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NASA NTRS2015

Wilson Corners SWMU 001 2014 Annual Long Term Monitoring Report Kennedy Space Center, Florida

This document presents the findings of the 2014 Long Term Monitoring (LTM) that was completed at the Wilson Corners site, located at the National Aeronautics and Space Administration (NASA) John F. Kennedy Space Center (KSC), Florida. The goals of the 2014 annual LTM event were to evaluate the groundwater flow direction and gradient and to monitor the vertical and downgradient horizontal extent of the volatile organic compounds (VOCs) in groundwater at the site. The LTM activities consisted of an annual groundwater sampling event in December 2014, which included the collection of water levels from the LTM wells. During the annual groundwater sampling event, depth to groundwater was measured and VOC samples were collected using passive diffusion bags (PDBs) from 30 monitoring wells. In addition to the LTM sampling, additional assessment sampling was performed at the site using low-flow techniques based on previous LTM results and assessment activities. Assessment of monitoring well MW0052DD was performed by collecting VOC samples using low-flow techniques before and after purging 100 gallons from the well. Monitoring well MW0064 was sampled to supplement shallow VOC data north of Hot Spot 2 and east of Hot Spot 4. Monitoring well MW0089 was sampled due to its proximity to MW0090. MW0090 is screened in a deeper interval and had an unexpected detection of trichloroethene (TCE) during the 2013 LTM, which was corroborated during the March 2014 verification sampling. Monitoring well MW0130 was sampled to provide additional VOC data beneath the semi-confining clay layer in the Hot Spot 2 area.

Monitoring↗

NASA NTRSDate not supplied

Training Airline Pilots for Improved Flight Path Monitoring: The Sensemaking Model Framework

The importance and benefit of improved monitoring is increasingly recognized. Improved training may be a valuable intervention. Our study (conducted 2019) assessed and trained airline First Officers on flight path monitoring skills. The exploratory study assessed monitoring pre-training in a simulator session that included monitoring challenges (8 or 7 events). A 1-hour interactive training followed, based on the Sensemaking Model of Monitoring; it presented concepts and examples using a slide deck, discussion, and simple activities. Post-training assessment used scenarios with analogous monitoring challenges (7 or 8 events) but a different setting. Performance showed significant and relatively consistent improvement. Training monitoring as sensemaking merits further investigation.

training↗

NASA NTRSDate not supplied

Eye-Tracking Analysis from a Flight-Director-Use and Pilot-Monitoring Study

Eye tracking may be a useful tool to investigate pilot monitoring and develop and conduct training. There is increased interest from airlines to use eye-tracking technologies in flight simulators. However, much is still unknown about how to best utilize eye-tracking data in pilot training. This paper presents eye-tracking results from a pilot-monitoring training study with 19 pilots. All pilots completed 15 monitoring challenges across four operational scenarios in a B737-700 full flight simulator. In addition, the study investigated the impact of having the flight director engaged or disengaged on the pilot monitoring side in the final approach. It was hypothesized that pilots would focus less on the primary flight display with the flight director off and look more around in the cockpit. To assess this, pilots performed half of the scenarios with the flight director on and half with the flight director off. However, pilots monitoring tended to look less at the primary flight display with the flight director on as indicated by lower Proportion Dwell Times, contrary to the hypothesis. Next, eye-tracking data were analyzed from two monitoring challenges involving waypoint restrictions and two involving extending the flaps at appropriate airspeeds. Pilots that successfully completed the challenges appeared to focus more on areas of interest that contained the most relevant information to successfully complete the challenge. In addition, successful pilots seemed to adapt their monitoring strategy more to the challenge at hand as observed by a distinct shift in focus on either the primary flight display or the navigation display depending on the challenge. Our findings suggest the importance of flexible gaze allocation across specific situations and raise the question whether and to what degree prespecified patterns of eye fixation can be identified and trained.

eye tracking↗

NASA NTRSDate not supplied

Eye-Tracking Analysis from a Flight-Director-Use and Pilot-Monitoring Study

eye tracking↗

NASA NTRS2021

General Services Administration Reclamation Yard (SWMU 010) 2020-2021 Groundwater Monitoring Report

