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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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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Automated control of hierarchical systems using value-driven methods

An introduction is given to the Value-driven methodology, which has been successfully applied to solve a variety of difficult decision, control, and optimization problems. Many real-world decision processes (e.g., those encountered in scheduling, allocation, and command and control) involve a hierarchy of complex planning considerations. For such problems it is virtually impossible to define a fixed set of rules that will operate satisfactorily over the full range of probable contingencies. Decision Science Applications' value-driven methodology offers a systematic way of automating the intuitive, common-sense approach used by human planners. The inherent responsiveness of value-driven systems to user-controlled priorities makes them particularly suitable for semi-automated applications in which the user must remain in command of the systems operation. Three examples of the practical application of the approach in the automation of hierarchical decision processes are discussed: the TAC Brawler air-to-air combat simulation is a four-level computerized hierarchy; the autonomous underwater vehicle mission planning system is a three-level control system; and the Space Station Freedom electrical power control and scheduling system is designed as a two-level hierarchy. The methodology is compared with rule-based systems and with other more widely-known optimization techniques.

Pugh, George E.↗
NASA NTRS2006

Scheduling Software for Complex Scenarios

Preparing a vehicle and its payload for a single launch is a complex process that involves thousands of operations. Because the equipment and facilities required to carry out these operations are extremely expensive and limited in number, optimal assignment and efficient use are critically important. Overlapping missions that compete for the same resources, ground rules, safety requirements, and the unique needs of processing vehicles and payloads destined for space impose numerous constraints that, when combined, require advanced scheduling. Traditional scheduling systems use simple algorithms and criteria when selecting activities and assigning resources and times to each activity. Schedules generated by these simple decision rules are, however, frequently far from optimal. To resolve mission-critical scheduling issues and predict possible problem areas, NASA historically relied upon expert human schedulers who used their judgment and experience to determine where things should happen, whether they will happen on time, and whether the requested resources are truly necessary.

Source record↗
NASA NTRS2015

Impact of Airspace Charges on Transatlantic Aircraft Trajectories

Aircraft flying over the airspace of different countries are subject to over-flight charges. These charges vary from country to country. Airspace charges, while necessary to support the communication, navigation and surveillance services, may lead to aircraft flying routes longer than wind-optimal routes and produce additional carbon dioxide and other gaseous emissions. This paper develops an optimal route between city pairs by modifying the cost function to include an airspace cost whenever an aircraft flies through a controlled airspace without landing or departing from that airspace. It is assumed that the aircraft will fly the trajectory at a constant cruise altitude and constant speed. The computationally efficient optimal trajectory is derived by solving a non-linear optimal control problem. The operational strategies investigated in this study for minimizing aircraft fuel burn and emissions include flying fuel-optimal routes and flying cost-optimal routes that may completely or partially reduce airspace charges en route. The results in this paper use traffic data for transatlantic flights during July 2012. The mean daily savings in over-flight charges, fuel cost and total operation cost during the period are 17.6 percent, 1.6 percent, and 2.4 percent respectively, along the cost- optimal trajectories. The transatlantic flights can potentially save $600,000 in fuel cost plus $360,000 in over-flight charges daily by flying the cost-optimal trajectories. In addition, the aircraft emissions can be potentially reduced by 2,070 metric tons each day. The airport pairs and airspace regions that have the highest potential impacts due to airspace charges are identified for possible reduction of fuel burn and aircraft emissions for the transatlantic flights. The results in the paper show that the impact of the variation in fuel price on the optimal routes is to reduce the difference between wind-optimal and cost-optimal routes as the fuel price increases. The additional fuel consumption is quantified using the 30 percent variation in fuel prices during March 2014 to March 2015.

aircraft scheduling↗
NASA NTRS1992

The application of artificial intelligence to astronomical scheduling problems

Efficient utilization of expensive space- and ground-based observatories is an important goal for the astronomical community; the cost of modern observing facilities is enormous, and the available observing time is much less than the demand from astronomers around the world. The complexity and variety of scheduling constraints and goals has led several groups to investigate how artificial intelligence (AI) techniques might help solve these kinds of problems. The earliest and most successful of these projects was started at Space Telescope Science Institute in 1987 and has led to the development of the Spike scheduling system to support the scheduling of Hubble Space Telescope (HST). The aim of Spike at STScI is to allocate observations to timescales of days to a week observing all scheduling constraints and maximizing preferences that help ensure that observations are made at optimal times. Spike has been in use operationally for HST since shortly after the observatory was launched in Apr. 1990. Although developed specifically for HST scheduling, Spike was carefully designed to provide a general framework for similar (activity-based) scheduling problems. In particular, the tasks to be scheduled are defined in the system in general terms, and no assumptions about the scheduling timescale are built in. The mechanisms for describing, combining, and propagating temporal and other constraints and preferences are quite general. The success of this approach has been demonstrated by the application of Spike to the scheduling of other satellite observatories: changes to the system are required only in the specific constraints that apply, and not in the framework itself. In particular, the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. This talk will discuss recent progress made in scheduling search techniques, the lessons learned from early HST operations, the application of Spike to other problem domains, and plans for the future evolution of the system.

