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At least 667 records · Page 37

Conflict Detection Performance Analysis for Function Allocation Using Time-Shifted Recorded Traffic Data

The performance of the conflict detection function in a separation assurance system is dependent on the content and quality of the data available to perform that function. Specifically, data quality and data content available to the conflict detection function have a direct impact on the accuracy of the prediction of an aircraft's future state or trajectory, which, in turn, impacts the ability to successfully anticipate potential losses of separation (detect future conflicts). Consequently, other separation assurance functions that rely on the conflict detection function - namely, conflict resolution - are prone to negative performance impacts. The many possible allocations and implementations of the conflict detection function between centralized and distributed systems drive the need to understand the key relationships that impact conflict detection performance, with respect to differences in data available. This paper presents the preliminary results of an analysis technique developed to investigate the impacts of data quality and data content on conflict detection performance. Flight track data recorded from a day of the National Airspace System is time-shifted to create conflicts not present in the un-shifted data. A methodology is used to smooth and filter the recorded data to eliminate sensor fusion noise, data drop-outs and other anomalies in the data. The metrics used to characterize conflict detection performance are presented and a set of preliminary results is discussed.

Guerreiro, Nelson M.↗

An overview of results from the ion diagnostics sensors flown on DS1

The Deep Space 1 (DS1) mission has successfully validated the use of ion propulsion technology for interplanetary spacecraft. The NASA Solar Electric Propulsion (SEP) Technology Applications Readiness (NSTAR) Project developed the Ion Propulsion Subsystem (IPS) for DS1. As part of the NSTAR validation effort, the NSTAR Project included a diagnostics element to characterize the local environment produced during IPS operations and its effects on spacecraft subsystems and science instruments. An integrated, comprehensive set of diagnostics, the NSTAR Diagnostics Package (NPD) was developed and operated on DS1 to characterize the IPS environment. The DS1 Spacecraft Team officially assigned the name “IPS Diagnostics Subsystems (IDS)” to the NDP for the DS1 mission. During the technology validation phase of the DS1 mission, a large amount of data was collected from the IDS under a variety of IPS operating conditions. IDS was able to characterize the contamination environment, charge-exchange xenon ion and electron population and energies, plasma noise and electromagnetic noise, and magnetic fields associated with IPS. The results presented here describe the charge-exchange plasma, contamination, plasma wave/EMI, and DC magnetic environments critical to designers of future space missions using ion propulsion

Henty, M. D.↗

Feasibility of source-free DAS logging for next-generation borehole imaging

Characterizing and monitoring geologic formations around a borehole are crucial for energy and environmental applications. However, conventional wireline sonic logging usually cannot be used in high-temperature environments nor is the tool feasible for long-term monitoring. We introduce and evaluate the feasibility of a source-free distributed-acoustic-sensing (DAS) logging method based on borehole DAS ambient noise. Our new logging method provides a next-generation borehole imaging tool. The tool is source free because it uses ever-present ambient noises as sources and does not need a borehole sonic source that cannot be easily re-inserted into a borehole after well completion for time-lapse monitoring. The receivers of our source-free DAS logging tool are fiber optic cables cemented behind casing, enabling logging in harsh, high-temperature environments, and eliminating the receiver repeatability issue of conventional wireline sonic logging for time-lapse monitoring. We analyze a borehole DAS ambient noise dataset to obtain root-mean-squares (RMS) amplitudes and use these amplitudes to infer subsurface elastic properties. We find that the ambient noise RMS amplitudes correlate well with anomalies in conventional logging data. The source-free DAS logging tool can advance our ability to characterize and monitor subsurface geologic formations in an efficient and cost-effective manner, particularly in high-temperature environments such as geothermal reservoirs. Further validation of the source-free DAS logging method using other borehole DAS ambient noise data would enable the new logging tool for wider applications.

