Results for “contingency analysis” — Page 8

NASA NTRS1981

Satellite services system analysis study. Volume 4: Service equipment concepts

Payload deployment equipment is discussed, including payload separation, retention structures, the remote manipulator system, tilt tables, the payload installation and deployment aid, the handling and positioning aid, and spin tables. Close proximity retrieval, and on-orbit servicing equipment is discussed. Backup and contingency equipment is also discussed. Delivery and retrieval of high-energy payloads are considered. Earth return equipment, the aft flight deck, optional, and advanced equipment are also discussed.

Source record↗

NASA NTRS2014

Modified ACES Portable Life Support Integration, Design, and Testing for Exploration Missions

NASA's next generation of exploration missions provide a unique challenge to designers of EVA life support equipment, especially in a fiscally-constrained environment. In order to take the next steps of manned space exploration, NASA is currently evaluating the use of the Modified ACES (MACES) suit in conjunction with the Advanced Portable Life Support System (PLSS) currently under development. This paper will detail the analysis and integration of the PLSS thermal and ventilation subsystems into the MACES pressure garment, design of prototype hardware, and hardware-in-the-loop testing during the spring 2014 timeframe. Prototype hardware was designed with a minimal impact philosophy in order to mitigate design constraints becoming levied on either the advanced PLSS or MACES subsystems. Among challenges faced by engineers were incorporation of life support thermal water systems into the pressure garment cavity, operational concept definition between vehicle/portable life support system hardware, and structural attachment mechanisms while still enabling maximum EVA efficiency from a crew member's perspective. Analysis was completed in late summer 2013 to 'bound' hardware development, with iterative analysis cycles throughout the hardware development process. The design effort will cumulate in the first ever manned integration of NASA's advanced PLSS system with a pressure garment originally intended primarily for use in a contingency survival scenario.

Kelly, Cody↗

NASA NTRS2013

The Regolith Biters: A Divide-And-Conquer Architecture for Sample-Return Missions

The collective interaction of simple systems can be leveraged to attain complex goals. Based on this principle, we envision space system architectures where the core functional components are decoupled, autonomous, and cooperative. We aim to pursue this vision in the context of small-body sample-return missions. After all, no experimental study sheds more light into our understanding of the origin and evolution of the Solar System than the analysis of samples from asteroids and comets. We also believe that their study is important from a strategic perspective: meteorite impacts pose a direct and credible threat to life on Earth, and the development of contingency small-body deflection missions presupposes some knowledge of the target body. The current architectural paradigm for sample-return missions is centered around a design where spacecraft and sampling device are merged into a single, complex system. We argue that this monolithic approach couples the navigation and sample-collection problems, making both more difficult. In contrast, we propose a decoupled system based on the coordinated interaction between a spacecraft and a collective of small, simple devices - the Regolith Biters (RBs). A spacecraft carrying a number of RBs would travel to the vicinity of a small body. From a favorable vantage point, and while remaining within a safe distance in a non-colliding trajectory, it would release the RBs towards the target body. Upon encountering the body, they would bite the regolith (thus retaining a sample), and eject back to orbit. The spacecraft, being endowed with appropriate navigation and tracking capabilities, would rendezvous with and collect those RBs within its reach, and bring them back to Earth. Separating the navigation and sampling concerns removes the need for proximity operations with the small body-the stage in current architectures that carries the most challenges and risks. Eliminating the need for proximity operations brings back to the discussion the exploration of exciting prospects, like highly active comets, fast-rotating bodies, and binary systems. Distributing the sampling problem among a collective of agents provides the opportunity to sample multiple regions in a single mission. It also provides robustness to various environmental conditions, and may enable the distributed, in situ characterization of the body. In the search for reliability, current architectures rely on complexity: an elaborate system should succeed at once. We rely on numbers: a given agent may fail at any stage, but success is attained by the collective.

