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At least 487 records · Page 27

The Evolution of a Pitch-Angle "Bite-Out" Scattering Signature Caused by EMIC Wave Activity: A Case Study

Electromagnetic ion cyclotron (EMIC) waves are understood to be one of the dominant drivers of relativistic electron loss from Earth's radiation belts. Theory predicts that the associated gyroresonant wave‐particle interaction results in a distinct energy‐dependent “bite‐out” signature in the normalized flux distribution of electrons as they are scattered into the loss cone. We identify such signatures along with the responsible EMIC waves captured in situ by the Van Allen Probes on 15–16 February 2017. Using the cold plasma approximation, we predict the pitch‐angle cutoffs for the scattering signature for the captured EMIC wave and find it in good agreement with the observed electron bite‐out scattering signature. Employing the close conjunction between the Van Allen Probes and THEMIS during this time, we explore the temporal and spatial evolution of the scattering signature, as well as the surrounding wave activity, and find that the scattering signature formed during continued wave activity over a period less than a day. These results are consistent with wave‐particle interaction theory and support the hypothesis that EMIC waves are an important mechanism for rapid relativistic electron loss from the radiation belts.

Bingley, L.↗

Uncertainty Quantification of Inducer Natural Frequency using Conditional Assessment of Modeling and Modal Testing of Simpler Systems

The low pressure fuel pump inducer of the new Space Launch System RS25 core stage engine operates in a highly complex environment that substantially affects its modal characteristics. Some of the more important effects are fluid-added mass resulting from operation within a light liquid (Hydrogen), and the magnification of this effect due to tight tip clearance. Since higher order cavitation has been identified as a significant harmonic driver, knowledge of the natural frequency of potentially excitable modes is critical for safe operation, but this frequency cannot be measured during the severe operational environment. A comprehensive testing and analysis program has therefore been performed over the last four years to identify the nominal value and uncertainty of the frequency by modeling and testing four simpler structures which share some of the characteristics of the operational inducer. This testing was used to assess and adjust modeling techniques and excellent correlation was achieved. Identification of the uncertainty in the inducer frequency itself was still problematic, however. This difficulty led to an investigation of Bayesian uncertainty quantification techniques, and to the application of the relatively simple technique of Multi-Variate Normal conditional distributions to calculate the inducer natural frequency uncertainty. Assumptions on prior distributions of uncertainty of the fluid-added mass and tip clearance effect are initially applied to models of each of the simple structures and the inducer itself, and these uncertainties are propagated to generate natural frequencies using design of experiments. Simple response surfaces are then created from this data in order to calculate a Covariance Matrix relating all of these natural frequencies. Finally, the results from modal test of the simple structures are considered to be observations and used to calculate the conditional variance of the desired inducer frequencies. As this method is less rigorous than more complicated Bayesian methods reported in the literature, a conservative factor is applied to the result, but the resulting uncertainty is still significantly less than originally estimated and will greatly assist certification of the inducer for use in the engine.

Uncertainty Quantification↗

Uncertainty Quantification of Inducer Eigenvalues using Conditional Assessment of Models and Modal Test of Simpler Systems

The low pressure fuel pump inducer of the new Space Launch System RS25 core stage engine operates in a highly complex environment that substantially affects its modal characteristics. Some of the more important effects are fluid-added mass resulting from operation within a light liquid (Hydrogen), and the magnification of this effect due to tight tip clearance. Since higher order cavitation has been identified as a significant harmonic driver, knowledge of the natural frequency of potentially excitable modes is critical for safe operation, but this frequency cannot be measured during the severe operational environment. A comprehensive testing and analysis program has therefore been performed over the last four years to identify the nominal value and uncertainty of the frequency by modeling and testing four simpler structures which share some of the characteristics of the operational inducer. This testing was used to assess and adjust modeling techniques and excellent correlation was achieved. Identification of the uncertainty in the inducer frequency itself was still problematic, however. This difficulty led to an investigation of Bayesian uncertainty quantification techniques, and to the application of the relatively simple technique of Multi-Variate Normal conditional distributions to calculate the inducer natural frequency uncertainty. Assumptions on prior distributions of uncertainty of the fluid-added mass and tip clearance effect are initially applied to models of each of the simple structures and the inducer itself, and these uncertainties are propagated to generate natural frequencies using design of experiments. Simple response surfaces are then created from this data in order to calculate a Covariance Matrix relating all of these natural frequencies. Finally, the results from modal test of the simple structures are considered to be observations and used to calculate the conditional variance of the desired inducer frequencies. As this method is less rigorous than more complicated Bayesian methods reported in the literature, a conservative factor is applied to the result, but the resulting uncertainty is still significantly less than originally estimated and will greatly assist certification of the inducer for use in the engine.