58 GEOSCIENCES↗

Automated scanning probe microscopy of combinatorial ferroelectric libraries: Gaussian-process-guided exploration and noise-aware experiment planning

Combinatorial materials libraries provide an efficient route for mapping composition–property relationships, but their broader impact depends on rapid, quantitative, and functionally relevant characterization. Scanning Probe Microscopy (SPM), including piezoresponse force microscopy (PFM), offers significant potential for quantitative, functionally relevant combi-library readouts. Here, we implement a fully automated SPM workflow for ferroelectric combinatorial libraries and benchmark Gaussian-process-based Bayesian optimization strategies for autonomous experiment planning. The workflow integrates automated probe motion, contact optimization, imaging, and dual amplitude resonance tracking-PFM spectroscopy, and uses scalarized spectroscopic observables to guide subsequent measurements. Stage motion, probe engagement, in-contact tuning, imaging, spectroscopy, and the choice of the next measurement location all proceed without human input. We demonstrate the approach on Sm-doped BiFeO 3 and Zn x Mg 1−x O libraries. By comparing vanilla Bayesian optimization with a measured-noise variant, we show that explicit treatment of local reproducibility can improve modeling of composition-dependent response when the measured variance is physically meaningful, but can also reduce robustness when variability is dominated by outliers or topographic artifacts. Furthermore, these results establish automated SPM as a bridge between combinatorial synthesis and quantitative functional characterization.

Liu, Yu [University of Tennessee, Knoxville, TN (U↗

Anomalous magnetic noise in an imperfectly flat landscape in the topological magnet Dy 2 Ti 2 O 7

Noise generated by motion of charge and spin provides a unique window into materials at the atomic scale. From temperature of resistors to electrons breaking into fractional quasiparticles, “listening” to the noise spectrum is a powerful way to decode underlying dynamics. Here, we use ultrasensitive superconducting quantum interference device (SQUIDs) to probe the puzzling noise in a frustrated magnet, the spin-ice compound Dy 2 Ti 2 O 7 (DTO), revealing cooperative and memory effects. DTO is a topological magnet in three dimensions—characterized by emergent magnetostatics and telltale fractionalized magnetic monopole quasiparticles—whose real-time dynamical properties have been an enigma from the very beginning. We show that DTO exhibits highly anomalous noise spectra, differing significantly from the expected Brownian noise of monopole random walks, in three qualitatively different regimes: equilibrium spin ice, a “frozen” regime extending to ultralow temperatures, and a high-temperature “anomalous” paramagnet. We present several distinct mechanisms that give rise to varied colored noise spectra. In addition, we identify the structure of the local spin-flip dynamics as a crucial ingredient for any modeling. Thus, the dynamics of spin ice reflects the interplay of local dynamics with emergent topological degrees of freedom and a frustration-generated imperfectly flat energy landscape, and as such, it points to intriguing cooperative and memory effects for a broad class of magnetic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Vibration-based health characterization of multiple IMUs in UAV applications

