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Viewgraph presentation on the design and testing Liquid Hydrogen Barge Vaporizers at NASA John C. Stennis Space Center is shown. The topics include: 1) Vaporizer Requirements; 2) Vaporizer Design; 3) LH2 # 2 Vaporizer Statistics; 4) Corrective Actions; and 5) Lessons Learned.
Many types of hazard and risk analyses are used during the life cycle of complex systems, including Failure Modes and Effects Analysis (FMEA), Hazard Analysis, Fault Tree and Event Tree Analysis, Probabilistic Risk Assessment, Reliability Analysis and analysis of Problem Reporting and Corrective Action (PRACA) databases. The success of these methods depends on the availability of input data and the analysts knowledge. Standard nomenclature can increase the reusability of hazard, risk and problem data. When nomenclature in the source texts is not standard, taxonomies with mapping words (sets of rough synonyms) can be combined with semantic search to identify items and tag them with metadata based on a rich standard nomenclature. Semantic search uses word meanings in the context of parsed phrases to find matches. The NASA taxonomies provide the word meanings. Spacecraft taxonomies and ontologies (generalization hierarchies with attributes and relationships, based on terms meanings) are being developed for types of subsystems, functions, entities, hazards and failures. The ontologies are broad and general, covering hardware, software and human systems. Semantic search of Space Station texts was used to validate and extend the taxonomies. The taxonomies have also been used to extract system connectivity (interaction) models and functions from requirements text. Now the Reconciler semantic search tool and the taxonomies are being applied to improve search in the Space Shuttle PRACA database, to discover recurring patterns of failure. Usual methods of string search and keyword search fall short because the entries are terse and have numerous shortcuts (irregular abbreviations, nonstandard acronyms, cryptic codes) and modifier words cannot be used in sentence context to refine the search. The limited and fixed FMEA categories associated with the entries do not make the fine distinctions needed in the search. The approach assigns PRACA report titles to problem classes in the taxonomy. Each ontology class includes mapping words - near-synonyms naming different manifestations of that problem class. The mapping words for Problems, Entities and Functions are converted to a canonical form plus any of a small set of modifier words (e.g. non-uniformity NOT + UNIFORM.) The report titles are parsed as sentences if possible, or treated as a flat sequence of word tokens if parsing fails. When canonical forms in the title match mapping words, the PRACA entry is associated with the corresponding Problem, Entity or Function in the ontology. The user can search for types of failures associated with types of equipment, clustering by type of problem (e.g., all bearings found with problems of being uneven: rough, irregular, gritty ). The results could also be used for tagging PRACA report entries with rich metadata. This approach could also be applied to searching and tagging failure modes, failure effects and mitigations in FMEAs. In the pilot work, parsing 52K+ truncated titles (the test cases that were available), has resulted in identification of both a type of equipment and type of problem in about 75% of the cases. The results are displayed in a manner analogous to Google search results. The effort has also led to the enrichment of the taxonomy, adding some new categories and many new mapping words. Further work would make enhancements that have been identified for improving the clustering and further reducing the false alarm rate. (In searching for recurring problems, good clustering is more important than reducing false alarms). Searching complete PRACA reports should lead to immediate improvement.
