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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 271 records · Page 15

SatNet: A Benchmark for Satellite Scheduling Optimization

Satellites provide essential services such as networking and weather tracking, and the number of near-earth and deep space satellites are expected to grow rapidly in the coming years. Communications with terrestrial ground stations is one of the critical functionalities of any space mission. Satellite scheduling is a problem that has been scientifically investigated since the 1970s. A central aspect of this problem is the need to consider resource contention and satellite visibility constraints as they require line of sight. Due to the combinatorial nature of the problem, prior solutions such as linear programs and evolutionary algorithms require extensive compute capabilities to output a feasible schedule for each scenario. Machine learning based scheduling can provide an alternative solution by training a model with historical data and generating a schedule quickly with model inference. We present SatNet, a benchmark for satellite scheduling optimization based on historical data from the NASA Deep Space Network. We propose formulation of the satellite scheduling problem as a Markov Decision Process and use reinforcement learning (RL) policies to generate schedules. The nature of constraints imposed by SatNet differ from other combinatorial optimization problems such as vehicle routing studied in prior literature. Our initial results indicate that RL is an alternative optimization approach that can generate candidate solutions of comparable quality to existing state-of-the-practice results. However, we also find that RL policies overfit to the training dataset and do not generalize well to new data, thereby necessitating continued research on reusable and generalizable agents.

Wilson, Brian↗

Psychological Health Maintenance on Space Station Freedom

The scheduling of crew rotations for up to 180 days on Space Station Freedom presents a special challenge for behavioral scientists who are tasked with providing psychological support for the crews, their families, and mission flight controllers. Preflight psychological support planning may minimize the negative impact of psychological and social issues on mission success, as well as assist NASA management in making real-time mission planning decisions in the event of a significant social event (for example, the death of a family member). During flight, the combined psychological, emotional, and social stressors on the astronauts must be monitored, along with other aspects of their health. The Health Maintenance Facility (HMF) will have the capability of providing preventive, diagnostic, and therapeutic assistance for significant psychiatric and interpersonal problems which may develop. Psychological support will not end with the termination of the mission. Mental health professionals must be part of the team of medical personnel whose job will be to facilitate the transition—physical and mental—from the space environment back to planet Earth. This paper reviews each phase of mission planning for Space Station Freedom and specifies those factors that may be critical for psychological health maintenance on extended-duration space missions.

Patricia A Santy↗

Thermal design of the Wide Field/Planetary Camera

The Wide Field/Planetary Camera is an imaging system developed by the Jet Propulsion Laboratory for the NASA Hubble Space Telescope currently scheduled to be launched in December 1989 aboard the space shuttle. The temperature control design of the instrument utilizes multilayered insulation, electric resistance heaters, aluminum/ammonia heat pipes, thermoelectric coolers, temperature control coatings, and space radiators. A feedback control system maintains stable sensor temperatures. Thermal capacitance maintains stable optics and electronics temperatures during transient conditions. Schedule slips and launch delays have allowed extensive thermal testing of the instrument. Six instrument thermal vacuum tests and a spacecraft thermal vacuum test were performed. Several modifications have been made to the instrument to correct icing and contamination problems that have been discovered during thermal vacuum testing. This paper describes the thermal design, last instrument thermal vacuum test, results, and thermal model correlation.

Garcia, R. D.↗

Backscatter Modeling at 2.1 Micron Wavelength for Space-Based and Airborne Lidars Using Aerosol Physico-Chemical and Lidar Datasets

Space-based and airborne coherent Doppler lidars designed for measuring global tropospheric wind profiles in cloud-free air rely on backscatter, beta from aerosols acting as passive wind tracers. Aerosol beta distribution in the vertical can vary over as much as 5-6 orders of magnitude. Thus, the design of a wave length-specific, space-borne or airborne lidar must account for the magnitude of 8 in the region or features of interest. The SPAce Readiness Coherent Lidar Experiment under development by the National Aeronautics and Space Administration (NASA) and scheduled for launch on the Space Shuttle in 2001, will demonstrate wind measurements from space using a solid-state 2 micrometer coherent Doppler lidar. Consequently, there is a critical need to understand variability of aerosol beta at 2.1 micrometers, to evaluate signal detection under varying aerosol loading conditions. Although few direct measurements of beta at 2.1 micrometers exist, extensive datasets, including climatologies in widely-separated locations, do exist for other wavelengths based on CO2 and Nd:YAG lidars. Datasets also exist for the associated microphysical and chemical properties. An example of a multi-parametric dataset is that of the NASA GLObal Backscatter Experiment (GLOBE) in 1990 in which aerosol chemistry and size distributions were measured concurrently with multi-wavelength lidar backscatter observations. More recently, continuous-wave (CW) lidar backscatter measurements at mid-infrared wavelengths have been made during the Multicenter Airborne Coherent Atmospheric Wind Sensor (MACAWS) experiment in 1995. Using Lorenz-Mie theory, these datasets have been used to develop a method to convert lidar backscatter to the 2.1 micrometer wavelength. This paper presents comparison of modeled backscatter at wavelengths for which backscatter measurements exist including converted beta (sub 2.1).