Inertial measurement units (IMUs) are vital in UAV navigation for vehicle attitude and position estimation, especially in the frequently-occurring case of temporary loss of GPS capabilities. Degradation in these units could yield inaccurate position estimates, resulting in incorrect input for vehicle control systems. A wide variety of these units exist to meet the needs of UAV operators, general aviation, and military vehicles. In recent decades, lightweight and inexpensive MEMS sensors have grown in popularity with respect to UAVs. Studies into the failure modes of MEMS devices suggest that vibration is one of the leading causes of MEMS degradation. MEMS sensors are generally encased in their own hermetic packaging, as their small size and sensitivity cause them to be particularly vulnerable to air damping and particulate contamination when exposed. Exposure to excessive vibration can cause cracking in this packaging as well as damage to connecting electronics, with recorded results that cause sensors to act outside of their specifications, potentially providing unreliable input to controllers. A prior study from the Politecnico di Torino looked into the degradation of MEMS IMUs, specifically the AXIS-AIS402, for aerospace and vibrating environments. In the study, the authors found that after exposing MEMS IMUs to simulated vibrations from working conditions of aerospace applications, the sensors showed increased noise and increased bias instability. At NASA Ames, several widely-used MEMS IMUs were selected for a new IMU degradation study, comparing accelerometer performance before and after exposure to similar levels of vibration simulating aerospace conditions. The IMUs were selected from the Pixhawk autopilot systems, hobby sUAS, or prior experimental studies at NASA. Additionally, the industrial grade VectorNav-100 IMU was selected as a ground truth reference point to which the performance of the test sensors can be compared. In the study, each sensor is exposed to functional levels of UAV vibration as replicated on a single-frequency vibratory table in the NASA Ames SHARP Laboratory, and each accelerometer is characterized for bias, drift, and noise characteristics both before and after vibratory exposure. The focus of this study is to monitor the health of the IMU sensors and determine if sensor degradation can be detected from output error and frequency spectrum analysis, rather than from microscopic examination of the sensors. In this case, sensor degradation and faulty data can be more easily detectable by non-experts hoping to use these sensors as an important piece of an integrated package. In addition, specific sensor degradation modes potentially leading to in-flight hazards could be identified, such as accelerated levels of drift and altered temperature response. The overall goal of this work is to increase levels of safety for future users of these sensors and to provide a clear analysis of sensor limitations currently lacking in most sensor specification documentation.

IMUs↗

Background noise measurements from jet exit vanes designed to reduced flow pulsations in an open-jet wind tunnel

Many open jet wind tunnels experience pulsations of the flow which are typically characterized by periodic low frequency velocity and pressure variations. One method of reducing these fluctuations is to install vanes around the perimeter of the jet exit to protrude into the flow. Although these vanes were shown to be effective in reducing the fluctuation content, they can also increase the test section background noise level. The results of an experimental acoustic program in the Langley 4- by 7-Meter Tunnel is presented which evaluates the effect on tunnel background noise of such modifications to the jet exit nozzle. Noise levels for the baseline tunnel configuration are compared with those for three jet exit nozzle modifications, including an enhanced noise reduction configuration that minimizes the effect of the vanes on the background noise. Although the noise levels for this modified vane configuration were comparable to baseline tunnel background noise levels in this facility, installation of these modified vanes in an acoustic tunnel may be of concern because the noise levels for the vanes could be well above background noise levels in a quiet facility.

Hoad, D. R.↗

Two-Stage, 90-GHz, Low-Noise Amplifier

A device has been developed for coherent detection of the polarization of the cosmic microwave background (CMB). A two-stage amplifier has been designed that covers 75-110 GHz. The device uses the emerging 35-nm InP HEMT technology recently developed at Northrop Grumman Corporation primarily for use at higher frequencies. The amplifier has more than 18 dB gain and less than 35 K noise figure across the band. These devices have noise less than 30 K at 100 GHz. The development started with design activities at JPL, as well as characterization of multichip modules using existing InP. Following processing, a test campaign was carried out using single-chip modules at 100 GHz. Successful development of the chips will lead to development of multichip modules, with simultaneous Q and U Stokes parameter detection. This MMIC (monolithic microwave integrated circuit) amplifier takes advantage of performance improvements intended for higher frequencies, but in this innovation are applied at 90 GHz. The large amount of available gain ultimately leads to lower possible noise performance at 90 GHz.

Samoska, Lorene A.↗

Seismic imaging of the Ecuadorian forearc and arc from joint ambient noise, local, and teleseismic tomography: catching the Nazca slab in the act of flattening