Integrated Vehicle Health Management (IVHM) systems have been pursued as highly integrated systems that include smart sensors, diagnostic and prognostics software for assessments of real-time and life-cycle vehicle health information. Inclusive to such a system is the requirement to monitor the environmental health within the vehicle and the occupants of the vehicle. In this regard an enterprise approach to informatics is used to develop a methodology entitled, Comprehensive Environmental Informatics System (CEIS). The hardware and software technologies integrated into this system will be embedded in the vehicle subsystems, and maintenance operations, to provide both real-time and life-cycle health information of the environment within the vehicle cabin and of its occupants. This comprehensive information database will enable informed decision making and logistics management. One key element of the CEIS is interoperability for data acquisition and archive between environment and human system monitoring. With comprehensive components the data acquired in this system will use model based reasoning systems for subsystem and system level managers, advanced on-board and ground-based mission and maintenance planners to assess system functionality. Knowledge databases of the vehicle health state will be continuously updated and reported for critical failure modes, and routinely updated and reported for life cycle condition trending. Sufficient intelligence, including evidence-based engineering practices which are analogous to evidencebased medicine practices, will be included in the CEIS to result in more rapid recognition of off-nominal operation to enable quicker corrective actions. This will result from better information (rather than just data) for improved crew/operator situational awareness, which will produce significant vehicle and crew safety improvements, as well as increasing the chance for mission success, future mission planning as well as training. Other benefits include improved reliability, increase safety in operations and cost of operations. The cost benefits stem from significantly reduced processing and operations manpower, predictive maintenance for systems and subjects. The improvements in vehicle functionality and cost will result from increased prognostic and diagnostic capability due to the detailed total human exploration system health knowledge from CEIS. A collateral benefit is that there will be closer observations of the vehicle occupants as wrist watch sized devices are worn for continuous health monitoring. Additional database acquisition will stem from activities in countermeasure practices to ensure peak performance capability by occupants of the vehicle. The CEIS will provide data from advanced sensing technologies and informatics modeling which will be useful in problem troubleshooting, and improving NASA s awareness of systems during operation.
The paper introduces the concept of the long range forecasting function, which is then used to identify periods of peak oversubscription of resources years before they actually happen, so that proper corrective actions (construction of additional antennas, reduction in support committment to the impacted projects) can be implemented.
Thee unmanned planetary spacecraft to the outer planets have been controlled and operated successfully in space for an accumulated total of 66 years. The Voyager 1 and 2 spacecraft each have been in space for more than 26 years. The Galileo spacecraft was in space for 14 years, including eight years in orbit about Jupiter. During the flight operations for these missions, anomalies for the ground data system and the flight systems have been tracked using the anomaly reporting tool at the Jet Propulsion Laboratory. A total of 3300 incidents, surprises, and anomaly reports have been recorded in the database. This paper describes methods and results for classifying and identifying trends relative to ground system vs. flight system, software vs. hardware, and corrective actions. There are several lessons learned from these assessments that significantly benefit the design and planning for long life missions of the future. These include the necessity for having redundancy for successful operation of the spacecraft, awareness that anomaly reporting is dependent on mission activity not the age of the spacecraft, and the need for having a program to maintain and transfer operation knowledge and tools to replacement flight team members.
In-flight Spatial Disorientation (SD) in pilots is a serious threat to aviation safety. Indeed, SD may play a much larger role in aviation accidents than the approximate 6-8% reported by the National Transportation Safety Board (NTSB) each year, because some accidents coded by the NTSB as aircraft control-not maintained (ACNM) may actually result from SD. The purpose of this study is to determine whether SD is underestimated as a cause of fatal general aviation (GA) accidents in the NTSB database. Fatal GA airplane accidents occurring between January 1995 and December 1999 were reviewed from the NTSB aviation accident database. Cases coded as ACNM or SD as the probable cause were selected for review by a panel of aerospace medicine specialists. Using a rating scale, each rater was instructed to determine if SD was the probable cause of the accident. Agreement between the raters and agreement between the raters and the NTSB were evaluated by Kappa statistics. The raters agreed that 11 out of 20 (55%) accidents coded by the NTSB as ACNM were probably caused by SD (p less than 0.05). Agreement between the raters and the NTSB did not reach significance (p greater than 0.05). The 95% C.I. for the sampling population estimated that between 33-77% of cases that the NTSB identified as ACNM could be identified by aerospace medicine experts as SD. Aerospace medicine specialists agreed that some cases coded by the NTSB as ACNM were probably caused by SD. Consequently, a larger number of accidents may be caused by the pilot succumbing to SD than indicated in the NTSB database. This new information should encourage regulating agencies to insure that pilots receive SD recognition training, enabling them to take appropriate corrective actions during flight. This could lead to new training standards, ultimately saving lives among GA airplane pilots.
