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NASA NTRS2018

Snow in the Changing Sea-Ice Systems

Snow is the most reflective, and also the most insulative, natural material on Earth. Consequently, it is an integral part of the sea-ice and climate systems. However, the spatial and temporal heterogeneities of snow pose challenges for observing, understanding and modelling those systems under anthropogenic warming. Here, we survey the snow-ice system, then provide recommendations for overcoming present challenges. These include: collecting process-oriented observations for model diagnostics and understanding snow-ice feedbacks, and improving our remote sensing capabilities of snow for monitoring large-scale changes in snow on sea ice. These efforts could be achieved through stronger coordination between the observational, remote sensing and modelling communities, and would pay dividends through distinct improvements in predictions of polar environments.

Snow↗

NASA NTRS1996

Optical Diagnostics of Solution Crystal Growth

Non-contact optical techniques such as, optical heterodyne, ellipsometry and interferometry, for real time in-situ monitoring of solution crystal growth are demonstrated. Optical heterodyne technique has the capability of measuring the growth rate as small as 1A/sec. In a typical Michelson interferometer set up, the crystal is illuminated by a Zeeman laser with frequency omega(sub 1) and the reference beam with frequency omega(sub 2). As the crystal grows, the phase of the rf signal changes with respect to the reference beam and this phase change is related to the crystal growth rate. This technique is demonstrated with two examples: (1) by measuring the copper tip expansion/shrinkage rate and (2) by measuring the crystal growth rate of L-Arginine Phosphate (LAP). The first test shows that the expansion/shrinkage rate of copper tip was fast in the beginning, and gets slower as the expansion begins to stabilize with time. In crystal growth, the phase change due the crystal growth is measured using a phase meter and a strip chart recorder. Our experimental results indicate a varied growth rate from 69.4 to 92.6A per sec. The ellipsometer is used to study the crystal growth interface. From these measurements and a theoretical modeling of the interface, the various optical parameters can be deduced. Interferometry can also be used to measure the growth rate and concentration gradient in the vicinity of the crystal.

Kim, Yongkee↗

NASA NTRSDate not supplied

Auroral ovals versus flare ribbons: Optical footprints of explosive magnetic field reconfiguration in Earth’s magnetosphere and the Sun’s corona

Despite drastically different plasma conditions in the two systems, eruptive energy release events in solar active regions and in Earth’s magnetosphere have a lot in common. Both solar active region eruptions and the substorm activity in the nightside magnetosphere are known to be associated with an abrupt large-scale reorganization of the supporting magnetic systems enabling the conversion and dissipation of the stored free magnetic energy. The rate of energy accumulation in either system tends to be by orders of magnitude slower than the energy release rate, leading to the formation of an impulsive loading-unloading cycle involving a relatively long pre-reconnection phase (substorm growth phase, pre-flare stressing of an active region magnetic field), a short and explosive reconnection phase (substorm breakup and expansion, eruptive flares and CMEs), and a prolonged post-reconnection phase (substorm recovery phase and the post-flare active region reconfiguration). In Earth’s magnetosphere, this loading-unloading cycle is diagnosed by monitoring characteristic changes in the particle precipitation pattern in the northern and southern auroral ovals marking the boundary between the open and close magnetic flux. The position, shape, structure, and dynamics of the auroral borealis were shown to communicate critically important information about an upcoming substorm, the location and timing of the initial reconnection onset, and the subsequent return of the magnetosphere to a lower-energy state. On the Sun, a similar role is played by the chromospheric flare ribbons which enable a detailed diagnostics of the overlying reconnecting magnetic field. In this talk, we’ll discuss similarities and differences in using auroral and flare ribbon observations for monitoring eruptive energy release in respectively Earth’s magnetosphere and solar corona. Special emphasis will be placed on the quantitative interpretation of the two types of optical signatures for empirical diagnostics of the underlying reconnection activity and for constraining its theoretical models. We’ll also compare forecasting capabilities of the two types of optical signatures in the context of space weather prediction objectives.

