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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Mission operations management

Redefining the approach and philosophy that operations management uses to define, develop, and implement space missions will be a central element in achieving high efficiency mission operations for the future. The goal of a cost effective space operations program cannot be realized if the attitudes and methodologies we currently employ to plan, develop, and manage space missions do not change. A management philosophy that is in synch with the environment in terms of budget, technology, and science objectives must be developed. Changing our basic perception of mission operations will require a shift in the way we view the mission. This requires a transition from current practices of viewing the mission as a unique end product, to a 'mission development concept' built on the visualization of the end-to-end mission. To achieve this change we must define realistic mission success criteria and develop pragmatic approaches to achieve our goals. Custom mission development for all but the largest and most unique programs is not practical in the current budget environment, and we simply do not have the resources to implement all of our planned science programs. We need to shift our management focus to allow us the opportunity make use of methodologies and approaches which are based on common building blocks that can be utilized in the space, ground, and mission unique segments of all missions.

Rocco, David A.↗
NASA NTRS2008

Juno Mission Simulation

The Juno spacecraft is planned to launch in August of 2012 and would arrive at Jupiter four years later. The spacecraft would spend more than one year orbiting the planet and investigating the existence of an ice-rock core; determining the amount of global water and ammonia present in the atmosphere, studying convection and deep- wind profiles in the atmosphere; investigating the origin of the Jovian magnetic field, and exploring the polar magnetosphere. Juno mission management is responsible for mission and navigation design, mission operation planning, and ground-data-system development. In order to ensure successful mission management from initial checkout to final de-orbit, it is critical to share a common vision of the entire mission operation phases with the rest of the project teams. Two major challenges are 1) how to develop a shared vision that can be appreciated by all of the project teams of diverse disciplines and expertise, and 2) how to continuously evolve a shared vision as the project lifecycle progresses from formulation phase to operation phase. The Juno mission simulation team addresses these challenges by developing agile and progressive mission models, operation simulations, and real-time visualization products. This paper presents mission simulation visualization network (MSVN) technology that has enabled a comprehensive mission simulation suite (MSVN-Juno) for the Juno project.

space vehicles↗
NASA NTRS2006

STS-121: Discovery Post Launch Press Briefing

The briefing begins with Dean Acousta (NASA Press Secretary) introducing Michael Griffin (NASA Administrator), Bill Gerstenmaier (Associate Administrator for Space Operations) Wayne Hale (Space Shuttle Program Manager), John Shannon (Chairman, Mission Management Team, JSC), and Mike Leinbach (NASA Launch Director). The teams effort and dedication paid off in the form of a perfect launch and the weather cooperated. The Mission Management Team no problems during inspection. Debris assessment at 2 min. 47 sec. and 4 min. 50 sec. will be discussed when that information becomes available.The floor was then open for questions from the press.

Source record↗
NASA NTRS2006

Advanced Technologies for Future Spacecraft Cockpits and Space-based Control Centers

The National Aeronautics and Space Administration (NASA) is embarking on a new era of Space Exploration, aimed at sending crewed spacecraft beyond Low Earth Orbit (LEO), in medium and long duration missions to the Lunar surface, Mars and beyond. The challenges of such missions are significant and will require new technologies and paradigms in vehicle design and mission operations. Current roles and responsibilities of spacecraft systems, crew and the flight control team, for example, may not be sustainable when real-time support is not assured due to distance-induced communication lags, radio blackouts, equipment failures, or other unexpected factors. Therefore, technologies and applications that enable greater Systems and Mission Management capabilities on-board the space-based system will be necessary to reduce the dependency on real-time critical Earth-based support. The focus of this paper is in such technologies that will be required to bring advance Systems and Mission Management capabilities to space-based environments where the crew will be required to manage both the systems performance and mission execution without dependence on the ground. We refer to this concept as autonomy. Environments that require high levels of autonomy include the cockpits of future spacecraft such as the Mars Exploration Vehicle, and space-based control centers such as a Lunar Base Command and Control Center. Furthermore, this paper will evaluate the requirements, available technology, and roadmap to enable full operational implementation of onboard System Health Management, Mission Planning/re-planning, Autonomous Task/Command Execution, and Human Computer Interface applications. The technology topics covered by the paper include enabling technology to perform Intelligent Caution and Warning, where the systems provides directly actionable data for human understanding and response to failures, task automation applications that automate nominal and Off-nominal task execution based on human input or integrated health state-derived conditions. Shifting from Systems to Mission Management functions, we discuss the role of automated planning applications (tactical planning) on-board, which receive data from the other cockpit automation systems and evaluate the mission plan against the dynamic systems and mission states and events, to provide the crew with capabilities that enable them to understand, change, and manage the timeline of their mission. Lastly, we discuss the role of advanced human interface technologies that organize and provide the system md mission information to the crew in ways that maximize their situational awareness and ability to provide oversight and control of aLl the automated data and functions.