Uncertainty Quantification↗

New Constraints on the Volatile Deposit in Mercury’s North Polar Crater, Prokofiev

We present new high-resolution topographic, illumination, and thermal models of Mercury’s 112 km-diameter north polar crater, Prokofiev. The new models confirm previous results that water ice is stable at the surface within the permanently shadowed region (PSR) of Prokofiev for geologic timescales. The largest radar-bright region in Prokofiev is confirmed to extend up to several kilometers past the boundary of its PSR making it unique on Mercury for hosting a significant radar-bright area outside a PSR. The near-infrared normal albedo distribution of Prokofiev’s PSR suggests the presence of a darkening agent rather than pure surface ice. Linear mixture models predict at least roughly half of the surface area to be covered with this dark material. Using improved altimetry in this crater, we place an upper limit of 26 m on its ice deposit thickness. The 1 km-baseline topographic slope and roughness of the radar-bright deposit are lower than the non-radar-bright floor although the difference is not statistically significant when compared to the non-radar-bright floor’s natural topographic variations. These results place new constraints on the nature of Prokofiev’s volatile deposit that will inform future missions, such as BepiColombo.

Michael K Barker↗

Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker–Planck Equations

The Fokker-Planck (FP) equation is a foundational partial differential equation (PDE) in stochastic processes involving Brownian motions. However, the curse of dimensionality (CoD) poses a formidable challenge when dealing with high-dimensional FP equations. Although Monte Carlo simulation and (vanilla) Physics-Informed Neural Networks (PINNs) have shown the potential to tackle CoD, both methods exhibit significant numerical errors in high dimensions when dealing with the probability density function (PDF) associated with Brownian motion. The point-wise PDF values tend to decrease exponentially as dimensionality increases, surpassing the precision of numerical simulations and resulting in substantial errors. In addition, due to its massive sampling, Monte Carlo fails to offer fast sampling. Modeling the logarithm likelihood (LL) via vanilla PINNs transforms the FP equation into a notoriously difficult Hamilton-Jacobi-Bellman (HJB) equation, which is impractical for PINN learning, whose error grows rapidly with dimension. To this end, we propose a novel approach utilizing a score-based solver to fit the score function in stochastic differential equations (SDEs). The score function, defined as the gradient of the LL, plays a fundamental role in inferring LL and PDF and enables fast SDE sampling, offering an effective means to overcome the CoD. Three fitting methods, Score Matching (SM), Sliced Score Matching (SSM), and Score-PINN, are introduced, each contributing unique advantages in computational complexity, accuracy, and generality. The proposed score-based SDE solver operates in two stages: first, employing score matching or Score-PINN to acquire the score function; and second, solving the LL via an ordinary differential equation (ODE) using the obtained score function. Comparative evaluations across these methods showcase varying trade-offs. The proposed methodology is evaluated across diverse SDEs, including anisotropic Ornstein-Uhlenbeck processes, geometric Brownian motion, and Brownian motion with varying eigenspace. We also test various distributions, including Gaussian, Log-normal, Laplace, and Cauchy distributions. The numerical results demonstrate the score-based SDE solver’s stability, speed, and performance across different experimental settings, solidifying its potential as a solution to CoD for high-dimensional FP equations.