SUMMARY The Ecuadorian Andes are a complex region characterized by accreted oceanic terranes driven by the ongoing subduction of the oceanic Nazca plate beneath South America. Present-day tectonics in Ecuador are linked to the downgoing plate geometry featuring the subduction of the aseismic, oceanic Carnegie Ridge, which is currently entering the trench. Using seismic tomography, we jointly invert arrival times of P and S waves from local and teleseismic earthquakes with surface wave dispersion curves to image the structure of the forearc and magmatic arc of the Ecuadorian Andes. Our data set includes > 100 000 traveltimes recorded at 294 stations across Ecuador. Our images show the basement of the central forearc is composed of accreted oceanic terranes with high elastic wave speeds. Inboard of the Carnegie Ridge, the westernmost forearc and coastal cordilleras display relatively low Vp and Vs and high Vp/Vs values, which we attribute to the increased hydration and fracturing of the overriding plate due to the subduction of the thick oceanic crust of the Carnegie Ridge. We additionally image across-arc differences in magmatic architecture. The frontal volcanic arc overlies accreted terranes and is characterized by low velocities and high Vp/Vs indicative of partial melt reservoirs which are limited to the upper crust. In contrast, the main arc displays regions of partial melt across a wider range of depths. The Subandean zone of Ecuador has two active volcanoes built on continental crust suggesting the arc is expanding eastwards. The mid to lower crust does not show indications of being modified from the magmatic process. We infer that the slab is in the process of flattening as a consequence of early-stage subduction of the buoyant Carnegie Ridge.

58 GEOSCIENCES↗

Invariants of optimal minimal-order observer-based compensators

The relations characterizing the optimal minimal-order observer-based compensators for a linear time-invariant multivariable system with a random initial state (or, equivalently, known initial state and white plant-driving noise) have been reported by Miller (1973). In this note we establish in general that the plant transfer function uniquely determines the optimal compensator transfer function, and that this characterizes precisely the degrees of freedom in the compensator design; computational implications of this result are indicated.

Blanvillain, P. J.↗

Radiometric and Radiation Response of Visible FPAs

The readout integrated circuit (ROIC) used in these devices was originally developed for use in space based infrared systems operating at deep cryogenic temperatures and was selected because of its proven tolerance to total ionizing radiation? The detectors are a 128 x 128 array of 60 pm x 60 pm pixel elements that have been anti-reflection (AR) coated to improve the response at very short wavelengths. These visible focal plane arrays were operated at -40 C (233 K). Two focal planes were characterized using cobalt-60 radiation to produce ionizing total dose damage in the VFPAs. Both operational and performance data were obtained as functions of total dose. The first device tested showed no appreciable change in responsivity or noise up to 300 krad(Si). However, at the next dose level of 600 krad(Si), the readout was non-operational due to failure in the digital circuitry. The second device was characterized to a total dose of 750 krad(Si) with no observed change in responsivity. An increase dark current was observed in both devices, and in the second device, the dark current caused an increase in noise at low irradiance at 400 krad(Si) and above. The increase in dark current was somewhat un-expected for visible PIN detectors. The median dark current increased more than two orders of magnitude at 300 krad(Si) for the first device and a factor of 350 at 750 krad(Si) for pixels near the edge for the second device. The dark current was found to be a strong function of detector bias, with pixels near the edge of the array showing a greater increase in dark current with bias than those near the center. Since the optical response was not a function of bias, it is hypothesized that the dark current is a surface effect and that the variation in dark current with location is due to a variation in pixel bias, caused by a voltage drop across the pixel common lead. As the total dose increased, the dark current and the voltage drop increased

Hubbs, John↗

Chromospheric Variability: Analysis of 36 years of Time Series from the National Solar Observatory/Sacramento Peak Ca II K-line Monitoring Program