Johnston, Mark D.↗
NASA NTRS2004

A Comparison of Techniques for Scheduling Earth-Observing Satellites

Scheduling observations by coordinated fleets of Earth Observing Satellites (EOS) involves large search spaces, complex constraints and poorly understood bottlenecks, conditions where evolutionary and related algorithms are often effective. However, there are many such algorithms and the best one to use is not clear. Here we compare multiple variants of the genetic algorithm: stochastic hill climbing, simulated annealing, squeaky wheel optimization and iterated sampling on ten realistically-sized EOS scheduling problems. Schedules are represented by a permutation (non-temperal ordering) of the observation requests. A simple deterministic scheduler assigns times and resources to each observation request in the order indicated by the permutation, discarding those that violate the constraints created by previously scheduled observations. Simulated annealing performs best. Random mutation outperform a more 'intelligent' mutator. Furthermore, the best mutator, by a small margin, was a novel approach we call temperature dependent random sampling that makes large changes in the early stages of evolution and smaller changes towards the end of search.

Globus, Al↗
NASA NTRS2016

Transmission Scheduling and Routing Algorithms for Delay Tolerant Networks

The challenges of data processing, transmission scheduling and routing within a space network present a multi-criteria optimization problem. Long delays, intermittent connectivity, asymmetric data rates and potentially high error rates make traditional networking approaches unsuitable. The delay tolerant networking architecture and protocols attempt to mitigate many of these issues, yet transmission scheduling is largely manually configured and routes are determined by a static contact routing graph. A high level of variability exists among the requirements and environmental characteristics of different missions, some of which may allow for the use of more opportunistic routing methods. In all cases, resource allocation and constraints must be balanced with the optimization of data throughput and quality of service. Much work has been done researching routing techniques for terrestrial-based challenged networks in an attempt to optimize contact opportunities and resource usage. This paper examines several popular methods to determine their potential applicability to space networks.

Space Networking↗
NASA NTRS1994

A mission planning concept and mission planning system for future manned space missions

The international character of future manned space missions will compel the involvement of several international space agencies in mission planning tasks. Additionally, the community of users requires a higher degree of freedom for experiment planning. Both of these problems can be solved by a decentralized mission planning concept using the so-called 'envelope method,' by which resources are allocated to users by distributing resource profiles ('envelopes') which define resource availabilities at specified times. The users are essentially free to plan their activities independently of each other, provided that they stay within their envelopes. The new developments were aimed at refining the existing vague envelope concept into a practical method for decentralized planning. Selected critical functions were exercised by planning an example, founded on experience acquired by the MSCC during the Spacelab missions D-1 and D-2. The main activity regarding future mission planning tasks was to improve the existing MSCC mission planning system, using new techniques. An electronic interface was developed to collect all formalized user inputs more effectively, along with an 'envelope generator' for generation and manipulation of the resource envelopes. The existing scheduler and its data base were successfully replaced by an artificial intelligence scheduler. This scheduler is not only capable of handling resource envelopes, but also uses a new technology based on neuronal networks. Therefore, it is very well suited to solve the future scheduling problems more efficiently. This prototype mission planning system was used to gain new practical experience with decentralized mission planning, using the envelope method. In future steps, software tools will be optimized, and all data management planning activities will be embedded into the scheduler.

Wickler, Martin↗
NASA NTRS1989

A variable-gain output feedback control design approach

A multi-model design technique to find a variable-gain control law defined over the whole operating range is proposed. The design is formulated as an optimal control problem which minimizes a cost function weighing the performance at many operating points. The solution is obtained by embedding into the Multi-Configuration Control (MCC) problem, a multi-model robust control design technique. In contrast to conventional gain scheduling which uses a curve fit of single model designs, the optimal variable-gain control law stabilizes the plant at every operating point included in the design. An iterative algorithm to compute the optimal control gains is presented. The methodology has been successfully applied to reconfigurable aircraft flight control and to nonlinear flight control systems.

