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NASA NTRS2010

Phase-Conjugate Receiver for Gaussian-State Quantum Illumination

An active optical sensor probes a region of free space that is engulfed in bright thermal noise to determine the presence (or absence) of a weakly reflecting target. The returned light (which is just thermal noise if no target is present, and thermal noise plus a weak reflection of the probe beam if a target is present) is measured and processed by a receiver and a decision is made on whether a target is present. It has been shown that generating an entangled pair of photons (which is a highly nonclassical state of light), using one photon as the probe beam and storing the other photon for comparison to the returned light, has superior performance to the traditional classical-light (coherent-state) target detection sensors. An entangled-photon transmitter and optimal receiver combination can yield up to a factor of 4 (i.e., 6 dB) gain in the error-probability exponent over a coherent state transmitter and optimal receiver combination, in a highly lossy and noisy scenario (when both sensors have the same number of transmitted photons). However, the receiver that achieves this advantage is not known. One structured receiver can close half of the 6-dB gap (i.e., a 3-dB improvement). It is based on phase-conjugating the returned light, then performing dual-balanced difference detection with the stored half of the entangled-photon pair. Active optical sensors are of tremendous value to NASA s missions. Although this work focuses on target detection, it can be extended to imaging (2D, 3D, hyperspectral, etc.) scenarios as well, where the image quality can be better than that offered by traditional active sensors. Although the current work is theoretical, NASA s future missions could benefit significantly from developing and demonstrating this capability. This is an optical receiver design whose components are, in principle, all implementable. However, the work is currently entirely theoretical. It is necessary to: 1. Demonstrate a bench-top proof of the theoretical principle, 2. Create an operational prototype off-the-bench, and 3. Build a practical sensor that can fly in a mission.

Erkmen, Baris I.↗

NASA NTRS2001

A Diagnostic Analysis of the Kennedy Space Center LDAR Network: Data Characteristics - 1

An analytic framework is developed in which to analyze climatological VHF (66 MHz) radiation measurements taken by the Kennedy Space Center Lightning Detection and Ranging (LDAR) network. A 19 month noise-filtered sample of LDAR observations is examined using this framework. It is found that the climatological impulsive VHF source density as observed by LDAR falls off approximately 10 dB every 71 km of ground range away from the network centroid (a 31 km e-folding scale). The underlying vertical distribution of impulsive VHF sources is approximately normally distributed with a mean altitude of 9 km and a standard deviation of 2.7 km; this implies that the loss of below-horizon sources has a negligible effect on column-integrated source densities within a 200 km ground range. At medium to far ranges, location errors are primarily radial and have a slightly asymmetric distribution whose standard deviation increases as r(exp 2). Error moments estimated from observed lightning are significantly higher than those from aircraft-based signal generator or analytic estimates. LDAR bulk flash detection efficiency is predicted to be above 90% to 94-113 km range from the network centroid and to fall below 10% at ranges greater than 200-240 km.

Boccippio, D. J.↗

DOE OSTI2023

PROTEUS: Machine Learning Driven Resilience for Extreme-scale Systems

The objective of this project is to design, develop, and evaluate scalable software to enhance resilience, data checkpointing, program restart, and analysis. The proposed tasks are to 1) develop scalable machine learning techniques to learn temporal change patterns in a scalable and in-situ manner, and to minimize data movement and maximize learning locally closest to data; 2) design a concise data representation and indexing mechanism to capture the distribution of changes in data that can guarantee point-wise user-defined tolerable errors while reducing the data storage requirements by an order of magnitude or more; 3) develop data reduction techniques as library modules; 4) exploit local SSD for minimizing data movement in storage hierarchy; 5) develop anomaly detection algorithms that can predict corruptions based on learning of emerging patterns; 6) develop software libraries to be incorporated within widely used data formats and APIs; and 7) evaluate the proposed software using DOE scientific applications. The outcomes of the proposed work are to satisfy many synergistic data reduction and resilience requirements for large-scale data intensive applications executed on extreme-scale computing systems. The developed mechanism for error-bound data approximation is directly applicable to existing scientific applications. Through machine learning from historical events and change distribution, this work will enable anomaly detection for DOE computer facility.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1976

