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This slide presentation reviews the precursor analysis for flight and ground based anomaly risk significance. It includes information on accident precursor analysis, real models vs. models, and probabilistic analysis.
Accident Precursor Analysis (APA) serves as the bridge between existing risk modeling activities, which are often based on historical or generic failure statistics, and system anomalies, which provide crucial information about the failure mechanisms that are actually operative in the system and which may differ in frequency or type from those in the various models. These discrepancies between the models (perceived risk) and the system (actual risk) provide the leading indication of an underappreciated risk. This paper presents an APA process developed specifically for NASA Earth-to-Orbit space systems. The purpose of the process is to identify and characterize potential sources of system risk as evidenced by anomalous events which, although not necessarily presenting an immediate safety impact, may indicate that an unknown or insufficiently understood risk-significant condition exists in the system. Such anomalous events are considered accident precursors because they signal the potential for severe consequences that may occur in the future, due to causes that are discernible from their occurrence today. Their early identification allows them to be integrated into the overall system risk model used to intbrm decisions relating to safety.
Accident Precursor Analysis (APA) serves as the bridge between existing risk modeling activities, which are often based on historical or generic failure statistics, and system anomalies, which provide crucial information about the failure mechanisms that are actually operative in the system. APA docs more than simply track experience: it systematically evaluates experience, looking for under-appreciated risks that may warrant changes to design or operational practice. This paper presents the pilot application of the NASA APA process to Space Shuttle Orbiter systems. In this effort, the working sessions conducted at Johnson Space Center (JSC) piloted the APA process developed by Information Systems Laboratories (ISL) over the last two years under the auspices of NASA's Office of Safety & Mission Assurance, with the assistance of the Safety & Mission Assurance (S&MA) Shuttle & Exploration Analysis Branch. This process is built around facilitated working sessions involving diverse system experts. One important aspect of this particular APA process is its focus on understanding the physical mechanism responsible for an operational anomaly, followed by evaluation of the risk significance of the observed anomaly as well as consideration of generalizations of the underlying mechanism to other contexts. Model completeness will probably always be an issue, but this process tries to leverage operating experience to the extent possible in order to address completeness issues before a catastrophe occurs.
This viewgraph presentation reviews the implementation of Accident Precursor Analysis (APA), as well as the evaluation of In-Flight Investigations (IFI) and Problem Reporting and Corrective Action (PRACA) data for the identification of unrecognized accident potentials on the International Space Station.
Catastrophic accidents are usually preceded by precursory events that, although observable, are not recognized as harbingers of a tragedy until after the fact. In the nuclear industry, the Three Mile Island accident was preceded by at least two events portending the potential for severe consequences from an underappreciated causal mechanism. Anomalies whose failure mechanisms were integral to the losses of Space Transportation Systems (STS) Challenger and Columbia had been occurring within the STS fleet prior to those accidents. Both the Rogers Commission Report and the Columbia Accident Investigation Board report found that processes in place at the time did not respond to the prior anomalies in a way that shed light on their true risk implications. This includes the concern that, in the words of the NASA Aerospace Safety Advisory Panel (ASAP), "no process addresses the need to update a hazard analysis when anomalies occur" At a broader level, the ASAP noted in 2007 that NASA "could better gauge the likelihood of losses by developing leading indicators, rather than continue to depend on lagging indicators". These observations suggest a need to revalidate prior assumptions and conclusions of existing safety (and reliability) analyses, as well as to consider the potential for previously unrecognized accident scenarios, when unexpected or otherwise undesired behaviors of the system are observed. This need is also discussed in NASA's system safety handbook, which advocates a view of safety assurance as driving a program to take steps that are necessary to establish and maintain a valid and credible argument for the safety of its missions. It is the premise of this handbook that making cases for safety more experience-based allows NASA to be better informed about the safety performance of its systems, and will ultimately help it to manage safety in a more effective manner. The APA process described in this handbook provides a systematic means of analyzing candidate accident precursors by evaluating anomaly occurrences for their system safety implications and, through both analytical and deliberative methods used to project to other circumstances, identifying those that portend more serious consequences to come if effective corrective action is not taken. APA builds upon existing safety analysis processes currently in practice within NASA, leveraging their results to provide an improved understanding of overall system risk. As such, APA represents an important dimension of safety evaluation; as operational experience is acquired, precursor information is generated such that it can be fed back into system safety analyses to risk-inform safety improvements. Importantly, APA utilizes anomaly data to predict risk whereas standard reliability and PRA approaches utilize failure data which often is limited and rare.
