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At least 505 records · Page 28

Development of Neural Network for X-59 Air Data Probe Calibration

Two wind tunnel tests were conducted in the NASA Glenn Research Center (GRC) 8- by 6-Foot Supersonic Wind Tunnel to calibrate the nose-mounted air data probe for the X-59. The probe will be the primary instrument for the flight test of the X-59 for determining angle of attack, angle of sideslip, airspeed, and pressure altitude of the aircraft in flight. This paper documents the development of several neural net algorithms that can be used to relate air data probe port pressures from those tests to relevant X-59 flight parameters, such as angle of attack, angle of sideslip, mach number, and static and dynamic pressure. These calibration algorithms address accuracy effects for significant real-world conditions, such as initial sensor measurement uncertainties, assumed parameter constraints on NN modelling errors, and malfunctioning or plugged ports. Resultant integrated uncertainties are provided for each algorithm; these uncertainties are then used to estimate the effects on relevant X-59 mission parameters.

Kurtis Roy Long↗

Construction of a Fluid Flowfield from Discrete Point Data using Machine Learning

Many verification and validation procedures in aerospace engineering involve the comparison of computational fluid dynamics (CFD) data to experimental results from sources like wind tunnel tests. However, an incongruity exists between the data available from these sources: flow visualization is available by default in computational data, whereas in most experimental setups the available data is far more discrete and far more limited: integrated forces and moments, discrete pressure and temperature probes, etc. When differences exist between quantities of interest like lift and drag coefficients, the lack of full-field flow data from the experiments complicates most attempts to reconcile why the different data sources disagree. To this end, a shallow neural network, constrained by certain fluid flow properties, was trained to approximate flow field snapshots given only discrete data like that available in a wind tunnel test. The constructed snapshots, even for complex incompressible fluid flows, were found to agree at the large scales with the true flow fields. With this tool, researchers can more readily and easily understand why quantities of interest differ between their experimental and computational datasets. This in turn improves the resulting data's uncertainty measures.

Yury Lebedev↗

Particle Size Distribution Parameters from SAGE III/ISS Extinction Spectra

Stratospheric aerosols play key roles in the chemistry and radiation balance of the atmosphere and are a key input parameter for global chemistry and climate models. The degree to which aerosols impact chemistry and radiation balance depends primarily on the relative abundance of different sized particles within the sample volume, often referred to as the particle size distribution (PSD). If the PSD is accurately known then other key modeling parameters (e.g., surface area density and effective radius) can be derived. Historically, occultation observations from orbital instruments such as SAGE III/ISS have been used to infer these PSD parameters by inverting the extinction coefficient spectra. However, past efforts routinely failed to account for measurement uncertainty and lacked a rigorous estimate of the inferred PSD uncertainty. We carried out a series of simulations to evaluate the accuracy of these inferences and, for every valid SAGE III/ISS extinction spectrum, determined the range of PSD parameters that fell withing the bounds of the extinction error bars. Special application of this method was applied to estimate the impact of the 2022 Hunga Tonga eruption had on particle size distributions.

Travis N Knepp↗

Sage III/ISS Stratospheric Aerosols and Gas Experiment An Earth Science Mission on the International Space Station

Stratospheric aerosols play key roles in the chemistry and radiation balance of the atmosphere and are a key input parameter for global chemistry and climate models. The degree to which aerosols impact chemistry and radiation balance depends primarily on the relative abundance of different sized particles within the sample volume, often referred to as the particle size distribution (PSD). If the PSD is accurately known then other key modeling parameters (e.g., surface area density and effective radius) can be derived. Historically, occultation observations from orbital instruments such as SAGE III/ISS have been used to infer these PSD parameters by inverting the extinction coefficient spectra. However, past efforts routinely failed to account for measurement uncertainty and lacked a rigorous estimate of the inferred PSD uncertainty. We developed a PSD solution algorithm that infers single mode and bimodal distribution parameters and applied this algorithm to the SAGE II and SAGE III/ISS data record. Herein we describe the algorithm, evaluate its performance, and show results from the 2022 Hunga Tonga eruption.

