Results for “Contingency Management” — Page 10

NASA NTRSDate not supplied

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗

NASA NTRS2021

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗

NASA NTRS2007

Shuttle Entry Imaging Using Infrared Thermography

During the Columbia Accident Investigation, imaging teams supporting debris shedding analysis were hampered by poor entry image quality and the general lack of information on optical signatures associated with a nominal Shuttle entry. After the accident, recommendations were made to NASA management to develop and maintain a state-of-the-art imagery database for Shuttle engineering performance assessments and to improve entry imaging capability to support anomaly and contingency analysis during a mission. As a result, the Space Shuttle Program sponsored an observation campaign to qualitatively characterize a nominal Shuttle entry over the widest possible Mach number range. The initial objectives focused on an assessment of capability to identify/resolve debris liberated from the Shuttle during entry, characterization of potential anomalous events associated with RCS jet firings and unusual phenomenon associated with the plasma trail. The aeroheating technical community viewed the Space Shuttle Program sponsored activity as an opportunity to influence the observation objectives and incrementally demonstrate key elements of a quantitative spatially resolved temperature measurement capability over a series of flights. One long-term desire of the Shuttle engineering community is to calibrate boundary layer transition prediction methodologies that are presently part of the Shuttle damage assessment process using flight data provided by a controlled Shuttle flight experiment. Quantitative global imaging may offer a complementary method of data collection to more traditional methods such as surface thermocouples. This paper reviews the process used by the engineering community to influence data collection methods and analysis of global infrared images of the Shuttle obtained during hypersonic entry. Emphasis is placed upon airborne imaging assets sponsored by the Shuttle program during Return to Flight. Visual and IR entry imagery were obtained with available airborne imaging platforms used within DoD along with agency assets developed and optimized for use during Shuttle ascent to demonstrate capability (i.e., tracking, acquisition of multispectral data, spatial resolution) and identify system limitations (i.e., radiance modeling, saturation) using state-of-the-art imaging instrumentation and communication systems. Global infrared intensity data have been transformed to temperature by comparison to Shuttle flight thermocouple data. Reasonable agreement is found between the flight thermography images and numerical prediction. A discussion of lessons learned and potential application to a potential Shuttle boundary layer transition flight test is presented.

Horvath, Thomas↗

NASA NTRS2005

Infrared On-Orbit RCC Inspection With the EVA IR Camera: Development of Flight Hardware From a COTS System

In November 2004, NASA's Space Shuttle Program approved the development of the Extravehicular (EVA) Infrared (IR) Camera to test the application of infrared thermography to on-orbit reinforced carbon-carbon (RCC) damage detection. A multi-center team composed of members from NASA's Johnson Space Center (JSC), Langley Research Center (LaRC), and Goddard Space Flight Center (GSFC) was formed to develop the camera system and plan a flight test. The initial development schedule called for the delivery of the system in time to support STS-115 in late 2005. At the request of Shuttle Program managers and the flight crews, the team accelerated its schedule and delivered a certified EVA IR Camera system in time to support STS-114 in July 2005 as a contingency. The development of the camera system, led by LaRC, was based on the Commercial-Off-the-Shelf (COTS) FLIR S65 handheld infrared camera. An assessment of the S65 system in regards to space-flight operation was critical to the project. This paper discusses the space-flight assessment and describes the significant modifications required for EVA use by the astronaut crew. The on-orbit inspection technique will be demonstrated during the third EVA of STS-121 in September 2005 by imaging damaged RCC samples mounted in a box in the Shuttle's cargo bay.

Gazanik, Michael↗

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 NTRS2008

Heart Rhythm Monitoring in the Constellation Lunar and Launch/Landing EVA Suit: Recommendations from an Expert Panel

Currently there are several physiological monitoring requirements for Extravehicular Activity (EVA) in the Human-Systems Interface Requirements (HSIR) document, including continuous heart rhythm monitoring. However, it is not known whether heart rhythm monitoring in the lunar surface space suit is a necessary capability for lunar surface operations or in launch/landing suit the event of a cabin depressurization enroute to or from the moon. Methods: Current US astronaut corps demographic information was provided to an expert panel of cardiovascular medicine experts, including specialists in electrophysiology, exercise physiology, interventional cardiology and arrhythmia. This information included averages for male/female age, body mass index (BMI), blood pressure, cholesterol, inflammatory markers, echocardiogram, ranges for coronary artery calcium (CAC) scores for long duration astronauts, and ranges for heart rate (HR) and metabolic (MET) rates obtained during microgravity and lunar EVA. Results: The panel determined that no uncontrolled hazard was likely to occur in the suit during lunar surface or contingency microgravity ops that would require ECG monitoring in the highly screened US astronaut population. However having the capability for rhythm monitoring inside the vehicle (IVA) was considered critical to manage an astronaut in distress. Discussion: Heart rate (HR) monitoring alone allows effective monitoring of astronaut health and function. Consequently, electrocardiographic (ECG) monitoring capability as a clinical tool is not essential in the lunar or launch/landing space suit. However, the panel considered that rhythm monitoring could be useful in certain clinical situations, it was not considered required for safe operations. Also, lunar vehicles should be required to have ECG monitoring capability with a minimum of 5-lead ECG (derived 12- lead) for IVA medical assessments.