V. M. Uritskiy↗

NASA NTRS2015

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Gas Turbine Engines↗

NASA NTRS2016

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

Diagnosis↗

NASA NTRS1994

Mission Evaluation Room Intelligent Diagnostic and Analysis System (MIDAS)

The role of Mission Evaluation Room (MER) engineers is to provide engineering support during Space Shuttle missions, for Space Shuttle systems. These engineers are concerned with ensuring that the systems for which they are responsible function reliably, and as intended. The MER is a central facility from which engineers may work, in fulfilling this obligation. Engineers participate in real-time monitoring of shuttle telemetry data and provide a variety of analyses associated with the operation of the shuttle. The Johnson Space Center's Automation and Robotics Division is working to transfer advances in intelligent systems technology to NASA's operational environment. Specifically, the MER Intelligent Diagnostic and Analysis System (MIDAS) project provides MER engineers with software to assist them with monitoring, filtering and analyzing Shuttle telemetry data, during and after Shuttle missions. MIDAS off-loads to computers and software, the tasks of data gathering, filtering, and analysis, and provides the engineers with information which is in a more concise and usable form needed to support decision making and engineering evaluation. Engineers are then able to concentrate on more difficult problems as they arise. This paper describes some, but not all of the applications that have been developed for MER engineers, under the MIDAS Project. The sampling described herewith was selected to show the range of tasks that engineers must perform for mission support, and to show the various levels of automation that have been applied to assist their efforts.

Pack, Ginger L.↗

DOE OSTI2019

Optimization of switch diagnostics on the MAIZE linear transformer driver

The MAIZE Linear Transformer Driver is made of 40 capacitor-switch-capacitor `bricks' connected in parallel. When these 40 bricks are charged to 100-kV and then discharged synchronously, the MAIZE facility generates a 1-MA current pulse with a 100-ns rise time into a matched load impedance. Discharging each of the capacitors in a brick is carried out by the breakdown of a spark-gap switch, a process which results in the emission of light. Monitoring this output light with a fiber optic coupled to a photomultiplier tube (PMT) and an oscilloscope channel provides information on switch performance and timing jitter– whether a switch red early, late, or in phase with the other switches. However, monitoring each switch with a dedicated detector- oscilloscope channel can be problematic for facilities where the number of switches to be monitored (e.g., 40 on MAIZE) greatly exceeds the number of detector-oscilloscope channels available. The technique of using fibers to monitor light emission from switches can be optimized by treating a PMT as a binary digit or bit and using a combinatorial encoding scheme, where each switch is monitored by a unique combination of fiber- PMT-oscilloscope channels simultaneously. By observing the unique combination of ber-PMT-oscilloscope channels that are turned on, the pre-firing or late-firing of a single switch on MAIZE can be identified by as few as six PMT-oscilloscope channels. The number of PMT-oscilloscope channels, N , required to monitor X switches can be calculated by 2 N = X + 1, where the number '2' is selected because the PMT-oscilloscope acts as a bit. Here, we demonstrate the use of this diagnostic technique on MAIZE. In conclusion, we also present an analysis of how this technique could be scaled to monitor the tens of thousands of switches proposed for various next generation pulsed power facilities.

47 OTHER INSTRUMENTATION↗

NASA NTRSDate not supplied

Repurposing Drilling Control Diagnostics for Subsurface Edge Detection and Boundary Advisement During Planetary Drilling

Informed decision-making during lunar drilling and sampling missions will require data monitoring tools and specialized ground data systems. Accurate and updated situational awareness, with ongoing data monitoring, is critical for timely responses by to incoming science data. Traverse plans and scheduled activities may need to be flexibly changed in order to react to unexpected data or situations. Unlike (for example) Mars missions, the relative lightspeed closeness of the Moon allows for near-real-time ground processing of incoming mission and instrument data. An Apollo-class lunar regolith drill will in a sense “travel” a meter or two vertically at a given subsurface characterization site. As the drill penetrates into lunar regolith, it is likely to encounter a range of material densities, orientations, fracture toughness, and (perhaps) ice percentages. Lunar drill telemetry can provide science teams with a valuable first look into the subsurface structure, the regolith bulk properties, and constituents at each drilled site. Real-time AI-based recognition and reaction to downhole situations has been developed for automated deeper drilling on Mars and beyond. We can leverage the same knowledge bases and pattern-matching as areal-time interpreter of the subsurface, a situational awareness tool during drilling operations. We recently (Sept. 2019) demonstrated this AI drilling monitoring and analysis capability, in control of in-situ drilling and sampling operations, mounted on a KREX-2 rover in Chile’s Atacama Desert. Terrestrial automated drilling log analyses in oil exploration have used similar machine learning techniques in classifying and identifying features in drilling logs –but these typically are designed assuming a drilling fluid influencing downhole measurements and data (permeability, resistivity). Drilling models and existing AI software designed to detect and respond to drilling faults and hard materials can be repurposed, for near-real-time (ground-based) interpretation of drilling telemetry –a potentially valuable advisory tool for strata boundaries and changes in drilling parameters. On the Moon, this approach could be used to study the structure and to some extent the composition of lunar regolith vs. borehole depth, based on recognizable variations in fracture hardness, drilling energy and penetration rates while actively drilling. Since the early 2000s, a series of increasingly-capable real-time drilling telemetry interpretation and characterization software tools have been developed. These subsurface models and software tools have monitored the real-time drilling data received, and automatically identified changes in drill behavior (e.g., encountering a harder target layer, bit inclusions, drill choking due to infall downhole, and others) correlating these with subsurface structures and features. We discuss the mappings between drill borehole parameters, faults or events detected, and modeled changes in rock layer boundaries, in examples drawn from field testing at analog sites in an Arctic impact crater, Rio Tinto, and Chile’s Atacama Desert. These demonstrate how subsurface structural boundaries led to fault detections and responses by the software.

