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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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NASA NTRS2017

Beyond Control Centers

For NASA's Resource Prospector (RP) Lunar Rover Mission, we are moving away from a control center concept, to a fully distributed operation utilizing control nodes, with decision support from anywhere via mobile devices. This operations concept will utilize distributed information systems, notifications, mobile data access, and optimized mobile data display for off-console decision support. We see this concept of operations as a step in the evolution of mission operations from a central control center concept to a mission operations anywhere concept. The RP example is part of a trend, in which mission expertise for design, development and operations is distributed across countries and across the globe. Future spacecraft operations will be most cost efficient and flexible by following this distributed expertise, enabling operations from anywhere. For the RP mission we arrived at the decision to utilize a fully distributed operations team, where everyone operates from their home institution, based on evaluating the following factors: the requirement for physical proximity for near-real time command and control decisions; the cost of distributed control nodes vs. a centralized control center; the impact on training and mission preparation of flying the team to a central location. Physical proximity for operational decisions is seldom required, though certain categories of decisions, such as launch abort, or close coordination for mission or safety-critical near-real-time command and control decisions may benefit from co-location. The cost of facilities and operational infrastructure has not been found to be a driving factor for location in our studies. Mission training and preparation benefit from having all operators train and operate from home institutions.

Operations↗

NASA NTRS2006

Cassini Distributed Instrument Operations: What We've Learned Since Saturn Orbit Insertion

The Cassini mission to Saturn is complex with 12 science teams conducting distributed operations across the United States and Europe. Each Team includes scientists from around the world who actively participate in operations, including observation design, instrument commanding, downlink processing, and archiving. This represents a change in how JPL complex deep-space missions have been operated. Since Saturn Orbit Insertion (SOI), the Cassini Project has spent 17 months conducting science operations and has gained real-world experience that has tested the assumptions and rationale for this approach. We have learned that many of the expected benefits have been realized, but there were numerous unexpected challenges as well. This paper will discuss the lessons learned from the Cassini Tour experience to date. It will revisit the assumptions and rationale behind the distributed instrument operations design and will describe the results, good and bad, of implementing this method of operations. We will describe how Instrument Teams are structured, their roles and responsibilities, what challenges they faced going into orbital operations (the 'tour') and what creative solutions were proposed when funding limitations and schedule milestones prevented optimum solutions. We will also discuss the problems that have been encountered both on the ground and with the instruments, how these problems and anomalies were overcome, and what was learned along the way about the characteristics of distributed instrument operations.

Cassini↗

NASA NTRS2006

Cassini distributed instrument operations – what we’ve learned since Saturn orbit insertion

The Cassini mission to Saturn is complex with 12 science teams conducting distributed operations across the United States and Europe. Each Team includes scientists from around the world who actively participate in operations, including observation design, instrument commanding, downlink processing, and archiving. This represents a change in how JPL complex deep-space missions have been operated. Since Saturn Orbit Insertion (SOI), the Cassini Project has spent 17 months conducting science operations and has gained realworld experience that has tested the assumptions and rationale for this approach. We have learned that many of the expected benefits have been realized, but there were numerous unexpected challenges as well. This paper will discuss the lessons learned from the Cassini Tour experience to date. It will revisit the assumptions and rationale behind the distributed instrument operations design and will describe the results, good and bad, of implementing this method of operations. We will describe how Instrument Teams are structured, their roles and responsibilities, what challenges they faced going into orbital operations (the “tour”) and what creative solutions were proposed when funding limitations and schedule milestones prevented optimum solutions. We will also discuss the problems that have been encountered both on the ground and with the instruments, how these problems and anomalies were overcome, and what was learned along the way about the characteristics of distributed instrument operations.