Asteroids↗

NASA NTRS2021

Analysis of Mars 2020 Perseverance Entry, Descent, and Landing Attitude Initialization Performance

The Mars 2020 Perseverance rover successfully landed at Jezero Crater on February 18, 2021. To perform this feat, the entry, descent, and landing navigation filter must be initialized with an estimate of the spacecraft state, which includes attitude from the cruise attitude control subsystem. Accuracy of this initial attitude estimate has an impact on important metrics such as touchdown velocity. This paper presents a post-landing reconstruction of the attitude initialization error budget, showing that the requirement of 0.15 deg ($3\sigma$, per axis) was met. Each error source is described and analyzed, including flight telemetry where possible. Analysis of the error budget shows that it is driven by systematic sun sensor errors, star-scanner-to-sun-sensor alignment stability, and inertial-measurement-unit-to-sun-sensor alignment stability. Finally, a contingency plan to initialize the navigation filter in the event of a star scanner failure is presented. While this plan was not needed in flight, results indicate that the attitude initialization requirement could have still been met in this off-nominal scenario.

Lo, Kevin D.↗

NASA NTRS2012

Hypervelocity Impact Initiation of Explosive Transfer Lines

The Gemini, Apollo and Space Shuttle spacecraft utilized explosive transfer lines (ETL) in a number of applications. In each case the ETL was located behind substantial structure and the risk of impact initiation by micrometeoroids and orbital debris was negligible. A current NASA program is considering an ETL to synchronize the actuation of pyrobolts to release 12 capture latches in a contingency. The space constraints require placing the ETL 50 mm below the 1 mm thick 2024-T72 Whipple shield. The proximity of the ETL to the thin shield prompted analysts at NASA to perform a scoping analysis with a finite-difference hydrocode to calculate impact parameters that would initiate the ETL. The results suggest testing is required and a 12 shot test program with surplused Shuttle ETL is scheduled for February 2012 at the NASA White Sands Test Facility. Explosive initiation models are essential to the analysis and one exists in the CTH library for HNS I, but not the HNS II used in the Shuttle 2.5 gr/ft rigid shielded mild detonating cord (SMDC). HNS II is less sensitive than HNS I so it is anticipated that these results using the HNS I model are conservative. Until the hypervelocity impact test results are available, the only check on the analysis was comparison with the Shuttle qualification test result that a 22 long bullet would not initiate the SMDC. This result was reproduced by the hydrocode simulation. Simulations of the direct impact of a 7 km/s aluminum ball, impacting at 0 degree angle of incidence, onto the SMDC resulted in a 1.5 mm diameter ball initiating the SMDC and 1.0 mm ball failing to initiate it. Where one 1.0 mm ball could not initiate the SMDC, a cluster of six 1.0 mm diameter aluminum balls striking simultaneously could. Thus the impact parameters that will result in initiating SMDC located behind a Whipple shield will depend on how well the shield fragments the projectile and spreads the fragments. An end-to-end simulation of the impact of an aluminum ball onto a Whipple shield covering SMDC is problematic due to the hydrocode fracture models. Regardless, two simulations were performed resulting in a 5 mm ball initiating the SMDC and a 4 mm ball failing to initiate the SMDC.

Bjorkman, Michael D.↗

NASA NTRSDate not supplied

Supportability Concepts for Crewed Deep Space Exploration

Supportability—defined as the set of system characteristics that influence the logistics and support required to enable safe and effective operations—will be a much larger driver of mass, risk, and crew time for future human space exploration due to the more challenging mission context. For Mars, systems must operate in a logistically isolated environment for much longer durations than previous missions, which results in a higher probability of system failure and therefore an increased need for maintenance or contingency options. Mars missions also lack access to quick aborts, which increases the consequences of an unrecoverable system failure. Together, this higher likelihood and consequence of failure results in an increase in supportability-related risk. Supportability analysis is an important part of systems development that helps designers better understand the impacts of system and mission decisions on risk, mass, and crew time. The real-world processes that drive maintenance requirements and other supportability-related characteristics are probabilistic, and therefore they require different conceptual approaches and models than are used for more deterministic aspects of space systems. This paper provides an overview of supportability analysis, addresses key concepts, and provides examples of how supportability analysis can be incorporated into system development. Specifically, system supportability involves stochastic processes, and therefore must be evaluated using probabilistic models. These models can be used to perform sensitivity analysis even if system characteristics are not yet fully defined. Failure rates cannot be measured directly, but tests provide valuable data that can help refine those estimates. Human spaceflight architectures are complex, and exhibit coupled behavior that should be examined with integrated systems analysis that includes an assessment of supportability.