drilling advisor↗

NASA NTRS1964

Flight study of a vehicle operational status and monitoring system

An analog onboard monitoring system was installed on a YF-12 airplane as the first phase of a program to monitor the engine inlet and portions of the airplane's electrical and fuel management subsystems in flight. The system provided data which were considered to form a suitable base for diagnostic test logic and decision criteria for the rest of the program. The data were also adequate for the purpose of maintaining the engine inlet and identifying malfunctions within it. The investigation showed that the requirements of an onboard monitoring system should be considered during the original design of the system to be monitored.

Love, J. E.↗

DOE OSTI2021

Extremum Seeking-Based Control System for Particle Accelerator Beam Loss Minimization

Particle accelerators throughout the world vary widely in terms of age and availability of advanced noninvasive diagnostics that provide varying levels of detail about the accelerated beams. Additionally, beam loss measurements and current monitors are ubiquitous in the accelerator community, they are noninvasive, and they are some of the most important metrics in terms of preventing damage or irradiation of beam pipes and equipment for high-energy machines. However, beam loss and current measurements are difficult to use for feedback tuning because of a lack of a known analytic relationship between scalar loss measurements throughout an accelerator and the hundreds of thousands of parameters that influence the beam and time variation of the beam source itself. In this work, we present a model-independent extremum seeking (ES) controller, which has been implemented for automated tuning and optimization of the Los Alamos Neutron Science Center (LANSCE) linear ion accelerator based only on scalar quantities, such as beam loss or flux measurements. We demonstrate the approach on various accelerator subsystems, including groups of radio frequency (RF) accelerating cavities, quadrupole magnets, bending magnets, and steering magnets. This tool is now available as a use graphical user interface (GUI) in the LANSCE control room, allowing beam physicists to choose arbitrary groups of parameters and beam loss or current monitors for adaptive tuning.

43 PARTICLE ACCELERATORS↗

NASA NTRS1987

Knowledge based jet engine diagnostics

A fielded expert system automates equipment fault isolation and recommends corrective maintenance action for Air Force jet engines. The knowledge based diagnostics tool was developed as an expert system interface to the Comprehensive Engine Management System, Increment IV (CEMS IV), the standard Air Force base level maintenance decision support system. XMAM (trademark), the Expert Maintenance Tool, automates procedures for troubleshooting equipment faults, provides a facility for interactive user training, and fits within a diagnostics information feedback loop to improve the troubleshooting and equipment maintenance processes. The application of expert diagnostics to the Air Force A-10A aircraft TF-34 engine equipped with the Turbine Engine Monitoring System (TEMS) is presented.

Jellison, Timothy G.↗

NASA NTRS2000

Remote Diagnosis of the International Space Station Utilizing Telemetry Data

Modern systems such as fly-by-wire aircraft, nuclear power plants, manufacturing facilities, battlefields, etc., are all examples of highly connected network enabled systems. Many of these systems are also mission critical and need to be monitored round the clock. Such systems typically consist of embedded sensors in networked subsystems that can transmit data to central (or remote) monitoring stations. Moreover, many legacy are safety systems were originally not designed for real-time onboard diagnosis, but a critical and would benefit from such a solution. Embedding additional software or hardware in such systems is often considered too intrusive and introduces flight safety and validation concerns. Such systems can be equipped to transmit the sensor data to a remote-processing center for continuous health monitoring. At Qualtech Systems, we are developing a Remote Diagnosis Server (RDS) that can support multiple simultaneous diagnostic sessions from a variety of remote subsystems.