Garcia-Galan, Carlos↗
NASA NTRSDate not supplied

Achieving Resilient In-Flight Performance for Advanced Air Mobility through Simplified Vehicle Operations

A research and development (R&D) approach is proposed for developing and validating concepts and technologies to achieve vehicle autonomy goals of Advanced Air Mobility (AAM) through Simplified Vehicle Operations (SVO). The approach applies resilience-engineering and human-automation teaming (HAT) principles to a framework for defining vehicle-based functions for the management of missions and flight trajectories, focusing initially on the en route flight domain. To achieve the SVO goal of reducing pilot training requirements and thereby increasing the pilot pool for AAM, while at the same time promoting ever-safer operations, a framework for identifying essential functions is proposed. In this framework, functions are first categorized by high-level functional purpose (mission management, flightpath management, tactical operations, and vehicle control) and then subcategorized by attributes of resilient-performing systems (abilities to monitor, respond, learn, and anticipate). The categorization by functional purpose provides structure within which HAT designs can be holistically explored and total levels of human vs. automation responsibility can be varied. The subcategorization by resilient-system attributes provides a mechanism for capturing safety-critical functions that may not be codified in current operational procedures and training curricula, particularly those where humans proactively enhance safety in currently undocumented ways. An R&D approach consisting of seven strategies is proposed in which automation engineering and human-factors communities can collaborate in the research, development, and design of an SVO roadmap to enable the ambitious objectives of AAM.

AAM↗
NASA NTRSDate not supplied

A Technical Overview of the Mission Engagement Onboarding Process Managed by the Mission Engagement Working Group (MEWG)

NASA's intricate network, encompassing the Near Space Network (NSN) and Deep Space Network (DSN), plays a pivotal role in supporting an array of space missions. These range from those in Low Earth Orbit (LEO) and Geosynchronous Orbit (GEO), to the more distant Cislunar and Deep Space endeavors. To manage the vast communications needs, we utilize multiple ground stations globally, coupled with the Tracking and Data Relay Satellite System (TDRSS). The Mission Engagement Working Group (MEWG), within the Commercialization, Innovation, and Synergies (CIS) division, stands as the primary gateway for all Space Communications and Network (SCaN) communication and navigation requests. This includes not only NASA's internal missions but also extends to other governmental agencies and commercial sector endeavors. How does the MEWG Process Work? - Initial Contact : Clients initiate their interaction with the NSN by submitting their service requirements through a dedicated online portal. - Preliminary Assessment by MEWG: Upon submission, MEWG embarks on a primary screening of the request. This involves evaluating the client's identity and the foundational concept of their mission. - Detailed Analysis by the NSN Team: Parallelly, the NSN team conducts a comprehensive review of the service request. This often necessitates additional clarification from the requester, ensuring that the final assessment is both thorough and accurate. - Coordination & Streamlining: MEWG's overarching objective is to effectively log, classify, orchestrate, and guarantee that pertinent actions are delegated based on initial client interactions. Acting as the central hub for these primary contacts, MEWG ensures that each request is sufficiently detailed for an in-depth evaluation. - Feedback & Remediation: If a request is deemed unsuitable or lacking, MEWG doesn't merely reject it. Instead, the team discerns the reasons for the inadequacy and suggests potential rectification strategies. This approach ensures that feedback delivered to clients is precise, prompt, constructive, and actionable. Conclusion: This plenary presentation will detail the efforts of the MEWG resulting in a greatly streamlined and refined onboarding process for space communication Direct-To-Earth (DTE) and Space Relay (SR) support requests. By centralizing the preliminary interactions and assessments, we've reduced the complexity for clients, ensuring they engage with a singular, efficient, and responsive point of contact. This initiative, we believe, fortifies NASA's commitment to fostering effective and synergistic collaborations with its partners.

