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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Space Station Mission Planning System (MPS) development study. Volume 2

The process and existing software used for Spacelab payload mission planning were studied. A complete baseline definition of the Spacelab payload mission planning process was established, along with a definition of existing software capabilities for potential extrapolation to the Space Station. This information was used as a basis for defining system requirements to support Space Station mission planning. The Space Station mission planning concept was reviewed for the purpose of identifying areas where artificial intelligence concepts might offer substantially improved capability. Three specific artificial intelligence concepts were to be investigated for applicability: natural language interfaces; expert systems; and automatic programming. The advantages and disadvantages of interfacing an artificial intelligence language with existing FORTRAN programs or of converting totally to a new programming language were identified.

Klus, W. J.↗
NASA NTRS1971

Launch Vehicle Estimating Factors for Use in Advance Space Mission Planning

This launch vehicle reference document contains mission characteristic and launch vehicle capability data for use by NASA and particularly the Office of Space Science and Applications (OSSA) in the preparation of future mission plans. The data in this reference book are derived from sources that are considered to be sufficiently accurate for advance planning. In no instance should these data be used for detailed mission planning without concurrence of the Director of Launch Vehicle and Propulsion Programs. This edition reflects updates in vehicle performance and possible availability and introduces a section on the Space Shuttle. The Shuttle section has been coordinated with the Office of Manned Space Flight.

McGolrick, Joseph E.↗
NASA NTRS1993

Natural environment application for NASP-X-30 design and mission planning

The NASA/MSFC Mission Analysis Program has recently been utilized in various National Aero-Space Plane (NASP) mission and operational planning scenarios. This paper focuses on presenting various atmospheric constraint statistics based on assumed NASP mission phases using established natural environment design, parametric, threshold values. Probabilities of no-go are calculated using atmospheric parameters such as temperature, humidity, density altitude, peak/steady-state winds, cloud cover/ceiling, thunderstorms, and precipitation. The program although developed to evaluate test or operational missions after flight constraints have been established, can provide valuable information in the design phase of the NASP X-30 program. Inputting the design values as flight constraints the Mission Analysis Program returns the probability of no-go, or launch delay, by hour by month. This output tells the X-30 program manager whether the design values are stringent enough to meet his required test flight schedules.

Johnson, D. L.↗
NASA NTRS1995

Mission planning for the Lidar in Space Technology Experiment

Developing a mission planning system for a Space Shuttle mission is a complex procedure. Several months of preparation are required to develop a plan that optimizes science return during the short operations time frame. Further complicating the scenario is the necessity to schedule around crew activities and other payloads which share Orbiter resources. SpaceTec, Inc. developed the mission planning system for the Lidar In Space Technology Experiment, or LITE, which flew on Space Shuttle mission STS-64 in September of 1994. SpaceTec used a combination of off-th-shelf and in-house developed software to analyze various mission scenarios both premission and real-time during the flight. From this analysis, SpaceTec developed a comprehensive mission plan that met the mission objectives.

Redifer, Matthew E.↗
NASA NTRS2010

Improving the Operations of the Earth Observing One Mission via Automated Mission Planning

We describe the modeling and reasoning about operations constraints in an automated mission planning system for an earth observing satellite - EO-1. We first discuss the large number of elements that can be naturally represented in an expressive planning and scheduling framework. We then describe a number of constraints that challenge the current state of the art in automated planning systems and discuss how we modeled these constraints as well as discuss tradeoffs in representation versus efficiency. Finally we describe the challenges in efficiently generating operations plans for this mission. These discussions involve lessons learned from an operations model that has been in use since Fall 2004 (called R4) as well as a newer more accurate operations model operational since June 2009 (called R5). We present analysis of the R5 software documenting a significant (greater than 50%) increase in the number of weekly observations scheduled by the EO-1 mission. We also show that the R5 mission planning system produces schedules within 15% of an upper bound on optimal schedules. This operational enhancement has created value of millions of dollars US over the projected remaining lifetime of the EO-1 mission.