Detection of nuclear gamma rays from Centaurus A

Results are reported for an observation of nuclear gamma rays in the energy range between 0.033 and 12.25 MeV from Centaurus A using a balloon-borne actively collimated NaI(Tl) crystal scintillation counter. The observing procedure is outlined, no systematic errors are found in the data, and power-law fits to the source's energy spectrum are attempted. A power law of approximately 0.86E to the -1.9 power photon/sq cm/sec per keV is shown to give an acceptable fit to the continuum, and the detection of two gamma-ray lines at 1.6 and 4.5 MeV, respectively, is discussed. It is found that the low-energy gamma-ray luminosity of Cen A is 9.4 by 10 to the 43rd power erg/sec for a distance of 5 Mpc and that Cen A is apparently variable in low-energy gamma radiation. It is suggested that the broad feature detected at 1.6 MeV may be due to three blended lines (possibly excited Ne-20, Mg-24, and Si-28), the 4.5-MeV line is most likely due to deexcitation of excited C-12, and the nuclear excitation results from either cosmic-ray bombardment of Cen A's interstellar medium or nucleosynthesis within the source.

Hall, R. D.↗

NASA NTRS1999

On-Line Analysis of Physiologic and Neurobehavioral Variables During Long-Duration Space Missions

The goal of this project is to develop reliable statistical algorithms for on-line analysis of physiologic and neurobehavioral variables monitored during long-duration space missions. Maintenance of physiologic and neurobehavioral homeostasis during long-duration space missions is crucial for ensuring optimal crew performance. If countermeasures are not applied, alterations in homeostasis will occur in nearly all-physiologic systems. During such missions data from most of these systems will be either continually and/or continuously monitored. Therefore, if these data can be analyzed as they are acquired and the status of these systems can be continually assessed, then once alterations are detected, appropriate countermeasures can be applied to correct them. One of the most important physiologic systems in which to maintain homeostasis during long-duration missions is the circadian system. To detect and treat alterations in circadian physiology during long duration space missions requires development of: 1) a ground-based protocol to assess the status of the circadian system under the light-dark environment in which crews in space will typically work; and 2) appropriate statistical methods to make this assessment. The protocol in Project 1, Circadian Entrainment, Sleep-Wake Regulation and Neurobehavioral will study human volunteers under the simulated light-dark environment of long-duration space missions. Therefore, we propose to develop statistical models to characterize in near real time circadian and neurobehavioral physiology under these conditions. The specific aims of this project are to test the hypotheses that: 1) Dynamic statistical methods based on the Kronauer model of the human circadian system can be developed to estimate circadian phase, period, amplitude from core-temperature data collected under simulated light- dark conditions of long-duration space missions. 2) Analytic formulae and numerical algorithms can be developed to compute the error in the estimates of circadian phase, period and amplitude determined from the data in Specific Aim 1. 3) Statistical models can detect reliably in near real- time (daily) significant alternations in the circadian physiology of individual subjects by analyzing the circadian and neurobehavioral data collected in Project 1. 4) Criteria can be developed using the Kronauer model and the recently developed Jewett model of cognitive -performance and subjective alertness to define altered circadian and neurobehavioral physiology and to set conditions for immediate administration of countermeasures.

