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NASA NTRS1988

Cosmological parameters and evolution of the galaxy luminosity function

The relationship between the observed distribution of discrete sources of a flux limited sample, the luminosity function of these sources, and the cosmological model is discussed. It is stressed that some assumptions about the form and evolution of the luminosity function must be made in order to determine the cosmological parameters from the observed distribution of sources. Presented is a method to test the validity of these assumptions using the observations. It is shown how, using higher moments of the observed distribution, one can determine, independently of the cosmological model, all parameters of the luminosity function except those describing evolution of the density and the luminosity of the luminosity function. These methods are applied to the sample of approximately 1000 galaxies recently used by Loh and Spillar to determine a value of the cosmological density parameter Omega approx = 1. It is shown that the assumptions made by Loh and Spillar about the luminosity function are inconsistent with the data, and that a self-consistent treatment of the data indicates a lower value of Omega approx = 0.2 and a flatter luminosity function. It should be noted, however, that incompleteness in the sample could cause a flattening of the luminosity function and lower the calculated value of Omega and that uncertainty in the values of these parameters due to random fluctuations is large.

Caditz, David↗

NASA NTRS1989

Cosmological parameters and evolution of the galaxy luminosity function

Caditz, David↗

DOE OSTI2025

Numerical Analysis of High-Order Modes in SRF Resonators for Particle Accelerators

Over the past decades, superconducting technology has rapidly evolved towards high accelerating gradients and low surface resistance, making it possible to operate particle accelerators with high average beam currents and large duty factors. However, RF losses due to coherent excitation of the HOM become the limiting factor for these regimes. Unlike the cavity operating mode, which is tuned separately, the HOM parameters can significantly vary from one cavity to another due to finite mechanical tolerances during the manufacturing process. Thus, it is of utmost importance to know the HOM parameter spread in advance in order to predict unexpected cryogenic losses, overheating of beam line components and maintain stable beam dynamics. In this paper, we present a method for generating cavity geometry with an arbitrary spread of mechanical imperfections and numerically evaluating HOM statistics. Knowing the spread of HOM parameters, we calculated the probability of resonant HOM losses in SRF accelerating cavities used in CW beam current machines such as the PIP-II and LCLS-II linacs, as well as for the SRF crab-cavity for the ILC project. Finally, we present experimental results of HOM spectra measurements in hundreds of 1.3 GHz cavities installed in LCLS-II cryomodules. Studying the effects of HOM excitation results in specifications of the SRF cavity and cryomodule and can significantly impact the efficiency and reliability of the machine operation.

Lunin, Andrei [Fermilab] (ORCID:0000000290096792)↗

DOE OSTI2022

Sensitivity Analysis of Wind and Turbulence Predictions With Mesoscale‐Coupled Large Eddy Simulations Using Ensemble Machine Learning

Abstract Coupling between mesoscale models and large‐eddy simulation (LES) models is increasingly used to more realistically represent the wide range of scales of atmospheric motions affecting boundary layer winds and turbulence that need to be simulated accurately for applications such as wind energy. However, such mesoscale‐to‐microscale coupled modeling frameworks are potentially affected by a large number of uncertain closure parameters. Here, we investigate the sensitivity associated with six closure parameters related to a 1.5‐order subgrid‐scale turbulence closure for an ensemble of mesoscale‐coupled LES. The simulations are performed using the Weather Research and Forecasting model nested from horizontal resolutions of greater than a kilometer down to tens of meters. Closure parameters are varied to generate perturbed parameter ensembles for two case studies of highly sheared, convective boundary layers observed in the Columbia Basin of Oregon and Washington during the Second Wind Forecast Improvement Project. Machine learning algorithms are used to explore the sensitivity of LES predictions, considering the effects of the perturbed physical parameters alongside categorical factors such as the case study identity, measurement location, and LES resolution. For the conditions we examine, a single parameter, the eddy viscosity coefficient, is the dominant source of parametric sensitivity and its importance is comparable to the categorical factors for several of the simulation response variables we examine.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1978

