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NASA NTRS2008

Problem Reporting System

The Problem Reporting System (PRS) is a Web application, running on two Web servers (load-balanced) and two database servers (RAID-5), which establishes a system for submission, editing, and sharing of reports to manage risk assessment of anomalies identified in NASA's flight projects. PRS consolidates diverse anomaly-reporting systems, maintains a rich database set, and incorporates a robust engine, which allows tracking of any hardware, software, or paper process by configuring an appropriate life cycle. Global and specific project administration and setup tools allow lifecycle tailoring, along with customizable controls for user, e-mail, notifications, and more. PRS is accessible via the World Wide Web for authorized user at most any location. Upon successful log-in, the user receives a customizable window, which displays time-critical 'To Do' items (anomalies requiring the user s input before the system moves the anomaly to the next phase of the lifecycle), anomalies originated by the user, anomalies the user has addressed, and custom queries that can be saved for future use. Access controls exist depending on a user's role as system administrator, project administrator, user, or developer, and then, further by association with user, project, subsystem, company, or item with provisions for business-to-business exclusions, limitations on access according to the covert or overt nature of a given project, all with multiple layers of filtration, as needed. Reporting of metrics is built in. There is a provision for proxy access (in which the user may choose to grant one or more other users to view screens and perform actions as though they were the user, during any part of a tracking life cycle - especially useful during tight build schedules and vacations to keep things moving). The system also provides users the ability to have an anomaly link to or notify other systems, including QA Inspection Reports, Safety, GIDEP (Government-Industry Data Exchange Program) Alert, Corrective Actions, and Lessons Learned. The PRS tracking engine was designed as a very extensible and scalable system, able to support additional applications, with future development possibilities already discussed, including Incident Surprise Anomalies (for anomalies occurring during Operations phases of NASA Flight projects), GIDEP and NASA Alerts, and others.

Potter, Don↗

NASA NTRS2020

MSL Telecom Automated Anomaly Detection

The Mars Science Laboratory (MSL) Telecom Operations Team at the Jet Propulsion Laboratory (JPL) has implemented a machine learning system in order to automate the anomaly detection process as a part of daily operations. Machine learning enables reliable detection of anomalies in Telecom-related telemetry and automated reporting of Telecom subsystem status, resulting in an 90% reduction in team workload and improved anomaly detection reliability. At present, machine learning methods are used to detect: 1. Anomalous long-term trends in telemetry data 2. Anomalous time-domain evolution of telemetry values Both types of anomalies pose their own unique challenges that are addressed in different ways. In the first case, long term trending of daily minima, maximum, and mean telemetry values in temperatures, currents, voltages, and radio frequency (RF) power levels is used in addition to hard threshold safety checks to look for changes in long-term equipment health and performance. Long-term trending methods allow for ordinary seasonal variations in these quantities caused by temperature changes over the course of the Martian year while allowing operators to determine whether current performance remains in line with historical values from previous years. Changes in long-term trends can provide important insights into the health and status of the rover's on-board systems as well as valuable early warning if subtle degradation begins to take hold. But while trending of daily statistics is valuable, it does not detect anomalies in the short-term time evolution of data over the course of minutes or hours during a day, and this task is handled with short-term shape analysis. Principal components analysis (PCA) has been found to provide robust detection of short-term anomalies, and several examples of the use of PCA to detect actual anomalous events will be provided here. In using PCA, we use both the percentage of explained variance and also a log likelihood test on the PCA expansion coefficients to flag telemetry data for human review. Previous work in the field of spacecraft anomaly detection includes [1] for MSL and [2] for some other JPL missions.

Mukai, Ryan↗

DOE OSTI2021

Investigation of Scale-Dependent Groundwater/Surface-water Exchange in Rivers by Gradient Self-Potential Logging: Numerical Modeling and Field Experiments