97 MATHEMATICS AND COMPUTING↗

A comparative review of radiation aerosol models

Aerosol characteristics to be introduced into a set of models within a framework of a Standard Radiation Atmosphere (SRA) are reviewed, and a reconciliation of the Toon and Pollack (TP) global model with the SRA models is attempted. Among the topics discussed are physical and radiative characteristics, radiation aerosol models, albedo for single scattering, and phase function and spectral variation of extinction. Size distribution models are also covered, inclusive the Junge power law, and the modified gamma-, log normal-, and zold-distribution. Recommendations include modifying the SRA profile VI to resemble the Elterman profile modified in the TP model, improving discontinuity at the tropopause level for all SRA models, and retaining the same log-normal size distribution for all SRA components.

Lenoble, J.↗

Analysis of field size distributions, LACIE test sites 5029, 5033, and 5039, Anhwei Province, People's Republic of China

A study was made of the field size distributions for LACIE test sites 5029, 5033, and 5039, People's Republic of China. Field lengths and widths were measured from LANDSAT imagery, and field area was statistically modeled. Field size parameters have log-normal or Poisson frequency distributions. These were normalized to the Gaussian distribution and theoretical population curves were made. When compared to fields in other areas of the same country measured in the previous study, field lengths and widths in the three LACIE test sites were 2 to 3 times smaller and areas were smaller by an order of magnitude.

Podwysocki, M. H.↗

Information extraction techniques for multispectral scanner data

The applicability of recognition-processing procedures for multispectral scanner data from areas and conditions used for programming the recognition computers to other data from different areas viewed under different measurement conditions was studied. The reflective spectral region approximately 0.3 to 3.0 micrometers is considered. A potential application of such techniques is in conducting area surveys. Work in three general areas is reported: (1) Nature of sources of systematic variation in multispectral scanner radiation signals, (2) An investigation of various techniques for overcoming systematic variations in scanner data; (3) The use of decision rules based upon empirical distributions of scanner signals rather than upon the usually assumed multivariate normal (Gaussian) signal distributions.

Malila, W. A.↗

A study of lunar impact crater size-distributions

In view of the discrepancies in published crater frequency data, effects modifying production size distributions of impact craters are discussed. The resulting criteria are applied to the determination of the size distributions of unmodified impact crater populations in selected lunar regions of different ages. The measured cumulative crater frequencies are used to obtain a general calibration size distribution curve by a normalization procedure. Deviations of measured size distributions from the calibration distribution are strongly suggestive of the existence of processes having modified the primary impact crater population.

Neukum, G.↗

Probabilistic structural analysis of a truss typical for space station

A three-bay, space, cantilever truss is probabilistically evaluated using the computer code NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) to identify and quantify the uncertainties and respective sensitivities associated with corresponding uncertainties in the primitive variables (structural, material, and loads parameters) that defines the truss. The distribution of each of these primitive variables is described in terms of one of several available distributions such as the Weibull, exponential, normal, log-normal, etc. The cumulative distribution function (CDF's) for the response functions considered and sensitivities associated with the primitive variables for given response are investigated. These sensitivities help in determining the dominating primitive variables for that response.

Pai, Shantaram S.↗

Normalizing flows for domain adaptation when identifying Λ hyperon events

Here this study focuses on the application of a normalizing flow as a method of domain adaptation when classifying physics data. Normalizing flows offer a way to transform data points between two different distributions. The present study investigates a novel method of transforming latent representations of physics data to a normal distribution and then to a physics distribution again. The final distribution models a simulated distribution. After being transformed, the data can be classified by a neural network trained on labeled simulation data. The present study succeeds in training two normalizing flows that can transform between data (or simulation) and a Gaussian distribution.

47 OTHER INSTRUMENTATION↗

Bayesian mixture model approach to quantifying the empirical nuclear saturation point