Roll tracking effects of G-vector tilt and various types of motion washout

In a dogfight scenario, the task was to follow the target's roll angle while suppressing gust disturbances. All subjects adopted the same behavioral strategies in following the target while suppressing the gusts, and the MFP-fitted math model response was generally within one data symbol width. The results include the following: (1) comparisons of full roll motion (both with and without the spurious gravity tilt cue) with the static case. These motion cues help suppress disturbances with little net effect on the visual performance. Tilt cues were clearly used by the pilots but gave only small improvement in tracking errors. (2) The optimum washout (in terms of performance close to real world, similar behavioral parameters, significant motion attenuation (60 percent), and acceptable motion fidelity) was the combined attenuation and first-order washout. (3) Various trends in parameters across the motion conditions were apparent, and are discussed with respect to a comprehensive model for predicting adaptation to various roll motion cues.

Jex, H. R.↗

NASA NTRS1985

The Nagoya cosmic-ray muon spectrometer 3, part 4: Track reconstruction method

One of the greatest problems in measuring particle trajectories with an optical or visual detector system, is the reconstruction of trajectories in real space from their recorded images. In the Nagoya cosmic-ray muon spectrometer, muon tracks are detected by wide gap spark chambers and their images are recorded on the photographic film through an optical system of 10 mirrors and two cameras. For the spatial reconstruction, 42 parameters of the optical system should be known to determine the configuration of this system. It is almost impossible to measure this many parameters directly with usual techniques. In order to solve this problem, the inverse transformation method was applied. In this method, all the optical parameters are determined from the locations of fiducial marks in real space and the locations of their images on the photographic film by the non-linear least square fitting.

Shibata, S.↗

NASA NTRS1989

Space station contamination modeling

Current plans for the operation of Space Station Freedom allow the orbit to decay to approximately an altitude of 200 km before reboosting to approximately 450 km. The Space Station will encounter dramatically increasing ambient and induced environmental effects as the orbit decays. Unfortunately, Shuttle docking, which has been of concern as a high contamination period, will likely occur during the time when the station is in the lowest orbit. The combination of ambient and induced environments along with the presence of the docked Shuttle could cause very severe contamination conditions at the lower orbital altitudes prior to Space Station reboost. The purpose here is to determine the effects on the induced external environment of Space Station Freedom with regard to the proposed changes in altitude. The change in the induced environment will be manifest in several parameters. The ambient density buildup in front of ram facing surfaces will change. The source of such contaminants can be outgassing/offgassing surfaces, leakage from the pressurized modules or experiments, purposeful venting, and thruster firings. The third induced environment parameter with altitude dependence is the glow. In order to determine the altitude dependence of the induced environment parameters, researchers used the integrated Spacecraft Environment Model (ISEM) which was developed for Marshall Space Flight Center. The analysis required numerous ISEM runs. The assumptions and limitations for the ISEM runs are described.

Gordon, T. D.↗

NASA NTRS2008

Compressible Boundary Layer Predictions at High Reynolds Number using Hybrid LES/RANS Methods

Simulations of compressible boundary layer flow at three different Reynolds numbers (Re(sub delta) = 5.59x10(exp 4), 1.78x10(exp 5), and 1.58x10(exp 6) are performed using a hybrid large-eddy/Reynolds-averaged Navier-Stokes method. Variations in the recycling/rescaling method, the higher-order extension, the choice of primitive variables, the RANS/LES transition parameters, and the mesh resolution are considered in order to assess the model. The results indicate that the present model can provide good predictions of the mean flow properties and second-moment statistics of the boundary layers considered. Normalized Reynolds stresses in the outer layer are found to be independent of Reynolds number, similar to incompressible turbulent boundary layers.

