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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Study of charge trapping in CZT detectors

A semiconductor detection material, Cadmium Zinc Telluride, was investigated for potential use as a particle detector for space flight applications. Our set of detectors was determined to be flawed for particle detection methods, likely due to charge transport mechanisms within the detector material, or due to reduced voltage required to avoid dielectric breakdown. It was observed that the method of crystal growth may play a role in the performance, but performance may also vary between manufacturers using the same growth method. It is recommended to perform further study at a larger proton beam facility.

47 OTHER INSTRUMENTATION↗
NASA NTRS1977

Effects of detector threshold, location of the sun, and flight altitude upon spectral variations in remote sensing over water

Photographic flights with Hasselblad cameras were flown on August 28, 1975, at altitudes from 2.66 and 5.3 kilometers over an ocean acid waste dump site while acid dumping was in progress. Repeated flights resulted in broadband spectral radiance data between the wavelengths of 500 to 900 nanometers for sun elevation angles that varied from 26 to 48 degrees, and at all sun azimuth angles over the range of off-nadir angles from 0 to 35 degrees. From film densitometer data, it is shown that before spectral variations in remotely sensed data can be used to quantify substances in water, the longer wavelength data must be above the detection level of the detector, radiance data between + or - 45 degrees in the direction of the sun must be avoided, and off-nadir camera correction factors must be applied to the observed radiance data.

Bressette, W. E.↗
NASA NTRS1981

The 1979 Clear Air Turbulence Flight Test Program

The flight experiments for clear air turbulence (CAT) detection and measurement concepts are described. The test were conducted over the western part of the United States during the winter season of 1979 aboard NASA's Galileo 2 flying laboratory. A carbon dioxide pulsed Doppler lidar and an infrared radiometer were tested for the remote detection and measurement of CAT. Two microwave radiometers were evaluated for their ability to provide encounter warning and altitude avoidance information.

Weaver, E. A.↗
NASA NTRS1997

A low molecular weight artificial RNA of unique size with multiple probe target regions

Artificial RNAs (aRNAs) containing novel sequence segments embedded in a deletion mutant of Vibrio proteolyticus 5S rRNA have previously been shown to be expressed from a plasmid borne growth rate regulated promoter in E. coli. These aRNAs accumulate to high levels and their detection is a promising tool for studies in molecular microbial ecology and in environmental monitoring. Herein a new construct is described which illustrates the versatility of detection that is possible with aRNAs. This 3xPen aRNA construct carries a 72 nucleotide insert with three copies of a unique 17 base probe target sequence. This aRNA is 160 nucleotides in length and again accumulates to high levels in the E. coli cytoplasm without incorporating into ribosomes. The 3xPen aRNA illustrates two improvements in detection. First, by appropriate selection of insert size, we obtained an aRNA which provides a unique and hence, easily quantifiable peak, on a high resolution gel profile of low molecular weight RNAs. Second, the existence of multiple probe targets results in a nearly commensurate increase in signal when detection is by hybridization. These aRNAs are naturally amplified and carry sequence segments that are not found in known rRNA sequences. It thus may be possible to detect them directly. An experimental step involving RT-PCR or PCR amplification of the gene could therefore be avoided.

Non-NASA Center↗
NASA NTRS2011

Global CALIPSO Observations of Aerosol Changes Near Clouds

Several recent studies have found that clouds are surrounded by a transition zone of rapidly changing aerosol optical properties and particle size. Characterizing this transition zone is important for better understanding aerosol-cloud interactions and aerosol radiative effects, and also for improving satellite retrievals of aerosol properties. This letter presents a statistical analysis of a monthlong global data set of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar observations over oceans. The results show that the transition zone is ubiquitous over all oceans and extends up to 15 km away from clouds. They also show that near-cloud enhancements in backscatter and particle size are strongest at low altitudes, slightly below the top of the nearest clouds. Also, the enhancements are similar near illuminated and shadowy cloud sides, which confirms that the asymmetry of Moderate Resolution Imaging Spectroradiometer reflectances found in an earlier study comes from 3-D radiative processes and not from differences in aerosol properties. Finally, the effects of CALIPSO aerosol detection and cloud identification uncertainties are discussed. The findings underline the importance of accounting for the transition zone to avoid potential biases in studies of satellite aerosol products, aerosol-cloud interactions, and aerosol direct radiative effects.