Srivastava, V.↗

Comet Observations with SIRTF

Comet observations are included in the programs of the Guaranteed Time Observers (GTO) on the Space Infrared Telescope Facility (SIRTF), scheduled to be in space and operational for five years beginning in late 2003. SIRTF is a cryogenic telescope with three basic instruments for imaging, photometry and spectroscopy from 3.6 m to 160 m. All of these capabilities will be used in studies of comets. The intent is to study the infrared radiation (emission) from comets (and dust tails, where relevant) in all stages of evolution, starting with Kuiper Belt objects and Centaurs (thermal emission at 24,70, and 160 m to derive dimensions and albedos). Active comets will be observed spectroscopically and in deep thermal images. Several known or suspected extinct comets will be observed spectroscopically (5-37 m) for information on their surface compositions. There are opportunities for Guest Observers (GO) to propose additional comet work. .

Cruikshank, Dale P.↗

Physiological considerations for EVA in the Space Station era

The physiological parameters that will affect EMU design and operational scheduling for the Space Station Program are discussed. The system must be designed to safely and effectively handle the increased frequency of extravehicular activity projected for longer flight periods than in the past. In order to minimize the risk of decompression sickness a proper combination of equilibration time to cabin pressure, suit pressure, and prebreathing denitrogenation, is necessary. Effective thermal exchange is projected to be automatically controlled and to have an 8-hr 1000 BTU/hr capability. Physiological changes due to adaptation to weightlessness must be considered in scheduling for their impact on performance/fatigue and in coping with motion sickness. Radiation protection to the limit of 80 rad/quarter must be achieved by scheduling to avoid periodic proton and solar flare exposure, and by additional EMU shielding. Additional EMU considerations are the control of microorganisms and the higher pressure requirement for emergency O2 purge.

Horrigan, D. J., Jr.↗

Planning to Explore: Using a Coordinated Multisource Infrastructure to Overcome Present and Future Space Flight Planning Challenges

Few human endeavors present as much of a planning and scheduling challenge as space flight, particularly manned space flight. Just on the operational side of it, efforts of thousands of people across hundreds of organizations need to be coordinated. Numerous tasks of varying complexity and nature, from scientific to construction, need to be accomplished within limited mission time frames. Resources need to be carefully managed and contingencies worked out, often on a very short notice. From the beginning of the NASA space program, planning has been done by large teams of domain experts working months, sometimes years, to put together a single mission. This approach, while proven very reliable up to now, is becoming increasingly harder to sustain. Elevated levels of NASA space activities, from deployment of the new Crew Exploration Vehicle (CEV) and completion of the International Space Station (ISS), to the planned lunar missions and permanent lunar bases, will put an even greater strain on this largely manual process. While several attempts to automate it have been made in the past, none have fully succeeded. In this paper we describe the current NASA planning methods, outline their advantages and disadvantages, discuss the planning challenges of upcoming missions and propose a distributed planning/scheduling framework (CMMD) aimed at unifying and optimizing the planning effort. CMMD will not attempt to make the process completely automated, but rather serve in a decision support capacity for human managers and planners. It will help manage information gathering, creation of partial and consolidated schedules, inter-team negotiations, contingencies investigation, and rapid re-planning when the situation demands it. The fist area of CMMD application will be planning for Extravehicular Activities (EVA) and associated logistics. Other potential applications, not only in the space flight domain, and future research efforts will be discussed as well.

Balaban, Edward↗

Photovoltaic power modules for NASA's manned space station

The capability and the safety of manned spacecraft are largely dependent upon reliable electric power systems. Two similar space power systems able to survive the low Earth orbit environment, are being considered for NASA's Manned Space Station (SS), scheduled to begin operation in the mid 1990's. The Space Station Electric Power System (EPS) is composed of Photovoltaic (PV) Power Modules, Solar Dynamic (SD) Power Modules, and the Power Management and Distribution (PMAD) System. One EPS configuration will deliver 37.5 kW of PV based, utility grade, ac power to SS users. A second 75 kWe PV based EPS option is also being considered for SS deployment. The two EPS options utilize common modules and differ only in the total number of PV Power Modules used. Each PV Power Module supplies 18.75 kWe of ac power and incorporates its own energy storage and thermal control. The general requirements and the current preliminary design configuration of the Space Station PV Power Modules are examined.