Travis N. Knepp↗

A Facility Effect Characterization Test of the BHT-6000 Hall Thruster

During the development of the BHT-6000 Hall thruster for flight on NASA’s Power and Propulsion Element, a facility effect test campaign was performed on an engineering unit of the thruster. Testing occurred in Vacuum Facility 5 at NASA Glenn Research Center. The goal of the test campaign was to characterize the behavior of the BHT-6000 Hall thruster as functions of facility effects such that the thruster’s in-flight behavior can be reasonably bounded. In particular, the behavior of the thruster with regard to the background pressure and electrical environment was tested. The background pressure was controlled by injecting supplemental propellant flow into the environment, while the electrical environment was controlled by biasing the facility beam dump. Thrust was found to remain constant over the tested range of pressures while specific impulse was found to increase slightly (1 to 1.5% over a range of up to 20 μTorr, depending on operating point). Plasma plume properties, particularly of ions exiting the side of the thruster, were found to be highly sensitive to pressure and may require pressures of less than a few μTorr for accurate measurements. The thruster was found to operate identically with changing beam dump bias voltage to within measurement uncertainties.

Electric propulsion↗

A Facility Effect Characterization Test of the BHT6000 Hall Thruster

During the development of the BHT-6000 Hall thruster for flight on NASA’s Power and Propulsion Element, a facility effect test campaign was performed on an engineering unit of the thruster. Testing occurred in Vacuum Facility 5 at NASA Glenn Research Center. The goal of the test campaign was to characterize the behavior of the BHT-6000 Hall thruster as functions of facility effects such that the thruster’s in-flight behavior can be reasonably bounded. In particular, the behavior of the thruster with regard to the background pressure and electrical environment was tested. The background pressure was controlled by injecting supplemental propellant flow into the environment, while the electrical environment was controlled by biasing the facility beam dump. Thrust was found to remain constant over the tested range of pressures while specific impulse was found to increase slightly (1 to 1.5% over a range of up to 20 μTorr, depending on operating point). Plasma plume properties, particularly of ions exiting the side of the thruster, were found to be highly sensitive to pressure and may require pressures of less than a few μTorr for accurate measurements. The thruster was found to operate identically with changing beam dump bias voltage to within measurement uncertainties.

Electric propulsion↗

Automation of Geometric Accuracy Assessment Algorithm

When end-users are using multiple satellite images for a study the first step is often the assessment and rectification of geolocation offsets. We have developed an automated algorithm to calculate the geometric offsets between two satellite images. It splits both images into subset images (chips) and resamples them to a common resolution. Offsets are imposed on matching chips and the Pearson Cross Correlation (PCC) value calculated for each offset, where the best PCC gives the true offsets. With the true offsets corrected for, a quality of image registration is calculated, measurement uncertainty (MU). The MU threshold value is non-uniform across sensors because it depends on spectral characteristics of each sensor. Previously, the MU threshold was determined by manual inspection for each new sensor assessed. In this study, we automated MU threshold determination. 1/MU vs calculated offset approximates a Gaussian function in shape, see abstract image. A Gaussian function is fit to this dataset, and the root of the third derivative is calculated and applied as a quality threshold, removing the data of lower quality from the final assessment of image offsets. We apply this algorithm to commercial satellite data for proof of concept.

Alana Semple↗

Mock Truss-Braced Wing Loads Calibration Research Utilizing Fiber-Optic Sensors

In support of the National Aeronautics and Space Administration Advanced Air Transonic Transport Truss-Braced Wing structural research, the Armstrong Flight Research Center Flight Loads Laboratory is performing pathfinder tests on a small, scaled test article (dubbed the mock Truss-Braced Wing) to study the application of a loads calibration on a truss-braced wing structure. The addition of a truss to the wing structure, as opposed to a purely cantilever beam setup, changes the strain-gage-based loads calibration techniques. In a truss-braced configuration, the internal shear and moments, inboard of the truss-wing connection, are not directly representative of the external aerodynamic loading as is the case for a traditional cantilever configuration. A 3-axis load cell was used at the wing-to-strut interface to estimate the load sharing between the two structural members. Crosstalk within the 3-axis load cell is added to the measurement uncertainties of the calibration effort, and the results, including crosstalk uncertainties, are presented. The calibration tests presented in this report are used as a pathfinder for developing an understanding how to perform loads calibration on a truss-braced wing structural configuration. The use of distributed fiber-optic strain sensors is leveraged to provide a near-full-span strain profile along the leading and trailing edge of the wing structure for strain-based loads calibration.

