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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Integrated scheduling and resource management

This paper examines the problem of integrated scheduling during the Space Station era. Scheduling for Space Station entails coordinating the support of many distributed users who are sharing common resources and pursuing individual and sometimes conflicting objectives. This paper compares the scheduling integration problems of current missions with those anticipated for the Space Station era. It examines the facilities and the proposed operations environment for Space Station. It concludes that the pattern of interdependecies among the users and facilities, which are the source of the integration problem is well structured, allowing a dividing of the larger problem into smaller problems. It proposes an architecture to support integrated scheduling by scheduling efficiently at local facilities as a function of dependencies with other facilities of the program. A prototype is described that is being developed to demonstrate this integration concept.

Ward, M. T.↗
NASA NTRS1997

The International Space Station Assembly on Schedule

As engineers continue to prepare the International Space Station (ISS) for in-orbit assembly in the year 2002, ANSYS software has proven instrumental in resolving a structural problem in the project's two primary station modules -- Nodes 1 and 2. Proof pressure tests performed in May revealed "low temperature, post-yield creep" in some of the Nodes' gussets, which were designed to reinforce ports for loads from station keeping and reboost motion of the entire space station. An extensive effort was undertaken to characterize the creep behavior of the 2219-T851 aluminum forging material from which the gussets were made. Engineers at Sverdrup Technology, Inc. (Huntsville, AL) were responsible for conducting a combined elastic-plastic-creep analysis of the gussets to determine the amount of residual compressive stress which existed in the gussets following the proof pressure tests, and to determine the stress-strain history in the gussets while on-orbit. Boeing, NASA's Space Station prime contractor, supplied the Finite Element Analysis (FEA) model geometry and developed the creep equations from the experimental data taken by NASA's Marshall Space Flight Center and Langley Research Center. The goal of this effort was to implement the uniaxial creep equations into a three dimensional finite element program, and to determine analytically whether or not the creep was something that the space station program could live with. The objective was to show analytically that either the creep rate was at an acceptable level, or that the node module had to be modified to lower the stress levels to where creep did not occur. The elastic-plastic-creep analysis was performed using the ANSYS finite element program of ANSYS, Inc. (Houston, PA). The analysis revealed that the gussets encountered a compressive stress of approximately 30,000 pounds per square inch (psi) when unloaded. This compressive residual stress significantly lowered the maximum tension stress in the gussets which decreased the creep strain rate. The analysis also showed that the gussets would not experience a great deal of creep from future pressure tests if braces or struts proposed by Boeing were installed to redistribute stress away from them. Subsequent analysis of on-orbit station keeping and reboost loads convinced Boeing that the gussets should be removed altogether.

Source record↗
NASA NTRS2014

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial-optimization problems that encompasses, among many others, the problem of generating optimal space-data communications schedules.

ground stations↗
NASA NTRS1991

The range scheduling aid

The Air Force Space Command schedules telemetry, tracking and control activities across the Air Force Satellite Control network. The Range Scheduling Aid (RSA) is a rapid prototype combining a user-friendly, portable, graphical interface with a sophisticated object-oriented database. The RSA has been a rapid prototyping effort whose purpose is to elucidate and define suitable technology for enhancing the performance of the range schedulers. Designing a system to assist schedulers in their task and using their current techniques as well as enhancements enabled by an electronic environment, has created a continuously developing model that will serve as a standard for future range scheduling systems. The RSA system is easy to use, easily ported between platforms, fast, and provides a set of tools for the scheduler that substantially increases his productivity.

Halbfinger, Eliezer M.↗
NASA NTRS2009

Peer-to-Peer Planning for Space Mission Control

Planning and scheduling for space operations entails the development of applications that embed intimate domain knowledge of distinct areas of mission control, while allowing for significant collaboration among them. The separation is useful because of differences in the planning problem, solution methods, and frequencies of replanning that arise in the different disciplines. For example, planning the activities of human spaceflight crews requires some reasoning about all spacecraft resources at timescales of minutes or seconds, and is subject to considerable volatility. Detailed power planning requires managing the complex interplay of power consumption and production, involves very different classes of constraints and preferences, but once plans are generated they are relatively stable.

