Results for “Accident Analysis” — Page 13

NASA NTRS1999

An Experimental and Numerical Study of Icing Effects on the Performance and Controllability of a Twin Engine Aircraft

In September 1997 the National Transportation Safety Board (NTSB) requested assistance from the NASA Lewis Research Center (LeRC) Icing Branch in the investigation of an aircraft accident that was suspected of being caused by ice contamination. In response to the request NASA agreed to perform an experimental and computational study. The main activities that NASA performed were LERC Icing Research Tunnel (IRT) testing to define ice shapes and 2-D Navier-Stokes analysis to determine the performance degradation that those ice shapes would have caused. An IRT test was conducted in January 1998. Most conditions for the test were based upon raw and derived data from the Flight Data Recorder (FDR) recovered from the accident and upon the current understanding of the Meteorological conditions near the accident. Using a two-dimensional Navier-Stokes code, the flow field and resultant lift and drag were calculated for the wing section with various ice shapes accreted in the IRT test. Before the final calculations could be performed extensive examinations of geometry smoothing and turbulence were conducted. The most significant finding of this effort is that several of the five-minute ice accretions generated in the IRT were found by the Navier-Stokes analysis to produce severe lift and drag degradation. The information generated by this study suggests a possible scenario for the kind of control upset recorded in the accident. Secondary findings were that the ice shapes accreted in the IRT were mostly limited to the protected pneumatic boot region of the wing and that during testing, activation of the pneumatic boots cleared most of the ice.

Reehorst, A.↗

NASA NTRS2018

A Prognostic Launch Vehicle Probability of Failure Assessment Methodology for Conceptual Systems Predicated on Human Causal Factors

Create an improved method to calculate reliability of a conceptual launch vehicle system prior to fabrication by using historic data of actual root causes of failures. While failures have unique "proximate causes", there are typically a finite amount of common "root causes". Heretofore launch vehicle reliability evaluation typically hardware-centric statistical analyses, while most root causes of failures are been shown to be human-centric. A method based on human-centric root causes can be used to quantify reliability assessments and focus proposed actions to mitigate problems. Existing methods have been optimistic in their projections of launch vehicle reliability compared to actuals. Hypothesis: reliability of a conceptual launch vehicle can be more accurately evaluated based on a rational, probabilistic approach using past failure assessment teams' findings predicated on human-centric causes."Human Reliability Analysis Methods Selection Guidance for NASA"Chandler F.T., et al., NASA HQ/OSMA study group, July 2006. Outside HRA experts from academia, other federal labs, and the private sector. 50 system reliability methods considered, fourteen selected for further study, four finally selected as best suited for human spaceflight. Probabilistic Risk Analysis (PRA) + Human Reliability Analysis (HRA) enabled incorporating effects and probabilities of human errors. While four down-selected methods deemed appropriate for failure assessment, it did not appear that these methods could be concisely applied to perform major system-wide assessment of probability of failure of a conceptual design without becoming unwieldy."Engineering a Safer World", Detailed, comprehensive study external to NASA Leveson N. G., MIT, 2011.Systems-Theoretic Accident Model and Processes (STAMP). All-encompassing accident model based on systems theory analyzed accidents after they occurred and created approaches to prevent occurrence in developing systems not focused on failure prevention per se, but rather reducing hazards by influencing human behavior through use of constraints, hierarchical control structures, and process models to improve system safetySystem Theoretic Process Analysis (STPA) addresses predictive part of problem (a "hazard analysis"). Includes all causal factors identified in STAMP: "...design errors, software flaws, component interaction accidents, cognitively complex human decision-making errors, and social organizational and management factors contributing to accidents" can guide design process rather than require it to exist before-hand did not appear capable of concise application for system-wide assessment of probability of failure of a conceptual design without becoming unwieldy.

Williams, Craig H.↗

NASA NTRS1969

Hydrodynamics of a new concept of primary containment by energy absorption

Fluid dynamical analysis for idealized reactors system with spherical symmetry determines the effect which the destructive component of a nuclear accident produces on primary containment structures. Steel strands surrounding the reactor cavity in the biological shield exhibit plastic deformation to achieve the energy absorption.