Brown, Emery N.↗

DOE OSTI2022

Nondestructive Damage Detection of Concrete With Alkali-Silica Reactions Using Coda Wave and Anomaly Detection

An anomaly detection model for early damage detection for concrete structures undergoing alkali-silica reaction (ASR) is presented. It is difficult to detect ASR initiation and early damage without a reference expansion measurement. Coda waves, or the multiply scattered portion of ultrasonic waves, have been found to be indicative of small changes in complex material such as concrete. The relationship between concrete damage and relative velocity change and decorrelation of coda waves has been studied, but a generalized model which detects when damage occurs in a concrete structure is still lacking. The presented method uses features extracted from coda waves to detect early damage in concrete structures. The model uses unsupervised learning and only requires data from undamaged structures for training. During the training process, the reconstruction error of the training data is minimized. When the data collected from damaged concrete structures is used as an input of the model, it returns high reconstruction errors that indicate the occurrence of damage in the structures. The performance of the model is validated using experimental studies and has been shown to generalize across two different ASR specimens.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2017

UAS Well Clear Recovery Against Non-Cooperative Intruders Using Vertical Maneuvers

This paper documents a study that drove the development of a mathematical expression in the detect-and-avoid (DAA) minimum operational performance standards (MOPS) for unmanned aircraft systems (UAS). This equation describes the conditions under which vertical maneuver guidance should be provided during recovery of DAA well clear separation with a non-cooperative VFR aircraft. Although the original hypothesis was that vertical maneuvers for DAA well clear recovery should only be offered when sensor vertical rate errors are small, this paper suggests that UAS climb and descent performance should be considered-in addition to sensor errors for vertical position and vertical rate-when determining whether to offer vertical guidance. A fast-time simulation study involving 108,000 encounters between a UAS and a non-cooperative visual-flight-rules aircraft was conducted. Results are presented showing that, when vertical maneuver guidance for DAA well clear recovery was suppressed, the minimum vertical separation increased by roughly 50 feet (or horizontal separation by 500 to 800 feet). However, the percentage of encounters that had a risk of collision when performing vertical well clear recovery maneuvers was reduced as UAS vertical rate performance increased and sensor vertical rate errors decreased. A class of encounter is identified for which vertical-rate error had a large effect on the efficacy of horizontal maneuvers due to the difficulty of making the correct left/right turn decision: crossing conflict with intruder changing altitude. Overall, these results support logic that would allow vertical maneuvers when UAS vertical performance is sufficient to avoid the intruder, based on the intruder's estimated vertical position and vertical rate, as well as the vertical rate error of the UAS' sensor.

UAS in the NAS↗

NASA NTRS2005

First Test of Fan Active Noise Control (ANC) Completed

With the advent of ultrahigh-bypass engines, the space available for passive acoustic treatment is becoming more limited, whereas noise regulations are becoming more stringent. Active noise control (ANC) holds promise as a solution to this problem. It uses secondary (added) noise sources to reduce or eliminate the offending noise radiation. The first active noise control test on the low-speed fan test bed was a General Electric Company system designed to control either the exhaust or inlet fan tone. This system consists of a "ring source," an induct array of error microphones, and a control computer. Fan tone noise propagates in a duct in the form of spinning waves. These waves are detected by the microphone array, and the computer identifies their spinning structure. The computer then controls the "ring source" to generate waves that have the same spinning structure and amplitude, but 180 out of phase with the fan noise. This computer generated tone cancels the fan tone before it radiates from the duct and is heard in the far field. The "ring source" used in these tests is a cylindrical array of 16 flat-plate acoustic radiators that are driven by thin piezoceramic sheets bonded to their back surfaces. The resulting source can produce spinning waves up to mode 7 at levels high enough to cancel the fan tone. The control software is flexible enough to work on spinning mode orders from -6 to 6. In this test, the fan was configured to produce a tone of order 6. The complete modal (spinning and radial) structure of the tones was measured with two builtin sets of rotating microphone rakes. These rakes provide a measurement of the system performance independent from the control system error microphones. In addition, the far-field noise was measured with a semicircular array of 28 microphones. This test represents the first in a series of tests that demonstrate different active noise control concepts, each on a progressively more complicated modal structure. The tests are in preparation for a demonstration on a flight-type engine.