Chien, Steve A.↗
NASA NTRS2017

Towards the Development of a Global, Satellite-Based, Terrestrial Snow Mission Planning Tool

A global, satellite-based, terrestrial snow mission planning tool is proposed to help inform experimental mission design with relevance to snow depth and snow water equivalent (SWE). The idea leverages the capabilities of NASA's Land Information System (LIS) and the Tradespace Analysis Tool for Constellations (TAT-C) to harness the information content of Earth science mission data across a suite of hypothetical sensor designs, orbital configurations, data assimilation algorithms, and optimization and uncertainty techniques, including cost estimates and risk assessments of each hypothetical permutation. One objective of the proposed observing system simulation experiment (OSSE) is to assess the complementary or perhaps contradictory information content derived from the simultaneous collection of passive microwave (radiometer), active microwave (radar), and LIDAR observations from space-based platforms. The integrated system will enable a true end-to-end OSSE that can help quantify the value of observations based on their utility towards both scientific research and applications as well as to better guide future mission design. Science and mission planning questions addressed as part of this concept include: What observational records are needed (in space and time) to maximize terrestrial snow experimental utility? How might observations be coordinated (in space and time) to maximize this utility? What is the additional utility associated with an additional observation? How can future mission costs be minimized while ensuring Science requirements are fulfilled?

Mission Desig↗
NASA NTRS2017

Towards the Development of a Global, Satellite-based, Terrestrial Snow Mission Planning Tool

A global, satellite-based, terrestrial snow mission planning tool is proposed to help inform experimental mission design with relevance to snow depth and snow water equivalent (SWE). The idea leverages the capabilities of NASAs Land Information System (LIS) and the Tradespace Analysis Tool for Constellations (TAT C) to harness the information content of Earth science mission data across a suite of hypothetical sensor designs, orbital configurations, data assimilation algorithms, and optimization and uncertainty techniques, including cost estimates and risk assessments of each hypothetical orbital configuration.One objective the proposed observing system simulation experiment (OSSE) is to assess the complementary or perhaps contradictory information content derived from the simultaneous collection of passive microwave (radiometer), active microwave (radar), and LIDAR observations from space-based platforms. The integrated system will enable a true end-to-end OSSE that can help quantify the value of observations based on their utility towards both scientific research and applications as well as to better guide future mission design. Science and mission planning questions addressed as part of this concept include:1. What observational records are needed (in space and time) to maximize terrestrial snow experimental utility?2. How might observations be coordinated (in space and time) to maximize utility? 3. What is the additional utility associated with an additional observation?4. How can future mission costs being minimized while ensuring Science requirements are fulfilled?

Mission Design↗
NASA NTRS2009

Mission Planning and Scheduling System for NASA's Lunar Reconnaissance Mission

In the framework of NASA's return to the Moon efforts, the Lunar Reconnaissance Orbiter (LRO) is the first step. It is an unmanned mission to create a comprehensive atlas of the Moon's features and resources necessary to design and build a lunar outpost. LRO is scheduled for launch in April, 2009. LRO carries a payload comprised of six instruments and one technology demonstration. In addition to its scientific mission LRO will use new technologies, systems and flight operations concepts to reduce risk and increase productivity of future missions. As part of the effort to achieve robust and efficient operations, the LRO Mission Operations Team (MOT) will use its Mission Planning System (MPS) to manage the operational activities of the mission during the Lunar Orbit Insertion (LOI) and operational phases of the mission. The MPS, based on GMV's flexplan tool and developed for NASA with Honeywell Technology Solutions (prime contractor), will receive activity and slew maneuver requests from multiple science operations centers (SOC), as well as from the spacecraft engineers. flexplan will apply scheduling rules to all the requests received and will generate conflict free command schedules in the form of daily stored command loads for the orbiter and a set of daily pass scripts that help automate nominal real-time operations.