Fistedis, S. H.↗

NASA NTRS1979

Interpretation of results

An analysis of the risks to the nation which may arise due to carbon fiber release from air carrier accidents was presented. The purpose of this report is to place these risks in perspective by examining their implications for society as a whole. Some additional aspects of risk estimation which were not dealt with by simulation modeling approach are addressed and open issues which may require further study are indicated.

Source record↗

NASA NTRSDate not supplied

Application of Objectives-Driven Assurance Cases to System Development in an Evolving Acquisition Model

System properties such as “safety” and “dependability” cannot, in practice, be proven, and must be argued in an “assurance case” aimed at supporting risk-acceptance decisions that have to be made by system acquirers and/or regulatory authorities. The paper is concerned with applications of the “assurance case” idea early in design and development of new systems, when (apart from dedicated testing) the only available operating experience information derives from previous (non-identical) systems. Much of the discussion is based on an evolving acquisition model at the US National Aeronautics and Space Administration; previously, most major systems were developed in-house, but some major systems will now be developed by and acquired from commercial providers. Key points discussed include the following. (1) By promoting a particular kind of focused discussion between acquirers and providers, the use of assurance cases should be particularly valuable under the new acquisition model. (2) In principle, objectives-driven (sometimes called “performance-based”) approaches to assurance of performance have significant advantages in cases where they are applicable. (3) For truly novel systems, completeness of the safety analysis is a significant issue; it is important for the assurance case to include a commitment by the provider (or applicant) to seriously pursue analysis of operating experience, so that previously unrecognized hazards can be identified and addressed. (4) Inquiries into major accidents often point to deficiencies in management oversight in all parts of the life cycle; management processes need to be addressed in the formulation and the implementation of an assurance case. Under the new acquisition model, these considerations imply a serious reconsideration of the way in which the development process is managed by both providers and acquirers.

Objectives-driven↗

NASA NTRS2004

Anomaly Analysis: NASA's Engineering and Safety Center Checks Recurring Shuttle Glitches

The NASA Engineering and Safety Center (NESC), set up in the wake of the Columbia accident to backstop engineers in the space shuttle program, is reviewing hundreds of recurring anomalies that the program had determined don't affect flight safety to see if in fact they might. The NESC is expanding its support to other programs across the agency, as well. The effort, which will later extend to the International Space Station (ISS), is a principal part of the attempt to overcome the normalization of deviance--a situation in which organizations proceeded as if nothing was wrong in the face of evidence that something was wrong--cited by sociologist Diane Vaughn as contributing to both space shuttle disasters.

Morring, Frank, Jr.↗

NASA NTRS2002

[High Pressure Gas Tanks]

Four high-pressure gas tanks, the basis of this study, were especially made by a private contractor and tested before being delivered to NASA Kennedy Space Center. In order to insure 100% reliability of each individual tank the staff at KSC decided to again submit the four tanks under more rigorous tests. These tests were conducted during a period from April 10 through May 8 at KSC. This application further validates the predictive safety model for accident prevention and system failure in the testing of four high-pressure gas tanks at Kennedy Space Center, called Continuous Hazard Tracking and Failure Prediction Methodology (CHTFPM). It is apparent from the variety of barriers available for a hazard control that some barriers will be more successful than others in providing protection. In order to complete the Barrier Analysis of the system, a Task Analysis and a Biomechanical Study were performed to establish the relationship between the degree of biomechanical non-conformities and the anomalies found within the system on particular joints of the body. This relationship was possible to obtain by conducting a Regression Analysis to the previously generated data. From the information derived the body segment with the lowest percentage of non-conformities was the neck flexion with 46.7%. Intense analysis of the system was conducted including Preliminary Hazard Analysis (PHA), Failure Mode and Effect Analysis (FMEA), and Barrier Analysis. These analyses resulted in the identification of occurrences of conditions, which may be becoming hazardous in the given system. These conditions, known as dendritics, may become hazards and could result in an accident, system malfunction, or unacceptable risk conditions. A total of 56 possible dendritics were identified. Work sampling was performed to observe the occurrence each dendritic. The out of control points generated from a Weighted c control chart along with a Pareto analysis indicate that the dendritics "Personnel not Wearing Proper Protective and Hose/tubing located in high-traffic area" which account for 59.18% of total dendritic frequency need to be addressed to reduce the chance of a hazard from occurring. However, the occurrences of some dendritics are more important than others. As a result immediate, from a Weighted c perspective, corrective action should be taken to ameliorate the cause of the Class A dendritic "Personnel located under suspended or moving loads" rather than just the most commonly occurring dendritics. In any case the vast majority of data obtained indicates that testing operations possess a relatively high degree of safety.