Source record↗

NASA NTRS1976

Uhuru observations of the Norma X-ray burster

Four X-ray bursts consistent with a single source in Norma are reported which were discovered by reexamining Uhuru data obtained between 1970 and 1973. The temporal and spectral characteristics of the bursts are described and shown to be similar to those displayed by bursts from the globular cluster NGC 6224. An error box of the source location is given, and it is found that both the position and intensity of the four bursts are consistent with those of 10 bursts detected by the Vela satellites in 1976. It is concluded that the source is the same as that observed by the Vela and is an X-ray burster with characteristics similar to those of certain other bursters. XB 1608-52 is suggested as the designation of this burster, possible burst models are considered, and it is noted that the error box of the present source contains an identified globular cluster.

Grindlay, J.↗

DOE OSTI2020

Evaluation of a pair-based, joint-likelihood association approach for regional infrasound event identification

SUMMARY A Bayesian framework for the association of infrasonic detections is presented and evaluated for analysis at regional propagation scales. A pair-based, joint-likelihood association approach is developed that identifies events by computing the probability that individual detection pairs are attributable to a hypothetical common source and applying hierarchical clustering to identify events from the pair-based analysis. The framework is based on a Bayesian formulation introduced for infrasonic source localization and utilizes the propagation models developed for that application with modifications to improve the numerical efficiency of the analysis. Clustering analysis is completed using hierarchical analysis via weighted linkage for a non-Euclidean distance matrix defined by the negative log-joint-likelihood values. The method is evaluated using regional synthetic data with propagation distances of hundreds of kilometres in order to study the sensitivity of the method to uncertainties and errors in backazimuth and time of arrival. The method is found to be robust and stable for typical uncertainties, able to effectively distinguish noise detections within the data set from those in events, and can be made numerically efficient due to its ease of parallelization.

58 GEOSCIENCES↗

NASA NTRS1973

Detection of S02 and N02 in Stack Plume by Raman Scattering and Fluorescence

We have been studying laser-Raman radar which can be used as the remote detector of sulfur dioxide concentration in the stack plume of boiler exhaust gas, and some results have been published. In this paper, we report the interference of nitrogen dioxide fluorescence against sulfur dioxide Raman scattering and the measuring method of sulfur dioxide and nitrogen dioxide concentration. In a stack plume, high density dust and high concentration carbon dioxide are included, therefore very strong Mie back-scattering and carbon dioxide Raman scattering are observed. The separation of these scattering signals from sulfur dioxide Raman signal was the first problem for the laser-Raman radar. But, this problem was solved by using the filter which have high resolving power. It is well known that nitrogen dioxide can be excited to emit fluorescence of broad spectrum by blue-green light. The light source of the laser-Raman radar is SH of Nd:YAG laser, and boiler exhaust gas includes several tens ppm of nitrogen dioxide, then the interference of nitrogen dioxide fluorescence brings the error to sulfur dioxide measurement. 'rhe rejection of the interference can be achieved by the subtraction of the nitrogen dioxide fluorescence contribution from detected signal at sulfur dioxide Raman scattering wavelength. The nitrogen dioxide fluorescence contribution can be measured by two methods. The first is to convert the nitrogen dioxide fluorescence intensity which is measured at a different wavelength from sulfur dioxide Raman line into the one at sulfur dioxide Raman line. The second is to convert the detected signal intensity, which is obtained when the range gate is set just behind the plume, into the one obtained at the range of the plume using the difference of the time dependence between sulfur dioxide Raman scattering and nitrogen dioxide fluorescence. Nitrogen dioxide fluorescence has lifetime of about 300nS, while Raman scattering has none. By either of the two methods, the contribution of nitrogen dioxide fluorescence is determined. Then, we can measure the nitrogen dioxide and sulfur dioxide concentration.The minimum detectable concentration and the experimental results of the remote sensing of sulfur dioxide and nitrogen dioxide in stack plume will be discussed in detail.