The equation of state (EOS) in the limit of infinite symmetric nuclear matter exhibits an equilibrium density, $n_0 \approx 0.16 \, \mathrm{fm}^{-3}$, at which the pressure vanishes and the energy per particle attains its minimum, $E_0 \approx -16 \, \mathrm{MeV}$. Although not directly measurable, the nuclear saturation point $(n_0,E_0)$ can be extrapolated by density functional theory (DFT), providing tight constraints for microscopic interactions derived from chiral effective field theory (EFT). However, when considering several DFT predictions for $(n_0,E_0)$ from Skyrme and Relativistic Mean Field (RMF) models together, a discrepancy between these model classes emerges at high confidence levels that each model prediction's uncertainty cannot explain. How can we leverage these DFT constraints to rigorously benchmark nuclear saturation properties of chiral interactions? To address this question, we present a Bayesian mixture model that combines multiple DFT predictions for $(n_0,E_0)$ using an efficient conjugate prior approach. The inferred posterior distribution for the saturation point's mean and covariance matrix follows a Normal-inverse-Wishart class, resulting in posterior predictives in the form of correlated, bivariate $t$-distributions. The DFT uncertainty reports are then used to mix these posteriors using an ordinary Monte Carlo approach. At the 95\% credibility level, we estimate $n_0 \approx 0.157 \pm 0.010 \, \mathrm{fm}^{-3}$ and $E_0 \approx -15.97 \pm 0.40 \, \mathrm{MeV}$ for the marginal (univariate) $t$-distributions. Combined with chiral EFT calculations of the pure neutron matter EOS, we obtain bivariate normal distributions for the nuclear symmetry energy and its slope parameter evaluated at $n_0$: $S_v \approx 32.0 \pm 1.1 \, \mathrm{MeV}$ and $L\approx 52.6\pm 8.1 \, \mathrm{MeV}$ (95\%), respectively. Furthermore, our Bayesian framework is publicly available, so practitioners can readily use and extend our results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Intermediate Wake of a Thin Flat Plate with a Circular Trailing Edge

The intermediate wakes of thin flat plates with circular trailing edges (TEs) are investigated here with direct numerical simulations (DNSs). The separating boundary layers are turbulent in all cases. The near wake in two thin-plate cases (IN & NS), with a focus on the vortex shedding process, was explored in a recent article. Intermittent shedding was observed in Case IN. Case NS, with half the TE diameter of Case IN, was an essentially non-shedding case. A third case (ST) with a sharp trailing edge was also investigated and found to exhibit an intermittent wake instability. The objectives of the present study are twofold. The first is to determine if the wake instability found in Case ST exists in Cases IN and NS as well. The second is to provide the distributions of the turbulent normal intensities and shear stress in the wake and to understand these distributions via the budget terms in the corresponding transport equations. The results show that both Cases IN & NS exhibit a wake instability in the intermediate wake region, that is similar to that found earlier in Case ST. We note that in Case IN, the presence of an intermediate-wake instability results in the co-existence of two different types of instability within a single wake. The distributions of the turbulent normal intensities and shear stress, and the budget terms for the streamwise intensity are included and discussed here. All the budget terms contribute appreciably to the overall budget in the transport equation for streamwise normal intensity.

Rai, Man Mohan↗

Interplanetary Fast Shocks and Associated Drivers Observed through the Twenty-Third Solar Minimum by WIND Over its First 2.5 Years

A list of the interplanetary (IP) shocks observed by WIND from its launch (in November 1994) to May 1997 is presented. Forty two shocks were identified. The magnetohydrodynamic nature of the shocks is investigated, and the associated shock parameters and their uncertainties are accurately computed using a practical scheme which combines two techniques. These techniques are a combination of the "pre-averaged" magnetic-coplanarity, velocity-coplanarity, and the Abraham-Schrauner-mixed methods, on the one hand, and the Vinas and Scudder [1986] technique for solving the non-linear least-squares Rankine-Hugoniot shock equations, on the other. Within acceptable limits these two techniques generally gave the same results, with some exceptions. The reasons for the exceptions are discussed. It is found that the mean strength and rate of occurrence of the shocks appears to correlated with the solar cycle. Both showed a decrease in 1996 coincident with the time of the lowest ultraviolet solar radiance, indicative of solar minimum and start of solar cycle 23, which began around June 1996. Eighteen shocks appeared to be associated with corotating interaction regions (CIRs). The distribution of their shock normals showed a mean direction peaking in the ecliptic plane and with a longitude (phi(sub n)) in that plane between perpendicular to the Parker spiral and radial from the Sun. When grouped according to the sense of the direction of propagation of the shocks the mean azimuthal (longitude) angle in GSE coordinates was approximately 194 deg for the fast-forward and approximately 20 deg for the fast-reverse shocks. Another 16 shocks were determined to be driven by solar transients, including magnetic clouds. These shocks had a broader distribution of normal directions than those of the CIR cases with a mean direction close to the Sun-Earth line. Eight shocks of unknown origin had normal orientation well off the ecliptic plane. No shock propagated with longitude phi(sub n) >= 220 +/- 10 deg, this would suggest strong hindrance to the propagation of shocks contra a rather tightly winding Parker spiral. Examination of the obliquity angle theta(sub Bn) (that between the shock normal and the upstream interplanetary magnetic field) for the full set of shocks revealed that about 58% was quasi-perpendicular, and some were very nearly perpendicular. About 32% of the shocks were oblique, and the rest (only 10%) were quasi-parallel, with one on Dec. 9, 1996 that showed field pulsations. Small uncertainty in the estimated angle theta(sub Bn) was obtained for about 10 shocks with magnetosonic Mach numbers between 1 and 2, hopefully significantly contributing to studies researching particle acceleration mechanisms at IP shocks, and to investigations where accurate values of theta(sub Bn) are crucial.