Exchanges of groundwater and surface-water are fundamental to a wide range of water-supply and water-quality management issues but challenging to map beyond the reach scale. Waterborne gradient self-potential (SP) measurements are directly sensitive to water flow through riverbed sediments and can be used to infer exchange locations, direction (gain versus loss), scale, and relative changes, but to date applications to river corridor hydrology are limited. Numerical modeling and field experiments were therefore performed herein, each emphasizing waterborne gradient SP logging for identifying and locating focused vertical groundwater discharge (surface-water gain) and recharge (surface-water loss) in a river. Two and three-dimensional numerical models were constructed to simulate the polarities, appearances, and peak amplitudes of streaming-potential and electric-field anomalies on a riverbed and in the surface-water that were attributable to steady-state vertical fluxes of groundwater through high-permeability conduits in the riverbed. Effects of varied hydraulic length-scale of exchange and surface-water depth were tested through numerical modeling. Modeling results aided in data acquisition and interpretation for three repeated field experiments performed along a 1.5–2.0 km reach of the Quashnet River in Cape Cod, Massachusetts, where focused, meter-scale groundwater discharges occur at discrete locations within otherwise ubiquitous and more diffuse groundwater upwelling conditions. Strong gradient SP anomalies were repeatedly measured in the Quashnet River at previously confirmed locations of focused groundwater discharge, showing the efficacy of waterborne gradient SP logging in identifying and characterizing groundwater/surface water exchange dynamics at multiple river network scales.

Engineering↗

NASA NTRS2015

Groundwater Variability Across Temporal and Spatial Scales in the Central and Northeastern U.S.

Depth-to-water measurements from 181 monitoring wells in unconfined or semi-confined aquifers in nine regions of the central and northeastern U.S. were analyzed. Groundwater storage exhibited strong seasonal variations in all regions, with peaks in spring and lows in autumn, and its interannual variability was nearly unbounded, such that the impacts of droughts, floods, and excessive pumping could persist for many years. We found that the spatial variability of groundwater storage anomalies (deviations from the long term mean) increases as a power function of extent scale (square root of area). That relationship, which is linear on a log-log graph, is common to other hydrological variables but had never before been shown with groundwater data. We describe how the derived power function can be used to determine the number of wells needed to estimate regional mean groundwater storage anomalies with a desired level of accuracy, or to assess uncertainty in regional mean estimates from a set number of observations. We found that the spatial variability of groundwater storage anomalies within a region often increases with the absolute value of the regional mean anomaly, the opposite of the relationship between soil moisture spatial variability and mean. Recharge (drainage from the lowest model soil layer) simulated by the Variable Infiltration Capacity (VIC) model was compatible with observed monthly groundwater storage anomalies and month-to-month changes in groundwater storage.

Groundwater↗

NASA NTRS2015

Groundwater Variability Across Temporal and Spatial Scales in the Central and Northeastern U.S.

water cycle↗

DOE OSTI2021

HP in Cybersecurity: CyOTE

The U.S. Department of Energy’s (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER), through the Cybersecurity for the Operational Technology Environment (CyOTE) Program, worked with energy sector asset owners and operators (AOOs), partners, and Idaho National Laboratory (INL) to develop capabilities for AOOs to independently detect adversarial tactics, techniques, and procedures (TTPs) within their operational technology (OT) environments. Unlike the approach taken with commercial security solutions, CyOTE seeks to tie anomalies in cyber operations to a cyber-attack. By stringing together multiple techniques in the OT environment, AOOs can identify attack campaigns with ever decreasing impacts. The CyOTE methodology applies fundamental concepts of perception and comprehension to a universe of knowns and unknowns increasingly disaggregated into observables, anomalies, and triggering events. MITRE’s ATT&CK® Framework for Industrial Control Systems (ICS) is used as a common lexicon to identify a set of triggering events related to three Use Cases – Alarm Logs, Human-Machine Interface (HMI), and Remote Logins – which together account for 87 percent of the techniques commonly used by adversaries. The CyOTE methodology is also appropriate for OT-related anomalies perceived outside the three Use Cases, such as through the energy system itself.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

IViz-OT (Intrusion Detection Visualizer for Operational Technology Network) [SWR-22-63]

The Visualizer dashboard provides grid operator highly-trusted alarming environment for an ongoing or potential cyber-attack based on system anomalies and network-based verification. Once anomalies are detected by the IDS tool (HIDES, NREL SWR-19-65), this platform stores the signatures or alert logs that are generated by the intrusion detector, lays out the detailed summary of the possible alerts, and maps these attacks with high-level scenarios. These scenarios are later combined to define a final event using a decision tree approach and a final report is generated out of this tool for further forensic analysis. It also supports authentication and authorization to support roles-based access control (RBAC) for users and a group of people.