Choi, Jung-Il↗

NASA NTRS2005

Advanced Method to Estimate Fuel Slosh Simulation Parameters

The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. The nutation of a spacecraft spinning about its minor axis typically grows exponentially and the rate of growth is characterized by the Nutation Time Constant (NTC). For launch vehicles using spin-stabilized upper stages, fuel slosh in the spacecraft propellant tanks is usually the primary source of energy dissipation. For analytical prediction of the NTC this fuel slosh is commonly modeled using simple mechanical analogies such as pendulums or rigid rotors coupled to the spacecraft. Identifying model parameter values which adequately represent the sloshing dynamics is the most important step in obtaining an accurate NTC estimate. Analytic determination of the slosh model parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices and elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the equations of motion for the mechanical analog are hand-derived, evaluated, and their results are compared with the experimental results. The proposed research is an effort to automate the process of identifying the parameters of the slosh model using a MATLAB/SimMechanics-based computer simulation of the experimental setup. Different parameter estimation and optimization approaches are evaluated and compared in order to arrive at a reliable and effective parameter identification process. To evaluate each parameter identification approach, a simple one-degree-of-freedom pendulum experiment is constructed and motion is induced using an electric motor. By applying the estimation approach to a simple, accurately modeled system, its effectiveness and accuracy can be evaluated. The same experimental setup can then be used with fluid-filled tanks to further evaluate the effectiveness of the process. Ultimately, the proven process can be applied to the full-sized spinning experimental setup to quickly and accurately determine the slosh model parameters for a particular spacecraft mission. Automating the parameter identification process will save time, allow more changes to be made to proposed designs, and lower the cost in the initial design stages.

Schlee, Keith↗

NASA NTRSDate not supplied

Trajectory Planning and Online Performance Model Estimation for Advanced Air Mobility

We propose a framework for adaptive guidance based on optimal control and estimation using closed-loop performance models. In the proposed approach, parameters of a reduced-order performance model are estimated in real time so that trajectories and guidance commands are replanned with more accurate knowledge of the system's response and performance capabilities. To apply this methodology to flight control systems, we introduce a simple yet expressive performance model modified from a reference linear design model. The proposed framework is applied to guidance of a simulated Advanced Air Mobility class concept aircraft experiencing control effector failures. We demonstrate that, by optimizing performance model parameters in real time, guidance commands can be intelligently adjusted to recover system stability and the performance of a full-order vehicle model, even in the event of effector failures. Furthermore, the reduced-order performance model requires a fraction of the computational cost of the full-order model, facilitating real-time use of adaptive, optimal guidance.

Differential dynamic programming↗

NASA NTRSDate not supplied

Trajectory Planning and Online Performance Model Estimation for Advanced Air Mobility

Differential dynamic programming↗

DOE OSTI2022

Decoding Golden Eagle Movement Behavior from High-Resolution, Variable-Rate Telemetry Data Through Bayesian Filtering

The recent advances in animal tracking technology have enabled the collection of a vast amount of in situ data regarding the movement of wildlife at high spatiotemporal resolution. These data are usually available at variable time resolutions and contains noise (error) originating from GPS fixes. Decoding movement characteristics, particularly of flying animals, from telemetry data while handling these factors is a challenging yet important task for conservation purposes. Typically, this task is broken into two subtasks: resampling, and model calibration. The resampling subtask converts the variable rate positional data into a constant time interval data, while the model calibration subtask uses the resampled data to tune time-invariant parameters of the proposed models. For telemetry data at high temporal resolutions (order of 1 second), it is very challenging to decouple noise from actual movements using interpolation-based resampling techniques. Any errors introduced during resampling can significantly alter the the calibration and prediction attributes of the movement model. We address this problem through a unified Bayesian state-space framework that can handle both the resampling and calibration tasks in a single step. In addition, we use the speed and heading of the bird from telemetry data to regularize the position information of the bird. We use a Kalman filtering approach to include these nonlinearly related motion parameters within the state space framework. We cross-validated to quantify how this inclusion affects the model performance in estimating true bird movements. The relationship between the true state of the bird and environmental and topographical covariates is then represented parametrically. These parameters are then tuned using stochastic sampling strategies like Markov Chain Monte Carlo (MCMC). We use the telemetry data collected from golden eagles in the western USA to demonstrate the applicability of this approach to build a predictive, probabilistic movement model. Our preliminary results show that this approach provides improved predictive performance in terms of capturing higher-order motion parameters such as angular and horizontal accelerations, which may have simpler and more direct relationships with environmental covariates than corresponding speeds. In this talk, we will demonstrate how this state-space approach benefits the prediction capabilities of a movement model in simulating golden eagle paths through a wind power plant in Wyoming given certain atmospheric conditions. The model outcomes are aimed at informing mitigation strategies that can minimize the potential for collisions of golden eagles with wind turbines.