Francisco Peña↗

NAIRAS Version 3 Atmospheric Ionizing Radiation Validation: Comparisons to RaD-X Measurements

The Nowcast of Aerospace Ionizing RAdiation System (NAIRAS) model predicts dosimetric and radiative flux quantities for assessing human radiation exposure levels and radiation effects on flight electronic systems from the surface of the Earth to deep space. NAIRAS version 3 includes many updates and improvements to the model. In this paper, NAIRAS version 3 dosimetric quantities are compared to observations of the atmospheric radiation environment taken during the Radiation Dosimetry Experiment (RaD-X) flight campaign. The RaD-X campaign consisted of a high-altitude balloon flight, with altitudes up to 40 km, and four coordinated aircraft flights covering an altitude range from 6-20 km. The RaD-X measurement data from the different flight platforms were acquired in September 2015 and at nearly the same vertical cutoff rigidity (3-4 GV). High quality, flight-averaged measurement data were provided at seven altitudes, which correspond to regions of fundamentally different radiation transport and collisional interaction physics. The NAIRAS model agrees with the RaD-X measurements to within 30% over the entire altitude domain of the flight campaign (0-40 km), which is within the measurement uncertainty.

Christopher J Mertens↗

Safeguards Modeling for Advanced Nuclear Facility Design.

Future nuclear fuel cycle facilities will see a significant benefit from considering materials accountancy requirements early in the design process. The Material Protection, Accounting, and Control Technologies (MPACT) working group is demonstrating Safeguards and Security by Design (SSBD) for a notional electrochemical reprocessing facility as part of a 2020 Milestone. The idea behind SSBD is to consider regulatory requirements early in the design process to provide more optimized systems and avoid costly retrofits later in the design process. Safeguards modeling, using single analyst tools, allows the designer to efficiently consider materials accountancy approaches that meet regulatory requirements. However, safeguards modeling also allows the facility designer to go beyond current regulations and work toward accountancy designs with rapid response and lower thresholds for detection of anomalies. This type of modeling enables new safeguards approaches and may inform future regulatory changes. The Separation and Safeguards Performance Model (SSPM) has been used for materials accountancy system design and analysis. This paper steps through the process of designing a Material Control and Accountancy (MC&A) system, presents the baseline system design for an electrochemical reprocessing facility, and provides performance metrics from the modeling analysis. The most critical measurements in the electrochemical facility are the spent fuel input, electrorefiner salt, and U/TRU product output measurements. Finally, material loss scenario analysis found that measurement uncertainties (relative standard deviations) for Pu would need to be at 1% (random and systematic error components) or better in order to meet domestic detection goals or as high as 3% in order to meet international detection goals, based on a 100 metric ton per year plant size.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

AN OVERVIEW OF THE DESIGN AND PERFORMANCE TESTING OF A 275 BAR INTEGRALLY GEARED SUPERCRITICAL CO2 COMPRESSOR FOR POWER GENERATION

An integrally geared compressor-expander (compander) for supercritical CO2 (sCO2) was developed to convert thermal energy to electricity. With operating pressures of 275 bar, this turbomachine represents the state of the art in integrally geared machine architecture, hitting compressor inlet densities of 600 kg/m3 and discharge pressures of 275 bar. The product development was funded by the Department of Energy’s Energy Efficiency and Renewable Energy Office under EE0007114 to advance the state of the art in concentrated solar power applications; however, the technology itself is agnostic to heat source, and is predicted to achieve a thermal-to-electric conversion efficiency of 50% for any indirect heat source capable of providing turbine inlet temperatures of 700°C or greater. While the program encompassed the design and testing for the compressor and turbine elements, this paper will focus on the compressor design and operation. The paper will begin with an introduction to the cycle design and analysis of an indirectly heated integrally geared sCO2 compander, a discussion of the mechanical and aerodynamic design of the compressor that is a two stage radial compressor operating subcritically at 27,512 rpm, and will then proceed to describe the test facility and measured data to characterize the performance and robustness of the machine. The paper will conclude with a discussion on lessons learned throughout the course of commissioning and testing. Practical aspects of testing a compressor operating near the dome including complications relating to obtaining an accurate compressor flow map, efficiency calculations, flow unsteadiness, and associated measurement uncertainties will be discussed.