Barreiro, Javier↗
NASA NTRS1989

Genetic algorithms applied to the scheduling of the Hubble Space Telescope

A prototype system employing a genetic algorithm (GA) has been developed to support the scheduling of the Hubble Space Telescope. A non-standard knowledge structure is used and appropriate genetic operators have been created. Several different crossover styles (random point selection, evolving points, and smart point selection) are tested and the best GA is compared with a neural network (NN) based optimizer. The smart crossover operator produces the best results and the GA system is able to evolve complete schedules using it. The GA is not as time-efficient as the NN system and the NN solutions tend to be better.

Sponsler, Jeffrey L.↗
NASA NTRS2010

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA's space data-communications infrastructure, the Space Network and the Ground Network, provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft via orbiting relay satellites and ground stations. An implementation of the methods and algorithms disclosed herein will be a system that produces globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary search, a class of probabilistic strategies for searching large solution spaces, constitutes the essential technology in this disclosure. Also disclosed are methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithm itself. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally, with applicability to a very broad class of combinatorial optimization problems.

Rash, James L.↗
NASA NTRS2017

Utilization of the International Space Station for Crew Autonomous Scheduling Test (CAST)

The United States space policy is evolving toward missions beyond low Earth orbit. In an effort to meet that policy, NASA has recognized Autonomous Mission Operations (AMO) as a valuable capability. Identified within AMO capabilities is the potential for autonomous planning and replanning during human spaceflight operations. That is allowing crew members to collectively or individually participate in the development of their own schedules. Currently, dedicated mission operations planners collaborate with international partners to create daily plans for astronauts aboard the International Space Station (ISS), taking into account mission requirements, ground rules, and various vehicle and payload constraints. In future deep space operations the crew will require more independence from ground support due to communication transmission delays. Furthermore, crew members who are provided with the capability to schedule their own activities are able to leverage direct experience operating in the space environment, and possibly maximize their efficiency. CAST (Crew Autonomous Scheduling Test) is an ISS investigation designed to analyze three important hypotheses about crew autonomous scheduling. First, given appropriate inputs, the crew is able to create and execute a plan in a reasonable period of time without impacts to mission success. Second, the proximity of the planner, in this case the crew, to the planned operations increases their operational efficiency. Third, crew members are more satisfied when given a role in plan development. This paper presents the results from a single astronaut test subject who participated in five CAST sessions. The details on the operational philosophy of CAST are discussed, including the approach to crew training, selection criteria for test days, and data collection methods. CAST is a technology demonstration payload sponsored by the ISS Research Science and Technology Office, and performed by experts in Mission Operations Planning from the Flight Operations Directorate at NASA Johnson Space Center, and researchers across multiple NASA centers. It is hoped the results of this investigation will guide NASA's implementation of autonomous mission operations for long duration human space missions to Mars and beyond.

Healy, Matthew↗
NASA NTRS1990

Lessons learned from the Hubble Space Telescope planning and scheduling system implementation and operation

The major challenge of the NASA Hubble Space Telescope (HST) Ground System has been the implementation of the planning and scheduling system. This paper describes the operational flow of HST from science proposals to the actual execution of science observations on board the HST. The paper provides a collection of lessons learned over the 10 years that have covered the definition, development, test, and initial operation of HST's planning and scheduling system.

Ruitberg, Edward O.↗
NASA NTRS2011

Automated scheduling for NASA’s Deep Space Network

This paper describes the DSN Scheduling Engine (DSE) component of a new scheduling system being deployed for NASA’s Deep Space Network. The DSE provides core automation functionality for scheduling the network, including the interpretation of scheduling requirements expressed by users, their elaboration into tracking passes, and resolving conflicts and constraint violations. The DSE incorporates both systematic search and repair-based algorithms, used for different phases and purposes in the overall system. It has been integrated in with a web application which provides its functionality to all DSN users through a standard web browser. The system is in the process of deployment to operational status.