Supportability↗

NASA NTRSDate not supplied

Supportability Concepts for Crewed Deep Space Exploration

Supportability—defined as the set of system characteristics that influence the logistics and support required to enable safe and effective operations—will be a much larger driver of mass, risk, and crew time for future human space exploration due to the more challenging mission context. For Mars, systems must operate in a logistically isolated environment for much longer durations than previous missions, which results in a higher probability of system failure and therefore an increased need for maintenance or contingency options. Mars missions also lack access to quick aborts, which increases the consequences of an unrecoverable system failure. Together, this higher likelihood and consequence of failure results in an increase in supportability-related risk. Supportability analysis is an important part of systems development that helps designers better understand the impacts of system and mission decisions on risk, mass, and crew time. The real-world processes that drive maintenance requirements and other supportability-related characteristics are probabilistic, and therefore they require different conceptual approaches and models than are used for more deterministic aspects of space systems. This paper provides an overview of supportability analysis, addresses key concepts, and provides examples of how supportability analysis can be incorporated into system development. Specifically, system supportability involves stochastic processes, and therefore must be evaluated using probabilistic models. These models can be used to perform sensitivity analysis even if system characteristics are not yet fully defined. Failure rates cannot be measured directly, but tests provide valuable data that can help refine those estimates. Human spaceflight architectures are complex, and exhibit coupled behavior that should be examined with integrated systems analysis that includes an assessment of supportability.

Supportability↗

NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗

NASA NTRS2024

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗

NASA NTRS2010

Earth Return Navigation Analysis for Manned Spacecraft Using Optical and Radiometric Measurements

Future manned space missions will travel beyond low Earth orbit with more stringent navigation requirements and fewer navigation resources than used for the Apollo Program of the 1960s. A study has been performed to assess radiometric and optical tracking capabilities necessary to meet nominal and contingency Earth entry flight path angle requirements. Results indicate that 3 tracking stations will be insufficient for meeting nominal entry requirements, while the performance of a 6 station architecture is dependent on the entry geometry. Optical tracking results indicate that a narrow-angle camera is required for satisfying contingency Earth return requirements.

GN&C↗

NASA NTRS2001

CFD Simulations in Support of Shuttle Orbiter Contingency Abort Aerodynamic Database Enhancement

Modern Computational Fluid Dynamics (CFD) techniques were used to compute aerodynamic forces and moments of the Space Shuttle Orbiter in specific portions of contingency abort trajectory space. The trajectory space covers a Mach number range of 3.5-15, an angle-of-attack range of 20deg-60deg, an altitude range of 100-190 kft, and several different settings of the control surfaces (elevons, body flap, and speed brake). Presented here are details of the methodology and comparisons of computed aerodynamic coefficients against the values in the current Orbiter Operational Aerodynamic Data Book (OADB). While approximately 40 cases have been computed, only a sampling of the results is provided here. The computed results, in general, are in good agreement with the OADB data (i.e., within the uncertainty bands) for almost all the cases. However, in a limited number of high angle-of-attack cases (at Mach 15), there are significant differences between the computed results, especially the vehicle pitching moment, and the OADB data. A preliminary analysis of the data from the CFD simulations at Mach 15 shows that these differences can be attributed to real-gas/Mach number effects. The aerodynamic coefficients and detailed surface pressure distributions of the present simulations are being used by the Shuttle Program in the evaluation of the capabilities of the Orbiter in contingency abort scenarios.