wilkes, jason↗

Online Model-Free Chance-Constrained Distribution System Voltage Control Using DERs: Preprint

This paper proposes an online data-driven distributed energy resource management system (DERMS) optimization method using chance-constrained formulation to address distribution system voltage regulation. This is achieved via the local sensitivity factor (LSF)-enabled reformulation of the DER control into a linear programming (LP) problem, which is easy and computationally efficient to solve. The LSF is estimated using online measurements and does not need the assumption of node load information. The latter is usually required for existing optimization-based methods but is difficult to obtain in practice. To mitigate measurement uncertainties, a scenario-based chance-constrained formulation is constructed. Compared with other control methods, the results carried out in a realistic distribution system show that the proposed method can effectively eliminate voltage violation issues.

chance-constrained optimization↗

Measurement of Rayleigh Scattering in Liquid Argon at Vacuum Ultraviolet Wavelengths

Liquid argon based experiments are limited in scintillation light analysis capabilities due to inconsistent measured values of fundamental constants essential for reconstructing scintillation events. This experiment measures the Rayleigh scattering length of vacuum ultraviolet light propagating in liquid argon to support liquid argon experiments by expanding the scope of scintillation signal analysis. Preliminary results are presented for the Rayleigh scattering length in arange of vacuum ultraviolet wavelengths, including the liquid argon scintillation peak wavelength. Currently, further data collection and analysis is required to reduce measurement uncertainty as well as quantify and correct for other effects such as the photon detector temperature dependence. Results will contribute to the development of new photon detector system analysis methods for liquid argon experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Validating Irradiance Models for High-Latitude Vertical Bifacial Photovoltaic Systems

Bifacial photovoltaic systems oriented vertically facing east-west are an emerging design, targeting production in morning and afternoon hours and providing competitive annual energy yield to traditional south-tilted modules for high latitude locations. The accuracy of existing bifacial PV models when modules are oriented vertically has yet to be examined in detail. Here, we compare four bifacial PV irradiance models in ~150 locations between 15-80 degrees N on the utility-scale, finding higher inter-model deviations for vertical PV systems than south-tilted across all latitudes less than 75 degrees N. We validate model-predicted irradiance with test-site data collected in Golden, Colorado and Fairbanks, Alaska for E-W vertical and south-tilted arrays. View factor models agree with E-W vertical test-site data in Golden with RMSE=15%. Modelling error increases for the Alaskan test-site to RMSE values between 21-30%, driven in part by high albedo measurement uncertainty during snowy months.

bifacial↗

Component-Level Inverse Design of Transmon Qubits Using Neural Networks

Designing a superconducting qubit to realize specific Hamiltonian parameters typically requires iterating through a time and compute-intensive forward loop in which the designer chooses a layout geometry, simulates it, extracts circuit parameters such as capacitances, and refines the geometry. We study the inverse version of this task using a neural-network workflow that maps target Hamiltonian parameters directly to component-level layout parameters, which we subsequently demonstrate on a planar transmon layout. During training, we pair the inverse model with a frozen forward surrogate model and evaluate the loss in Hamiltonian space rather than in layout-parameter space. In validation against a conventional EM solver, 97% of generated designs produce usable geometries, and the inverse-plus-surrogate pipeline reaches mean percent errors of 0.73% for qubit frequency and 1.58% for anharmonicity, comparable to or below the fabrication and simulation-to-measurement uncertainty expected for academic-process transmon devices of this type. A single pipeline query takes ~60 ms on CPU, versus ~2 min for a conventional EM capacitance extraction on the same hardware, a speedup of approximately 2,000x. Batching minimizes the AI model inference overhead, reducing the runtime to 3.1 microseconds per sample on CPU and 2.6 microseconds per sample on GPU at a batch size of 2048, resulting in speedups of 3.9 x 10^7 and 4.6 x 10^7, respectively, relative to a single conventional CPU EM extraction. Our results indicate that component-level inverse design usefully extends and complements conventional EM simulation, including for small datasets on the order of 1,000 samples.