Analysis of more than 36 years of time series of seven parameters measured in the NSO/AFRL/Sac Peak K-line monitoring program elucidates five elucidates five components of the variation: (1) the solar cycle (period approx. 11 years), (2) quasi-periodic variations (periods approx 100 days), (3) a broad band stochastic process (wide range of periods), (4) rotational modulation, and (5) random observational errors. Correlation and power spectrum analyses elucidate periodic and aperiodic variation of the chromospheric parameters. Time-frequency analysis illuminates periodic and quasi periodic signals, details of frequency modulation due to differential rotation, and in particular elucidates the rather complex harmonic structure (1) and (2) at time scales in the range approx 0.1 - 10 years. These results using only full-disk data further suggest that similar analyses will be useful at detecting and characterizing differential rotation in stars from stellar light-curves such as those being produced by NASA's Kepler observatory. Component (3) consists of variations over a range of timescales, in the manner of a 1/f random noise process. A timedependent Wilson-Bappu effect appears to be present in the solar cycle variations (1), but not in the stochastic process (3). Component (4) characterizes differential rotation of the active regions, and (5) is of course not characteristic of solar variability, but the fact that the observational errors are quite small greatly facilitates the analysis of the other components. The recent data suggest that the current cycle is starting late and may be relatively weak. The data analyzed in this paper can be found at the National Solar Observatory web site http://nsosp.nso.edu/cak_mon/, or by file transfer protocol at ftp://ftp.nso.edu/idl/cak.parameters.

Solar physics↗

Characterizing the Superconducting-to-Normal Transition in Mo/Au Transition-Edge Sensor Bilayers

We are developing arrays of Mo/Au bilayer transition-edge sensors (TES's) for applications in future X-ray astronomy missions such as NASA's Constellation-X. The physical properties of the superconducting-to-normal transition in our TES bilayers, while often reproducible and characterized, are not well understood. The addition of normal metal features on top of the bilayer are found to change the shape and temperature of the transition, and they typically reduce the unexplained 'excess' noise. In order to understand and potentially optimize the properties of the transition, we have been studying the temperature, widths and current dependence of these transitions. We report on the characterization of devices both deposited on silicon substrates and suspended on thin silicon nitride membranes. This includes key device parameters such as the logarithmic resistance sensitivity with temperature alpha, and the logarithmic resistance sensitivity with current beta, of the phase-transition. We investigate alpha and beta as a function of current, both at fixed and varying bias points in the transition. Using Ginzburg-Landau theory for the current dependence of the superconducting transition temperature, we investigate the relationship between alpha and beta and compare our measured and theoretical estimates.

Smith, Stephen J.↗

DarkNESS: Characterization of Space Multi-Chip Module Skipper-CCDs and Readout Electronics

The DarkNESS mission has the goal of deploying a 6U CubeSat fitted with an array of skipper-CCDs in Low Earth Orbit (~400 km). The new instrument will take measurements of diffuse x-rays and look for signatures of dark matter decay in the spectrum. DarkNESS will also perform a direct search for strongly interacting sub-GeV dark matter in regions of the parameter space not accessible to ground based experiments [1]. Skipper-CCDs allow for low-noise astronomical observations which can extend the discovery reach for direct dark matter search experiments. This paper will discuss the laboratory characterization of the two key components of the scientific payload: the space Multi-Chip Module (sMCM), and their readout electronics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Performance Characterization of UV Science Cameras Developed for the Chromospheric Lyman-Alpha Spectro-Polarimeter

The NASA Marshall Space Flight Center (MSFC) has developed a science camera suitable for sub-orbital missions for observations in the UV, EUV and soft X-ray. Six cameras will be built and tested for flight with the Chromospheric Lyman-Alpha Spectro-Polarimeter (CLASP), a joint National Astronomical Observatory of Japan (NAOJ) and MSFC sounding rocket mission. The goal of the CLASP mission is to observe the scattering polarization in Lyman-alpha and to detect the Hanle effect in the line core. Due to the nature of Lyman-alpha polarization in the chromosphere, strict measurement sensitivity requirements are imposed on the CLASP polarimeter and spectrograph systems; science requirements for polarization measurements of Q/I and U/I are 0.1 percent in the line core. CLASP is a dual-beam spectro- polarimeter, which uses a continuously rotating waveplate as a polarization modulator, while the waveplate motor driver outputs trigger pulses to synchronize the exposures. The CCDs are operated in frame-transfer mode; the trigger pulse initiates the frame transfer, effectively ending the ongoing exposure and starting the next. The strict requirement of 0.1 percent polarization accuracy is met by using frame-transfer cameras to maximize the duty cycle in order to minimize photon noise. Coating the e2v CCD57-10 512x512 detectors with Lumogen-E coating allows for a relatively high (30 percent) quantum efficiency at the Lyman-alpha line. The CLASP cameras were designed to operate with a gain of 2.0 +/- 0.5, less than or equal to 25 e- readout noise, less than or equal to 10 e-/second/pixel dark current, and less than 0.1percent residual non-linearity. We present the results of the performance characterization study performed on the CLASP prototype camera; system gain, dark current, read noise, and residual non-linearity.