Garcia, Gonzalo↗
NASA NTRS1976

Scheduling algorithm for mission planning and logistics evaluation users' guide

The scheduling algorithm for mission planning and logistics evaluation (SAMPLE) program is a mission planning tool composed of three subsystems; the mission payloads subsystem (MPLS), which generates a list of feasible combinations from a payload model for a given calendar year; GREEDY, which is a heuristic model used to find the best traffic model; and the operations simulation and resources scheduling subsystem (OSARS), which determines traffic model feasibility for available resources. The SAMPLE provides the user with options to allow the execution of MPLS, GREEDY, GREEDY-OSARS, or MPLS-GREEDY-OSARS.

Chang, H.↗
NASA NTRS1990

Applications of artificial intelligence to mission planning

The scheduling problem facing NASA-Marshall mission planning is extremely difficult for several reasons. The most critical factor is the computational complexity involved in developing a schedule. The size of the search space is large along some dimensions and infinite along others. It is because of this and other difficulties that many of the conventional operation research techniques are not feasible or inadequate to solve the problems by themselves. Therefore, the purpose is to examine various artificial intelligence (AI) techniques to assist conventional techniques or to replace them. The specific tasks performed were as follows: (1) to identify mission planning applications for object oriented and rule based programming; (2) to investigate interfacing AI dedicated hardware (Lisp machines) to VAX hardware; (3) to demonstrate how Lisp may be called from within FORTRAN programs; (4) to investigate and report on programming techniques used in some commercial AI shells, such as Knowledge Engineering Environment (KEE); and (5) to study and report on algorithmic methods to reduce complexity as related to AI techniques.

Ford, Donnie R.↗
NASA NTRS2005

Tools of the Future: How Decision Tree Analysis Will Impact Mission Planning

The universe is infinitely complex; however, the human mind has a finite capacity. The multitude of possible variables, metrics, and procedures in mission planning are far too many to address exhaustively. This is unfortunate because, in general, considering more possibilities leads to more accurate and more powerful results. To compensate, we can get more insightful results by employing our greatest tool, the computer. The power of the computer will be utilized through a technology that considers every possibility, decision tree analysis. Although decision trees have been used in many other fields, this is innovative for space mission planning. Because this is a new strategy, no existing software is able to completely accommodate all of the requirements. This was determined through extensive research and testing of current technologies. It was necessary to create original software, for which a short-term model was finished this summer. The model was built into Microsoft Excel to take advantage of the familiar graphical interface for user input, computation, and viewing output. Macros were written to automate the process of tree construction, optimization, and presentation. The results are useful and promising. If this tool is successfully implemented in mission planning, our reliance on old-fashioned heuristics, an error-prone shortcut for handling complexity, will be reduced. The computer algorithms involved in decision trees will revolutionize mission planning. The planning will be faster and smarter, leading to optimized missions with the potential for more valuable data.

Otterstatter, Matthew R.↗
NASA NTRS2018

Cassini's Grand Finale: A Mission Planning Retrospective

On September 15, 2017, Cassini plunged deep into Saturn, down to where the atmosphere was sufficiently dense to destroy the spacecraft, making it part of Saturn forever. In the five months leading up to its destruction, Cassini flew between Saturn and its rings 22 times, collecting data from the never before-explored region of the Kronian system. These orbits, the Grand Finale of Cassini, were the culmination of years of planning by the Cassini flight team. This paper looks back upon the mission planning effort in particular, comparing the baseline operational scenarios and contingency plans to the as flown Grand Finale. The bulk of the Grand Finale mission planning effort was focused on the environmental hazards present in the region between Saturn and its rings: the dust and the atmosphere. Dust hazard and atmospheric transit contingency plans were in place to help ensure spacecraft health and maximize science data return. The dust hazard plan gave the operations team the option to turn the spacecraft to a safe attitude during ring-plane crossings had the dust environment proved more threatening than anticipated. The atmospheric transit plan would have made use of an orbital trim maneuver in order to raise or lower periapsis depending on the density of the atmosphere. The proximal environment did have its surprises, though they were good surprises. The dust was significantly less hazardous than predicted. So much so that elements of the contingency plan were leveraged in order to remove a dust hazard protection from the baseline plan, rather than add one to it. While the atmosphere was substantially denser than predicted, it was not dense enough to warrant a periapsis-raise maneuver and actually meant that better in-situ data was gathered. Ultimately, from a mission planning perspective, the Grand Finale went better than expected.