Tran, Daniel↗
NASA NTRS2011

Options for Parallelizing a Planning and Scheduling Algorithm

Space missions have a growing interest in putting multi-core processors onboard spacecraft. For many missions processing power significantly slows operations. We investigate how continual planning and scheduling algorithms can exploit multi-core processing and outline different potential design decisions for a parallelized planning architecture. This organization of choices and challenges helps us with an initial design for parallelizing the CASPER planning system for a mesh multi-core processor. This work extends that presented at another workshop with some preliminary results.

parallel algorithms↗
NASA NTRS2019

Lessons Learned from International Space Station Crew Autonomous Scheduling Test

In 2017, our team investigated and evaluated the novel concept of operations of astronaut self-scheduling (rescheduling their own timeline without creating violations) onboard International Space Station (ISS). Five test sessions were completed for this technology demonstration called Crew Autonomous Scheduling Test (CAST). For the first time in a spaceflight operational environment, an ISS crewmember planned, rescheduled, and executed their activities in real-time on a mobile device while abiding by flight and scheduling constraints. This paper discusses the lessons learned from deployment to execution.

planning and scheduling↗
NASA NTRS2012

Automating Mid- and Long-Range Scheduling for NASA's Deep Space Network

NASA has recently deployed a new mid-range scheduling system for the antennas of the Deep Space Network (DSN), called Service Scheduling Software, or S(sup 3). This system is architected as a modern web application containing a central scheduling database integrated with a collaborative environment, exploiting the same technologies as social web applications but applied to a space operations context. This is highly relevant to the DSN domain since the network schedule of operations is developed in a peer-to-peer negotiation process among all users who utilize the DSN (representing 37 projects including international partners and ground-based science and calibration users). The initial implementation of S(sup 3) is complete and the system has been operational since July 2011. S(sup 3) has been used for negotiating schedules since April 2011, including the baseline schedules for three launching missions in late 2011. S(sup 3) supports a distributed scheduling model, in which changes can potentially be made by multiple users based on multiple schedule "workspaces" or versions of the schedule. This has led to several challenges in the design of the scheduling database, and of a change proposal workflow that allows users to concur with or to reject proposed schedule changes, and then counter-propose with alternative or additional suggested changes. This paper describes some key aspects of the S(sup 3) system and lessons learned from its operational deployment to date, focusing on the challenges of multi-user collaborative scheduling in a practical and mission-critical setting. We will also describe the ongoing project to extend S(sup 3) to encompass long-range planning, downtime analysis, and forecasting, as the next step in developing a single integrated DSN scheduling tool suite to cover all time ranges.

scheduling↗
NASA NTRS2012

Automating Mid- and Long-Range Scheduling for the NASA Deep Space Network

NASA has recently deployed a new mid-range scheduling system for the antennas of the Deep Space Network (DSN), called Service Scheduling Software, or S(sup 3). This system was designed and deployed as a modern web application containing a central scheduling database integrated with a collaborative environment, exploiting the same technologies as social web applications but applied to a space operations context. This is highly relevant to the DSN domain since the network schedule of operations is developed in a peer-to-peer negotiation process among all users of the DSN. These users represent not only NASA's deep space missions, but also international partners and ground-based science and calibration users. The initial implementation of S(sup 3) is complete and the system has been operational since July 2011. This paper describes some key aspects of the S(sup 3) system and on the challenges of modeling complex scheduling requirements and the ongoing extension of S(sup 3) to encompass long-range planning, downtime analysis, and forecasting, as the next step in developing a single integrated DSN scheduling tool suite to cover all time ranges.

Deep Space Network↗
NASA NTRSDate not supplied

Promoting Crew Autonomy in a Human Spaceflight Earth Analog Mission through Self-Scheduling

Deep space exploration missions face the challenge of communication transmission latencies between ground stations and astronaut crews due to increasing distance between the Earth and spacecraft in transit. To address this, research at NASA has aimed toward supporting crew autonomy by enabling astronauts to schedule their own timelines with minimal oversight from Mission Control. While self-scheduling has been shown to be feasible, it is yet to be studied as an integral part of autonomous crew operations. The current paper reviews the operationalization of self-scheduling and a number of related objectives during Campaign 6 of HERA, a Human Exploration Research Analog. Research objectives include studying the effects of phasic autonomy over the course of a 45-day mission, evaluating differences in scheduling performance produced by software interface aids, and deploying a novel measure of crew attitudes toward self-scheduling and plan execution.

crew autonomy↗