Devin L Bitner↗
NASA NTRSDate not supplied

A Technical Overview of the Mission Engagement Onboarding Process Managed by the Mission Engagement Working Group (MEWG)

NASA's intricate network, encompassing the Near Space Network (NSN) and Deep Space Network (DSN), plays a pivotal role in supporting an array of space missions. These range from those in Low Earth Orbit (LEO) and Geosynchronous Orbit (GEO), to the more distant Cislunar and Deep Space endeavors. To manage the vast communications needs, we utilize multiple ground stations globally, coupled with the Tracking and Data Relay Satellite System (TDRSS). The Mission Engagement Working Group (MEWG), within the Commercialization, Innovation, and Synergies (CIS) division, stands as the primary gateway for all Space Communications and Network (SCaN) communication and navigation requests. This includes not only NASA's internal missions but also extends to other governmental agencies and commercial sector endeavors. How does the MEWG Process Work? - Initial Contact : Clients initiate their interaction with the NSN by submitting their service requirements through a dedicated online portal. - Preliminary Assessment by MEWG: Upon submission, MEWG embarks on a primary screening of the request. This involves evaluating the client's identity and the foundational concept of their mission. - Detailed Analysis by the NSN Team: Parallelly, the NSN team conducts a comprehensive review of the service request. This often necessitates additional clarification from the requester, ensuring that the final assessment is both thorough and accurate. - Coordination & Streamlining: MEWG's overarching objective is to effectively log, classify, orchestrate, and guarantee that pertinent actions are delegated based on initial client interactions. Acting as the central hub for these primary contacts, MEWG ensures that each request is sufficiently detailed for an in-depth evaluation. - Feedback & Remediation: If a request is deemed unsuitable or lacking, MEWG doesn't merely reject it. Instead, the team discerns the reasons for the inadequacy and suggests potential rectification strategies. This approach ensures that feedback delivered to clients is precise, prompt, constructive, and actionable. Conclusion: This plenary presentation will detail the efforts of the MEWG resulting in a greatly streamlined and refined onboarding process for space communication Direct-To-Earth (DTE) and Space Relay (SR) support requests. By centralizing the preliminary interactions and assessments, we've reduced the complexity for clients, ensuring they engage with a singular, efficient, and responsive point of contact. This initiative, we believe, fortifies NASA's commitment to fostering effective and synergistic collaborations with its partners.

Devin Bitner↗
NASA NTRS1972

Vehicle management and mission planning systems with shuttle applications

A preliminary definition of a concept for an automated system is presented that will support the effective management and planning of space shuttle operations. It is called the Vehicle Management and Mission Planning System (VMMPS). In addition to defining the system and its functions, some of the software requirements of the system are identified and a phased and evolutionary method is recommended for software design, development, and implementation. The concept is composed of eight software subsystems supervised by an executive system. These subsystems are mission design and analysis, flight scheduler, launch operations, vehicle operations, payload support operations, crew support, information management, and flight operations support. In addition to presenting the proposed system, a discussion of the evolutionary software development philosophy that the Mission Planning and Analysis Division (MPAD) would propose to use in developing the required supporting software is included. A preliminary software development schedule is also included.

Source record↗
NASA NTRS1984

Missions/Planning Panel

A panel discussion was held to develop a viewpoint of space power technology needs and state of readiness for future mission scenarios. Among the points made in the discussion, it was agreed that missions, particularly the far term ones, do serve to drive technology; however, as the missions become nearer term, issues of schedule and cost severely limit the willingness to accept risk. There are, in fact, no rewards to a mission manager for introducing new technology. Mission downscaling is the usual response to technology limitations. All panelists agreed that there exists a serious gap between when technologists feel their job is done and what mission managers need for decision. Typically a two to three year engineering development gap exists. It is essential to take technologies to the engineering model level and conduct a flight demonstration to close this gap. All agreed that increased effort should be made to achieve stronger interactions between planners and technologists and that workshops like the present one are a step in the right direction. Technologists need mission credibility and vice versa.

Fordyce, J. S.↗
NASA NTRS1973

Vehicle management and mission planning in support of shuttle operations.

An operational approach to shuttle mission planning during high flight frequency years (20 or more flights per year) is described wherein diverse mission planning functions interface via an interactive computer system and common data base. The Vehicle Management and Mission Planning System (VMMPS) is proposed as a means of helping to accomplish the mission planning function. The VMMPS will link together into an interactive system the major mission planning areas such as trajectory, crew, vehicle performance, and launch operations. A common data base will be an integral part of the system and the concept of standard mission types and phases will be used to minimize mission to mission uniqueness. The use of this system will eliminate much redundancy and replanning, shorten interface times between functions, and provide a means to evaluate unplanned events and modify schedules.