Sturm II, Erick J.↗
NASA NTRS2006

Development and Execution of End-of-Mission Operations Case Study of the UARS and ERBS End-of-Mission Plans

This Paper is a case study of the development and execution of the End-of-Mission plans for the Earth Radiation Budget Satellite (ERBS) and the Upper Atmosphere Research Satellite (UARS). The goals of the End-of-Mission Plans are to minimize the time the spacecraft remains on orbit and to minimize the risk of creating orbital debris. Both of these Missions predate the NASA Management Instructions (NMI) that directs missions to provide for safe mission termination. Each spacecrafts had their own unique challenges, which required assessing End-of-Mission requirements versus spacecraft limitations. Ultimately the End-of- Mission operations were about risk mitigation. This paper will describe the operational challenges and the lessons learned executing these End-of-Mission Plans

Hughes, John↗
NASA NTRS1993

Mission planning for an Earth observation low Earth orbiter: ERS-1

ERS-1, the first European Remote Sensing satellite, has a payload which consists primarily of microwave instruments and is in a polar sun-synchronous orbit. All ground and on-board activities from user requests to delivery of data products are combined into one integrated system. In view of the high number of products which can be generated by ERS-1, the Mission Planning System (MPS), which plans the on-board activities of ERS-1, is an essential tool for operations since manual planning of the large number of daily operations is out of the question. In addition the MPS, in line with the integrated nature of the ERS-1 system, also plans activities at the prime ground station, including among others, the operation of the payload data processing systems there. This paper outlines the operations concepts for ERS-1 mission planning, and describes the Mission Planning System used at the ERS-1 Control Center. Novel functionalities, such as automatic resource clash resolution, are described. A critical discussion gives lessons learned for future mission planning systems.

Lockyer, Paul↗
NASA NTRS2006

Stardust Entry: Landing and Population Hazards in Mission Planning and Operations

The 385 kg Stardust mission was launched on Feb 7, 1999 on a mission to collect samples from the tail of comet Wild 2 and from interplanetary space. Stardust returned to Earth in the early morning of January 15, 2006. The sample return capsule landed in the Utah Test and Training Range (UTTR) southwest of Salt Lake City. Because Stardust was landing on Earth, hazard analysis was required by the National Aeronautics and Space Administration, UTTR, and the Stardust Project to ensure the safe return of the landing capsule along with the safety of people, ground assets, and aircraft. This paper focuses on the requirements affecting safe return of the capsule and safety of people on the ground by investigating parameters such as probability of impacting on UTTR, casualty expectation, and probability of casualty. This paper introduces the methods for the calculation of these requirements and shows how they affected mission planning, site selection, and mission operations. By analyzing these requirements before and during entry it allowed for the selection of a robust landing point that met all of the requirements during the actual landing event.

Desai, P.↗
NASA NTRS1985

On orbit mission planning using the shuttle trajectory and launch window expert system

With the Space Transportation System (STS) entering the operational era, the need for standardized, automated, mission planning computer tools has become apparent. In order to support an increased flight rate without an increase in manpower, quicker and more efficient methods are needed to perform standard tasks. The Shuttle Trajectory and Launch Window Expert System (STALEX) was developed to automate many aspects of early mission planning for space shuttle missions carrying geosynchronous communications satellites. Most of the commercial Shuttle missions planned for the next 3 years will carry at least one of this type of satellite. The applications of STALEX include payload deployment scheduling, launch window analysis, orbital trajectory determination, and landing opportunity selection.

Ahlf, P. R.↗