Woncik, Pam↗

NASA NTRS2006

Implementing Distributed Operations: A Comparison of Two Deep Space Missions

Two very different deep space exploration missions--Mars Exploration Rover and Cassini--have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a mission of more than ten years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process. Additionally, MER has benefited from the initial co-location of its entire operations team, and from having a single Principal Investigator, while Cassini operations have had to reconcile multiple science teams distributed from before launch. Cassini has faced greater challenges in implementing effective distributed operations. Because extensive early planning is required to capture science opportunities on its tour and because sequence development takes significantly longer than sequence execution, multiple teams are contributing to multiple sequences concurrently. The complexity of integrating inputs from multiple teams is exacerbated by spacecraft operability issues and resource contention among the teams, each of which has their own Principal Investigator. Finally, much of the technology that MER has exploited to facilitate distributed operations was not available when the Cassini ground system was designed, although later adoption of web-based and telecommunication tools has been critical to the success of Cassini operations.

Cassini Mission↗

NASA NTRS1999

Flying Cassini With Virtual Operations Teams

The Cassini Program's challenge is to fly a large, complex mission with a reduced operations budget.

vitual↗

NASA NTRS2004

Science Opportunity Analyzer (SOA): Not Just Another Pretty Face

This viewgraph presentation reviews the Science Opportunity Analyzer (SOA). For the first time at JPL, the Cassini mission to Saturn is using distributed science operations for sequence generation. This means that scientist at other institutions has more responsibility to build the spacecraft sequence. Tools are required to support the sequence development. JPL tools required a complete configuration behind a firewall, and the tools that the user community had developed did not interface with the JPL tools. Therefore the SOA was created to bridge the gap between the remote scientists and the JPL operations teams. The presentation reviews the development of the SOA, and what was required of the system. The presentation reviews the functions that the SOA performed.

mission planning↗

NASA NTRS2006

Implementing distributed operations : a comparison of two Deep Space Missions

Two very different deep space exploration missions—Mars Exploration Rover and Cassini—have made use of distributed operations for their science teams. In the case of MER, the distributed operations capability was implemented only after the prime mission was completed, as the rovers continued to operate well in excess of their expected mission lifetimes; Cassini, designed for a prime mission of four years, had planned for distributed operations from its inception. The rapid command turnaround timeline of MER, as well as many of the operations features implemented to support it, have proven to be conducive to distributed operations. These features include: a single science team leader during the tactical operations timeline, highly integrated science and engineering teams, processes and file structures designed to permit multiple team members to work in parallel to deliver sequencing products, web-based spacecraft status and planning reports for team-wide access, and near-elimination of paper products from the operations process.

Larsen, Barbara↗

NASA NTRS1999

Automated Planning and Scheduling for Planetary Rover Distributed Operations

Automated planning and Scheduling, including automated path planning, has been integrated with an Internet-based distributed operations system for planetary rover operations. The resulting prototype system enables faster generation of valid rover command sequences by a distributed planetary rover operations team. The Web Interface for Telescience (WITS) provides Internet-based distributed collaboration, the Automated Scheduling and Planning Environment (ASPEN) provides automated planning and scheduling, and an automated path planner provided path planning. The system was demonstrated on the Rocky 7 research rover at JPL.

Backes, Paul G.↗

NASA NTRS2018

Information Displays and Crew Configurations for UTM Operations

In this paper we discuss how team configuration may influence how infor-mation is shared among team members for low-altitude Unmanned Aircraft Systems (UAS) operations. NASA collected and analyzed observation data gathered during a series of field tests for the UAS Traffic Management (UTM) project. The field tests were part of a larger effort aimed at advancing the UTM concept, conducted at six test-sites spread across the USA. Ground control station (GCS) concepts, flight-crew composition, and crew-size var-ied within and across test-sites. Flight crews took two strategic approaches to organizing their teams. The first of the two approaches was implemented by one third of the flight crews. These crews integrated the role of UTM opera-tor into the duties of existing crew members, merging the current roles with this new one, keeping the UTM Operator collocated with the flight crew. The remaining two thirds implemented a distributed team configuration, where a single UTM operator distributed support across multiple crews. Results from our data collection efforts revealed that UTM Operator location influenced whether flight crews used verbal communication versus displays to acquire UTM information.