Scheuring, Richard A.↗

NASA NTRSDate not supplied

Streamlining Tactical Operator Handoffs During Multi-Vehicle Applications

Increased automation has shifted the operator control paradigm from a single operator controlling a single vehicle, to multiple operators collaborating to control multiple vehicles; this paradigm is known as m:N. Many questions remain unanswered in this new operational paradigm about the division of assets as workload for individual operators varies overtime. This paper explores the management of workload by enabling operators to temporarily handoff vehicles among each other. A study was conducted to explore both a manual and assisted method for performing handoffs during manipulated contingency scenarios. The assisted handoff method allowed subjects to easily choose and group nominal and/or contingency vehicles. The number of contingencies was also manipulated to determine the effect workload had on how pilots utilized the ability to handoff vehicles. Results show subjects performed handoffs more often when there were more contingencies and when the assisted handoff tool was available. In addition, the assisted tool make subjects feel more comfortable, enabling them to feel like they could take longer to resolve contingency situations. Lastly, even during contingencies, subjects were able to successfully complete secondary tasks.

M:N operations↗

NASA NTRSDate not supplied

Streamlining Tactical Operator Handoffs During Multi-Vehicle Operations

Increased automation has shifted the operator control paradigm from a single operator controlling a single vehicle, to multiple operators collaborating to control multiple vehicles; this paradigm is known as m:N. Many questions remain unanswered in this new operational paradigm about the division of assets as workload for individual operators varies over time. This paper explores the management of workload by enabling operators to temporarily handoff vehicles among each other. A study was conducted to explore both a manual and assisted method for performing handoffs during manipulated contingency scenarios. The assisted handoff method allowed subjects to easily choose and group nominal and/or contingency vehicles. The number of contingencies was also manipulated to determine the effect workload had on how pilots utilized the ability to handoff vehicles. Results show subjects performed handoffs more often when there were more contingencies and when the assisted handoff tool was available. In addition, the assisted tool made subjects feel more comfortable, enabling them to feel like they could take longer to resolve contingency situations. Lastly, even during contingencies, subjects were able to successfully complete secondary tasks.

m:N operations↗

NASA NTRSDate not supplied

Preliminary Development of Multi-Vehicle (m:N) Operations with NASA Langley’s Remote Vehicle Operations Center

To achieve the vision of Advanced Air Mobility (AAM), a transition from localized operations of aircraft to remote operations is being pursued across many use cases. This transition will allow fewer human operators to manage more increasingly autonomous aircraft (i.e., m operators managing N vehicles, or m:N). To study this operational concept, the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) has developed a prototype remote vehicle operations center and ground control station (GCS) software to conduct research with simulated and real flight operations. To date, flight operations at LaRC have been limited to one vehicle per operator. However, the current paper describes initial development and considerations for enabling m:N flight operations at LaRC. Further, the research described in this paper provides the foundation for a concept of operations (ConOps) that will be developed to support remote operators managing multiple increasingly autonomous vehicles, with the goal of exploring human-autonomy teaming (HAT) concepts that enable more advanced m:N operations. Two key enablers have been identified to facilitate successful m:N operations: GCS software updates for multi-vehicle management and procedural updates for vehicle handoffs during off-nominal events. Additionally, specific modifications were identified across five key areas: technology and software, team structure, inter-team communication, contingency plans, and operator decision flows. Next steps in forming the LaRC m:N ConOps will include working with subject-matter experts to identify off-nominal scenarios, implementing the recommended GCS functionality for m:N operations, and performing integration testing of facility capabilities and new operational procedures. Although the future m:N ConOps will be tailored to the NASA LaRC remote operations facility and flight range, it is intended to be a transparent, accessible, and reality-based exemplar for external organizations seeking to create or evaluate their own m:N operational concepts.

m:N↗

NASA NTRS1998

Risk Management Structured for Today's Environment

Today's project management environment provides NASA with myriad challenges. We have smaller budgets and, consequently, smaller programs and shorter lead times. We have less money for development, and no money to recover from contingencies or mishaps. The NASA Administrator is leading the Agency away from operations, instilling a renewed focus on scientific research and the development and application of new cutting-edge technologies. We are using performance-based and fixed-price contracts with industry, and we are forming more and more partnerships with the international community. In addition to the environment, we have many NASA-unique conditions that challenge mission success. They include a higher level of performance requirements, limited production numbers, higher development efforts and cost, the inability to operate a space element fully under realistic conditions on the ground, limited access to the product during operation, and, of course, the need for more science for fewer dollars and on a shorter schedule.