Varnai, Tamas↗
DOE OSTI2021

Active Neutron Interrogation as a Method for Verification of the Absence of Special Nuclear Material in Arms Control Dismantlement

The next step in arms control reductions will deal with both strategic and non-strategic weapons, presenting new and hard challenges for verification. One verification approach that might be used in support of these reductions is the concept of deferred verification, which forgoes inspections at sensitive nuclear sites and relies on an inspection regime having access to the open segment of a State's nuclear sector, in "monitored transfer zones." A component of this approach is the anticipated need for an instrument suite capable of detecting well-shielded highly-enriched uranium or plutonium where it isn't supposed to be. This specific need was recently identified by the United Nations Institute for Disarmament Research in an enabling operating concept they call "contain and dispose." At the foundation of this approach is the idea that items declared as "not nuclear" are, by definition, not treaty limited and are thus "fair-game" for inspection and questioning. Active Neutron Interrogation (ANI), using beta-delayed neutron emissions as the signature for special nuclear material (SNM) detection, is a promising method to address this challenge. The method is quick, has high sensitivity and high specificity for detecting shielded SNM, is robust against changing background radiation environments, is robust against the presence of unknown shielding, and avoids the use of gamma-ray spectrometry which may introduce complications due to the potential release of sensitive information. This paper will present recent research activities exploring technical aspects of using ANI as a FAIRGAME verification method and discuss future prospects and research needs

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
NASA NTRS1989

Experiments in fault tolerant software reliability

Twenty functionally equivalent programs were built and tested in a multiversion software experiment. Following unit testing, all programs were subjected to an extensive system test. In the process sixty-one distinct faults were identified among the versions. Less than 12 percent of the faults exhibited varying degrees of positive correlation. The common-cause (or similar) faults spanned as many as 14 components. However, a majority of these faults were trivial, and easily detected by proper unit and/or system testing. Only two of the seven similar faults were difficult faults, and both were caused by specification ambiguities. One of these faults exhibited variable identical-and-wrong response span, i.e. response span which varied with the testing conditions and input data. Techniques that could have been used to avoid the faults are discussed. For example, it was determined that back-to-back testing of 2-tuples could have been used to eliminate about 90 percent of the faults. In addition, four of the seven similar faults could have been detected by using back-to-back testing of 5-tuples. It is believed that most, if not all, similar faults could have been avoided had the specifications been written using more formal notation, the unit testing phase was subject to more stringent standards and controls, and better tools for measuring the quality and adequacy of the test data (e.g. coverage) were used.

Mcallister, David F.↗
NASA NTRS2009

Progress Towards the Remote Sensing of Aircraft Icing Hazards

NASA has teamed with the FAA, DoD, industry, and academia for research into the remote detection and measurement of atmospheric conditions leading to aircraft icing hazards. The ultimate goal of this effort is to provide pilots, controllers, and dispatchers sufficient information to allow aircraft to avoid or minimize their exposure to the hazards of in-flight icing. Since the hazard of in-flight icing is the outcome of aircraft flight through clouds containing supercooled liquid water and strongly influenced by the aircraft s speed and configuration and by the length of exposure, the hazard cannot be directly detected, but must be inferred based upon the measurement of conducive atmospheric conditions. Therefore, icing hazard detection is accomplished through the detection and measurement of liquid water in regions of measured sub-freezing air temperatures. The icing environment is currently remotely measured from the ground with a system fusing radar, lidar, and multifrequency microwave radiometer sensors. Based upon expected ice accretion severity for the measured environment, a resultant aircraft hazard is then calculated. Because of the power, size, weight, and view angle constraints of airborne platforms, the current ground-based solution is not applicable for flight. Two current airborne concepts are based upon the use of either multifrequency radiometers or multifrequency radar. Both ground-based and airborne solutions are required for the future since groundbased systems can provide hazard detection for all aircraft in airport terminal regions while airborne systems will be needed to provide equipped aircraft with flight path coverage between terminal regions.