Haylo, Nesim↗
NASA NTRS1997

2 kWe Solar Dynamic Ground Test Demonstration Project: Executive Summary - Volume 1

The Solar Dynamic Ground Test Demonstration (SDGTD) successfully demonstrated a solar-powered closed Brayton cycle system in a relevant space thermal environment. In addition to meeting technical requirements the project was completed 4 months ahead of schedule and under budget. The following conclusions can be supported: 1. The component technology for solar dynamic closed Brayton cycle technology has clearly been demonstrated. 2. The thermal, optical, control, and electrical integration aspects of systems integration have also been successfully demonstrated. Physical integration aspects were not attempted as these tend to be driven primarily by mission-specific requirements. 3. System efficiency of greater than 15 percent (all losses fully accounted for) was demonstrated using equipment and designs which were not optimized. Some preexisting hardware was used to minimize cost and schedule. 4. Power generation of 2 kWe. 5. A NASA/industry team was developed that successfully worked together to accomplish project goals. The material presented in this report will show that the technology necessary to design and fabricate solar dynamic electrical power systems for space has been successfully developed and demonstrated. The data will further show that achieved results compare well with pretest predictions. The next step in the development of solar dynamic space power will be a flight test.

Alexander, Dennis↗
NASA NTRS1987

Logistics and operations integration requirements to support Space Station servicing of free flying spacecraft - OMV flight operation

The logistics of OMV free-flyer servicing are examined, with emphasis on integrating the OMV operations into the overall STS-Space Station system. The depletion rate of consumables and lifetimes of free-flyer components are known quantities, which permits definition of a predictable maintenance schedule. Servicing with an OMV will depend on the position and capabilities of the OMV, Shuttle and Station when free-flyer maintenance is needed. Optimized orbital servicing of free-flyers will involve coordination of and resolution of schedule conflicts among STS, the OMV and the Station. The scheduled availability of any of the three components will be predicted in terms of probabilities that any one of the components will not be needed for another mission while performing the mission they are on.

Bell, Jerome A.↗
NASA NTRS1975

Tug fleet and ground operations schedules and controls. Volume 1: Executive summary

This study presents Tug Fleet and Ground Operations Schedules and Controls plan. This plan was developed and optimized out of a combination of individual Tug program phased subplans, special emphasis studies, contingency analyses and sensitivity analyses. The subplans cover the Tug program phases: (1) Tug operational, (2) Interim Upper Stage (IUS)/Tug fleet utilization, (3) and IUS/Tug payload integration, (4) Tug site activation, (5) IUS/Tug transition, (6) Tug acquisition. Resource requirements (facility, GSE, TSE, software, manpower, logistics) are provided in each subplan, as are appropriate Tug processing flows, active and total IUS and Tug fleet requirements, fleet management and Tug payload integration concepts, facility selection recommendations, site activation and IUS to Tug transition requirements. The impact of operational concepts on Tug acquisition is assessed and the impact of operating Tugs out of KSC and WTR is analyzed and presented showing WTR as a delta. Finally, cost estimates for fleet management and ground operations of the DDT&E and operational phases of the Tug program are given.

Source record↗
NASA NTRS1982

Project analysis and integration area

A simulation program that investigates the relationship between manpower requirements and equipment availability in the presence of scheduled and unscheduled maintenance is presented. A method for optimization of metallization patterns is presented.

Aster, R. W.↗
NASA NTRS1991

A trajectory planning scheme for spacecraft in the space station environment

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is special because the space station will define a multivehicle environment in space. The optimization surface is a complex nonlinear function of the initial conditions of the chase and target crafts. Small permutations in the input conditions can result in abrupt changes to the optimization surface. Since no prior knowledge about the number or location of local minima on the surface is available, the optimization must be capable of functioning on a multimodal surface. It was reported in the literature that the simulated annealing algorithm is more effective on such surfaces than descent techniques using random starting points. The simulated annealing optimization was found to be capable of identifying a minimum fuel, two-burn trajectory subject to four constraints which are integrated into the optimization using a barrier method. The computations required to solve the optimization are fast enough that missions could be planned on board the space station. Potential applications for on board planning of missions are numerous. Future research topics may include optimal planning of multi-waypoint maneuvers using a knowledge base to guide the optimization, and a study aimed at developing robust annealing schedules for potential on board missions.

Soller, Jeffrey Alan↗
NASA NTRS2002

Science Goal Driven Observing and Spacecraft Autonomy

Spacecraft autonomy will be an integral part of mission operations in the coming decade. While recent missions have made great strides in the ability to autonomously monitor and react to changing health and physical status of spacecraft, little progress has been made in responding quickly to science driven events. For observations of inherently variable targets and targets of opportunity, the ability to recognize early if an observation will meet the science goals of a program, and react accordingly, can have a major positive impact on the overall scientific returns of an observatory and on its operational costs. If the onboard software can reprioritize the schedule to focus on alternate targets, discard uninteresting observations prior to downloading, or download a subset of observations at a reduced resolution, the spacecraft's overall efficiency will be dramatically increased. The science goal monitoring (SGM) system is a proof-of-concept effort to address the above challenge. The SGM will have an interface to help capture higher level science goals from the scientists and translate them into a flexible observing strategy that SGM can execute and monitor. We are developing an interactive distributed system that will use on-board processing and storage combined with event-driven interfaces with ground-based processing and operations, to enable fast re-prioritization of observing schedules, and to minimize time spent on non-optimized observations.