Quintana, Rolando↗

NASA NTRSDate not supplied

The Role of NASA Engineering & Safety Center (NESC) in Advancing NASA’s Astrophysics Missions (Past, Present, and Future)

The NASA Engineering & Safety Center (NESC) was established in 2003 (after the Columbia accident) to provide an independent technical resource for the resolution of challenging technical problems (through the use of studies, analysis, tests, etc.) for NASA programs and projects. Since its inception, NESC has completed nearly 1000 technical assessments for NASA’s Human Exploration and Operation Mission Directorate (HEOMD), Science Mission Directorate (SMD), Space Technology Mission Directorate (STMD), and Aeronautics Research Mission Directorate (ARMD). Of the SMD related assessments, several were for the resolution of technical problems, analysis, or studies related to NASA’s astrophysics missions in various phases of the project from design to operation. Some of the recent examples of NESC technical support for NASA astrophysics missions have been for: Hubble Space Telescope (HST), Chandra X-ray Observatory (CXO), Fermi Gamma-ray Space Telescope, Kepler Space Telescope, Transiting Exoplanet Survey Satellite (TESS), James Webb Space Telescope (JWST), and Laser Interferometer Space Antenna (LISA). In this paper, we outline some of the technical challenges faced by these astrophysics missions and describe how NESC contributed to their resolution. The case studies cover a wide range of disciplines involving space telescopes, detectors, lasers, and attitude control systems. These efforts include innovative solutions for extending the life of the missions, technical resolution of challenging problems, strategies for risk mitigation, and failure investigations combined with lessons learned reports to advance discipline knowledge, enhance NASA capabilities, and avoid future problems.

NASA↗

NASA NTRS1989

A mesoscale numerical simulation of an index for use in the forecasting of the potential severity of wet microbursts

This paper demonstrates the feasibility of using the wet microburst potential intensity index developed by Proctor (1989) for predicting the onset of a wet microburst. After describing the index and the principles involved in its derivation, the version 4.0 of the Mesoscale Atmospheric Simulation System (MASS) model described by Karyampudi et al. (1988) was used to illustrate how the index would perform as a forecast product. An analysis is presented of the use of the microburst potential intensity index in the numerical simulation of the DFR aircraft accident on August 2, 1985 in a downburst environment.

Zack, John W.↗

NASA NTRS1989

Numerical aerodynamic simulation of the space shuttle ascent environment

After the STS 51-L accident, an extensive review of the Space Shuttle Orbiter's ascent aerodynamic loads uncovered several questionable areas that required further analysis. The insight gained by comparing the Shuttle ascent CFD numerical simulations, obtained by the NASA Ames Space Shuttle Flow Simulation Group, to the current IVBC-3 aerodynamic loads database was instrumental in resolving uncertainties on the Orbiter payload bay doors and fuselage. Initial confidence in the numerical simulations was gained by comparing them with the limited flight data that had been obtained during the Orbiter Flight Test (OFT) program. Current CFD results exist for Mach numbers 0.6, 0.9, 1.05, 1.55, 2.0, and 2.5. Since the pre STS-1 wind tunnel test program (IA-105) often yields considerable differences when compared to STS-5 flight data, the M(sub infinity) = 1.05 transonic case is the most investigated. The IA308 mated-vehicle hot gas plume wind tunnel test, recently completed at AEDC 16T (transonic) and Lewis (hypersonic), is also used to compare with the computation where applicable.

