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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Surveillance system and method having an adaptive sequential probability fault detection test

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Herzog, James P.↗
NASA NTRS2006

Surveillance system and method having an adaptive sequential probability fault detection test

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Bickford, Randall L.↗
NASA NTRS2008

Surveillance System and Method having an Adaptive Sequential Probability Fault Detection Test

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Bickford, Randall L.↗
DOE OSTI2022

High bias machine learning for antineutrino-based safeguards for small reactors

The statistical methods used for antineutrino detection will need to be improved to effectively monitor the inventory of next-generation nuclear reactors. In this sensitivity study, we evaluate machine learning models compared to previously used statistical approaches to identify diversion scenarios in a simulated Advanced Fast Reactor (AFR)-100. A chi-square goodness-of-fit technique, which individually compares the simulated antineutrino yields to the expected antineutrino yield, resulted in precise but low diversion detection probability. Various support vector machine (SVM) models were applied with diverse training datasets to evaluate the robustness of the method towards unexpected or “unseen” diversion scenarios. Furthermore, our results indicate that while the SVM models significantly improved the detection probability of near-field antineutrino-based safeguards, up to a probability of ~0.04, for the simulated small reactor, the detection system still needs improvements to reach the 0.2 detection limit established by the International Atomic Energy Agency.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS1989

Costas loop lock detection in the advanced receiver

The advanced receiver currently being developed uses a Costas digital loop to demodulate the subcarrier. Previous analyses of lock detector algorithms for Costas loops have ignored the effects of the inherent correlation between the samples of the phase-error process. Accounting for this correlation is necessary to achieve the desired lock-detection probability for a given false-alarm rate. Both analysis and simulations are used to quantify the effects of phase correlation on lock detection for the square-law and the absolute-value type detectors. Results are obtained which depict the lock-detection probability as a function of loop signal-to-noise ratio for a given false-alarm rate. The mathematical model and computer simulation show that the square-law detector experiences less degradation due to phase jitter than the absolute-value detector and that the degradation in detector signal-to-noise ratio is more pronounced for square-wave than for sine-wave signals.

Mileant, A.↗
DOE OSTI2019

Analysis of Empirical Probability of Detection Data for Dissimilar Metal Welds

The U.S. Nuclear Regulatory Commission’s (NRC) Standard Review Plan (SRP) 3.6.3 describes leak-before- break (LBB) assessment procedures that can be used to assess compliance with the 10 CFR 50 Appendix A, General Design Criteria (GDC)-4 requirement that primary system pressure piping exhibit an extremely low probability of rupture. SRP 3.6.3 does not allow for assessment of piping systems with active degradation mechanisms, such as primary water stress corrosion cracking (PWSCC), which is currently occurring in systems that have been granted LBB approvals. To address those piping systems approved for LBB that are experiencing PWSCC, the NRC Office of Nuclear Regulatory Research (RES) working cooperatively with the Electric Power Research Institute (EPRI) conducted a multi-year project to develop a probabilistic fracture mechanics code called eXtremely Low Probability of Rupture (xLPR) that can be used to assess compliance with the regulations. xLPR is a probabilistic computational tool capable of evaluating degradation in reactor coolant piping welds leading to rupture with extremely low probabilities of occurrence. This tool models the effects of active degradation mechanisms and the inspection and mitigation activities that are being undertaken to manage PWSCC degradation. Crack initiation and growth due to fatigue and primary water stress corrosion, along with mitigation methods (mechanical mitigation as well as chemical mitigation) and the effects of in-service inspection (ISI) and leak detection can be analyzed using this tool.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Influence of lure choice and survey duration on scent stations for carnivore surveys