Reehorst, Andrew↗
DOE OSTI2022

SAFE-OCC: A novelty detection framework for Convolutional Neural Network sensors and its application in process control

Herein we present a novelty detection framework for Convolutional Neural Network (CNN) sensors that we call Sensor-Activated Feature Extraction One-Class Classification (SAFE-OCC). We show that this framework enables the safe use of computer vision sensors in process control architectures. Emergent control applications use CNN models to map visual data to a state signal that can be interpreted by the controller. Incorporating such sensors introduces a significant system operation vulnerability because CNN sensors can exhibit high prediction errors when exposed to novel (abnormal) visual data. Unfortunately, identifying such novelties in real-time is nontrivial. To address this issue, the SAFE-OCC framework leverages the convolutional blocks of the CNN to create an effective feature space to conduct novelty detection using a desired one-class classification technique. This approach engenders a feature space that directly corresponds to that used by the CNN sensor and avoids the need to derive an independent latent space. We demonstrate the effectiveness of SAFE-OCC via simulated control environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Aircraft Fault Detection and Classification Using Multi-Level Immune Learning Detection

This work is an extension of a recently developed software tool called MILD (Multi-level Immune Learning Detection), which implements a negative selection algorithm for anomaly and fault detection that is inspired by the human immune system. The immunity-based approach can detect a broad spectrum of known and unforeseen faults. We extend MILD by applying a neural network classifier to identify the pattern of fault detectors that are activated during fault detection. Consequently, MILD now performs fault detection and identification of the system under investigation. This paper describes the application of MILD to detect and classify faults of a generic transport aircraft augmented with an intelligent flight controller. The intelligent control architecture is designed to accommodate faults without the need to explicitly identify them. Adding knowledge about the existence and type of a fault will improve the handling qualities of a degraded aircraft and impact tactical and strategic maneuvering decisions. In addition, providing fault information to the pilot is important for maintaining situational awareness so that he can avoid performing an action that might lead to unexpected behavior - e.g., an action that exceeds the remaining control authority of the damaged aircraft. We discuss the detection and classification results of simulated failures of the aircraft's control system and show that MILD is effective at determining the problem with low false alarm and misclassification rates.

Wong, Derek↗
DOE OSTI2017

Dark matter self-interactions from a general spin-0 mediator

Dark matter particles interacting via the exchange of very light spin-0 mediators can have large self-interaction rates and obtain their relic abundance from thermal freeze-out. At the same time, these models face strong bounds from direct and indirect probes of dark matter as well as a number of constraints on the properties of the mediator. We investigate whether these constraints can be consistent with having observable effects from dark matter self-interactions in astrophysical systems. For the case of a mediator with purely scalar couplings we point out the highly relevant impact of low-threshold direct detection experiments like CRESST-II, which essentially rule out the simplest realization of this model. These constraints can be significantly relaxed if the mediator has CP-violating couplings, but then the model faces strong constraints from CMB measurements, which can only be avoided in special regions of parameter space.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2000

Remote Sensing of In-Flight Icing Conditions: Operational, Meteorological, and Technological Considerations

