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At least 91 records · Page 5

Simulated annealing in orbital flight planning

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is unique because the space station will define the first true multivehicle environment in space. The optimization yields surfaces which are potentially complex, with multiple local minima. Because of the likelihood of these local minima, descent techniques are unable to offer robust solutions. Other deterministic optimization techniques were explored without success. The simulated annealing optimization is capable of identifying a minimum-fuel, two-burn trajectory subject to four constraints. Furthermore, the computational efforts involved in the optimization are such that missions could be planned on board the space station. Potential applications could include the on-site planning of rendezvous with a target craft of the emergency rescue of an astronaut. Future research will include multiwaypoint maneuvers, using a knowledge base to guide the optimization.

Soller, Jeffrey↗

Advanced software development workstation. Knowledge base design: Design of knowledge base for flight planning application

The development process of the knowledge base for the generation of Test Libraries for Mission Operations Computer (MOC) Command Support focused on a series of information gathering interviews. These knowledge capture sessions are supporting the development of a prototype for evaluating the capabilities of INTUIT on such an application. the prototype includes functions related to POCC (Payload Operation Control Center) processing. It prompts the end-users for input through a series of panels and then generates the Meds associated with the initialization and the update of hazardous command tables for a POCC Processing TLIB.

Izygon, Michel E.↗

Flight Planning for the International Space Station - Levitation Observation of Dendrite Evolution in Steel Ternary Alloy Rapid Solidification (LODESTARS)

During rapid solidification, a molten sample is cooled below its equilibrium solidification temperature to form a metastable liquid. Once nucleation is initiated, growth of the solid phase proceeds and can be seen as a sudden rise in temperature. The heat of fusion is rejected ahead of the growing dendrites into the undercooled liquid in a process known as recalescence. Fe-Cr-Ni alloys may form several equilibrium phases and the hypoeutectic alloys, with compositions near the commercially important 316 stainless steel alloy, are observed to solidify by way of a two-step process known as double recalescence. During double recalescence, the first temperature rise is associated with formation of the metastable ferritic solid phase with subsequent conversion to the stable austenitic phase during the second temperature rise. Selection of which phase grows into the undercooled melt during primary solidification may be accomplished by choice of the appropriate nucleation trigger material or by control of the processing parameters during rapid solidification. Due to the highly reactive nature of the molten sample material and in order to avoid contamination of the undercooled melt, a containerless electromagnetic levitation (EML) processing technique is used. In ground-based EML, the same forces that support the weight of the sample against gravity also drive convection in the liquid sample. However, in microgravity, the force required to position the sample is greatly reduced, so convection may be controlled over a wide range of internal flows. Space Shuttle experiments have shown that the double recalescence behavior of Fe-Cr-Ni alloys changes between ground and space EML experiments. This program is aimed at understanding how melt convection influences phase selection and the evolution of rapid solidification microstructures.

Flemings, Merton C.↗

Continued Research into Characterizing the Preturbulence Environment for Sensor Development, New Hazard Algorithms and Experimental Flight Planning

The purpose of the research was to develop and test improved hazard algorithms that could result in the development of sensors that are better able to anticipate potentially severe atmospheric turbulence, which affects aircraft safety. The research focused on employing numerical simulation models to develop improved algorithms for the prediction of aviation turbulence. This involved producing both research simulations and real-time simulations of environments predisposed to moderate and severe aviation turbulence. The research resulted in the following fundamental advancements toward the aforementioned goal: 1) very high resolution simulations of turbulent environments indicated how predictive hazard indices could be improved resulting in a candidate hazard index that indicated the potential for improvement over existing operational indices, 2) a real-time turbulence hazard numerical modeling system was improved by correcting deficiencies in its simulation of moist convection and 3) the same real-time predictive system was tested by running the code twice daily and the hazard prediction indices updated and improved. Additionally, a simple validation study was undertaken to determine how well a real time hazard predictive index performed when compared to commercial pilot observations of aviation turbulence. Simple statistical analyses were performed in this validation study indicating potential skill in employing the hazard prediction index to predict regions of varying intensities of aviation turbulence. Data sets from a research numerical model where provided to NASA for use in a large eddy simulation numerical model. A NASA contractor report and several refereed journal articles where prepared and submitted for publication during the course of this research.