Singh, Vivek Kumar↗

NASA NTRS1992

Determination of nitrogen to carbon abundance ratios from transition layer emission lines

We have finished studying the nitrogen to carbon abundance ratios for stars with different effective temperatures T(sub eff) and luminosities using transition layer emission lines and using spectra available in the IUE archives. The N/C abundance ratio determinations using transition layer emission lines are as accurate as the photospheric abundance determinations as found by comparison of results obtained by both methods for the same stars. Our measurements confirm photospheric abundance determinations in regions of the HR diagram where they can be obtained. Our studies have extended the temperature range to higher temperatures. They have shown the exact positions in the HR diagram where the mixing due to the outer convection zones reaches deep enough to bring nuclear processed material to the surface. This occurs at effective temperatures which are higher by delta log T(sub eff) approximately 0.04 or roughly 400 K than expected theoretically. Since the depth of the convection zone increases rapidly with decreasing T(sub eff) this may indicate considerable overshoot beyond the lower boundary of the convection zone. Our N/C abundance ratio determinations from transition layer emission lines have confirmed that the actual enrichment observed for some cool giants is larger than expected theoretically, again indicating a larger degree of mixing in several stars either from below or from above. For the supergiants it probably indicates overshoot above the convective core in the progenitor main sequence stars. For the more massive giants this may also be the case, though we did not find a correlation between delta log N/C and the absolute magnitudes, but these are rather uncertain. As byproducts of these studies we also found anomalies in Si/C and N/C abundance ratios for F giants which can be understood as the relict of surface abundance changes for their main sequence progenitors due to diffusion. This anomaly disappears for G giants, for which the depths of the convection zones are apparently deep enough to wipe out these element separations (Bohm-Vitense 1992).

Boehm-Vitense, Erika↗

DOE OSTI2021

Phasor-Measurement-Unit-Based Data Analytics Using Digital Twin and PhasorAnalytics Software

A major objective of this project was to apply GE’s commercial machine learning and data analytics toolsets to large-scale, real-world, anonymized Phasor Measurement Unit (PMU) datasets in order to extract signatures, correlated and/or causal factors, and precursor patterns associated with significant power system phenomena. The project had a particular emphasis on extraction of insights relevant to asset health monitoring, real-time load modeling and cybersecurity monitoring. Additionally, the team was directed to undertake a comprehensive data quality analysis for the provided datasets and encouraged to estimate the ‘machine-learning readiness’ of the datasets by documenting any major obstacles to the application of commercial machine learning algorithms. To accomplish the aforementioned objectives, the project team’s work centered around the identification of key event signatures and application of the identified event signatures for event detection and event classification. The industry-validated, semi-supervised machine learning strategy employed for event signature identification involved several major tasks, including data-preprocessing, generation of an overabundance of features, normal data identification, normality modeling, and event signature identification through a methodical, quantitative ranking of features in order of relevance to each studied event type. Throughout the project, data quality issues and mitigation techniques were investigated. In this report, insights are provided regarding the readiness of the provided synchrophasor datasets for application of machine learning and data analytics. The methodologies employed for this technical strategy are summarized in this report. With regards to data preprocessing and feature generation, the provided Training and Test Datasets were ingested into GE’s big data environment. Subsequently, the team applied bad data cleansing and data imputation scripts, event detection scripts, and application programming interfaces (APIs) to the datasets for convenient data access. The project team completed development and validation of dozens of physics-based, statistics-based and transformation-based feature functions used for the extraction of over 60 synchrophasor features. Using a new parallel feature generation technology developed on this project, over 60 features have been rapidly generated for the full two years’ worth of Training and Test Dataset data associated with both the Eastern and Western interconnects. Even accommodating for temporal down-sampling inherent to the feature extraction procedure, this parallel feature generation activity resulted in a massive feature set with a storage requirement approximately equal to that of the raw training dataset itself. With regards to normal data identification and normality modeling, a normality model was built using the feature data extracted from the Training Dataset and iteratively refined subsequent to incremental adjustments and expansions of the Training Dataset feature data. With respect to event characterization and signature identification, an event signature identification pipeline was developed and used in conjunction with the normality model to identify over 15 event signatures for key event categories within the Training Dataset. The identified event signatures were used to characterize hundreds of key events in terms of relative severity, duration, and location of the event. An investigation was undertaken to identify correlated and causal factors involved in transformer events. A separate investigation into temporal trends in ring-down analysis results was undertaken to determine possible associations between system dynamics and various other factors such as loading, season or year. To validate the identified event signatures, additional work was undertaken to develop signature-based anomaly detection and classification tools suitable for convenient application to the synchrophasor datasets. The anomaly detection and classification tools, suitable for online application, were then applied to the entirety of the Eastern Interconnect Training and Test Datasets. Performance of the event detection and classification tools was evaluated upon receipt of the Test Dataset event logs (i.e., the labels for events contained in the Test Dataset), and promising results were obtained despite several challenges (documented herein) associated with application of supervised or semi-supervised machine learning methods to large-scale, anonymized datasets. Finally, the detection and classification tools were used to detect, classify, and characterize thousands of new events not included in the original event logs provided by the DOE within both the Training and Test Datasets.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Anomaly Detection in Liquid Sodium Cold Trap Operation with Multisensory Data Fusion Using Long Short-Term Memory Autoencoder