Abstract Noninvasive, camera‐based, scent station surveys have become a common approach to estimate population parameters for mammalian carnivores. Many carnivores are particularly sensitive to olfactory cues; and, as such, the quality and quantity of odor attractant used during surveys can significantly affect the accuracy and precision of the survey. Additionally, survey length is also an important consideration because many mammalian predators are highly mobile and elusive in nature. Using scent station surveys in autumn 2013 and 2014 on the Savannah River Site, Aiken, South Carolina, USA, we tested the effects of 5 lures: fatty acid, fish oil, synthetic fermented egg, beaver castor, and skunk essence on visitation rates, visitation probability, and latency to visitation of multiple predator species. We also estimated occupancy probability for 2 carnivore species using different survey lengths to determine the effect of survey period on the precision of occupancy estimates. We found that skunk essence had greater visitation probability and visits than other lures evaluated. Species‐specific bait‐preference models revealed that raccoons ( Procyon lotor ) were more likely to visit skunk essence, and coyotes ( Canis latrans ) were less likely to visit fish oil as compared with fatty acid. Latency to visitation ranged from 104.7 to 112.1 hours and did not vary among scents. Longer survey durations resulted in more precise estimates of occupancy and detection probability. Our results suggest a wide range of scents commonly used for carnivore capture may perform as well as, or better than, fatty acid for noninvasive carnivore surveys. Further, study designs should carefully consider the duration of scent‐station surveys depending on the level of precision desired in estimates of occupancy and detection probability. © 2019 The Wildlife Society.

Webster, Sarah C.↗
NASA NTRS1980

The morphology of metallic ions in the upper atmosphere

Analysis of metallic ion data from a day-night pair of rockets, OGO 6, and the elliptic phases of AE-C and AE-D shows the presence of Fe(+) ions at altitudes above 400 km only at low magnetic latitudes. The detection probability of this ion decreases with altitude, with a maximum over the Atlantic and a minimum over India; the rocket data indicate ions in the E region during the day and on the bottom of the F layer at night. Mg(+) and Fe(+) are the dominant ions below 250 km at all latitudes, but Al(+), Na(+), Si(+), and Ca(+) are also detectable; a correlation was found between solar activity and metallic ion detection probability at low latitudes and high altitudes at night

Kumar, S.↗
DOE OSTI2024

Application of a Geochemically Informed Leak Detection (GILD) Model to CO 2 Injection Sites on the United States Gulf Coast

The Gulf Coast region possesses great potential for CO 2 enhanced oil recovery (EOR) and CO 2 storage. A geochemically informed leak detection (GILD) model has been applied to CO 2 injection sites on the Gulf Coast with considerations of measurement variability. The Jasper aquifer in Montgomery County, Texas, was chosen to demonstrate the method. Based on background data from wells in the area, combinations of mineral and fluid compositions were used to create 23 scenarios for the geochemical model. The output from the geochemical model was used to identify sensitive monitoring species, and response functions were generated for these as a function of the CO 2 leakage concentration. The sources of measurement variability for background conditions were characterized from the Jasper aquifer background data, and then normalized using the coefficient of variation of each species across the monitoring wells. Bayesian belief network (BBN) models were constructed, and measurement variability of different levels were added to compare leak detection probabilities. Increasing measurement variability decreased the power to detect a leak of a given size. For a moderately high CO 2 concentration of 0.2 mol/kg, the probability of detecting this leakage effect using pH as the monitoring variable in an aquifer with calcite decreases from 98% (no measurement variability) to 61% (medium variability) to 33% (high variability). The loss in power of the sampling protocol with increasing measurement variability is similar in magnitude when Ca 2+ or HCO 3 - is used as the monitoring parameter, but only for aquifers with calcite.

58 GEOSCIENCES↗
DOE OSTI2023

Modular chip-integrated photonic control of artificial atoms in diamond waveguides