This report presents a summary of the groundwater monitoring activities that occurred from October 2020 through June 2021 at General Services Administration Reclamation Yard, Solid Waste Management Unit 010, located at the John F. Kennedy Space Center (KSC), Florida. For the purposes of this report, two separate plumes, known as the Polychlorinated Biphenyl (PCB)/Volatile Organic Aromatic (VOA) Plume and the Chlorinated Volatile Organic Compound (VOC) Plume were identified for this site. The contaminants of concern (COCs) for the PCB/VOA Plume consists of PCBs, 1,2,4-trichlorobenzene, and breakdown products of 1,2,4-trichlorobenzene. The COCs for the Chlorinated VOC Plume are tetrachloroethene, trichloroethene, cis-1,2-dichloroethene, and vinyl chloride. The activities presented in this report include four field events: (1) October 2020 – Chlorinated VOC Plume groundwater sampling via Direct Push Technology (DPT) – 68 groundwater samples were collected from 14 locations at varying intervals; (2) December 2020 – Site-wide semi-annual water level measurements of 52 monitoring wells and sampling of 39 monitoring wells; (3) May 2021 – Chlorinated VOC Plume monitoring well installation – two monitoring wells were installed and screened from 10 to 20 feet below land surface (bls); and (4) May/June 2021 – Site-wide semi-annual water level measurements of 53 monitoring wells and sampling of 40 monitoring wells. Results showed substantial reduction of both plumes. Conclusions and recommendations are presented.

VOC↗

NASA NTRS2022

General Services Administration Reclamation Yard, SWMU 010, 2021 Groundwater Monitoring Report

This report presents a summary of the groundwater monitoring activities that occurred in November and December 2021 at General Services Administration Reclamation Yard, Solid Waste Management Unit 010, located at the John F. Kennedy Space Center (KSC), Florida. The site is monitored under KSC’s Resource Conservation and Recovery Act Corrective Action Program. This approach also meets the requirements of Chapter 62-780, Florida Administrative Code. For the purposes of this report, two separate plumes, known as the Polychlorinated Biphenyl (PCB)/Volatile Organic Aromatic (VOA) Plume and the Chlorinated Volatile Organic Compound (VOC) Plume, were identified for this site. The contaminants of concern (COCs) for the PCB/VOA Plume consists of PCBs, 1,2,4-trichlorobenzene, and breakdown products of 1,2,4-trichlorobenzene. The COCs for the Chlorinated VOC Plume are tetrachloroethene, trichloroethene, cis-1,2-dichloroethene, and vinyl chloride. The activities presented in this report include two field events: (1) November 2021 – PCB/VOA Plume groundwater sampling via Direct Push Technology – 70 groundwater samples were collected from 10 locations at varying intervals; and (2) December 2021 – Site-wide semi-annual water level measurements of 54 monitoring wells, redevelopment of 5 monitoring wells, and sampling of 35 monitoring wells. Results for the PCB/VOA plume demonstrated COCs have not rebounded since the 2018 source removal, with groundwater cleanup target levels (GCTLs) exceeded in the 10-30 ft. below ground surface interval only. In the Chlorinated VOC plume area, there were no detections of COCs above a GCTL for at least the second consecutive sampling event for the sampled wells. Cleanup objectives have been met, and it is recommended that VOC monitoring be discontinued. Underground injection control parameters will continue to be monitored in three wells until those analytes return to background concentrations.

GSA Reclamation Yard↗

NASA NTRS1972

Automated techniques for spacecraft monitoring

The feasibility of implementing automated spacecraft monitoring depends on four factors: sufficient computer resources, suitable monitoring function definitions, adequate spacecraft data, and effective and economical test systems. The advantages of automated monitoring lie in the decision-making speed of the computer and the continuous monitoring coverage provided by an automated monitoring program. Use of these advantages introduces a new concept of spacecraft monitoring in which system specialists, ground based or onboard, freed from routine and tedious monitoring, could devote their expertise to unprogrammed or contingency situations.