Sodium-cooled fast reactors (SFR), which use high temperature fluid near ambient pressure as coolant, are one of the most promising types of GEN IV reactors. One of the unique challenges of SFR operation is purification of high temperature liquid sodium with a cold trap to prevent corrosion and obstructing small orifices. We have developed a deep learning long short-term memory (LSTM) autoencoder for continuous monitoring of a cold trap and detection of operational anomaly. Transient data were obtained from the Mechanisms Engineering Test Loop (METL) liquid sodium facility at Argonne National Laboratory. The cold trap purification at METL is monitored with 31 variables, which are sensors measuring fluid temperatures, pressures and flow rates, and controller signals. Loss-of-coolant type anomaly in the cold trap operation was generated by temporarily choking one of the blowers, which resulted in temperature and flow rate spikes. The input layer of the autoencoder consisted of all the variables involved in monitoring the cold trap. The LSTM autoencoder was trained on the data corresponding to cold trap startup and normal operation regime, with the loss function calculated as the mean absolute error (MAE). The loss during training was determined to follow log-normal density distribution. During monitoring, we investigated a performance of the LSTM autoencoder for different loss threshold values, set at a progressively increasing number of standard deviations from the mean. The anomaly signal in the data was gradually attenuated, while preserving the noise of the original time series, so that the signal-to-noise ratio (SNR) averaged across all sensors decreased below unity. Results demonstrate detection of anomalies with sensor-averaged SNR < 1.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1983

Possible evidence for the driving of the winds of hot stars by Alfven waves

Ultraviolet spectra of the supergiants Alpha Cam (09.5 Ia), HD 105056 (ON9.7 Iae), and 15 Sgr (O9.7 Iab) are compared, and it is shown that the terminal outflow velocity, TOV, of HD 105056 is one-half that of the other two stars even though HD 105056 has the highest effective temperature of the three stars. This anomaly, together with the fact that the observed TOV values for early-type stars scatter about an empirical correlation between TOV and log T(eff) by an amount which is larger than the amount expected according to the observational errors in determining TOV and log T(eff), leads to the conclusion that an agent in addition to radiation, Alfven waves, is driving the winds of early-type stars.

Underhill, A. B.↗

NASA NTRS1992

Tethered Satellite System Contingency Investigation Board

The Tethered Satellite System (TSS-1) was launched aboard the Space Shuttle Atlantis (STS-46) on July 31, 1992. During the attempted on-orbit operations, the Tethered Satellite System failed to deploy successfully beyond 256 meters. The satellite was retrieved successfully and was returned on August 6, 1992. The National Aeronautics and Space Administration (NASA) Associate Administrator for Space Flight formed the Tethered Satellite System (TSS-1) Contingency Investigation Board on August 12, 1992. The TSS-1 Contingency Investigation Board was asked to review the anomalies which occurred, to determine the probable cause, and to recommend corrective measures to prevent recurrence. The board was supported by the TSS Systems Working group as identified in MSFC-TSS-11-90, 'Tethered Satellite System (TSS) Contingency Plan'. The board identified five anomalies for investigation: initial failure to retract the U2 umbilical; initial failure to flyaway; unplanned tether deployment stop at 179 meters; unplanned tether deployment stop at 256 meters; and failure to move tether in either direction at 224 meters. Initial observations of the returned flight hardware revealed evidence of mechanical interference by a bolt with the level wind mechanism travel as well as a helical shaped wrap of tether which indicated that the tether had been unwound from the reel beyond the travel by the level wind mechanism. Examination of the detailed mission events from flight data and mission logs related to the initial failure to flyaway and the failure to move in either direction at 224 meters, together with known preflight concerns regarding slack tether, focused the assessment of these anomalies on the upper tether control mechanism. After the second meeting, the board requested the working group to complete and validate a detailed integrated mission sequence to focus the fault tree analysis on a stuck U2 umbilical, level wind mechanical interference, and slack tether in upper tether control mechanism and to prepare a detailed plan for hardware inspection, test, and analysis including any appropriate hardware disassembly.