Remote-sensing systems that map aircraft icing conditions in the flight path from airports or aircraft would allow icing to be avoided and exited. Icing remote-sensing system development requires consideration of the operational environment, the meteorological environment, and the technology available. Operationally, pilots need unambiguous cockpit icing displays for risk management decision-making. Human factors, aircraft integration, integration of remotely sensed icing information into the weather system infrastructures, and avoid-and-exit issues need resolution. Cost, maintenance, power, weight, and space concern manufacturers, operators, and regulators. An icing remote-sensing system detects cloud and precipitation liquid water, drop size, and temperature. An algorithm is needed to convert these conditions into icing potential estimates for cockpit display. Specification development requires that magnitudes of cloud microphysical conditions and their spatial and temporal variability be understood at multiple scales. The core of an icing remote-sensing system is the technology that senses icing microphysical conditions. Radar and microwave radiometers penetrate clouds and can estimate liquid water and drop size. Retrieval development is needed; differential attenuation and neural network assessment of multiple-band radar returns are most promising to date. Airport-based radar or radiometers are the most viable near-term technologies. A radiometer that profiles cloud liquid water, and experimental techniques to use radiometers horizontally, are promising. The most critical operational research needs are to assess cockpit and aircraft system integration, develop avoid-and-exit protocols, assess human factors, and integrate remote-sensing information into weather and air traffic control infrastructures. Improved spatial characterization of cloud and precipitation liquid-water content, drop-size spectra, and temperature are needed, as well as an algorithm to convert sensed conditions into a measure of icing potential. Technology development also requires refinement of inversion techniques. These goals can be accomplished with collaboration among federal agencies including NASA, the FAA, the National Center for Atmospheric Research, NOAA, and the Department of Defense. This report reviews operational, meteorological, and technological considerations in developing the capability to remotely map in-flight icing conditions from the ground and from the air.

Ryerson, Charles C.↗
DOE OSTI2025

Development and testing of a continuous maritime monitor for radionuclide aerosols

Monitoring airborne concentrations of radionuclide activity may provide a timely warning to sea-based assets to avoid contamination from a radioactive plume. The development and testing of an automated aerosol monitoring system that can capture and detect radioactive particulate from marine air is presented. A custom electrostatic precipitator (ESP) was designed to capture particulate onto a reusable collection media. The collection efficiency of the ESP system for radon progeny was determined to be ~23%. A conservative calculation of the minimum detectable concentration of 214 Bi was estimated as 0.3-8 Bq/m 3 . The system was demonstrated in continuous operation, without consumables and limited maintenance, in a marine environment at the PNNL campus in Sequim, Washington. In conclusion, a successful 2-month deployment indicates the feasibility of the approach for continuous maritime monitoring for radionuclide aerosols.

Moore, Michael E. [Pacific Northwest National Labo↗
DOE OSTI2024

Exploring Robust Features for Improving Adversarial Robustness

While deep neural networks (DNNs) have revolutionized many fields, their fragility to carefully designed adversarial attacks impedes the usage of DNNs in safety-critical applications. In this article, we strive to explore the robust features that are not affected by the adversarial perturbations, that is, invariant to the clean image and its adversarial examples (AEs), to improve the model’s adversarial robustness. Specifically, we propose a feature disentanglement model to segregate the robust features from nonrobust features and domain-specific features. Here, the extensive experiments on five widely used datasets with different attacks demonstrate that robust features obtained from our model improve the model’s adversarial robustness compared to the state-of-the-art approaches. Moreover, the trained domain discriminator is able to identify the domain-specific features from the clean images and AEs almost perfectly. This enables AE detection without incurring additional computational costs. With that, we can also specify different classifiers for clean images and AEs, thereby avoiding any drop in clean image accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Substation Secondary Asset Health Monitoring and Management System (SSHM)