Papadopoulos, Periklis E.↗

NASA NTRS2012

Cascade Storage and Delivery System for a Multi Mission Space Exploration Vehicle (MMSEV)

NASA is developing a Multi Mission Space Exploration Vehicle (MMSEV) for missions beyond Low Earth Orbit (LEO). The MMSEV is a pressurized vehicle used to extend the human exploration envelope for Lunar, Near Earth Object (NEO), and Deep Space missions. The Johnson Space Center is developing the Environmental Control and Life Support System (ECLSS) for the MMSEV. The MMSEV s intended use is to support longer sortie lengths with multiple Extra Vehicular Activities (EVAs) on a higher magnitude than any previous vehicle. This paper presents an analysis of a high pressure oxygen cascade storage and delivery system that will accommodate the crew during long duration Intra Vehicular Activity (IVA) and capable of multiple high pressure oxygen fills to the Portable Life Support System (PLSS) worn by the crew during EVAs. A cascade is a high pressure gas cylinder system used for the refilling of smaller compressed gas cylinders. Each of the large cylinders are filled by a compressor, but the cascade system allows small cylinders to be filled without the need of a compressor. In addition, the cascade system is useful as a "reservoir" to accommodate low pressure needs. A regression model was developed to provide the mechanism to size the cascade systems subject to constraints such as number of crew, extravehicular activity duration and frequency, and ullage gas requirements under contingency scenarios. The sizing routine employed a numerical integration scheme to determine gas compressibility changes during depressurization and compressibility effects were captured using the Soave-Redlich-Kwong (SRK) equation of state. A multi-dimensional nonlinear optimization routine was used to find the minimum cascade tank system mass that meets the mission requirements. The sizing algorithms developed in this analysis provide a powerful framework to assess cascade filling, compressor, and hybrid systems to design long duration vehicle ECLSS architecture. 1

Yagoda, Evan↗

NASA NTRS1965

Ground testing at MSFC

The large-scale field collection of acoustic data and their analysis are described in this review. The entire sound-field program has the purpose of solving complex problems of excessive noise propagation associated with the static test firing of large space-booster powerplants. The site of data collection has been Mississippi Test Facility (MTF), where far-field sound-propagation and correlated meteorological measurements were initiated in 1962. The statistical evaluation of sound-measurement data shows that the polar distribution of sound in the springtime (at MTF) is determined mainly by the temperature field of the atmosphere. Greater deformation of sound-intensity polar distribution occurs in the autumn as a result of the influence of the wind field. The data on sound attenuation as a function of distance from its source revealed attenuation in excess of the expected magnitude. The excess was mainly between 1 and 10 kilometers from the source, with maximum attenuation (17 to 18 decibels) near 6 kilometers. Excess sound attenuation was compared with calculated sound dispersion. For all sound frequencies in all seasons the deviation between reference and empirical attenuation values formed a bell-shaped distribution on a semilogarithmic plot. The physical causes for the sound- attenuation behavior are considered to be atmospheric diffraction and scattering effects. Statistical analysis of sod-intensity extremes indicated amplification of the sound signals by focusing which could be expected along selected azimuths. Empirical amplification values showed the maximum occurring in winter (50 decibels at 22 kilometers). For the analysis of correlation between empirical sound data and local atmospheric sound- propagation conditions, #e concept of analytical classification of sound-velocity profiles has been developed. Examination of over a quarter-million individual sound-velocity profiles indicates that 33 profile types for heights up to 3 kilometers constitute the empirical possibilities of sound-propagation conditions in southeastern United States. Since the focusing qualities of each sound- velocity profile can be determined as a class characteristic, the overall probabilities of focusing occurrence can he obtained. The severity of focusing, as based upon lateral spread of focusing areas, has been determined. The data for MTF indicate focusing is most severe in winter, with the direction toward east being most affected. Sound propagation is a fluctuating phenomenon because atmospheric conditions vary continuously. A measuring system for analyzing the nonstationary sound-propagation phenomena has been established. The analysis of the acoustic fluctuation data is sup- posed to provide "dynamic” perturbation functions of sound, which are to be superimposed on the related characteristic sound-velocity-profile type. The ultimate result of the program will be the establishment of reliable contingency tables showing the relationship between atmospheric parameters and far-field sound intensities. These data will be the basis for more accurate sound-propagation forecasting for static firing tests.