A central goal in creating long-distance quantum networks and distributed quantum computing is the development of interconnected and individually controlled qubit nodes. Atom-like emitters in diamond have emerged as a leading system for optically networked quantum memories, motivating the development of visible-spectrum, multi-channel photonic integrated circuit (PIC) systems for scalable atom control. However, it has remained an open challenge to realize optical programmability with a qubit layer that can achieve high optical detection probability over many optical channels. Here, we address this problem by introducing a modular architecture of piezoelectrically actuated atom-control PICs (APICs) and artificial atoms embedded in diamond nanostructures designed for high-efficiency free-space collection. The high-speed four-channel APIC is based on a splitting tree mesh with triple-phase shifter Mach–Zehnder interferometers. This design simultaneously achieves optically broadband operation at visible wavelengths, high-fidelity switching (>40dB) at low voltages, submicrosecond modulation timescales (>30MHz), and minimal channel-to-channel crosstalk for repeatable optical pulse carving. Via a reconfigurable free-space interconnect, we use the APIC to address single silicon vacancy color centers in individual diamond waveguides with inverse tapered couplers, achieving efficient single photon detection probabilities (∼15%) and second-order autocorrelation measurements g (2) (0)<0.14 for all channels. The modularity of this distributed APIC–quantum memory system simplifies the quantum control problem, potentially enabling further scaling to thousands of channels.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Visualisation and outlier detection for probability density function ensembles

Abstract Exploratory data analysis (EDA) for functional data—data objects where observations are entire functions—is a difficult problem that has seen significant attention in recent literature. This surge in interest is motivated by the ubiquitous nature of functional data, which are prevalent in applications across fields such as meteorology, biology, medicine and engineering. Empirical probability density functions (PDFs) can be viewed as constrained functional data objects that must integrate to one and be nonnegative. They show up in contexts such as yearly income distributions, zooplankton size structure in oceanography and in connectivity patterns in the brain, among others. While PDF data are certainly common in modern research, little attention has been given to EDA specifically for PDFs. In this paper, we extend several methods for EDA on functional data for PDFs and compare them on simulated data that exhibit different types of variation, designed to mimic that seen in real‐world applications. We then use our new methods to perform EDA on the breakthrough curves observed in gas transport simulations for underground fracture networks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

The probability of detecting absorption features in gamma-ray burst spectra

It has recently been suggested that several mechanisms for the primary release of energy in gamma-ray bursts may result in the excitation of magnetospheric plasma oscillations (MPO) above the polar cap of a neutron star. The basic MPO idea is refined by determining the soft photon source (which damps the particle motion via inverse Compton scattering interactions) self-consistently by means of a Monte Carlo simulation for the deposition of back-scattered gamma-ray energy below the stellar photosphere. The observed fraction of bursts displaying low-energy absorption features may be understood in the context of a model wherein the overall spectrum changes with inclination angle due to the superposition of several components with different angular distributions. GRB spectra should display these cyclotron lines about 18 percent of the time, which is consistent with the KONUS and Ginga sets of data.

Melia, F.↗
NASA NTRS2003

Performance Evaluation Modeling of Network Sensors

Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.

probability of detection↗
NASA NTRS2011

Probability of Detection (POD) Demonstration Transferability

NASA Special Level POD demonstration tests are typically performed on flat plates of a single material containing fatigue cracks with aspect rations between 0.3 and 0.5. Subsequent fracture mechanics analyses consider aspect ratios that range from 0.1 to 0.5. There is debate within the NDE community about the detectability of shallow cracks associated with NASA Special Level penetrant inspections that are routinely performed by propellant tank manufactures. The objective of the task is to investigate effect of crack aspect ratio on POD crack sizes for the penetrant inspection technique.

Parker, Bradford H.↗
NASA NTRS2011

Probability of Detection (POD) Demonstration Transferability: Phase II

NASA Special Level POD demonstration tests are typically performed on flat plates of a single material containing fatigue cracks with aspect rations between 0.3 and 0.5. In many cases, the inspectors that pass the demonstration tests use (transfer) the NDE technique to inspect different materials and part geometries and for varying types of flaws. The objective of the task is to investigate several of the factors that may influence the transferability of POD demonstration tests. An existing set of 30 6061-T6 aluminum crack panels will be used to create parts with a square tube and pocket type geometries. These same aluminum crack panels were used in a study of the effect of penetrant sensitivity level on POD. Hence, we should be able to directly compare the POD for flat panels versus larger parts with more complex geometries.

Parker, Bradford H.↗