Electric Power Group, LLC (EPG) was awarded DOE OE0000850 to design, develop, and demonstrate a real-time software application for substation secondary equipment health monitoring and management at host utility American Electric Power (AEP), a cost share partner. This project addresses the need for monitoring substation equipment health and providing operators with tools to identify and take pre-emptive action to avoid catastrophic equipment failure. By monitoring synchrophasor data in real time, data anomalies that indicate potential asset failure can be detected and alerts can be sent to operators in time to take corrective actions. EPG developed two data driven algorithms to identify abnormal equipment signature patterns as well as a method using substation linear state estimation (SLSE). The software has been deployed on hardened PC’s and tested and validated for cost share partner AEP’s substations - 138kV and 765 kV. The SSHM software has been accepted by AEP and final demonstration of DOE - OE0000850 for AEP and DOE was successfully completed on March 17th, 2020. EPG developed the Substation Secondary Asset Health Monitoring (SSHM) Platform to analyze equipment failure signatures in PMU data and alert substation personnel when pre-emptive inspection, repairs and other actions are warranted to prevent potential catastrophic failures. This is the first system that automatically monitors the health of substation secondary assets and alerts users to emerging failures using synchrophasor measurements. SSHM uses high resolution PMU data from PTs, CTs, and CCVTs to analyze equipment signatures and identify anomalies that are precursor indicators of potential equipment failure. When an anomaly is detected, there is a likelihood of potential failure of monitored equipment, the system alerts the user with visual alarms including alarm trend charts and indicator lights on a oneline diagram of the substation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Plutonium Signatures in Molten-Salt Reactor Off-Gas Tank and Safeguards Considerations

Fluid-fueled molten-salt reactors (MSRs) are actively being developed by several companies, with plans to deploy them internationally. The current IAEA inspection tools are largely incompatible with the unique design features of liquid fuel MSRs (e.g., the complex fuel chemistry, circulating fuel inventory, bulk accountancy, and high radiation environment). For these reasons, safeguards for MSRs are seen as challenging and require the development of new techniques. This paper proposes one such technique through the observation of the reactor’s off-gas. Any reactor design using low-enriched uranium will build up plutonium as the fuel undergoes burnup. Plutonium has different fission product yields than uranium. Therefore, a shift in fission product production is expected with fuel evolution. The passive removal of certain gaseous fission products to the off-gas tank of an MSR provides a valuable opportunity for analysis without significant modifications to the design of the system. Uniquely, due to the gaseous nature of the isotopes, beta particle emissions are available for observation. The ratios of these fission product isotopes can, thus, be traced back to the relative amount and types of fissile isotopes in the core. This proposed technique represents an effective safeguards tool for bulk accountancy which, while avoiding being onerous, could be used in concert with other techniques to meet the IAEA’s timeliness goals for the detection of a diversion.

Dunkle, Nicholas (ORCID:000000027323011X)↗
DOE OSTI2016

THE HYDROGEN EPOCH OF REIONIZATION ARRAY DISH. I. BEAM PATTERN MEASUREMENTS AND SCIENCE IMPLICATIONS

The Hydrogen Epoch of Reionization Array (HERA) is a radio interferometer aiming to detect the power spectrum of 21 cm fluctuations from neutral hydrogen from the epoch of reionization (EOR). Drawing on lessons from the Murchison Widefield Array and the Precision Array for Probing the EOR, HERA is a hexagonal array of large (14 m diameter) dishes with suspended dipole feeds. The dish not only determines overall sensitivity, but also affects the observed frequency structure of foregrounds in the interferometer. This is the first of a series of four papers characterizing the frequency and angular response of the dish with simulations and measurements. In this paper, we focus on the angular response (i.e., power pattern), which sets the relative weighting between sky regions of high and low delay and thus apparent source frequency structure. We measure the angular response at 137 MHz using the ORBCOMM beam mapping system of Neben et al. We measure a collecting area of 93 m{sup 2} in the optimal dish/feed configuration, implying that HERA-320 should detect the EOR power spectrum at z ∼ 9 with a signal-to-noise ratio of 12.7 using a foreground avoidance approach with a single season of observations and 74.3 using a foreground subtraction approach. Finally, we study the impact of these beam measurements on the distribution of foregrounds in Fourier space.

79 ASTRONOMY AND ASTROPHYSICS↗