teams↗

NASA NTRS2010

Implementation of a Relay Coordination System for the Mars Network

Mars network relay operations involve the coordination of lander and orbiter teams through long-term and short-term planning, tactical changes and post-pass analysis. Much of this coordination is managed through email traffic and point-to-point file data exchanges. It is often difficult to construct a complete and accurate picture of the relay situation at any given moment, as there is no centralized store of correlated relay data. The Mars Relay Operations Service (MaROS) is being implemented to address the problem of relay coordination for current and next-generation relay missions. The service is provided for the purpose of coordinating communications sessions between landed spacecraft assets and orbiting spacecraft assets at Mars. The service centralizes a set of functions previously distributed across multiple spacecraft operations teams, and as such greatly improves visibility into the end-to-end strategic coordination process. Most of the process revolves around the scheduling of communications sessions between the spacecraft during periods of time when a landed asset on Mars is geometrically visible by an orbiting spacecraft. These "relay" sessions are used to transfer data both to and from the landed asset via the orbiting asset on behalf of Earth-based spacecraft operators. This paper will discuss the relay coordination problem space, overview the architecture and design selected to meet system requirements, and describe the first phase of system implementation

Allard, Daniel A.↗

NASA NTRS2011

MaROS: Information Management Service

This software is provided by the Mars Relay Operations Service (MaROS) task to a variety of Mars projects for the purpose of coordinating communications sessions between landed spacecraft assets and orbiting spacecraft assets at Mars. The Information Management Service centralizes a set of functions previously distributed across multiple spacecraft operations teams, and as such, greatly improves visibility into the end-to-end strategic coordination process. Most of the process revolves around the scheduling of communications sessions between the spacecraft during periods of time when a landed asset on Mars is geometrically visible by an orbiting spacecraft. These relay sessions are used to transfer data both to and from the landed asset via the orbiting asset on behalf of Earth-based spacecraft operators. This software component is an application process running as a Java virtual machine. The component provides all service interfaces via a Representational State Transfer (REST) protocol over https to external clients. There are two general interaction modes with the service: upload and download of data. For data upload, the service must execute logic specific to the upload data type and trigger any applicable calculations including pass delivery latencies and overflight conflicts. For data download, the software must retrieve and correlate requested information and deliver to the requesting client. The provision of this service enables several key advancements over legacy processes and systems. For one, this service represents the first time that end-to-end relay information is correlated into a single shared repository. The software also provides the first multimission latency calculator; previous latency calculations had been performed on a mission-by-mission basis.

Allard, Daniel A.↗

NASA NTRS2018

CARA Devolution ESMO Pilot Program

Information regarding the current effort ongoing with CARA to determine the steps needed to have a mission move away from being supported by CARA, otherwise referred to as Devolving/Devolution. Information regarding the working group established to undertake this effort, documents agreed that needed to be written and plans for a parallel operations period. The communication between ESMO and CARA during the Parallel Operations period will be as the following: – A daily email will be sent from ESMO to CARA describing each HIE that is being actively planned and worked, and the action that ESMO is planning on taking – A weekly email will be sent from ESMO to CARA listing the progress toward achieving the parallel operations success criteria – The CARA team will remain on distribution for ESMO HIE communications and CAM invitations associated with DAMs/RMMs during the parallel operations period – At a minimum, 2 members of the CARA team will be in attendance at all ESMO planning and review discussions – A monthly email will be sent from ESMO to CARA with the HIE metrics • During parallel operations, ESMO will contact NASA Headquarters to report any redDevolution Working Group laid out and completed all steps needed to begin parallel operations • Parallel Ops for ESMO began on 11/26 (CARA in shadow mode only) • Any lessons learned from parallel ops will be folded back into documents/templates • Hope to achieve all success criteria < 6 months • Decision for permanent devolution will be based on completion of parallel ops and other future documentation creation (CARA Standard and Handbook, etc) and reviews (ORR) event which is less than 2 days from TCA, including the proposed remediation, on an as-needed daily basis flow using SpaceTrack to send and receive data