Segnar, H. R.↗

NASA NTRS1986

An artificial intelligence approach to onboard fault monitoring and diagnosis for aircraft applications

Real-time onboard fault monitoring and diagnosis for aircraft applications, whether performed by the human pilot or by automation, presents many difficult problems. Quick response to failures may be critical, the pilot often must compensate for the failure while diagnosing it, his information about the state of the aircraft is often incomplete, and the behavior of the aircraft changes as the effect of the failure propagates through the system. A research effort was initiated to identify guidelines for automation of onboard fault monitoring and diagnosis and associated crew interfaces. The effort began by determining the flight crew's information requirements for fault monitoring and diagnosis and the various reasoning strategies they use. Based on this information, a conceptual architecture was developed for the fault monitoring and diagnosis process. This architecture represents an approach and a framework which, once incorporated with the necessary detail and knowledge, can be a fully operational fault monitoring and diagnosis system, as well as providing the basis for comparison of this approach to other fault monitoring and diagnosis concepts. The architecture encompasses all aspects of the aircraft's operation, including navigation, guidance and controls, and subsystem status. The portion of the architecture that encompasses subsystem monitoring and diagnosis was implemented for an aircraft turbofan engine to explore and demonstrate the AI concepts involved. This paper describes the architecture and the implementation for the engine subsystem.

Schutte, P. C.↗

NASA NTRS1992

Design and qualification of the SEU/TD Radiation Monitor chip

This report describes the design, fabrication, and testing of the Single-Event Upset/Total Dose (SEU/TD) Radiation Monitor chip. The Radiation Monitor is scheduled to fly on the Mid-Course Space Experiment Satellite (MSX). The Radiation Monitor chip consists of a custom-designed 4-bit SRAM for heavy ion detection and three MOSFET's for monitoring total dose. In addition the Radiation Monitor chip was tested along with three diagnostic chips: the processor monitor and the reliability and fault chips. These chips revealed the quality of the CMOS fabrication process. The SEU/TD Radiation Monitor chip had an initial functional yield of 94.6 percent. Forty-three (43) SEU SRAM's and 14 Total Dose MOSFET's passed the hermeticity and final electrical tests and were delivered to LL.

Buehler, Martin G.↗

NASA NTRS1993

Monitoring issues from a modeling perspective

Recognition that earth's climate and biogeophysical conditions are likely changing due to human activities has led to a heightened awareness of the need for improved long-term global monitoring. The present long-term measurement efforts tend to be spotty in space, inadequately calibrated in time, and internally inconsistent with respect to other instruments and measured quantities. In some cases, such as most of the biosphere, most chemicals, and much of the ocean, even a minimal monitoring program is not available. Recently, it has become painfully evident that emerging global change issues demand information and insights that the present global monitoring system simply cannot supply. This is because a monitoring system must provide much more than a statement of change at a given level of statistical confidence. It must describe changes in diverse parts of the entire earth system on regional to global scales. It must be able to provide enough input to allow an integrated physical characterization of the changes that have occurred. Finally, it must allow a separation of the observed changes into their natural and anthropogenic parts. The enormous policy significance of global change virtually guarantees an unprecedented level of scrutiny of the changes in the earth system and why they are happening. These pressures create a number of emerging challenges and opportunities. For example, they will require a growing partnership between the observational programs and the theory/modeling community. Without this partnership, the scientific community will likely fall short in the monitoring effort. The monitoring challenge before us is not to solve the problem now, but rather to set appropriate actions in motion so as to create the required framework for solution. Each individual piece needs to establish its role in the large problem and how the required interactions are to take place. Below, we emphasize some of the needs and opportunities that could and should be addressed through participation by the theoreticians and modelers in the global change monitoring effort.

Mahlman, Jerry D.↗

NASA NTRS2005

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Iverson, David L.↗

NASA NTRS1992

Remote maintenance monitoring system

A remote maintenance monitoring system retrofits to a given hardware device with a sensor implant which gathers and captures failure data from the hardware device, without interfering with its operation. Failure data is continuously obtained from predetermined critical points within the hardware device, and is analyzed with a diagnostic expert system, which isolates failure origin to a particular component within the hardware device. For example, monitoring of a computer-based device may include monitoring of parity error data therefrom, as well as monitoring power supply fluctuations therein, so that parity error and power supply anomaly data may be used to trace the failure origin to a particular plane or power supply within the computer-based device. A plurality of sensor implants may be rerofit to corresponding plural devices comprising a distributed large-scale system. Transparent interface of the sensors to the devices precludes operative interference with the distributed network. Retrofit capability of the sensors permits monitoring of even older devices having no built-in testing technology. Continuous real time monitoring of a distributed network of such devices, coupled with diagnostic expert system analysis thereof, permits capture and analysis of even intermittent failures, thereby facilitating maintenance of the monitored large-scale system.