Michael A. Greenfield↗

NASA NTRS2018

Small Unmanned Aerial System (UAS) Flight Testing of Enabling Vehicle Technologies for the UAS Traffic Management Project

Small unmanned aerial systems (sUAS) have been studied and results indicate that there is a large array of highly-beneficial applications. These applications are too numerous to list, but include search and rescue, fire spotting, precision agriculture, etc. to name a few. Typically sUAS vehicles weigh less than 55 pounds and will be performing flight operations in the presence of manned aircraft and other sUAS. Certain sUAS applications, such as package delivery, will include operations in the close proximity of the general public. The full benefit from sUAS is contingent upon the resolution of several technological areas to enable free and widespread use of these vehicles. Technological areas in question include, but are not limited to: autonomous sense and avoid and deconfliction of sUAS from other sUAS and manned aircraft, communications and interfaces between the vehicle and human operators, and high-reliability autonomous systems. The NASA UAS Traffic Management (UTM) project is endeavoring to develop a traffic management system and concept of operations for these types of vehicles. An extensive sUAS flight test effort was performed to partially address vehicle-related technological areas and to shape an understanding of future developmental and test efforts for vehicles intended to use the UTM traffic management system. The flight testing described herein had the following objectives: 1) Install and test Dedicated Short Range Communications (DSRC) systems developed for the automotive industry for potential sense and avoid sUAS applications; 2) Evaluate the use of cellular 4G systems to provide vehicle control; 3) Obtain high-resolution video imagery in support of image-based optical detection sense and avoid systems; 4) Acquire data in fixed-wing flight to support validation and maturation of an autonomous range containment system known as Safeguard in fixed-wing flight. A total of 53 flights were performed over 12 operational days at Beaver Dam Airpark in Elberon, VA. This work was sponsored by the UTM project that is part of the Aviation Operations and Safety Program (AOSP) at NASA.

Glaab, Louis J.↗

NASA NTRS2015

LADEE Preparations for Contingency Operations for the Lunar Orbit Insertion Maneuver

The Lunar Atmosphere and Dust Environment Explorer (LADEE) spacecraft was launched on September 6, 2013, and completed its mission on April 17, 2014 with a directed impact to the Lunar Surface. Its primary goals were to examine the lunar atmosphere, measure lunar dust, and to demonstrate high rate laser communications. The LADEE mission was a resounding success, achieving all mission objectives, much of which can be attributed to careful planning and preparation. This paper discusses the specific preparations for fault conditions that could occur during a highly-critical phase of the mission. To get to the Moon, the spacecraft traversed multiple phasing loops around the Earth, and then executed a breaking maneuver to achieve lunar orbit. This Lunar Orbit Insertion (LOI) maneuver was perhaps the most time-critical phase of the entire mission. The LOI maneuver had to occur within a twenty minute window in order to achieve lunar orbit with an acceptable amount of propellant remaining. Missing this window would have likely resulted in a loss of the entire mission. An additional challenge of the maneuver was that spacecraft was out of view for approximately one hour prior to the main thruster burn, with the burn needing to occur within five minutes after coming into view. These conditions resulted in unique challenges for ground operations and the fault management system. Early in the planning stages of the mission, the criticality and challenges of this maneuver were evident to the system designers. The major concern was that any triggering of the on-board fault management system, whether it is in response to a true fault or a false positive, would result in an unacceptable delay to the burn. Therefore the flight software was designed with a flexible fault management system, such that any or all of the fault management responses could be disabled for the lead up and execution of the maneuver. Later, a triage was conducted to develop a list of fault responses, mapped to various parts of the timeline of the maneuver. Some of these contingency responses were solely ground-based if the time to detect, diagnose, and respond were adequate. Other responses were automated on-board if the response time from the ground would have been inadequate. For instance, in order to recover from a system reboot, on-board automation would have automatically reconfigured the spacecraft for the burn and reoriented the spacecraft to the burn attitude.These contingency responses were practiced, over and over, during numerous rehearsals. Although the LOI maneuver was executed without having to use any of these contingencies, the LADEE team was adequately prepared for this highly critical phase of the mission.