Koratkar, Amuradha↗
NASA NTRS2010

Part-Task Simulation of Synthetic and Enhanced Vision Concepts for Lunar Landing

During Apollo, the constraints placed by the design of the Lunar Module (LM) window for crew visibility and landing trajectory were a major problem. Lunar landing trajectories were tailored to provide crew visibility using nearly 70 degrees look-down angle from the canted LM windows. Apollo landings were scheduled only at specific times and locations to provide optimal sunlight on the landing site. The complications of trajectory design and crew visibility are still a problem today. Practical vehicle designs for lunar lander missions using optimal or near-optimal fuel trajectories render the natural vision of the crew from windows inadequate for the approach and landing task. Further, the sun angles for the desirable landing areas in the lunar polar regions create visually powerful, season-long shadow effects. Fortunately, Synthetic and Enhanced Vision (S/EV) technologies, conceived and developed in the aviation domain, may provide solutions to this visibility problem and enable additional benefits for safer, more efficient lunar operations. Piloted simulation evaluations have been conducted to assess the handling qualities of the various lunar landing concepts, including the influence of cockpit displays and the informational data and formats. Evaluation pilots flew various landing scenarios with S/EV displays. For some of the evaluation trials, an eye glasses-mounted, monochrome monocular display, coupled with head tracking, was worn. The head-worn display scene consisted of S/EV fusion concepts. The results of this experiment showed that a head-worn system did not increase the pilot s workload when compared to using just the head-down displays. As expected, the head-worn system did not provide an increase in performance measures. Some pilots commented that the head-worn system provided greater situational awareness compared to just head-down displays.

Arthur, Jarvis J., III↗
NASA NTRS2005

Range Process Simulation Tool

Range Process Simulation Tool (RPST) is a computer program that assists managers in rapidly predicting and quantitatively assessing the operational effects of proposed technological additions to, and/or upgrades of, complex facilities and engineering systems such as the Eastern Test Range. Originally designed for application to space transportation systems, RPST is also suitable for assessing effects of proposed changes in industrial facilities and large organizations. RPST follows a model-based approach that includes finite-capacity schedule analysis and discrete-event process simulation. A component-based, scalable, open architecture makes RPST easily and rapidly tailorable for diverse applications. Specific RPST functions include: (1) definition of analysis objectives and performance metrics; (2) selection of process templates from a processtemplate library; (3) configuration of process models for detailed simulation and schedule analysis; (4) design of operations- analysis experiments; (5) schedule and simulation-based process analysis; and (6) optimization of performance by use of genetic algorithms and simulated annealing. The main benefits afforded by RPST are provision of information that can be used to reduce costs of operation and maintenance, and the capability for affordable, accurate, and reliable prediction and exploration of the consequences of many alternative proposed decisions.

Phillips, Dave↗
NASA NTRS2017

Augmented Method to Improve Thermal Data for the Figure Drift Thermal Distortion Predictions of the JWST OTIS Cryogenic Vacuum Test

The JWST Optical Telescope Element (OTE) assembly is the largest optically stable infrared-optimized telescope currently being manufactured and assembled, and is scheduled for launch in 2018. The JWST OTE, including the 18 segment primary mirror, secondary mirror, and the Aft Optics Subsystem (AOS) are designed to be passively cooled and operate near 45K. These optical elements are supported by a complex composite backplane structure. As a part of the structural distortion model validation efforts, a series of tests are planned during the cryogenic vacuum test of the fully integrated flight hardware at NASA JSC Chamber A. The successful ends to the thermal-distortion phases are heavily dependent on the accurate temperature knowledge of the OTE structural members. However, the current temperature sensor allocations during the cryo-vac test may not have sufficient fidelity to provide accurate knowledge of the temperature distributions within the composite structure. A method based on an inverse distance relationship among the sensors and thermal model nodes was developed to improve the thermal data provided for the nanometer scale WaveFront Error (WFE) predictions. The Linear Distance Weighted Interpolation (LDWI) method was developed to augment the thermal model predictions based on the sparse sensor information. This paper will encompass the development of the LDWI method using the test data from the earlier pathfinder cryo-vac tests, and the results of the notional and as tested WFE predictions from the structural finite element model cases to characterize the accuracies of this LDWI method.

Thermal Modeling↗