Tatro, Charles A.↗

Artificial intelligence and space power systems automation

Various applications of artificial intelligence to space electrical power systems are discussed. An overview is given of completed, on-going, and planned knowledge-based system activities. These applications include the Nickel-Cadmium Battery Expert System (NICBES) (the expert system interfaced with the Hubble Space Telescope electrical power system test bed); the early work with the Space Station Experiment Scheduler (SSES); the three expert systems under development in the space station advanced development effort in the core module power management and distribution system test bed; planned cooperation of expert systems in the Core Module Power Management and Distribution (CM/PMAD) system breadboard with expert systems for the space station at other research centers; and the intelligent data reduction expert system under development.

Weeks, David J.↗

Photovoltaic power modules for NASA's manned Space Station

The capability and the safety of manned spacecraft are largely dependent upon reliable electric power systems. Two similar space power systems able to survive the low earth orbit environment, are being considered for NASA's Manned Space Station (SS), scheduled to begin operation in the mid 1990's. The Space Station Electric Power System (EPS) is composed of Photovoltaic (PV) Power Modules, Solar Dynamic (SD) Power Modules, and the Power Management and Distribution (PMAD) System. One EPS configuration will deliver 37.5 kW of PV based, utility grade, ac power to SS users. A second 75 kWe PV based EPS option is also being considered for SS deployment. The two EPS options utilize common modules and differ only in the total number of PV Power Modules used. Each PV Power Module supplies 18.75 kWe of ac power and incorporates its own energy storage and thermal control. The general requirements and the current preliminary design configuration of the Space Station PV Power Modules are examined.

Tatro, C. A.↗

Space Shuttle mission: STS-67

The Space Shuttle Endeavor, scheduled to launch March 2, 1995 from NASA's Kennedy Space Center, will conduct NASA's longest Shuttle flight prior to date. The mission, designated STS-67, has a number of experiments and payloads, which the crew, commanded by Stephen S. Oswald, will have to oversee. This NASA press kit for the mission contains a general background (general press release, media services information, quick-look facts page, shuttle abort modes, summary timeline, payload and vehicle weights, orbital summary, and crew responsibilities); cargo bay payloads and activities (Astro 2, Get Away Special Experiments); in-cabin payloads (Commercial Minimum Descent Altitude Instrumentation Technology Associates Experiments, protein crystal growth experiments, Middeck Active Control Experiment, and Shuttle Amateur Radio Experiment); and the STS-67 crew biographies. The payloads and experiments are described and summarized to give an overview of the goals, objectives, apparatuses, procedures, sponsoring parties, and the assigned crew members to carry out the tasks.

Source record↗

Enabling New Operations Concepts for Lunar and Mars Exploration

The planning and scheduling of human space activities is an expensive and time-consuming task that seldom provides the crew with the control, flexibility, or insight that they need. During the past thirty years, scheduling software has seen only incremental improvements; however, software limitations continue to prevent even evolutionary improvements in the operations concept that is used for human space missions. Space missions are planned on the ground long before they are executed in space, and the crew has little input or influence on the schedule. In recent years the crew has been presented with a job jar of activities that they can do whenever they have time, but the contents of the jar is limited to tasks that do not use scarce shared resources and do not have external timing constraints. Consequently, the crew has no control over the schedule of the majority of their own tasks. As humans venture farther from earth for longer durations, it will become imperative that they have the ability to plan and schedule not only their own activities, but also the unattended activities of the systems, equipment, and robots on the journey with them. Significant software breakthroughs are required to enable the change in the operations concept. The crew does not have the time to build or modify the schedule by hand. They only need to issue a request to schedule a task and the system should automatically do the rest. Of course, the crew should not be required to build the complete schedule. Controllers on the ground should contribute the models and schedules where they have the better knowledge. The system must allow multiple simultaneous users, some on earth and some in space. The Mission Operations Laboratory at NASA's Marshall Space flight Center has been researching and prototyping a modeling schema, scheduling engine, and system architecture that can enable the needed paradigm shift - it can make the crew autonomous. This schema and engine can be the core of a planning and scheduling system that would enable multiple planners, some on the earth and some in space, to build one integrated timeline. Its modeling schema can capture all the task requirements; its scheduling engine can build the schedule automatically, and its architecture can allow those (on earth and in space) with the best knowledge of the tasks to schedule them. This paper describes the enabling technology and proposes an operations concept for astronauts autonomously scheduling their activities and the activities around them.