ESMO pilot devolution program↗

NASA NTRS1991

Magellan spacecraft team remote mission operations - Experience and application to future operations systems

The Magellan Venus radar mapping mission was NASA's first planetary launch in 11 years, heralding a successful return to unmanned planetary exploration. This paper first describes the spacecraft, its mission, and its Mission Operations System, including the remotely located spacecraft team. It then discusses how the flight team achieved mission success, in spite of the obstacles imposed by challenges from the spacecraft and its environment, which had to be resolved with the spacecraft team nearly 1000 miles distant from the rest of the flight team. Benefits of remotely distributed spacecraft operations are summarized and suggestions offered, based on Magellan experience, for future mission operations systems considering the use of distributed elements.

Ledbetter, Kenneth W.↗

NASA NTRS2016

Determination of Celestial Body Principal Axes via Gravity Field Estimation

The determination of physical parameters of celestial bodies provides critical navigational and scientific information. Determining the mass, rotation state, and density distribution is an important task of the navigation team on an operational mission. One representation of the internal density distribution, spherical harmonics, may be leveraged to compute the orientation of the principal axis frame of the celestial body, which in turn informs the dynamics of the body’s motion. Using data from NASA’s Dawn mission to the massive asteroids (1) Ceres and (4) Vesta, a method is proposed that refines the knowledge of the principal axis frame by utilizing estimated spherical harmonic coefficients. Applying an iterative rotation scheme to the solved-for body-fixed frame leads to convergence on a frame that is very close to the actual dynamical principal axis frame.

Takahashi, Yu↗

NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗

NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

activity planning↗

NASA NTRS2022

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol (Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

Kanefsky, Bob↗

NASA NTRS2002

A Virtual Mission Operations Center: Collaborative Environment

The Virtual Mission Operations Center - Collaborative Environment (VMOC-CE) intent is to have a central access point for all the resources used in a collaborative mission operations environment to assist mission operators in communicating on-site and off-site in the investigation and resolution of anomalies. It is a framework that as a minimum incorporates online chat, realtime file sharing and remote application sharing components in one central location. The use of a collaborative environment in mission operations opens up the possibilities for a central framework for other project members to access and interact with mission operations staff remotely. The goal of the Virtual Mission Operations Center (VMOC) Project is to identify, develop, and infuse technology to enable mission control by on-call personnel in geographically dispersed locations. In order to achieve this goal, the following capabilities are needed: Autonomous mission control systems Automated systems to contact on-call personnel Synthesis and presentation of mission control status and history information Desktop tools for data and situation analysis Secure mechanism for remote collaboration commanding Collaborative environment for remote cooperative work The VMOC-CE is a collaborative environment that facilitates remote cooperative work. It is an application instance of the Virtual System Design Environment (VSDE), developed by NASA Goddard Space Flight Center's (GSFC) Systems Engineering Services & Advanced Concepts (SESAC) Branch. The VSDE is a web-based portal that includes a knowledge repository and collaborative environment to serve science and engineering teams in product development. It is a "one stop shop" for product design, providing users real-time access to product development data, engineering and management tools, and relevant design specifications and resources through the Internet. The initial focus of the VSDE has been to serve teams working in the early portion of the system/product lifecycle - concept development, proposal preparation, and formulation. The VMOC-CE expands the application of the VSDE into the operations portion of the system lifecycle. It will enable meaningful and real-time collaboration regardless of the geographical distribution of project team members. Team members will be able to interact in satellite operations, specifically for resolving anomalies, through access to a desktop computer and the Internet. Mission Operations Management will be able to participate and monitor up to the minute status of anomalies or other mission operations issues. In this paper we present the VMOC-CE project, system capabilities, and technologies.

Medina, Barbara↗