Simpkins, Lorenz G.↗

NASA NTRS2004

Baseline Monitoring for Astrometry in Interferometry

One of the science goals of NASA's Navigator program is ground-based narrow-angle astrometry for extra-solar planet detection, which could be done as part of the proposed Outrigger Telescopes Project. The narrow-angle measurement process, which would use the outrigger telescopes, starts with the determination of the conventional interferometer astrometric baseline, determined from wide-angle astrometry of Hipparcos stars. A baseline monitor system would be employed at each outrigger telescope. This system monitors the pivot point of each telescope - the end point of the astrometric baseline - to measure telescope imperfections that would cause the baseline to vary with telescope rotation. The baseline monitor includes azimuth and elevation cameras that monitor runout along the azimuth and elevation axes of the telescopes. In conjunction with the baseline monitor system, a pivot monitor camera in the dual-star module is used to register the laser metrology corner-cube reflector to the telescope pivot, tying the narrow-angle baseline, which applies to the narrow-angle astrometric measurement, to the wide-angle baseline. In this paper we present the proposed designs for the baseline monitor and pivot-point camera.

pivot point↗

NASA NTRS2010

Monitoring Distributed Real-Time Systems: A Survey and Future Directions

Runtime monitors have been proposed as a means to increase the reliability of safety-critical systems. In particular, this report addresses runtime monitors for distributed hard real-time systems. This class of systems has had little attention from the monitoring community. The need for monitors is shown by discussing examples of avionic systems failure. We survey related work in the field of runtime monitoring. Several potential monitoring architectures for distributed real-time systems are presented along with a discussion of how they might be used to monitor properties of interest.

Goodloe, Alwyn E.↗

NASA NTRS2010

General Purpose Data-Driven Online System Health Monitoring with Applications to Space Operations

Modern space transportation and ground support system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional parameter limit checking, or model-based or rule-based methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults, failures, or precursors of significant failures. The Inductive Monitoring System (IMS) is a general purpose, data-driven system health monitoring software tool that has been successfully applied to several aerospace applications and is under evaluation for anomaly detection in vehicle and ground equipment for next generation launch systems. After an introduction to IMS application development, we discuss these NASA online monitoring applications, including the integration of IMS with complementary model-based and rule-based methods. Although the examples presented in this paper are from space operations applications, IMS is a general-purpose health-monitoring tool that is also applicable to power generation and transmission system monitoring.

Iverson, David L.↗

NASA NTRS2011

Health Monitor for Multitasking, Safety-Critical, Real-Time Software

Health Manager can detect Bad Health prior to a failure occurring by periodically monitoring the application software by looking for code corruption errors, and sanity-checking each critical data value prior to use. A processor s memory can fail and corrupt the software, or the software can accidentally write to the wrong address and overwrite the executing software. This innovation will continuously calculate a checksum of the software load to detect corrupted code. This will allow a system to detect a failure before it happens. This innovation monitors each software task (thread) so that if any task reports "bad health," or does not report to the Health Manager, the system is declared bad. The Health Manager reports overall system health to the outside world by outputting a square wave signal. If the square wave stops, this indicates that system health is bad or hung and cannot report. Either way, "bad health" can be detected, whether caused by an error, corrupted data, or a hung processor. A separate Health Monitor Task is started and run periodically in a loop that starts and stops pending on a semaphore. Each monitored task registers with the Health Manager, which maintains a count for the task. The registering task must indicate if it will run more or less often than the Health Manager. If the task runs more often than the Health Manager, the monitored task calls a health function that increments the count and verifies it did not go over max-count. When the periodic Health Manager runs, it verifies that the count did not go over the max-count and zeroes it. If the task runs less often than the Health Manager, the periodic Health Manager will increment the count. The monitored task zeroes the count, and both the Health Manager and monitored task verify that the count did not go over the max-count.