Nakahara, S.↗

NASA NTRS1991

Comparative study on the performance of power and bandwidth efficient modulations in LMSS under fading and interference

Aspects of error performance of various power and bandwidth efficient modulations for the land mobile satellite systems (LMSS) were investigated under multipath fading and interferences by using Monte-Carlo simulation. A differential detection for 16QAM (quadrature amplitude modulation) was proposed to cope with Ricean fading and Doppler shift. Computer simulation results show that the performance of 16QAM with differential detection is as good as that of 16PSK with coherent detection and 3 dB better than that of 16PSK with differential detection, although it degrades by about 4.5 dB as compared to 16QAM with coherent detection under an additive white Gaussian noise (AWGN) channel. For the nonlinear channels, 16QAM with modified signal constellations is introduced and analyzed. The simulation results show that the modified 16QAM exhibits a gain of 2.5 dB over 16PSK under traveling-wave tube nonlinearity, and about 4 dB gain over 16PSK at the bit error rate of 10 exp -5 under AWGN. Computer simulation results for modified 16 QAM under cochannel interference and adjacent-channel interference are also presented.

Liu, Jian↗

NASA NTRS1988

Node synchronization of viterbi decoders using state metrics

The concept of node synchronization using state metrics is investigated. The branch metrics are integrated over a fixed time interval and the results are compared to the detection threshold. If the threshold is exceeded, the out-of-sync hypothesis is accepted; otherwise, the in-sync hypothesis is accepted. It is shown that the detection threshold can be chosen independent of any particular convolutional code with fixed code rate and constant length if the code has reasonably good bit error rate performance. Three node synchronization schemes are compared: (1) a scheme using the syndrome; (2) a scheme using the frame-sync patterns; and (3) a scheme using the state metrics. At very low signal to noise ratios (SNR), scheme 2 can be faster than scheme 1. For Voyager's rate 1/2 and constraint length 7 convolutional code, this happens for SNRs of less than 0.7 dB. This result is obtained by assuming that the code frame-sync pattern has good aperiodic autocorrelation properties. For a fixed false alarm probability, the sequential detection scheme based on the syndrome is faster than scheme 3 with fixed integration time. A sequential detection technique is needed to improve the speed of scheme 3.

Cheng, U.↗

NASA NTRS2014

Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a generalized stability metric for time-varying loop=gain perturbations is needed for the AAC.

VanZwieten, Tannen↗

NASA NTRS2023

Potentially Underestimated Gas Flaring Activities—A New Approach to Detect Combustion Using Machine Learning and NASA’s Black Marble Product Suite

Monitoring changes in greenhouse gas (GHG) emission is critical for assessing climate mitigation efforts towards the Paris Agreement goal. A crucial aspect of science-based GHG monitoring is to provide objective information for quality assurance and uncertainty assessment of the reported emissions. Emission estimates from combustion events (gas flaring and biomass burning) are often calculated based on activity data (AD) from satellite observations, such as those detected from the visible infrared imaging radiometer suite (VIIRS) onboard the Suomi-NPP and NOAA-20 satellites. These estimates are often incorporated into carbon models for calculating emissions and removals. Consequently, errors and uncertainties associated with AD propagate into these models and impact emission estimates. Deriving uncertainty of AD is therefore crucial for transparency of emission estimates but remains a challenge due to the lack of evaluation data or alternate estimates. This work proposes a new approach using machine learning (ML) for combustion detection from NASA's Black Marble product suite and explores the assessment of potential uncertainties through comparison with existing detections. We jointly characterize combustion using thermal and light emission signals, with the latter improving detection of probable weaker combustion with less distinct thermal signatures. Being methodologically independent, the differences in ML-derived estimates with existing approaches can indicate the potential uncertainties in detection. The approach was applied to detect gas flares over the Eagle Ford Shale, Texas. We analyzed the spatio-temporal variations in detections and found that approximately 79.04% and 72.14% of the light emission-based detections are missed by ML-derived detections from VIIRS thermal bands and existing datasets, respectively. This improvement in combustion detection and scope for uncertainty assessment is essential for comprehensive monitoring of resulting emissions and we discuss the steps for extending this globally.