Deb, Somnath↗

DOE OSTI2023

Quantifying Burst Repeatability for Godiva IV

The minimum resolvable relative change in the neutron source emission of Godiva IV between bursts, i.e., burst repeatability, was quantified using a combination of activation monitors and a resistance temperature detector (RTD). Measurements support changes in the neutron source emission between bursts can be determined with a precision of 2.7%. The measurements were performed during a series of twelve Godiva IV bursts and were a collaborative effort between Los Alamos National Laboratory, Sandia National Laboratories, and Pacific Northwest National Laboratory. Gold, iron, nickel, and sulfur activation monitors were positioned in a sample holder in the central cavity of Godiva IV for each burst. The RTD is part of the Godiva burst diagnostic system and is in a fixed location in the safety block of Godiva IV. It is used to determine the temperature rise of the burst, i.e., the difference between the maximum temperature recorded during the burst and the initial temperature prior to the burst. Differences in either the specific activity of the activation monitor reactions, or the temperature rise can be used to determine the relative change in the neutron source emission for separate bursts, but historic results have proven that each method is susceptible to various sources of biases which generally cannot be isolated using a single method. We address this issue by applying both measurement methods and analyzing the correlation between them. The results presented in this work will be used to support future experiments with Godiva IV at the National Criticality Experiments Research Center (NCERC).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2004

Nanotube Activities at NASA-Johnson Space Center

Nanotube activities at NASA-Johnson Space Center include production, purification, characterization as well as applications of single wall carbon nanotubes (SWCNTs). A parametric study of the pulsed laser ablation process is recently completed to monitor the effect of production parameters including temperature, buffer gas, flow rate, pressure, and laser fluence. Enhancement of production is achieved by rastering the graphite target and by increasing the target surface temperature with a cw laser. In-situ diagnostics during production included time resolved passive emission and laser induced fluorescence from the plume. The improvement of the purity by a variety of steps in the purification process is monitored by characterization techniques including SEM, TEM, Raman, UV-VIS-NIR and TGA. A recently established NASA-JSC protocol for SWCNT characterization is undergoing revision with feedback from nanotube community. Efforts at JSC over the past five years in composites have centered on structural polymer/nanotube systems. Recent activities broadened this focus to multifunctional materials, supercapacitors, fuel cells, regenerable CO2 absorbers, electromagnetic shielding, radiation dosimetry and thermal management systems of interest for human space flight. Preliminary tests indicate improvement of performance in most of these applications because of the large Surface area as well as high electrical and thermal conductivity exhibited by SWCNTs. Comparison with existing technologies and possible future improvements in the SWCNT materials sill be presented.

Arepalli, Sivaram↗

DOE OSTI2021

Preprocessing for Unintended Conducted Emissions Classification with ResNet

Characterization of Unintended Conducted Emissions (UCE) from electronic devices is important when diagnosing electromagnetic interference, performing nonintrusive load monitoring (NILM) of power systems, and monitoring electronic device health, among other applications. Prior work has demonstrated that UCE analysis can serve as a diagnostic tool for energy efficiency investigations and detailed load analysis. While explaining the feature selection of deep networks with certainty is often not fully comprehensive, or in other applications, quite lacking, additional tools/methods for further corroboration and confirmation can help further the understanding of the researcher. This is true especially in the subject application of the study in this paper. Often the focus of such efforts is the selected features themselves, and there is not as much understanding gained about the noise in the collected data. If selected feature and noise characteristics are known, it can be used to further shape the design of the deep network or associated preprocessing. This is additionally difficult when the available data are limited, as in the case which the authors investigated in this study. Here, the authors present a novel work (which is a proposed complementary portion of the overall solution to the deep network classification explainability problem for this application) by applying a systematic progression of preprocessing and a deep neural network (ResNet architecture) to classify UCE data obtained via current transformers. By using a methodical application of preprocessing techniques prior to a deep classifier, hypotheses can be produced concerning what features the deep network deems important relative to what it perceives as noise. For instance, it is hypothesized in this particular study as a result of execution of the proposed method and periodic inspection of the classifier output that the UCE spectral features are relatively close to each other or to the interferers, as systematically reducing the beta parameter of the Kaiser window produced progressively better classification performance, but only to a point, as going below the Beta of eight produced decreased classifier performance, as well as the hypothesis that further spectral feature resolution was not as important to the classifier as rejection of the leakage from a spectrally distant interference. This can be very important in unpredictable low-FNR applications, where knowing the difference between features and noise is difficult. As a side-benefit, much was learned regarding the best preprocessing to use with the selected deep network for the UCE collected from these low power consumer devices obtained via current transformers. Baseline rectangular windowed FFT preprocessing provided a 62% classification increase versus using raw samples. After performing a more optimal preprocessing, more than 90% classification accuracy was achieved across 18 low-power consumer devices for scenarios in which the in-band features-to-noise ratio (FNR) was very poor.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2004