STATIC TESTING↗

NASA NTRS1990

High and low thrust mission analysis for a Mars exploration program

The purpose of the study is to identify limits, trends, and sensitivities of Mars Transportation System performance over several Mars mission opportunities. Two Mars Transfer Vehicle (MTV) configurations utilizing different propulsion systems (Chemical/Aerobrake and NEP - Nuclear Electric Propulsion) are outlined. The trades involved in comparing two MTS candidate designs are assessed. Mission analysis for mission opportunities beginning in around 2010 and continuing past 2030 is performed, and a Mars mission model is covered, along with orbit selection and NEP and Chemical/Aerobrake performance. The results of several sensitivity studies are given in order to allow for contingency planning in design and performance. It is concluded that the low-thrust system perform best, its vehicle mass is lower and its trip times are more stable.

Shepard, Kyle M.↗

NASA NTRS1977

A procedure used for a ground truth study of a land use map of North Alabama generated from LANDSAT data

A land use map of a five county area in North Alabama was generated from LANDSAT data using a supervised classification algorithm. There was good overall agreement between the land use designated and known conditions, but there were also obvious discrepancies. In ground checking the map, two types of errors were encountered - shift and misclassification - and a method was developed to eliminate or greatly reduce the errors. Randomly selected study areas containing 2,525 pixels were analyzed. Overall, 76.3 percent of the pixels were correctly classified. A contingency coefficient of correlation was calculated to be 0.7 which is significant at the alpha = 0.01 level. The land use maps generated by computers from LANDSAT data are useful for overall land use by regional agencies. However, care must be used when making detailed analysis of small areas. The procedure used for conducting the ground truth study together with data from representative study areas is presented.

Downs, S. W., Jr.↗

NASA NTRS1984

Guidelines for contingency planning NASA (National Aeronautics and Space Administration) ADP security risk reduction decision studies

Guidance is presented to NASA Computer Security Officials for determining the acceptability or unacceptability of ADP security risks based on the technical, operational and economic feasibility of potential safeguards. The risk management process is reviewed as a specialized application of the systems approach to problem solving and information systems analysis and design. Reporting the results of the risk reduction analysis to management is considered. Report formats for the risk reduction study are provided.

Tompkins, F. G.↗

NASA NTRS1981

High precision attitude determination for Magsat

A two phase approach to attitude determination software development is introduced. The prelaunch planning and software activities connected with the development and testing of the baseline system for processing nominal attitude data for MAGSAT are described and postlaunch analysis and modifications are outlined. Attitude data processing began 5 months after launch so that postlaunch anomalies could be accounted for. Another advantage of the two phase approach is that costs are reduced because the system is not burdened with software dealing with all possible contingencies. A definitive, continuous, time history of the three axis attitude of the spacecraft was generated to a precision of 20 arc sec (one standard deviation), in each axis. Sensor alignment determinations were done continuously because of the deletrious effects of changing alignments on attitude precision.

Abshire, G.↗

NASA NTRS2019

Sextant Navigation on the International Space Station: A Human Space Exploration Demo

Astronauts on board the International Space Station (ISS) tested a hand-held sextant to demonstrate potential use on future human exploration missions such as Orion and Gateway. The investigation, designed to aid in the development of emergency navigation methods for future crewed spacecraft, took place from June-December 2018. A sextant provides manual capability to perform star/planet-limb sightings and estimate vehicle state during loss of communication or other contingencies. Its simplicity and independence from primary systems make it useful as an emergency survival backup or confirming measurement source. The concept of using a sextant has heritage in Gemini, Apollo, and Skylab. This paper discusses the instrument selection, flight certification, crew training, product development, experiment execution, and data analysis. Preflight training consisted of a hands-on session with the instrument and practice in a Cupola mock-up with star field projector dome. The experiment itself consisted of several sessions with sextant sightings in the ISS Cupola module by two crew members. Sightings were taken on star pairs, star/moon limb, and moon diameter. The sessions were designed to demonstrate star identification and acquisition, sighting stability, accuracy, and lunar sights. Results are presented which demonstrate sightings within the accuracy goal of 60 arcseconds, even in the presence of window refraction effects and minimal crew training. The crew members provided valuable feedback on sighting products and microgravity stability techniques.

Exploration↗