions, and an adaptive interval algorithm in conjunction with minimum variance analysis was used to determine their wave vector. The properties of the waves are determined in both the spacecraft and plasma rest frame. The mean wave normal angle, with respect to the background magnetic field (B(sub 0)), plasma bulk flow velocity (V(sub b)), and the coplanarity plane (V(sub b) × B(sub 0)) are 23°, 56°, and 0°, respectively. The average peak frequencies were ∼31% of the electron gyrofrequency (ω(sub ce)) observed in the spacecraft frame and ∼18% of ω(sub ce) in the plasma rest frame. In the spacecraft frame, ∼99% of the emissions had a frequency <ω(sub ce), while 98% had a peak frequency <0.72 ω(sub ce) in the plasma rest frame. None of the waves had frequencies lower than the lower hybrid frequency, ω. From the probability density function of the electron plasma β(sub e), the ratio between the electron thermal and magnetic pressure, ∼99.6% of the waves were observed with β(sub e)<4 with a large narrow peak at 0.07 and two smaller, but wider, peaks at 1.26 and 2.28, while the average value was ∼1.25.

Magnetosheath emissions↗

Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty

Sensitivity analysis plays a critical role in quantifying uncertainty in the design of engineering systems. A variance-based global sensitivity analysis is often used to rank the importance of input factors, based on their contribution to the variance of the output quantity of interest. However, this analysis assumes that all input variability can be reduced to zero, which is typically not the case in a design setting. Distributional sensitivity analysis (DSA) instead treats the uncertainty reduction in the inputs as a random variable, and defines a variance-based sensitivity index function that characterizes the relative contribution to the output variance as a function of the amount of uncertainty reduction. This paper develops a computationally efficient implementation for the DSA formulation and extends it to include distributions commonly used in engineering design under uncertainty. Application of the DSA method to the conceptual design of a commercial jetliner demonstrates how the sensitivity analysis provides valuable information to designers and decision-makers on where and how to target uncertainty reduction efforts.

42 ENGINEERING↗

ANALYSIS OF VARIANCE-BASED MIXED MULTISCALE FINITE ELEMENT METHOD AND APPLICATIONS IN STOCHASTIC TWO-PHASE FLOWS

The stochastic partial differential systems have been widely used to model physical processes, where the inputs involve large uncertainties. Flows in random and heterogeneous porous media is one of the cases where the random inputs (e.g., permeability) are often modeled as a stochastic field with high-dimensional random parameters. To treat the high dimensionality and heterogeneity efficiently, model reduction is employed in both stochastic space and physical space. An analysis of variance (ANOVA)-based mixed multiscale finite element method MsFEM) is developed to decompose the high-dimensional stochastic problem into a set of lower-dimensional stochastic subproblems, which require much less computational complexity and significantly reduce the computational cost in stochastic space, and the mixed MsFEM can capture the heterogeneities on a coarse grid to greatly reduce the computational cost in the spatial domain. In addition, to enhance the efficiency of the traditional ANOVA method, an adaptive ANOVA method based on a new adaptive criterion is developed, where the most active dimensions can be selected to greatly reduce the computational cost before conducting ANOVA decomposition. This novel adaptive criterion is based on variance-decomposition method coupled with sparse-grid probabilistic collocation method or multilevel Monte Carlo method. The advantage of this adaptive criterion lies in its much lower computational overhead for identifying the active dimensions and interactions. A number of numerical examples in two-phase stochastic flows are presented and demonstrate the accuracy and performance of the adaptive ANOVA-based mixed Ms-FEM.

Wei, Jia↗

Sensitivity analysis of simulated SOA loadings using a variance-based statistical approach: SENSITIVITY ANALYSIS OF SOA