Bayesian methods↗

DOE OSTI2017

Particle Acceleration in Mildly Relativistic Shearing Flows: The Interplay of Systematic and Stochastic Effects, and the Origin of the Extended High-energy Emission in AGN Jets

The origin of the extended X-ray emission in the large-scale jets of active galactic nuclei (AGNs) poses challenges to conventional models of acceleration and emission. Although electron synchrotron radiation is considered the most feasible radiation mechanism, the formation of the continuous large-scale X-ray structure remains an open issue. As astrophysical jets are expected to exhibit some turbulence and shearing motion, we here investigate the potential of shearing flows to facilitate an extended acceleration of particles and evaluate its impact on the resultant particle distribution. Our treatment incorporates systematic shear and stochastic second-order Fermi effects. We show that for typical parameters applicable to large-scale AGN jets, stochastic second-order Fermi acceleration, which always accompanies shear particle acceleration, can play an important role in facilitating the whole process of particle energization. We study the time-dependent evolution of the resultant particle distribution in the presence of second-order Fermi acceleration, shear acceleration, and synchrotron losses using a simple Fokker–Planck approach and provide illustrations for the possible emergence of a complex (multicomponent) particle energy distribution with different spectral branches. We present examples for typical parameters applicable to large-scale AGN jets, indicating the relevance of the underlying processes for understanding the extended X-ray emission and the origin of ultrahigh-energy cosmic rays.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2014

Gas Chromatograph Method Optimization Trade Study for RESOLVE: 20-meter Column v. 8-meter Column

RESOLVE is the payload on a Class D mission, Resource Prospector, which will prospect for water and other volatile resources at a lunar pole. The RESOLVE payload's primary scientific purpose includes determining the presence of water on the moon in the lunar regolith. In order to detect the water, a gas chromatograph (GC) will be used in conjunction with a mass spectrometer (MS). The goal of the experiment was to compare two GC column lengths and recommend which would be best for RESOLVE's purposes. Throughout the experiment, an Inficon Fusion GC and an Inficon Micro GC 3000 were used. The Fusion had a 20m long column with 0.25mm internal diameter (Id). The Micro GC 3000 had an 8m long column with a 0.32mm Id. By varying the column temperature and column pressure while holding all other parameters constant, the ideal conditions for testing with each column length in their individual instrument configurations were determined. The criteria used for determining the optimal method parameters included (in no particular order) (1) quickest run time, (2) peak sharpness, and (3) peak separation. After testing numerous combinations of temperature and pressure, the parameters for each column length that resulted in the most optimal data given my three criteria were selected. The ideal temperature and pressure for the 20m column were 95 C and 50psig. At this temperature and pressure, the peaks were separated and the retention times were shorter compared to other combinations. The Inficon Micro GC 3000 operated better at lower temperature mainly due to the shorter 8m column. The optimal column temperature and pressure were 70 C and 30psig. The Inficon Micro GC 3000 8m column had worse separation than the Inficon Fusion 20m column, but was able to separate water within a shorter run time. Therefore, the most significant tradeoff between the two column lengths was peak separation of the sample versus run time. After performing several tests, it was concluded that better detection via good peak separation with a longer run time is a better asset than moderate peak separation with a shorter run time. Even given that RESOLVE is highly interested in water and that mission timeline is of significant importance given the short seven-to-ten-day mission timeline, worse detection with an 8m column may lead to overlooking other substances existing on the moon that could advance planetary science. Thus, I recommend the 20m column. However, if mission timeline and water separation are deemed the highest priority, the 8m column should be selected due to its ability to separate water within a shorter run time than the 20m column.