Source record↗

NASA NTRS2008

"Built-In" Action/Issues Tracking and Post-Ops Analysis Tool for Realtime Console Operations

Marshall Space Flight Center's (MSFC) Payload Operations Integration Center (POIC) for the International Space Station (ISS) uses a number of formal databases to manage and track flight plan changes, onboard and ground equipment anomalies, and other events. However, individual console positions encounter many action items and/or occurrences that don't fit neatly into the databases, and while console logs are comprehensive, manual or automated searches do not always yield consistent results. The Payload Communications Manager (PAYCOM) team, whose members speak directly with the ISS onboard crew with respect to NASA payload operations, has found a creative way to reformat a mandatory Daily Report to organize action items, standing reminders, significant events, and other comments. While the report keeps others appraised of PAYCOMs activities and issues of the moment, the format makes it easy to capture very brief summaries of the items in a "Roll Off Matrix", including start and stop dates, resolution, and possible applicability to future ops. The matrix provides accountability for all action items, gives direct insight into the issues surrounding various payloads and methods of dealing with them, yields indirect information on PAYCOM priorities and processes, and provides a roadmap that makes it easier to get back to extensive details if needed. This paper describes how the ISS PAYCOM Daily Report and Roll Off Matrix are organized, used, and inter-related to each other and the PAYCOM operations log. While the application is for a manned vehicle, the concepts could apply in a wide spectrum of operational settings.

Scott, David W.↗

NASA NTRSDate not supplied

Detecting Satellite Laser Ranging Station Data and Operational Anomalies with Machine Learning Isolation Forests at NASA's CDDIS

The International Laser Ranging Service (ILRS) is currently composed of 45 active satellite laser ranging (SLR) stations with several more set to join the network over the next several years. Station changes and histories are logged to files, but not always in real time. Sometimes these details are not added until long after changes have been made to the station –on occasion, years later. This in addition to unexpected hardware errors and other system issues that are not immediately detected impact the products generated by analysts. The ILRS Central Bureau (CB) and NASA’s Crustal Dynamics Data Information System (CDDIS) have worked to provide tools for station engineers to use. This includes the creation of station plots which contain temperature and pressure information along with LAser GEOdynamic Satellite (LAGEOS) and LAser RElativity Satellite (LARES) tracking information that enable the monitoring of station performance and todetermine whether the station has undergone any changes. As next steps, the CDDIS is working to enhance these station performance monitoring tools through machine learning. Isolation forest is an unsupervised machine learning algorithm commonly applied to anomaly detection. In this poster, the CDDIS details the steps taken to track anomalies within SLR station performance using isolation forest with LAGEOS and LARES satellite data.

Benjamin P Michael↗

NASA NTRS1985

HD 160538 and HD 185510 - Two active-chromosphere stars with hot companions

Short-wavelength ultraviolet spectra of two active-chromosphere giants, HD 160538 and HD 185510, show hot stellar continua and L-alpha absorption features. The hot companion of HD 160538 is a white dwarf whose ultraviolet spectrum is matched best to the energy distribution of a T(eff) = 30,000 K and log g = 8 model atmosphere. The ultraviolet spectrum of HD 185510 shows numerous absorption features and is identified as a B subdwarf. Since the giant star of each of these binary systems has no known abundance anomalies, these systems appear to be consistent with the mass-transfer scenario of barium-star formation.

Fekel, F. X.↗

NASA NTRS2010

Resolving the xi Boo Binary with Chandra, and Revealing the Spectral Type Dependence of the Coronal "Fip Effect"