Zoerner, Roger↗

NASA NTRS2014

Use of Semi-Autonomous Tools for ISS Commanding and Monitoring

As the International Space Station (ISS) has moved into a utilization phase, operations have shifted to become more ground-based with fewer mission control personnel monitoring and commanding multiple ISS systems. This shift to fewer people monitoring more systems has prompted use of semi-autonomous console tools in the ISS Mission Control Center (MCC) to help flight controllers command and monitor the ISS. These console tools perform routine operational procedures while keeping the human operator "in the loop" to monitor and intervene when off-nominal events arise. Two such tools, the Pre-positioned Load (PPL) Loader and Automatic Operators Recorder Manager (AutoORM), are used by the ISS Communications RF Onboard Networks Utilization Specialist (CRONUS) flight control position. CRONUS is responsible for simultaneously commanding and monitoring the ISS Command & Data Handling (C&DH) and Communications and Tracking (C&T) systems. PPL Loader is used to uplink small pieces of frequently changed software data tables, called PPLs, to ISS computers to support different ISS operations. In order to uplink a PPL, a data load command must be built that contains multiple user-input fields. Next, a multiple step commanding and verification procedure must be performed to enable an onboard computer for software uplink, uplink the PPL, verify the PPL has incorporated correctly, and disable the computer for software uplink. PPL Loader provides different levels of automation in both building and uplinking these commands. In its manual mode, PPL Loader automatically builds the PPL data load commands but allows the flight controller to verify and save the commands for future uplink. In its auto mode, PPL Loader automatically builds the PPL data load commands for flight controller verification, but automatically performs the PPL uplink procedure by sending commands and performing verification checks while notifying CRONUS of procedure step completion. If an off-nominal condition occurs during procedure execution, PPL Loader notifies CRONUS through popup messages, allowing CRONUS to examine the situation and choose an option of how PPL loader should proceed with the procedure. The use of PPL Loader to perform frequent, routine PPL uplinks offloads CRONUS to better monitor two ISS systems. It also reduces procedure performance time and decreases risk of command errors. AutoORM identifies ISS communication outage periods and builds commands to lock, playback, and unlock ISS Operations Recorder files. Operation Recorder files are circular buffer files of continually recorded ISS telemetry data. Sections of these files can be locked from further writing, be played back to capture telemetry data that occurred during an ISS loss of signal (LOS) period, and then be unlocked for future recording use. Downlinked Operation Recorder files are used by mission support teams for data analysis, especially if failures occur during LOS. The commands to lock, playback, and unlock Operations Recorder files are encompassed in three different operational procedures and contain multiple user-input fields. AutoORM provides different levels of automation for building and uplinking the commands to lock, playback, and unlock Operations Recorder files. In its automatic mode, AutoORM automatically detects ISS LOS periods, then generates and uplinks the commands to lock, playback, and unlock Operations Recorder files when MCC regains signal with ISS. AutoORM also features semi-autonomous and manual modes which integrate CRONUS more into the command verification and uplink process. AutoORMs ability to automatically detect ISS LOS periods and build the necessary commands to preserve, playback, and release recorded telemetry data greatly offloads CRONUS to perform more high-level cognitive tasks, such as mission planning and anomaly troubleshooting. Additionally, since Operations Recorder commands contain numerical time input fields which are tedious for a human to manually build, AutoORM's ability to automatically build commands reduces operational command errors. PPL Loader and AutoORM demonstrate principles of semi-autonomous operational tools that will benefit future space mission operations. Both tools employ different levels of automation to perform simple and routine procedures, thereby offloading human operators to perform higher-level cognitive tasks. Because both tools provide procedure execution status and highlight off-nominal indications, the flight controller is able to intervene during procedure execution if needed. Semi-autonomous tools and systems that can perform routine procedures, yet keep human operators informed of execution, will be essential in future long-duration missions where the onboard crew will be solely responsible for spacecraft monitoring and control.

Brzezinski, Amy S.↗

NASA NTRS2013

Definition, Capabilities, and Components of a Terrestrial Carbon Monitoring System

Research efforts for effectively and consistently monitoring terrestrial carbon are increasing in number. As such, there is a need to define carbon monitoring and how it relates to carbon cycle science and carbon management. There is also a need to identify capabilities of a carbon monitoring system and the system components needed to develop the capabilities. Capabilities that enable the effective application of a carbon monitoring system for monitoring and management purposes may include: reconciling carbon stocks and fluxes, developing consistency across spatial and temporal scales, tracking horizontal movement of carbon, attribution of emissions to originating sources, cross-sectoral accounting, uncertainty quantification, redundancy and policy relevance. Focused research is needed to integrate these capabilities for sustained estimates of carbon stocks and fluxes. Additionally, if monitoring is intended to inform management decisions, management priorities should be considered prior to development of a monitoring system.

Terrestrial↗