Column↗

DOE OSTI2021

Equivalence principle in Reissner–Nordström geometry

The Equivalence Principle is a key element in the development of General Relativity. In one of its formulations, the Equivalence Principle states that a reference frame at rest in a uniform gravitational field is equivalent to a reference frame in uniformly accelerated motion in the absence of any gravitation field. We analyze the spacetime surrounding a non-rotating spherically symmetric charged body, known as Reissner–Nordström geometry, and exhibit a coordinate transformation, which makes explicit its compatibility with the Equivalence Principle. We revisit the Schwarzschild case, previously analyzed in the literature. We also consider second order terms of the relevant expansion parameters in the approximate metric, which is needed for the computed curvature quantities to be correct at zeroth order.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Identification of key parameters controlling demographically structured vegetation dynamics in a land surface model: CLM4.5(FATES)

Vegetation plays an important role in regulating global carbon cycles and is a key component of the Earth system models (ESMs) that aim to project Earth's future climate. In the last decade, the vegetation component within ESMs has witnessed great progress from simple “big-leaf” approaches to demographically structured approaches, which have a better representation of plant size, canopy structure, and disturbances. These demographically structured vegetation models typically have a large number of input parameters, and sensitivity analysis is needed to quantify the impact of each parameter on the model outputs for a better understanding of model behavior. In this study, we conducted a comprehensive sensitivity analysis to diagnose the Community Land Model coupled to the Functionally Assembled Terrestrial Simulator, or CLM4.5(FATES). Specifically, we quantified the first- and second-order sensitivities of the model parameters to outputs that represent simulated growth and mortality as well as carbon fluxes and stocks for a tropical site with an extent of 1 x 1°. While the photosynthetic capacity parameter (V c,max25 )is found to be important for simulated carbon stocks and fluxes, we also show the importance of carbon storage and allometry parameters, which determine survival and growth strategies within the model. The parameter sensitivity changes with different sizes of trees and climate conditions. The results of this study highlight the importance of understanding the dynamics of the next generation of demographically enabled vegetation models within ESMs to improve model parameterization and structure for better model fidelity.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Sulfur flows of Ra Patera, Io

Voyager 1 imaging data have been used to investigate the color and morphology of several radial flow-like features at Ra Patera, a broad volcanic structure at approximately 8 deg latitude and 325 deg longitude on the Galilean satellite Io. It was found that downstream progressions of flow color and morphology are consistent with lava of a predominately sulfur composition cooling radiatively and erupting in the range of 470 to 520 K at effusion rates at 10 to the 10th to 10 to the 11th cubic cm/sec. This implies global resurfacing rates by volcanic flows on Io of the order of 1 cm/year. Calculated energy content and effusion rates for flows at Ra Patera, using the physical parameters of sulfur, are of the order of the largest known terrestrial basaltic eruptions and are consistent with calculations of globally available energy.

Pieri, D. C.↗

NASA NTRS1985

Shock acceleration of electrons and ions in solar flares

The simultaneous first-order Fermi shock acceleration of electrons, protons, and alpha particles are compared to observations of solar energetic particle events. For each event, a unique shock compression ratio in the range of approximately 1.6-3 produces spectra in good agreement with observation. The range in compression ratios predicts that the more than five orders of magnitude spread in electron-to-proton intensity ratios observed at MeV energies is compressed to about three orders of magnitude at an assumed injection energy of 100 keV. The remaining spread can be accounted for with a modest range of injection conditions. The model predicts that the acceleration time to a given energy will be approximately equal for electrons and protons, and for reasonable solar parameters, can be on the order of 1 s to approximately 100 MeV.

Ellison, D. C.↗