Jaap, John↗

Advanced timeline systems

The Mission Planning Division of the Mission Operations Laboratory at NASA's Marshall Space Flight Center is responsible for scheduling experiment activities for space missions controlled at MSFC. In order to draw statistically relevant conclusions, all experiments must be scheduled at least once and may have repeated performances during the mission. An experiment consists of a series of steps which, when performed, provide results pertinent to the experiment's functional objective. Since these experiments require a set of resources such as crew and power, the task of creating a timeline of experiment activities for the mission is one of resource constrained scheduling. For each experiment, a computer model with detailed information of the steps involved in running the experiment, including crew requirements, processing times, and resource requirements is created. These models are then loaded into the Experiment Scheduling Program (ESP) which attempts to create a schedule which satisfies all resource constraints. ESP uses a depth-first search technique to place each experiment into a time interval, and a scoring function to evaluate the schedule. The mission planners generate several schedules and choose one with a high value of the scoring function to send through the approval process. The process of approving a mission timeline can take several months. Each timeline must meet the requirements of the scientists, the crew, and various engineering departments as well as enforce all resource restrictions. No single objective is considered in creating a timeline. The experiment scheduling problem is: given a set of experiments, place each experiment along the mission timeline so that all resource requirements and temporal constraints are met and the timeline is acceptable to all who must approve it. Much work has been done on multicriteria decision making (MCDM). When there are two criteria, schedules which perform well with respect to one criterion will often perform poorly with respect to the other. One schedule dominates another if it performs strictly better on one criterion, and no worse on the other. Clearly, dominated schedules are undesireable. A nondominated schedule can be generated by some sort of optimization problem. Generally there are two approaches: the first is a hierarchical approach while the second requires optimizing a weighting or scoring function.

Bulfin, R. L.↗

Hubble Systems Optimize Hospital Schedules

Don Rosenthal, a former Ames Research Center computer scientist who helped design the Hubble Space Telescope's scheduling software, co-founded Allocade Inc. of Menlo Park, California, in 2004. Allocade's OnCue software helps hospitals reclaim unused capacity and optimize constantly changing schedules for imaging procedures. After starting to use the software, one medical center soon reported noticeable improvements in efficiency, including a 12 percent increase in procedure volume, 35 percent reduction in staff overtime, and significant reductions in backlog and technician phone time. Allocade now offers versions for outpatient and inpatient magnetic resonance imaging (MRI), ultrasound, interventional radiology, nuclear medicine, Positron Emission Tomography (PET), radiography, radiography-fluoroscopy, and mammography.

Source record↗

Scheduling lessons learned from the Autonomous Power System

The Autonomous Power System (APS) project at NASA LeRC is designed to demonstrate the applications of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution systems. The project consists of three elements: the Autonomous Power Expert System (APEX) for Fault Diagnosis, Isolation, and Recovery (FDIR); the Autonomous Intelligent Power Scheduler (AIPS) to efficiently assign activities start times and resources; and power hardware (Brassboard) to emulate a space-based power system. The AIPS scheduler was tested within the APS system. This scheduler is able to efficiently assign available power to the requesting activities and share this information with other software agents within the APS system in order to implement the generated schedule. The AIPS scheduler is also able to cooperatively recover from fault situations by rescheduling the affected loads on the Brassboard in conjunction with the APEX FDIR system. AIPS served as a learning tool and an initial scheduling testbed for the integration of FDIR and automated scheduling systems. Many lessons were learned from the AIPS scheduler and are now being integrated into a new scheduler called SCRAP (Scheduler for Continuous Resource Allocation and Planning). This paper will service three purposes: an overview of the AIPS implementation, lessons learned from the AIPS scheduler, and a brief section on how these lessons are being applied to the new SCRAP scheduler.

Ringer, Mark J.↗

Lessons Learned from NASA Goddard Space Flight Center’s Product Development Lead Training Schedule and Cost Development Workshop: Continuous Improvement

This presentation provides a status of the Goddard Space Flight Center (GSFC) effort to increase foundational knowledge of Product Development Leads (PDLs) in schedule and cost management including earned value management (EVM). In 2012, GSFC’s Engineering and Technology Directorate (ETD) implemented an in-house training program to prepare PDLs for managing the technical, cost, schedule, and risk aspects of spaceflight systems to meet their subsystem commitments. Developed in-house, the PDL training program provides an integrated approach to requirements development, risk, schedule and cost management, EVM, performance tracking, and other areas. The program has been held twice yearly since its inception with 531 participating and 451 completing the curriculum. In 2017, the program won the Robert H. Goddard award for Quality and Process Improvement. Program development and evolution were presented in the 2018 NASA Schedule and Cost Symposium. The presentation was so well received that this year we focus on one workshop within the program: Schedule and Cost Development, including EVM. We examine the on-going logic modeling process and how participant and stakeholder data influence workshop content and design, and how the disciplines of schedule and cost contribute to mission success. In this presentation we refresh you on how the approach integrates lecture, small group discussion, estimating, case study exercises, and problem solving. We update you on the data collected from participants and stakeholders, and we discuss how we use these data to measure training effectiveness. Specific topics include: • How the logic model is used as the backbone for continuous program improvement, • How feedback influences implementation and curriculum updates, • How data collection and analysis inform workshop content and development, including participant discoveries of EVM data, • How including the resource analyst and planner in the product development team supports project success.

Lessons Learned↗