The purpose of this paper is to discuss the implementation of a programmatic quality assurance discipline within the International Space Station Program and the resulting impact on safety. NASA culture has continued to stress safety at the expense of quality when both are extremely important and both can equally influence the success or failure of a Program or Mission. Although safety was heavily criticized in the media after Col~imbiaa, strong case can be made that it was the failure of quality processes and quality assurance in all processes that eventually led to the Columbia accident. Consequently, it is possible to have good quality processes without safety, but it is impossible to have good safety processes without quality. The ISS Program quality assurance function was analyzed as representative of the long-term manned missions that are consistent with the President s Vision for Space Exploration. Background topics are as follows: The quality assurance organizational structure within the ISS Program and the interrelationships between various internal and external organizations. ISS Program quality roles and responsibilities with respect to internal Program Offices and other external organizations such as the Shuttle Program, JSC Directorates, NASA Headquarters, NASA Contractors, other NASA Centers, and International Partner/participants will be addressed. A detailed analysis of implemented quality assurance responsibilities and functions with respect to NASA Headquarters, the JSC S&MA Directorate, and the ISS Program will be presented. Discussions topics are as follows: A comparison of quality and safety resources in terms of staffing, training, experience, and certifications. A benchmark assessment of the lessons learned from the Columbia Accident Investigation (CAB) Report (and follow-up reports and assessments), NASA Benchmarking, and traditional quality assurance activities against ISS quality procedures and practices. The lack of a coherent operational and sustaining quality assurance strategy for long-term manned space flight. An analysis of the ISS waiver processes and the Problem Reporting and Corrective Action (PRACA) process implemented as quality functions. Impact of current ISS Program procedures and practices with regards to operational safety and risk A discussion regarding a "defense-in-depth" approach to quality functions will be provided to address the issue of "integration vs independence" with respect to the roles of Programs, NASA Centers, and NASA Headquarters. Generic recommendations are offered to address the inadequacies identified in the implementation of ISS quality assurance. A reassessment by the NASA community regarding the importance of a "quality culture" as a component within a larger "safety culture" will generate a more effective and value-added functionality that will ultimately enhance safety.
The NASA White Sands Test Facility (WSTF) was requested to perform pyrovalve blowby tests in support of the Mars Observer Propulsion and Corrective Actions Test Program. Fifty-three tests were conducted in an attempt to characterize the blowby of commercial pyrovalves. Those pyrovalves used on NASA spacecraft are well represented, and the test data reported provide a basis for evaluating the performance of similar valves in other propulsion systems. The three test series conducted are subsequently described. All testing was done in the same test facility, with periodic changes that enhanced the test methodology.
This study investigated the Shuttle Program s belief that Space Transportation System (STS) wiring damage occurrences are random, that is, a constant occurrence rate. Using Problem Reporting and Corrective Action (PRACA)-derived data for STS Space Shuttle OV-103, wiring damage was observed to increase over the vehicle s life. Causal factors could include wiring physical deterioration, maintenance and inspection induced damage, and inspection process changes resulting in more damage events being reported. Induced damage effects cannot be resolved with existent data. Growth analysis (using Crow-AMSAA, or CA) resolved maintenance/inspection effects (e.g., heightened awareness) on all wire damages and indicated an overall increase since Challenger Return-to-Flight (RTF). An increasing failure or occurrence rate per flight cycle was seen for each wire damage mode; these (individual) rates were not affected by inspection process effects, within statistical error.