Cannon, Howard↗

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 NTRS2002

High-Rate Communications Outage Recorder Operations for Optimal Payload and Science Telemetry Management Onboard the International Space Station

All International Space Station (ISS) Ku-band telemetry transmits through the High-Rate Communications Outage Recorder (HCOR). The HCOR provides the recording and playback capability for all payload, science, and International Partner data streams transmitting through NASA's Ku-band antenna system. The HCOR is a solid-state memory recorder that provides recording capability to record all eight ISS high-rate data during ISS Loss-of-Signal periods. NASA payloads in the Destiny module are prime users of the HCOR; however, NASDA and ESA will also utilize the HCOR for data capture and playback of their high data rate links from the Kibo and Columbus modules. Marshall Space Flight Center's Payload Operations Integration Center manages the HCOR for nominal functions, including system configurations and playback operations. The purpose of this paper is to present the nominal operations plan for the HCOR and the plans for handling contingency operations affecting payload operations. In addition, the paper will address HCOR operation limitations and the expected effects on payload operations. The HCOR is manifested for ISS delivery on flight 9A with the HCOR backup manifested on flight 11A. The HCOR replaces the Medium-Rate Communications Outage Recorder (MCOR), which has supported payloads since flight 5A.1.

Shell, Michael T.↗

NASA NTRS2012

Feasibility Study of Two Candidate Reaction Wheel/thruster Hybrid Control Architecture Designs for the Cassini Spacecraft

As the first spacecraft to achieve orbit at Saturn in 2004, Cassini has collected science data throughout its four-year prime mission (2004-08), and has since been approved for a first and second extended mission through 2017. Cassini carries a set of three "fixed" reaction wheels and a backup reaction wheel (reaction wheel #4) is mounted on top of an articulable platform. If necessary, this platform could be articulated to orient the backup reaction wheel with the degraded wheel. The reaction wheels are used primarily for attitude control when precise and stable pointing of a science instrument such as the narrow angle camera is required. In 2001-02, reaction wheel #3 exhibited signs of bearing cage instability. As a result, reaction wheel #4 was articulated to align with reaction wheel #3. Beginning in July 2003, Cassini was controlled using wheel #1, #2, and #4. From their first use in the spring of 2000 until today, reaction wheels #1 and #2 have accumulated more than3.5 billions revolutions each. As such, in spite of very carefully management of the wheel spin rates by the mission operation team, there are some observed increases in the drag torque of the wheels' bearings. Hence, the mission operations team must prepare for the contingency scenario in which the reaction wheel #1 (in addition to wheel #3) had degraded. In this hypothetical fault scenario, the two remaining reaction wheels (#2 and #4) will not be able to provide precise and stable three-axis control of the spacecraft. In this study, we evaluate the feasibility of controlling Cassini using the two remaining reaction wheels and four thrusters to meet the science pointing requirements for two key science operational modes: the Optical Remote Sensing and Downlink, Fields, Particles, & Waves operation modes. The performance (e.g., pointing control error, pointing stability, hydrazine consumption rate, etc.) of the hybrid controllers in both operations scenarios will be compared with those achieved using an all-thruster controller design. Strength and weaknesses of the hybrid control architecture are assessed quantitatively.

Cassini↗

NASA NTRS1996

Managing Situation Awareness on the Flight Deck

Awareness is required of the plane, the path and the people, both now and in the future. The steps to situation awareness are to monitor and evaluate the current situation. Anticipate the future to stay ahead of the airplane and consider contingencies, having a plan for 'what if situations. Continually update and modify the plan and share it with all crew members.

Chappell, Sheryl L.↗

NASA NTRS1999

STS-93: Columbia / Chandra Mission Overview (from JSC)

A press briefing held on July 7, 1999 reviews the progress of the Chandra X ray Observatory project. The tape begins with an animated view of the launch of the Chandra X ray Observatory from the shuttle, as it was planned. Next is a press briefing. Bryan Austin, the Lead Flight Director, discusses the five day mission, and the reason for the shortened length, due to the added weight from the Chandra Observatory. He also reviews the other payloads, and activities that will take place during the mission. Kenneth Ledbetter, Science Director Mission Development, discusses the 4 great observatories and the role of each. They are the Hubble, which observed visible light; Compton Gamma Ray Observatory, the Chandra, and the Space Infrared Telescope Facility. A time line of the expected operational lifetime of each of the 4 great observatories is shown. Specific information about the Chandra Telescope is reviewed. The last press briefing presenter is Fred Wojtalik, who is the Chandra Program Manager. He reviews the Chandra's components, and acknowledges a few of the many companies that contributed to its building. He also reviews the orbital activation and checkout sequences. Question that follows, center around contingency plans if some part of the planned sequence is not successful. The costs are reviewed, and concerns about the Initial Upper Stage, the propulsion unit required to take the Chandra to its high orbit are addressed. The Chandra is planned to take an eliptical orbit, which is higher than the other space telescopes, thus far launched due to the requirement to avoid Earth generated X rays.

Source record↗