Kaplan, Michael L.↗

Towards a Formal Semantics of Flight Plans and Trajectories

In the National Airspace System, ight plans are often used only as a planning tool by air trac controllers and aircraft operators. These plans are implicitly translated into trajectories by the pilot or by the ight management system, and subsequently own by the aircraft. This translation process inevitably introduces di erences between the plan and the trajectory. However, given the current intended usage, exact correspondence between the plan and the trajectory is not needed. To achieve greater capacity and eciency, future air trac management concepts are being designed around the use of trajectories where predictability is extremely important. In this paper, a mathematical relationship between ight plans and trajectories is explored with the goal of making feasible, highly accurate predictions of future positions and velocities of aircraft. The goal here is to describe, in mathematically precise detail, a formal language of trajectories, whereby all receivers of the trajectory information will be able to arrive at precisely the same trajectory predication and to do this without having aircraft broadcast a large amount of data. Although even a four-dimensional ight plan is simple in structure, this paper will show that it is inherently ambiguous and will explore these issues in detail. In e ect, we propose that a rigorous semantics for ight plans can be developed and this will serve as an important stepping stone towards trajectory-based operations in the National Airspace System.

Hagen, George E.↗

Flight Planning and Procedures

The National Aeronautics and Space Administration (NASA) was founded in 1958 by President Eisenhower as a civilian lead United States federal agency designed to advance the science of space. Over the years, NASA has grown with a vision to "reach for new heights and reveal the unknown for the benefit of humankind" (About NASA). Mercury, Gemini, Apollo, Skylab, and Space Shuttle are just a few of the programs that NASA has led to advance our understanding of the universe. Each of the eleven main NASA space centers located across the United States plays a unique role in accomplishing that vision. Since 1961, Johnson Space Center (JSC) has led the effort for manned spaceflight missions. JSC has a mission to "provide and apply the preeminent capabilities to develop, operate, and integrate human exploration missions spanning commercial, academic, international, and US government partners" (Co-op Orientation). To do that, JSC is currently focused on two main programs, Orion and the International Space Station (ISS). Orion is the exploration vehicle that will take astronauts to Mars; a vessel comparable to the Apollo capsule. The International Space Station (ISS) is a space research facility designed to expand our knowledge of science in microgravity. The first piece of the ISS was launched in November of 1998 and has been in a continuous low earth orbit ever since. Recently, two sub-programs have been developed to resupply the ISS. The Commercial Cargo program is currently flying cargo and payloads to the ISS; the Commercial Crew program will begin flying astronauts to the ISS in a few years.

Rich, Allison C.↗

What Made Apollo A Success?

Spacecraft development, mission design planning, flight crew operations, and flight operations are considered. Spacecraft design principles and test activities are described. Determination of the best series of flights leading to a lunar landing at the earliest possible time, flight planning, techniques for establishing flight procedures and carrying out flight operations, and crew training and simulation activities are discussed.

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Shuttle operations era planning for flight operations

The Space Transportation System (STS) provides routine access to space for a wide range of customers in which cargos vary from single payloads on dedicated flights to multiple payloads that share Shuttle resources. This paper describes the flight operations planning process from payload introduction through flight assignment to execution of the payload objectives and the changes that have been introduced to improve that process. Particular attention is given to the factors that influence the amount of preflight preparation necessary to satisfy customer requirements. The partnership between the STS operations team and the customer is described in terms of their functions and responsibilities in the development of a flight plan. A description of the Mission Control Center (MCC) and payload support capabilities completes the overview of Shuttle flight operations.