Initial planetary explorations with the Apollo program had a veritable ground support army monitoring the safety and health of the 12 astronauts who performed lunar surface extravehicular activities (EVAs). Given the distances involved, this will not be possible on Mars. A spacesuit for Mars must be smart enough to replace that army. The next generation suits can do so using 2 software systems serving as virtual companions, LEGACI (Life support, Exploration Guidance Algorithm and Consumable Interrogator) and VIOLET (Voice Initiated Operator for Life support and Exploration Tracking). The system presented in this study integrates data inputs from a suite of sensors into the MIII suit s communications, avionics and informatics hardware for distribution to remote managers and data analysis. If successful, the system has application not only for Mars but for nearer term missions to the Moon, and the next generation suits used on ISS as well. Field tests are conducted to assess capabilities for next generation spacesuits at Johnson Space Center (JSC) as well as the Mars and Lunar analog (Devon Island, Canada). LEGACI integrates data inputs from a suite of noninvasive biosensors in the suit and the astronaut (heart rate, suit inlet/outlet lcg temperature and flowrate, suit outlet gas and dewpoint temperature, pCO2, suit O2 pressure, state vector (accelerometry) and others). In the Integrated Walkback Suit Tests held at NASA-JSC and the HMP tests at Devon Island, communication and informatics capabilities were tested (including routing by satellite from the suit at Devon Island to JSC in Houston via secure servers at VCU in Richmond, VA). Results. The input from all the sensors enable LEGACI to compute multiple independent assessments of metabolic rate, from which a "best" met rate is chosen based on statistical methods. This rate can compute detailed information about the suit, crew and EVA performance using test-derived algorithms. VIOLET gives LEGACI voice activation capability, allowing the crew to query the suit, and receive feedback and alerts that will lead to corrective action. LEGACI and VIOLET can also automatically control the astronaut's cooling and consumable use rate without crew input if desired. These findings suggest that non-invasive physiological and environmental sensors supported with data analysis can allow for more effective management of mission task performance during EVA. Integrated remote and local view of data metrics allow crewmember to receive real time feedback in synch with mission control in preventing performance shortcomings for EVA in exploration missions.
This paper provides an overview of the lessons learned from the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center s (GSFC) Flight Dynamics Facility s (FDF) support of the Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft emergency in February 2007, and the Tracking and Data Relay Satellite-3 (TDRS-3) spacecraft emergency in March 2006. A successful and timely recovery from both of these spacecraft emergencies depended on accurate knowledge of the orbit. Unfortunately, the combination of each spacecraft emergency with very little tracking data contributed to difficulties in estimating and predicting the orbit and delayed recovery efforts in both cases. In both the THEMIS and TDRS-3 spacecraft emergencies, numerous factors contributed to problems with obtaining nominal tracking data measurements. This paper details the various causative factors and challenges. This paper further enumerates lessons learned from FDF s recovery efforts involving the THEMIS and TDRS-3 spacecraft emergencies and scant tracking data, as well as recommendations for improvements and corrective actions. In addition, this paper describes the broad range of resources and complex navigation methods employed within the FDF for supporting critical navigation activities during all mission phases, including launch, early orbit, and on-orbit operations.
A recently invented method of measuring concentrations of phycocynanin-pigmented algae and bacteria in water is based on measurement of the spectrum of reflected sunlight. When present in sufficiently high concentrations, phycocynanin-pigmented microorganisms can be hazardous to the health of humans who use, and of animals that depend on, an affected body of water. The present method is intended to satisfy a need for a rapid, convenient means of detecting hazardous concentrations of phycocynanin-pigmented microorganisms. Rapid detection will speed up the issuance of public health warnings and performance of corrective actions. The method involves the measurement of light reflected from a body of water in at least two, but preferably five wavelength bands. In one version of the method, the five wavelength bands are bands 1, 3, 4, 5, and 7 of the Thematic Mapper (TM) multispectral imaging instrument aboard the Landsat-7 satellite (see table). In principle, other wavelength bands indicative of phycocynanin could be used alternatively or in addition to these five. Moreover, although the method was originally intended specifically for processing Landsat- 7 TM data, it is equally applicable to processing of data from other satellite-borne instruments or from airborne, hand-held, buoy-mounted, tower-mounted, or otherwise mounted instruments that measure radiances of light reflected from water in the wavelength bands of interest.
An EMU water processing kit (Airlock Coolant Loop Recovery A/L CLR) was developed as a corrective action to Extravehicular Mobility Unit (EMU) coolant flow disruptions experienced on the International Space Station (ISS) in May of 2004 and thereafter. Conservative schedules for A/L CLR use and component life were initially developed and implemented based on prior analysis results and analytical modeling. The examination of postflight samples and EMU hardware in November of 2006 indicated that the A/L CLR kits were functioning well and had excess capacity that would allow a relaxation of the initially conservative schedules of use and component life. A relaxed use schedule and list of component lives was implemented thereafter. Since the adoption of the relaxed A/L CLR schedules of use and component lives, several A/L CLR kit components, transport loop water samples and sensitive EMU transport loop components have been examined to gage the impact of the relaxed requirements. The intent of this paper is to summarize the findings of that evaluation, and to outline updated schedules for A/L CLR use and component life.