Seidel, Olivia [Fermilab; Texas U., Arlington]↗

Uncertainty Analysis of Sonic Boom Levels Measured in a Simulator at NASA Langley

A sonic boom simulator has been constructed at NASA Langley Research Center for testing the human response to sonic booms heard indoors. Like all measured quantities, sonic boom levels in the simulator are subject to systematic and random errors. To quantify these errors, and their net influence on the measurement result, a formal uncertainty analysis is conducted. Knowledge of the measurement uncertainty, or range of values attributable to the quantity being measured, enables reliable comparisons among measurements at different locations in the simulator as well as comparisons with field data or laboratory data from other simulators. The analysis reported here accounts for acoustic excitation from two sets of loudspeakers: one loudspeaker set at the facility exterior that reproduces the exterior sonic boom waveform and a second set of interior loudspeakers for reproducing indoor rattle sounds. The analysis also addresses the effect of pressure fluctuations generated when exterior doors of the building housing the simulator are opened. An uncertainty budget is assembled to document each uncertainty component, its sensitivity coefficient, and the combined standard uncertainty. The latter quantity will be reported alongside measurement results in future research reports to indicate data reliability.

Rathsam, Jonathan↗

Systematic uncertainties in the measurement of the neutron lifetime using the Lunar Prospector neutron spectrometer

The lifetime of free neutrons measured in the laboratory has a longstanding disparity of ≈9 s. A space-based technique has recently been proposed to independently measure the neutron lifetime using interactions between the galactic cosmic rays and a low atmosphere planetary body. This technique has not produced competitive results yet due to constraints of nonoptimized data that contain large systematic errors. We use data from the neutron spectrometer on-board NASA's Lunar Prospector, and study two large systematics in the measurement of neutron lifetime: the lunar subsurface temperature and the lunar surface composition. We use the HeCd and HeSn neutron spectrometer data when the spacecraft was in a highly elliptical orbit during the orbit insertion period. We report the neutron lifetime using four different models that each have different choices of surface temperature and composition. The 5° [Prettyman et al ., J. Geophys. Res.: Planets 111, 2005JE002656 (2006)] and 2° [Wilson et al., Phys. Rev. C 104, 045501 (2021)] rebinned maps result in 777.6±11.7 s and 739.6±10.8 s, respectively. For the 20° map (Prettyman et al., 2006), constant equatorial and a latitude-dependent temperature model result in 738.6±10.8 s and 767.3±11.2 s, respectively. Increasing the complexities of the models accounting for the systematic effects increase the measured lifetime. However, the reported measurements are not competitive with the laboratory results due to large unaccounted systematics resulting from nonoptimized measurements and modeling assumptions. This work serves as a study of systematic uncertainties for future neutron lifetime measurements using the space-based technique. We estimate the effect on the lifetime from the choice of temperature model to be to be 28.7 ±15.5 s, and choice of compositional map (for 20° and 5° maps) to be 10.3 ±12.2 s.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Measurement Accuracy and Uncertainty Analysis of the X-59 Air Data Probe Calibration Test Entry One

The X-59 is being developed to demonstrate quiet sonic boom technology. Data was obtained via two test entries in the NASA Glenn Research Center’s 8- by 6-Foot Supersonic Wind Tunnel to calibrate the X-59’s nose air data probe. The first entry tested two theoretically identical probes with the intention of one of the probes becoming the primary X-59 nose air data probe flight hardware and the other becoming a backup. A measurement accuracy and uncertainty analysis was performed on data obtained from the first test entry. The analysis showed that the uncertainties in the probe pressures were nearly identical for the two probes, with an average difference of 2.51 x 10-5 for the non-dimensional total pressure and 2.88 x 10-5 for the non-dimensional static pressures. The analysis also showed that the uncertainty in the probe yaw and pitch angles were 0.00034° and 0.01416°, respectively. This gives confidence in the X-59’s flight air data system.

Air Data Probe↗