Almost every year there is at least one technological disaster that highlights the challenge of managing technological risk. On February 1, 2003, the space shuttle Columbia and her crew were lost during reentry into the atmosphere. In the summer of 2003, there was a blackout that left millions of people in the northeast United States without electricity. Forensic analyses, congressional hearings, investigations by scientific boards and panels, and journalistic and academic research have yielded a wealth of information about the events that led up to each disaster, and questions have arisen. Why were the events that led to the accident not recognized as harbingers? Why were risk-reducing steps not taken? This line of questioning is based on the assumption that signals before an accident can and should be recognized. To examine the validity of this assumption, the National Academy of Engineering (NAE) undertook the Accident Precursors Project in February 2003. The project was overseen by a committee of experts from the safety and risk-sciences communities. Rather than examining a single accident or incident, the committee decided to investigate how different organizations anticipate and assess the likelihood of accidents from accident precursors. The project culminated in a workshop held in Washington, D.C., in July 2003. This report includes the papers presented at the workshop, as well as findings and recommendations based on the workshop results and committee discussions. The papers describe precursor strategies in aviation, the chemical industry, health care, nuclear power and security operations. In addition to current practices, they also address some areas for future research.
Four weather regimes occurring over the Atlantic area and their preferred precursors and successors are identified. The first pattern exhibits the typical European blocking dipole, the second one represents an enhanced zonal flow, the third one consists of a positive anomaly over Greenland, and the last one is characterized by a ridge over the eastern Atlantic Ocean. The backward and forward memory times of the different regimes are established. Preferred precursor and successor patterns are identified as the maxima of the composite probability densities of the anomalies occurring before the onsets and after the breaks. The preferred transitions between regimes are also examined. The systematic aspect of this study gives rise to multiple applications, especially for case and composite studies on model prediction errors.
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The objective of this paper is to present a method for importance analysis in parametric probabilistic modeling where the result of interest is the identification of potential engineering vulnerabilities associated with postulated anomalies in system behavior. In the context of Accident Precursor Analysis (APA), under which this method has been developed, these vulnerabilities, designated as anomaly vulnerabilities, are conditions that produce high risk in the presence of anomalous system behavior. The method defines a parameter-specific Parameter Vulnerability Importance measure (PVI), which identifies anomaly risk-model parameter values that indicate the potential presence of anomaly vulnerabilities, and allows them to be prioritized for further investigation. This entails analyzing each uncertain risk-model parameter over its credible range of values to determine where it produces the maximum risk. A parameter that produces high system risk for a particular range of values suggests that the system is vulnerable to the modeled anomalous conditions, if indeed the true parameter value lies in that range. Thus, PVI analysis provides a means of identifying and prioritizing anomaly-related engineering issues that at the very least warrant improved understanding to reduce uncertainty, such that true vulnerabilities may be identified and proper corrective actions taken.
Five small (55 days old, 196 +/- 5 g) (mean +/- SE) and five large (83 days old, 382 +/- 4 g) Sprague-Dawley strain, specific pathogen-free rats were exposed to a 7-day spaceflight and 12-h postflight recovery period. As measured in 3-micron sections, periodontal ligament (PDL) fibroblastlike cells were classified according to nuclear size: A + A' (40-79), B (80-119), C (120-169), and D (greater than or equal to 170 microns 3). Since the histogenesis sequence is A----A'----C----D----osteoblast, the relative incidence of A + A' to C + D is an osteogenic index. No difference in A + A' or C + D cells in small rats may reflect partial recovery of preosteoblast formation (A----C) during the 12-h postflight period. Large flight rats demonstrated increased numbers of A + A', indicating an inhibition of preosteoblast formation (A----C). At least in the older group, a 7-day flight is adequate to reduce PDL osteogenic potential (inhibition in PDL osteoblast differentiation and/or specific attrition of C + D cells) that does not recover by 12-h postflight.