A proposed system of portable illuminated signs, electronic monitoring equipment, and radio-communication equipment for preventing (or taking corrective action in response to) improper entry of aircraft, pedestrians, or ground vehicles onto active airport runways is described. The main overall functions of the proposed system would be to automatically monitor aircraft ground traffic on or approaching runways and to generate visible and/or audible warnings to affected pilots, ground-vehicle drivers, and control-tower personnel when runway incursions take place.
In a very short period of time the MER project successfully developed and tested a system, TIRS/DIMES, to improve the probability of success in the presence of large Martian winds. The successful development of TIRS/DIMES played a big role in the landing site selection process by enabling the landing of Spirit on Gusev crater, a site of very high scientific interest but with known high wind conditions. The performance of TIRS by Spirit at Gusev Crater was excellent. The velocity prediction error was small and Big TIRS was fired reducing the impact horizontal velocity from approximately 23 meters per second to approximately 11 meters per second, well within the airbag capabilities. The performance of TIRS by Opportunity at Meridiani was good. The velocity prediction error was rather large (approximately 6 meters per second, a less than 2 sigma value, but TIRS did not fire which was the correct action.
The use of a form of remote sensing to aid in the management of large turfgrass fields (e.g. golf courses) has been proposed. A turfgrass field of interest would be surveyed in sunlight by use of an airborne hyperspectral imaging system, then the raw observational data would be preprocessed into hyperspectral reflectance image data. These data would be further processed to identify turfgrass stresses, to determine the spatial distributions of those stresses, and to generate maps showing the spatial distributions. Until now, chemicals and water have often been applied, variously, (1) indiscriminately to an entire turfgrass field without regard to localization of specific stresses or (2) to visible and possibly localized signs of stress for example, browning, damage from traffic, or conspicuous growth of weeds. Indiscriminate application is uneconomical and environmentally unsound; the amounts of water and chemicals consumed could be insufficient in some areas and excessive in most areas, and excess chemicals can leak into the environment. In cases in which developing stresses do not show visible signs at first, it could be more economical and effective to take corrective action before visible signs appear. By enabling early identification of specific stresses and their locations, the proposed method would provide guidance for planning more effective, more economical, and more environmentally sound turfgrass-management practices, including application of chemicals and water, aeration, and mowing. The underlying concept of using hyperspectral imagery to generate stress maps as guides to efficient management of vegetation in large fields is not new; it has been applied in the growth of crops to be harvested. What is new here is the effort to develop an algorithm that processes hyperspectral reflectance data into spectral indices specific to stresses in turfgrass. The development effort has included a study in which small turfgrass plots that were, variously, healthy or subjected to a variety of controlled stresses were observed by use of a hand-held spectroradiometer. The spectroradiometer readings in the wavelength range from 350 to 1,000 nm were processed to extract hyperspectral reflectance data, which, in turn, were analyzed to find correlations with the controlled stresses. Several indices were found to be correlated with drought stress and to be potentially useful for identifying drought stress before visible symptoms appear.
Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.
The initial X-43A flight test, June 2, 2001, resulted in a mishap and loss of the vehicle. A mishap investigation board (MIB) report and findings, including the established root cause, were publicly released on July, 23, 2003. The X-43A Flight 1 Hyper-X Launch Vehicle (HXLV) failed because the vehicle control system design was deficient for the trajectory flown due to inaccurate analytical models (Pegasus heritage and HXLV specific), which overestimated the (control) system margin ? X-43A Mishap Investigation Report, Vol. I. ? included as Reference 1. Several specific errors were noted, 1) HXLV aerodynamics ? failure to model changes to wing, fin and rudder airfoil shapes due to addition of thermal protection system (TPS); 2) Fin actuation system (FAS) modeling ? under prediction of the control surface hinge moments and FAS compliance; and 3) Parametric uncertainties ? insufficient variation in the aerodynamic, FAS and control system models. In response to the MIB findings, the X-43A program has been working RTF through an approved Corrective Action Plan (CAP) over the last two years.