Champey, Patrick↗

Concentration fluctuations and flammability of cryo-compressed hydrogen and methane jets

Compressed hydrogen stored at cryogenic temperatures has a much higher density than room-temperature storage, which enables large-scale hydrogen storage and transport. An understanding of the release of cryogenic hydrogen from pressurized vessels is needed to evaluate the risk and safety concerns with the use of this fuel. Here, the present work extends the analysis of previous experimental studies that measured the gas concentrations of cryo-compressed hydrogen jets and methane jets using a laser Raman scattering diagnostic system. Since the Raman signals are very small, a denoising algorithm was applied to significantly reduce the noise to enable statistical analysis of the data. The transient features of the turbulent jets were characterized by their concentration intermittencies and probability density functions (PDFs). A two-part PDF was developed to predict the bimodal features of the jet concentration distributions. Then, the flammability factors of the cryogenic jets were calculated based on the intermittency and the PDF.

33 ADVANCED PROPULSION SYSTEMS↗

Comparative Evaluation of Spectral Methods for Robust Reactor Noise Estimation

Reactor noise analysis provides a noninvasive means to determine neutron kinetic parameters from stochastic fluctuations in detector signals. However, standard cross-power spectral density (CPSD) analyses can be sensitive to numerical processing choices, which may introduce processing-dependent systematic shifts in estimates of the prompt neutron decay constant (α) and limit reproducibility. This study uses a hybrid multitaper–Welch spectral estimator to analyze subcritical noise measurements from a fast-spectrum critical assembly. The decay constant α was extracted using three frequency-domain methods: the CPSD, the magnitude-squared coherence (MSC), and the generalized magnitude-squared coherence (GMSC). These coherence-based estimators normalize detector auto-spectral structure and are expected to reduce the sensitivity of fitted α values to processing parameters. A Sobol global sensitivity analysis identified which numerical inputs most strongly influence the fitted values of α. All estimators produced a linear dependence of α on inverse count rate, with delayed-critical extrapolations near 1.7 × 10 4 s −1 , in agreement within 8% of MCNP6.3 KOPTS benchmark calculations. Sensitivity results show that while the CPSD depends on both time-bin width and taper selection, the MSC and GMSC are dominated by time-bin width alone, indicating reduced parameter coupling and greater robustness to processing variability. These findings demonstrate the feasibility and practical value of coherence-based spectral estimators for extracting α from reactor noise and support their broader application to multi-detector and irregular datasets in subcritical system characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Parameter Estimation for Decoding Sensor Signals

This paper introduces a parameter estimation approach for decoding digital sensor signals in a cyber-physical system. For unknown or not fully characterized digital sensor data, it can be difficult to decipher a desired signal from background or noise. In a cyber-physical system with networked sensors, we can leverage knowledge of the physical system to inform the decoding of the digital signals. This work in progress is a case study on deciphering commercial vehicle on-board sensor networks that communicate through the Controller Area Network (CAN). By understanding the stock vehicle sensor network, a vehicle can be extended into a scalable research platform with minimal instrumentation. Our challenge was to localize desired sensor signals encoded in network traffic that included other sensor data, control messages, as well as encoding and security overhead. Due to the vehicle’s unknown sensor network, our approach developed methods to efficiently analyze and identify key signals despite the large state-space for potential signal embeddings.

Nice, Matthew↗