We investigate the sensitivity of secondary organic aerosol (SOA) loadings simulated by a regional chemical transport model to 7 selected tunable model parameters: 4 involving emissions of anthropogenic and biogenic volatile organic compounds, anthropogenic semi-volatile and intermediate volatility organics (SIVOCs), and NOx, 2 involving dry deposition of SOA precursor gases, and one involving particle-phase transformation of SOA to low volatility. We adopt a quasi-Monte Carlo sampling approach to effectively sample the high-dimensional parameter space, and perform a 250 member ensemble of simulations using a regional model, accounting for some of the latest advances in SOA treatments based on our recent work. We then conduct a variance-based sensitivity analysis using the generalized linear model method to study the responses of simulated SOA loadings to the tunable parameters. Analysis of SOA variance from all 250 simulations shows that the volatility transformation parameter, which controls whether particle-phase transformation of SOA from semi-volatile SOA to non-volatile is on or off, is the dominant contributor to variance of simulated surface-level daytime SOA (65% domain average contribution). We also split the simulations into 2 subsets of 125 each, depending on whether the volatility transformation is turned on/off. For each subset, the SOA variances are dominated by the parameters involving biogenic VOC and anthropogenic SIVOC emissions. Furthermore, biogenic VOC emissions have a larger contribution to SOA variance when the SOA transformation to non-volatile is on, while anthropogenic SIVOC emissions have a larger contribution when the transformation is off. NOx contributes less than 4.3% to SOA variance, and this low contribution is mainly attributed to dominance of intermediate to high NOx conditions throughout the simulated domain. The two parameters related to dry deposition of SOA precursor gases also have very low contributions to SOA variance. This study highlights the large sensitivity of SOA loadings to the particle-phase transformation of SOA volatility, which is neglected in most previous models.

Shrivastava, Manish↗

WE-D-BRE-07: Variance-Based Sensitivity Analysis to Quantify the Impact of Biological Uncertainties in Particle Therapy

Purpose: In particle therapy, treatment planning and evaluation are frequently based on biological models to estimate the relative biological effectiveness (RBE) or the equivalent dose in 2 Gy fractions (EQD2). In the context of the linear-quadratic model, these quantities depend on biological parameters (α, β) for ions as well as for the reference radiation and on the dose per fraction. The needed biological parameters as well as their dependency on ion species and ion energy typically are subject to large (relative) uncertainties of up to 20–40% or even more. Therefore it is necessary to estimate the resulting uncertainties in e.g. RBE or EQD2 caused by the uncertainties of the relevant input parameters. Methods: We use a variance-based sensitivity analysis (SA) approach, in which uncertainties in input parameters are modeled by random number distributions. The evaluated function is executed 10{sup 4} to 10{sup 6} times, each run with a different set of input parameters, randomly varied according to their assigned distribution. The sensitivity S is a variance-based ranking (from S = 0, no impact, to S = 1, only influential part) of the impact of input uncertainties. The SA approach is implemented for carbon ion treatment plans on 3D patient data, providing information about variations (and their origin) in RBE and EQD2. Results: The quantification enables 3D sensitivity maps, showing dependencies of RBE and EQD2 on different input uncertainties. The high number of runs allows displaying the interplay between different input uncertainties. The SA identifies input parameter combinations which result in extreme deviations of the result and the input parameter for which an uncertainty reduction is the most rewarding. Conclusion: The presented variance-based SA provides advantageous properties in terms of visualization and quantification of (biological) uncertainties and their impact. The method is very flexible, model independent, and enables a broad assessment of uncertainties. Supported by DFG grant WI 3745/1-1 and DFG cluster of excellence: Munich-Centre for Advanced Photonics.

60 APPLIED LIFE SCIENCES↗

Statistical analysis of Skylab 3

The results of endocrine/metabolic studies of astronauts on Skylab 3 are reported. One-way analysis of variance, contrasts, two-way unbalanced analysis of variance, and analysis of periodic changes in flight are included. Results for blood tests, and urine tests are presented.

Johnston, D. A.↗

Surrogate-driven Variance-based Sensitivity Analysis of Thermal Storage Tanks in Integrated Energy Systems

Sensitivity analysis and uncertainty quantification are essential steps for enhancing the accuracy of computational models by identifying and mitigating uncertainties. This study focuses on these steps for the Thermal Energy Delivery System at Idaho National Laboratory, specifically targeting the thermocline tank. Using a Modelica/Dymola simulation model, the study perturbed various design parameters and boundary conditions, including shape factor, porosity, outlet temperature, inlet mass flow rate, and system pressure, to predict and quantify uncertainty in the tank’s ax- ial temperature. A dataset of over 1,000 simulations was generated, and surrogate models were developed using the pyMAISE (Michigan Artificial Intelligence Standard Environment) library, which is an Automatic Machine Learning library for nuclear engineering applications. The optimal model, a feedforward neural network with two hidden layers, achieved an R2 score above 0.99 and a mean absolute error below 1 Kelvin. Sensitivity analyses using Sobol indices and Fourier amplitude sensitivity testing methods on this surrogate model revealed that the inlet mass flow rate at initial timestamps and porosity significantly impacts predicted temperatures across all sensors and time steps.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