On 2008 May 2, Chandra observed the X-ray spectrum of xi Boo (G8 V+K4 V), resolving the binary for the first time in X-rays and allowing the coronae of the two stars to be studied separately. With the contributions of ξ Boo A and B to the system's total X-ray emission now observationally established (88.5% and 11.5% respectively), consideration of mass loss measurements for GK dwarfs of various activity levels (including one for xi Boo) leads to the surprising conclusion that xi Boo B may dominate the wind from the binary, with xi Boo A's wind being very weak despite its active corona. Emission measure (EM) distributions and coronal abundances are computed for both stars and compared with Chandra measurements of other moderately active stars with G8-K5 spectral types, all of which exhibit a narrow peak in EM near log T = 6.6, indicating that the coronal heating process in these stars has a strong preference for this temperature. As is the case for the Sun and many other stars, our sample of stars shows coronal abundance anomalies dependent on the first ionization potential (FIP) of the element. We see no dependence of the degree of FIP effect on activity, but there is a dependence on spectral type, a correlation that becomes more convincing when moderately active main-sequence stars with a broader range of spectral types are considered. This clear dependence of coronal abundances on spectral type weakens if the stellar sample is allowed to be contaminated by evolved stars, interacting binaries or extremely active stars with logLX 29, explaining why this correlation has not been recognized in the past.

CHANDRA↗

NASA NTRS1997

The Cretaceous-Tertiary Impact Crater and the Cosmic Projectile that Produced it

Evidence gathered to date from topographic data, geophysical data, well logs, and drill-core samples indicates that the buried Chicxulub basin, the source crater for the approximately 65 Ma Cretaceous-Tertiary (K/T) boundary deposits, is approximately 300 km in diameter. A prominent topographic ridge and a ring of gravity anomalies mark the position of the basin rim at approximately 150 km from the center. Wells in this region recovered thick sequences of impact-generated breccias at 200-300 m below present sea level. Inside the rim, which has been severely modified by erosion following impact, the subsurface basin continues to deepen until near the center it is approximately 1 km deep. The best planetary analog for this crater appears to be the 270 km-diameter Mead basin on Venus. Seismic reflection data indicate that the central zone of downward displacement and excavation (the transient crater is approximately 130 km in diameter, consistent with previous studies of gravity anomaly data). Our analysis of projectile characteristics utilizes this information, coupled with conventional scaling relationships, and geochemical constraints on the mass of extraterrestrial material deposited within the K/T boundary layer. Results indicate that the Chicxulub crater would most likely be formed by a long-period comet composed primarily of nonsilicate materials (ice, hydrocarbons, etc.) and subordinate amounts (less than or equal to 50 percent) primitive chondritic material. This collision would have released the energy equivalent to between 4 x 10(exp 8) and 4 x 10(exp 9) megatons of TNT. Studies of terrestrial impact rates suggest that such an event would have a mean production rate of approximately 1.25 x 10(exp -9) y(exp -1). This rate is considerably lower than that of the major mass extinctions over the last 250 million years (approximately 5 x 10(exp -7) y(exp -1). Consequently, while there is substantial circumstantial evidence establishing the cause-effect link between the Chicxulub basin forming event and the K/T biological extinctions, the results of our analysis do not support models of impact as a common or singular causative agent of mass extinctions on Earth.

Sharpton, Virgil L.↗

NASA NTRS1990

Orbital transfer vehicle oxygen turbopump technology. Volume 2: Nitrogen and ambient oxygen testing

The testing of a rocket engine oxygen turbopump using high pressure ambient temperature nitrogen and oxygen as the turbine drive gas in separate test series is discussed. The pumped fluid was liquid nitrogen or liquid oxygen. The turbopump (TPA) is designed to operate with 400 F oxygen turbine drive gas which will be demonstrated in a subsequent test series. Following bearing tests, the TPA was finish machined (impeller blading and inlet/outlet ports). Testing started on 15 February 1989 and was successfully concluded on 21 March 1989. Testing started using nitrogen to reduce the ignition hazard during initial TPA checkout. The Hydrostatic Bearing System requires a Bearing Pressurization System. Initial testing used a separate bearing supply to prevent a rubbing start. Two test series were successfully completed with the bearing assist supplied only by the pump second stage output which entailed a rubbing start until pump pressure builds up. The final test series used ambient oxygen drive and no external bearing assist. Total operating time was 2268 seconds. There were 14 starts without bearing assist and operating speeds up to 80,000 rpm were logged. Teardown examination showed some smearing of silverplated bearing surfaces but no exposure of the underlying monel material. There was no evidence of melting or oxidation due to the oxygen exposure. The articulating, self-centering hydrostatic bearing exhibited no bearing load or stability problems. The only anomaly was higher than predicted flow losses which were attributed to a faulty ring seal. The TPA will be refurbished prior to the 400 F oxygen test series but its condition is acceptable, as is, for continued operating. This was a highly successful test program.

Brannam, R. J.↗