Slotnick, Jeff P.↗

NASA NTRS1992

Update to the safety program for the general-purpose heat source radioisotope thermoelectric generators for the Galileo and Ulysses missions

With the rescheduling of the Galileo and Ulysses launches and the use of new upper stages following the Challenger accident, the aerospace nuclear safety program for the general-purpose heat source radioisotope thermoelectric generators (GPHS-RTGs) was extended to accommodate the new mission scenarios. As in the original safety program, the objectives were to determine the response of the GPHS-RTG to the various postulated accident environments and to determine the risk (if any) associated with these postulated accidents. The extended GPHS-RTG safety program was successfully completed in sufficient time to prepare an updated Final Safety Analysis Report (FSAR) with revisions for the October 1989 launch of the Galileo spacecraft.

Bennett, Gary L.↗

NASA NTRS2013

Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Muti-agent System↗

NASA NTRS2006

EV13 Genesis Reentry Observations and Data Analysis

The Genesis spacecraft reentry represented a unique opportunity to observe a "calibrated meteor" from northern Nevada. Knowing its speed, mass, composition, and precise trajectory made it a good subject to test some of the algorithms used to determine meteoroid mass from observed brightness. It was also a good test of an inexpensive set of cameras which could be deployed to observe future shuttle reentries. The utility of consumer grade video cameras was evident during the STS-107 accident investigation and the Genesis reentry gave us the opportunity to specify and test commercially available cameras which could be used during future reentries. This report describes the video observations and their analysis, compares the results with a simple photometric model, describes the forward scatter radar experiment, and lists lessons learned from the expedition and implications for the Stardust reentry in January 2006 as well as future shuttle reentries.

Swift, Wesley R.↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRS2014

Loss of Signal, Aeromedical Lessons Learned from the STS-107 Columbia Space Shuttle Mishap

Loss of Signal, a NASA publication to be available in May 2014 presents the aeromedical lessons learned from the Columbia accident that will enhance crew safety and survival on human space flight missions. These lessons were presented to limited audiences at three separate Aerospace Medical Association (AsMA) conferences: in 2004 in Anchorage, Alaska, on the causes of the accident; in 2005 in Kansas City, Missouri, on the response, recovery, and identification aspects of the investigation; and in 2011, again in Anchorage, Alaska, on future implications for human space flight. As we embark on the development of new spacefaring vehicles through both government and commercial efforts, the NASA Johnson Space Center Human Health and Performance Directorate is continuing to make this information available to a wider audience engaged in the design and development of future space vehicles. Loss of Signal summarizes and consolidates the aeromedical impacts of the Columbia mishap process-the response, recovery, identification, investigative studies, medical and legal forensic analysis, and future preparation that are needed to respond to spacecraft mishaps. The goal of this book is to provide an account of the aeromedical aspects of the Columbia accident and the investigation that followed, and to encourage aerospace medical specialists to continue to capture information, learn from it, and improve procedures and spacecraft designs for the safety of future crews. This poster presents an outline of Loss of Signal contents and highlights from each of five sections - the mission and mishap, the response, the investigation, the analysis and the future.

Stepaniak, Phillip C.↗

NASA NTRS2005

Genesis Reentry Observations and Data Analysis

The Genesis spacecraft reentry represented a unique opportunity to observe a "calibrated meteor" from northern Nevada. Knowing its speed, mass, composition, and precise trajectory made it a good subject to test some of the algorithms used to determine meteoroid mass from observed brightness. It was also a good test of an inexpensive set of cameras that could be deployed to observe future shuttle reentries. The utility of consumer-grade video cameras was evident during the STS-107 accident investigation, and the Genesis reentry gave us the opportunity to specify and test commercially available cameras that could be used during future reentries. This Technical Memorandum describes the video observations and their analysis, compares the results with a simple photometric model, describes the forward scatter radar experiment, and lists lessons learned from the expedition and implications for the Stardust reentry in January 2006 as well as future shuttle reentries.

Suggs, R. M.↗