Theoretical analysis and quantitative measurements of shock tube precurser effects
Bulk compositions of 17 chondrules and one sample of matrix from CO3 Ornans were determined by instrumental neutron activation analysis. Chondrule precursor components deduced from chondrule compositions are characterized by: (1) common and slightly volatile siderophiles, Cr and chalcophiles, (2) refractory lithophiles and Na, (3) Mn, Si and modal pyroxene, and (4) FeO and olivine. Component 4 may be closely related to matrix material. Precursor components have now been inferred for OC, EH, CV, CM and CO chondrules. An MN- and Si-rich component occurs exclusively among carbonaceous chondrite chondrules. Although there are significant intergroup differences, common to chondrules in all chondrite groups are refractory-lithophile-rich, common-siderophile-rich, and (with the exception of EH) common-lithophile-rich components. This indicates that the siderophile/lithophile and refractory lithophile/common lithophile fractionations recorded in chondrite whole-rocks were established prior to chondrule formation at all nebular locations.
The Mars Program Planning Group (MPPG) was an agency wide effort, chartered in March 2012 by the NASA Associate Administrator for Science, in collaboration with NASA's Associate Administrator for Human Exploration and Operations, the Chief Scientist, and the Chief Technologist. NASA tasked the MPPG to develop foundations for a program-level architecture for robotic exploration of Mars that is consistent with the President's challenge of sending humans to the Mars system in the decade of the 2030s and responsive to the primary scientific goals of the 2011 NRC Decadal Survey for Planetary Science. The Mars Exploration Program Analysis Group (MEPAG) also sponsored a Precursor measurement Strategy Analysis Group (P-SAG) to revisit prior assessments of required precursor measurements for the human exploration of Mars. This paper will discuss the key results of the MPPG and P-SAG efforts to update and refine our understanding of the Strategic Knowledge Gaps (SKGs) required to successfully conduct human Mars missions.
The solar wind interaction with the geomagnetic field is studied using global auroral images obtained by the Ultraviolet Imager (UVI) on Polar. We study the dynam,cs of the poleward and equatorward boundaries of the auroral oval in response to the solar wind IMF on January 10, 1997 using a neural network algorithm to perform an automated morphological analysis. Poleward and equatorward boundaries identified by the algorithm demonstrate a clear growth motion with the southward turning of the IMF and growth and poleward expansion at substorm onset. The area poleward of the oval (polar cap) is found to increase in size coincident with the'southward turning of the IMF Bz component at 0220 UT and peaks at substorm onset at 0334 UT. The area of the oval, however, decreases continuously throughout the period of the polar cap area increase with a slight recovery observed during the substorm onset. These observations are consistent with the concept that magnetospheric dynamics are directly driven by the solar wind-geomagnetic field interactions.
Thermogravimetric analysis data are presented on the unmeltable polycarbosilazane precursor of silicon carbide-silicon nitride fibers, over the room temperature-1000 C range in a nitrogen atmosphere, in order to establish the weight loss at various temperatures during the precursor's pyrolysis to the fiber material. The fibers obtained by this method are excellent candidates for use in applications where the oxidation of carbon fibers (above 400 C) renders them unsuitable.
A new technique for rotating stall precursor identification in high-speed compressors has been developed at the NASA Lewis Research Center. This pseudo correlation integral method uses a mathematical algorithm based on chaos theory to identify nonlinear dynamic changes in the compressor. Through a study of four various configurations of a high-speed compressor stage, a multistage compressor rig, and an axi-centrifugal engine test, this algorithm, using only a single pressure sensor, has consistently predicted the onset of rotating stall.
The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions are responsible for a significant range across models, mostly in the case of ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind) reveals biases consistent with state-of-the-art climate models. The model-to- model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry.
The development of thin-film solar cells on flexible, lightweight, space-qualified durable substrates (i.e. Kapton) provides an attractive solution to fabricating solar arrays with high specific power, (W/kg). The syntheses and thermal modulation of ternary single source precursors, based on the [{LR}2Cu(SR')2In(SR')2] architecture in good yields are described. Thermogravimetric analyses (TGA) and Low temperature Differential Scanning Caloriometry, (DSC) demonstrate that controlled manipulation of the steric and electronic properties of either the group five-donor and/or chalcogenide moiety permits directed adjustment of the thermal stability and physical properties of the precursors. TGA-Evolved Gas Analysis, confirms that single precursors decompose by the initial extrusion of the sulphide moiety, followed by the loss of the neutral donor group, (L) to release the ternary chalcopyrite matrix. X-ray diffraction studies, EDS and SEM on the non-volatile pyrolized material demonstrate that these derivatives afford single-phase CuInS2/CuInSe2 materials at low temperature. Thin-film fabrication studies demonstrate that these single source precursors can be used in a spray chemical vapor deposition process, for depositing CuInS2 onto flexible polymer substrates at temperatures less than 400 C.