Holt, J. D.↗

SOFIA'S Challenge: Scheduling Airborne Astronomy Observations

The Stratospheric Observatory for Infrared Astronomy (SOFIA) is NASA's next generation airborne astronomical observatory, and will commence operations in 2005. The facility consists of a 747-SP modified to accommodate a 2.5 meter telescope. SOFIA is expected to fly an average of 140 science flights per year over its 20 year lifetime. Depending on the nature of the instrument used during flight, 5-15 observations per flight are expected. The SOFIA telescope is mounted aft of the wings on the port side of the aircraft and is articulated through a range of 20deg to 60deg of elevation. The telescope has minimal lateral flexibility; thus, the aircraft must turn constantly to maintain the telescope's focus on an object during observations. A significant problem in future SOFIA operations is that of scheduling flights in support of observations. Investigators are expected to propose small numbers of observations, and many observations must be grouped together to make up single flights. Flight planning for the previous generation airborne observatory, the Kuiper Airborne Observatory (KAO), was done by hand; planners had to choose takeoff time, observations to perform, and decide on setup-actions (called "dead-legs") to position the aircraft prior to observing. This task frequently required between 6-8 hours to plan one flight The scope of the flight planning problem for supporting GI observations with the anticipated flight rate for SOFIA makes the manual approach for flight planning daunting. In response, we have designed an Automated Flight Planner (AFP) that accepts as input a set of requested observations, designated flight days, weather predictions and fuel limitations, and searches automatically for high-quality flight plans that satisfy all relevant aircraft and astronomer specified constraints. The AFP can generate one candidate flight plan in 5-10 minutes, of computation time, a feat beyond the capabilities of human flight planners. The rate at which the AFP can generate flights enables humans to assess and analyze complex tradeoffs between fuel consumption, estimated science quality and the percentage of scheduled observations. Due to the changing nature of SOFIA scheduling problems, this functionality will play a crucial role in optimizing science and minimizing costs during operations. In the full paper, we will summarize the technical challenges that have been met in order to build this system. These include: design of the search algorithm, design of appropriate heuristics and approximations, and reduction in the size of the search space. We will also describe technical challenges that are currently being addressed, including the extension of the existing approach to handle new solution criteria. Finally, we will describe a variety of cultural challenges that the astronomical community must address in order to successfully use SOFIA, and describe how the AFT can be used to address some of these challenges. Specifically, many of the intended science users are accustomed to using ground-based or space-based observatories; we will identify some differences that arise due to the nature of airborne observatories, and how the AFT can be extended to provide useful services to ease these cultural differences.

Frank, Jeremy↗

Mission Control Center (MCC) system specification for the shuttle Orbital Flight Test (OFT) timeframe

The Mission Control Center Shuttle (MCC) Shuttle Orbital Flight Test (OFT) Data System (OFTDS) provides facilities for flight control and data systems personnel to monitor and control the Shuttle flights from launch (tower clear) to rollout (wheels stopped on runway). It also supports the preparation for flight (flight planning, flight controller and crew training, and integrated vehicle and network testing activities). The MCC Shuttle OFTDS is described in detail. Three major support systems of the OFTDS and the data types and sources of data entering or exiting the MCC were illustrated. These systems are the communication interface system, the data computation complex, and the display and control system.

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Enroute flight-path planning - Cooperative performance of flight crews and knowledge-based systems

Interface design issues associated with the introduction of knowledge-based systems into the cockpit are discussed. Such issues include not only questions about display and control design, they also include deeper system design issues such as questions about the alternative roles and responsibilities of the flight crew and the computer system. In addition, the feasibility of using enroute flight path planning as a context for exploring such research questions is considered. In particular, the development of a prototyping shell that allows rapid design and study of alternative interfaces and system designs is discussed.

Smith, Philip J.↗

NASA Long Duration Balloon capability development project

A NASA development program is described for establishing near-global long-duration balloon (LDB) capabilities for both Antarctic and midlatitude applications. The program is intended to evaluate, research, and develop the balloon structures and systems needed for scientific payloads of over 1500 lbs for periods of up to three weeks. The systems examined include: control functions, data processing, power, navigation/positioning, and telecommunications. Test flights of the LDB Development Project in Antarctica are reported in which a 28 million cu ft balloon was launched with 3611 lbs of suspended weight. The subsystems under development are reported to work effectively for the test flights. Planned flights for the LDB based on these developments include gamma-ray and X-ray campaigns, a long-duration test in Antarctica, and an experiment based on magnetic passive isotopes.

Stuchlik, D.↗