Pruett, W. R.↗
NASA NTRS2019

Managing Flagship Missions to Reduce Cost and Schedule

Flagship missions are highly complex with highly nested systems. This level of complexity poses unique management problems as complexity influences risk which, in turn, affects cost and schedule. Establishing a strong technical and programmatic leadership team is critical to mission success. Developing and using a mission architecture is critical to informing the management organization, product ownership, interface and integration relationships, schedule organization, and integration and test paths. In highly nested systems, the mission phasing can be significantly out of sync with product phasing. Targeted technology development prior to Phase A is critical to reducing risk. Early architecture, concept design, and requirements development is critical to reducing risk. Modular design; pathfinders; parallel manufacturing and integration and test paths; and properly handling institutional requirements across interfaces are all management techniques that can be applied to reduce risk. NASA’s large strategic missions, sometimes referred to as flagship missions, are designed to provide answers to some of the most compelling scientific questions being asked. These types of missions are a series of highly nested subsystems that pose unique management problems when compared to more traditional instrument and spacecraft designs. They typically have an overall architecture that is very complex and nested; they typically require a tremendous amount of technology development; they typically involve many contractors and subcontractors with many associated contracts; and they typically involve staff from all over the world. Successful management of a flagship requires the balance between science requirements, engineering and technology capabilities, and resource constraints. Mismanaging these flagship missions can and will lead to significant cost and schedule growth, both of which are detrimental to NASA’s overall reputation which, in turn, is detrimental to the development of future flagship missions. While many of the same management principles used on smaller instruments and spacecraft are relevant, managing flagship missions requires an evolution of those current best practices to better address the specific needs and additional complexity and vastness of these missions. This paper explores how to leverage lessons learned from previous flagship missions to better manage flagship missions in the future.

Hylan, Jason↗
NASA NTRS1976

The first Spacelab mission

The purpose of Spacelab, an Orbiter-mounted NASA/ESA laboratory, is to include in the Space Transportation System (STS) a payload carrier with maximum flexibility to accommodate multidisciplinary scientific payloads. The major Spacelab configurations obtained by combination of two basic elements, the module and pallet, are described along with the anticipated program of experiments and payloads, and mission management general concept. The first Spacelab 7-day mission is scheduled for flight in the second half of 1980, with the primary objective being to verify system performance capabilities. Detailed attention is given to the payload mission management responsibilities for the first flight, including program control, science management, payload interfaces, integrated payload mission planning, integration requirements, payload specialist training, payload integration, launch site integration, payload flight/mission operations, and postmission activities. The Spacelab configuration (including the long module and one pallet) and the overall schedule for this mission are presented.

Pace, R. E., Jr.↗
NASA NTRS2023

Distributed Sensing and Reasoning for Advanced Air Mobility Health Management and Mission Assurance

As envisioned, Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) will introduce new vehicles and operations within the national airspace, moving people and cargo safely and efficiently at a much larger scale than today. Driven by transformative technology and revolutionary aircraft, this movement must still manage technical, regulatory, operational, and policy challenges. NASA’s work in support of AAM and UAM includes, but is not limited to tools, technologies, and architectures for distributed sensing of aircraft, data & reasoning services exchange, Human-Autonomy Teaming (HAT), contingency management, and vehicle health management. This paper builds upon these concepts and evaluates the use of distributed sensing and infrastructure assistance towards health management and mission assurance of UAM vehicles in specific operational scenarios. Through analysis of these example missions, aided by the data produced by the conceptual distributed sensing and reasoning infrastructure, we define opportunities for state estimation, diagnosis, and key decision points affecting the health state of the vehicle and the airspace volume. As a result, we define a number of measurable health state parameters providing relevant information to drive decision-making in contingency situations or feed automation tools in support of operators and managers.

Safety↗
NASA NTRS1974

TERSSE: Definition of the Total Earth Resources System for the Shuttle Era. Volume 3: Mission and System Requirements for the Total Earth Resources System

Resource management missions to be performed by TERSSE are described. Mission and user requirements are defined along with information flows developed for each major resource management mission. Other topics discussed include: remote sensing platforms, remote sensor requirements, ground system architecture, and such related issues as cloud cover, resolution, orbit mechanics, and aircraft versus satellite.

Source record↗
NASA NTRSDate not supplied

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy↗
NASA NTRSDate not supplied

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy↗