gas flaring↗

DOE OSTI2024

Universal framework for simultaneous tomography of quantum states and SPAM noise

We present a general denoising algorithm for performing simultaneous tomography of quantum states and measurement noise. This algorithm allows us to fully characterize state preparation and measurement (SPAM) errors present in any quantum system. Our method is based on the analysis of the properties of the linear operator space induced by unitary operations. Given any quantum system with a noisy measurement apparatus, our method can output the quantum state and the noise matrix of the detector up to a single gauge degree of freedom. We show that this gauge freedom is unavoidable in the general case, but this degeneracy can be generally broken using prior knowledge on the state or noise properties, thus fixing the gauge for several types of state-noise combinations with no assumptions about noise strength. Such combinations include pure quantum states with arbitrarily correlated errors, and arbitrary states with block independent errors. This framework can further use available prior information about the setting to systematically reduce the number of observations and measurements required for state and noise detection. Our method effectively generalizes existing approaches to the problem, and includes as special cases common settings considered in the literature requiring an uncorrelated or invertible noise matrix, or specific probe states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2019

The LUVOIR Extreme Coronagraph for Living Planetary Systems (ECLIPS) II. Performance Evaluation, Aberration Sensitivity Analysis and Exoplanet Detection Simulations

Future space missions such as the Large UV-Optical-Infrared Surveyor (LUVOIR) and the Habitable Exoplanet Observatory (HabEx) require coronagraphs with active wavefront control to suppress starlight to discover and characterize habitable exoplanets. The Extreme Coronagraph for Living Planetary Systems (ECLIPS) is the coronagraph instrument on the LUVOIR Surveyor mission concept, an 8–15m segmented telescope. ECLIPS is split into three channels: UV (200 to 400 nm), optical (400 nm to 850 nm), and NIR (850 nm to 2.0 microns), with each channel equipped with two deformable mirrors for wavefront control, a suite of coronagraph masks, a low-order/out-of-band wavefront sensor, and separate science imagers and spectrographs. The Apodized Pupil Lyot Coronagraph (APLC) and the Vector Vortex Coronagraph (VVC) are the baselined mask technologies for ECLIPS to enable the required 10 -10 contrast for observations in the habitable zones of nearby stars. Their performance depends on active wavefront sensing and control, as well as metrology subsystems to compensate for aberrations induced by segment errors (piston and tip/tilt, among others), secondary mirror misalignment, and global low-order wavefront errors. Here we present the latest results of the simulation of these effects for the two technologies and discuss the achieved contrast for exoplanet detection and characterization after closed-loop wavefront estimation and control algorithms have been applied. Finally, we show simulated observations using high-fidelity spatial and spectral input models of complete planetary systems generated with the Haystacks code framework.

Roser Juanola-Parramon↗

DOE OSTI2021

Multielectrode Array Sensors to Enable Long-Duration Corrosion Monitoring and Control of Concentrating Solar Power Systems

Molten mixtures of MgCl2-KCl-NaCl are promising heat transfer fluid (HTF) candidates for the next generation of concentrating solar power systems (Gen3 CSP), because of their low cost, high decomposition temperature, and favorable heat transfer characteristics. However, if the chemistry of the salts is not properly controlled, molten chlorides can cause corrosion of high-temperature metal alloys, such as Inconel (R), in CSP systems. Here we demonstrate a corrosion monitoring system that can be used to monitor the health of the structural alloys over long durations. The monitoring system includes a multielectrode array voltammetry sensor that measures the redox potential of molten MgCl2-KCl-NaCl mixture as well as the presence of corrosion products and impurities. The sensors have been successfully operated in static molten salt environments for long durations, and are capable of detecting corrosion products, such as Cr2+ and Fe2+, quantitatively at low concentrations (i.e., approximately 100 ppm) with less than 4% error.

Concentrated solar power↗