Mariani, F.↗

Distributed Coordination of Networked Microgrids for Voltage Support in Bulk Power Grids

The increasing deployment of distributed energy resources (DERs) and microgrids (MGs) in power distribution systems has enabled the adjustment of reactive power consumption as seen at the substation, which can be used to provide voltage support for the bulk power system (BPS). Leveraging this new capability will provide greater resiliency to the power system as a whole. Here, the goal of this paper is to develop and compare three different algorithms, namely distributed optimal power flow, distributed consensus algorithm, and fully decentralized collaborative autonomy for unbalanced distribution systems for microgrid coordination. These algorithms use networked MGs to support the BPS voltage when a contingency at the bulk grid results in abnormally low voltages, which may be a precursor to voltage collapse. Our comparative analysis includes both qualitative and quantitative assessments of the three algorithms and a discussion of the trade-offs between the decentralized and distributed methods in normal and disrupted conditions. Each algorithm was evaluated on the modified IEEE 13-bus system and a real power distribution system at Chattanooga, Tennessee, that encompasses more than 4500 buses. Each algorithms excels differently and may be suited for different scenarios depending on the condition, operations, and priorities of the power and communication systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Benefit Assessment of the Precision Departure Release Capability Concept

A Precision Departure Release Capability concept is being evaluated by both the National Aeronautics and Space Administration and the Federal Aviation Administration as part of a larger goal of improving throughput, efficiency and capacity in integrated departure, arrival and surface operations. The concept is believed to have the potential of increasing flight efficiency and throughput by avoiding missing assigned slots and minimizing speed increase or path stretch to recover the slot. The main thrust of the paper is determining the impact of early and late departures from the departure runway when an aircraft has a slot assigned either at a meter fix or at the arrival airport. Results reported in the paper are for two scenarios. The first scenario considers flights out of Dallas/Fort Worth destined for Hartsfield-Jackson International Airport in Atlanta flying through the Meridian meter-fix in the Memphis Center with miles-in-trail constraints. The second scenario considers flights destined to George Bush Intercontinental/Houston Airport with specified airport arrival rate constraint. Results show that delay reduction can be achieved by allowing reasonable speed changes in scheduling. It was determined that the traffic volume between Dallas/Fort Worth and Atlanta via the Meridian fix is low and the departures times are spread enough that large departure schedule uncertainty can be tolerated. Flights can depart early or late within 90 minutes without accruing much more delay due to miles-in-trail constraint at the Meridian fix. In the Houston scenario, 808 arrivals from 174 airports were considered. Results show that delay experienced by the 16 Dallas/Fort Worth departures is higher if initial schedules of the remaining 792 flights are kept unaltered while they are rescheduled. Analysis shows that the probability of getting the initially assigned slot back after perturbation and rescheduling decreases with increasing standard deviation of the departure delay distributions. Results show that most Houston arrivals can be expected to be on time based on the assumed zero-mean Normal departure delay distributions achievable by Precision Departure Release Capability. In the current system, airport-departure delay, which is the sum of gate-departure delay and taxi-out delay, is observed at the airports. This delay acts as a bias, which can be reduced by Precision Departure Release Capability.

Palopo, Kee↗