Concept for Inclusion of Analytical and Computational Capability in Optical Plume Anomaly Detection (OPAD) for Measurement of Neutron Flux

Researchers are working on many konts to make possible high speed, automated classification and quantification of constituent materials in numerous environments. NASA's Marshall Space Flight Center has implemented a system for rocket engine flow fields/plumes; the Optical Plume Anomaly Detection (OPAD) system was designed to utilize emission and absorption spectroscopy for monitoring molecular and atomic particulates in gas plasma. An accompanying suite of tools and analytical package designed to utilize information collected by OPAD is known as the Engine Diagnostic Filtering System (EDIFIS). The current combination of these systems identifies atomic and molecular species and quantifies mass loss rates in H2/O2 rocket plumes. Additionally, efforts are being advanced to hardware encode components of the EDIFIS in order to address real-time operational requirements for health monitoring and management. This paper addresses the OPAD with its tool suite, and discusses what is considered a natural progression: a concept for migrating OPAD towards detection of high energy particles, including neutrons and gamma rays. The integration of these tools and capabilities will provide NASA with a systematic approach to monitor space vehicle internal and external environment.

Patrick, M. Clinton↗

DOE OSTI2021

High-Resolution 3D Acoustic Borehole Integrity Monitoring (Research Performance Progress Report Q2 2021)

Real-time, in-situ, high spatial resolution (sub-cm) imaging of the near-borehole environment would revolutionize wellbore diagnostics and integrity assessment by direct observation of defects. It is becoming increasingly apparent, that better understanding of the near-wellbore environment is required to meet the safety and operational needs in challenging environments such as those present in subsurface energy extraction (geothermal) and storage (CO2 sequestration) applications. Therefore, it is important to have a more robust ability to image the near-borehole and reliably detect defects. It was proposed to further develop and improve our advanced 3D imaging system to evaluate casing defects (e.g. corrosion) and cement quality in either open- or cased-borehole with the ultimate goal to develop a commercially deployable technology. The system consists of a unique acoustic source (LANL) and advanced inversion techniques for image processing (LANL, ORNL). This system will provide comprehensive borehole integrity monitoring with improved resolution over existing techniques. As an application of this imaging system, we will characterize the effectiveness of next-generation wellbore completion technology (NETL, SNL), and will demonstrate that, unlike current technology, the proposed approach can successfully characterize foamed cements.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Observation and characterisation of trapped electron modes in Wendelstein 7-X

In the past, quasi coherent (QC) modes were reported for nearly all tokamaks. The general definition describes modes as QC when the magnitude squared coherence is in the range of 0.3 to 0.6. QC modes are observed in the plasma core as well as in the plasma edge and can have quite different physical origins. The one in the core are observed in plasmas with low collisionality, where the electron temperature exceeds the ion temperature in the plasma core. This is the case for electron cyclotron heating in general. The origin of these modes are electrons trapped within a magnetic mirror, as reported in the past from various fusion devices. The so-called trapped-electron modes (TEMs) belong to drift wave instabilities and can be destabilized by electron-temperature gradients in the plasma core. From the diagnostic point of view, QC modes appear as fluctuations in electron density and temperature. Therefore, the microwave reflectometer is very well suited to monitor these modes. This paper describes experiments, conducted at the Wendelstein 7-X stellarator (W7-X), which aim at detecting QC modes at low wave numbers. A poloidal correlation reflectometer installed at W7-X, is able to measure low wave numbers ($k_\perp\unicode{x2A7D}{3.5}\,\textrm{cm}^{-1}$). For medium line-averaged densities ($\int n_\textrm{e}\unicode{x2A7D}{6 \times10^{19}}\,\textrm{m}^{-2}$) the plasma core is accessible for this diagnostic. For different magnetic configurations and plasma parameters, broad QC structures are observed in the coherence spectra. From the analysis of the rotation and the poloidal structure, these QC modes show the properties of electron-temperature-gradient driven TEMs. A linear relation between the mode velocity and the rotation frequency is found. The relation is uniform and confirms the nature of QC-mode observation as TEM in tokamaks, too.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