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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Pitch Guidance Optimization for the Orion Abort Flight Tests

The National Aeronautics and Space Administration created the Constellation program to develop the next generation of manned space vehicles and launch vehicles. The Orion abort system is initiated in the event of an unsafe condition during launch. The system has a controller gains schedule that can be tuned to reduce the attitude errors between the simulated Orion abort trajectories and the guidance trajectory. A program was created that uses the method of steepest descent to tune the pitch gains schedule by an automated procedure. The gains schedule optimization was applied to three potential abort scenarios; each scenario tested using the optimized gains schedule resulted in reduced attitude errors when compared to the Orion production gains schedule.

Stillwater, Ryan Allanque↗
NASA NTRS1992

Heuristic-based scheduling algorithm for high level synthesis

A new scheduling algorithm is proposed which uses a combination of a resource utilization chart, a heuristic algorithm to estimate the minimum number of hardware units based on operator mobilities, and a list-scheduling technique to achieve fast and near optimal schedules. The schedule time of this algorithm is almost independent of the length of mobilities of operators as can be seen from the benchmark example (fifth order digital elliptical wave filter) presented when the cycle time was increased from 17 to 18 and then to 21 cycles. It is implemented in C on a SUN3/60 workstation.

Mohamed, Gulam↗
NASA NTRS1988

Knowledge based tools for Hubble Space Telescope planning and scheduling: Constraints and strategies

The Hubble Space Telescope (HST) presents an especially challenging scheduling problem since a year's observing program encompasses tens of thousands of exposures facing numerous coupled constraints. Recent progress in the development of planning and scheduling tools is discussed which augment the existing HST ground system. General methods for representing activities, constraints, and constraint satisfaction, and time segmentation were implemented in a scheduling testbed. The testbed permits planners to evaluate optimal scheduling time intervals, calculate resource usage, and to generate long and medium range plans. Graphical displays of activities, constraints, and plans are an important feature of the system. High-level scheduling strategies using rule based and neural net approaches were implemented.

Miller, Glenn↗
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 NTRS2012

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.

Mixed Integer Programming↗
NASA NTRS1995

Scheduling time-critical graphics on multiple processors

This paper describes an algorithm for the scheduling of time-critical rendering and computation tasks on single- and multiple-processor architectures, with minimal pipelining. It was developed to manage scientific visualization scenes consisting of hundreds of objects, each of which can be computed and displayed at thousands of possible resolution levels. The algorithm generates the time-critical schedule using progressive-refinement techniques; it always returns a feasible schedule and, when allowed to run to completion, produces a near-optimal schedule which takes advantage of almost the entire multiple-processor system.

Meyer, Tom W.↗
NASA NTRS1987

Expert systems tools for Hubble Space Telescope observation scheduling

This paper discusses the utility of expert systems techniques for Hubble Space Telescope (HST) planning and scheduling and describes a plan for development of expert system tools which will augment the existing ground system. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool running on a LISP workstation.

Miller, Glenn↗
NASA NTRS1987

Expert systems tools for Hubble Space Telescope observation scheduling

The utility of expert systems techniques for the Hubble Space Telescope (HST) planning and scheduling is discussed and a plan for development of expert system tools which will augment the existing ground system is described. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool running on a LISP workstation.

Miller, Glenn↗
NASA NTRSDate not supplied

Spacecraft-Initiated Scheduling of Commercial Communications Services

We propose a software framework enabling a spacecraft in Earth orbit to schedule its own access to space communications services via ground stations and relay satellites. All operations are automated, without a human in the loop, allowing for highly responsive service to meet time-varying needs. We describe a modular software architecture allowing the framework to interface with the scheduling systems of several providers - both government and commercial. Specifically, we present the results of an experiment with Amazon Web Services (AWS) Ground Station, an operational commercial service provider. Proposed software executed scheduling of a ground station antenna with minimal lead time (less than 20 minutes before the start of a pass). During the contact AWS cloud infrastructure was used to demodulate, process, and distribute data products from an orbiting satellite. We believe this work demonstrates the framework's ability to interface with additional providers and potential to integrate more complex decision-making in the future to schedule optimal contacts.

Scheduling↗
NASA NTRSDate not supplied

Aerial Vehicle Routing and Scheduling for UAS Traffic Management: A Hybrid Monte Carlo Tree Search Approach

We present the Multi-Route Weighted Package Delivery Problem (MRWPDP) and a scalable solution methodology as a major step towards enabling an airspace deconfliction service for drone delivery operations. The problem is motivated by Strategic deconfliction under the FAA’s “Unmanned Aircraft Systems Traffic Management” Concept of Operations. MRWPDP falls under a class of vehicle routing and scheduling problems, and as such is NP-Hard. In MRWPDP, a graph network is given which consists of depots, drop-off sites, and multiple routes connecting the two. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is to optimally schedule the departure time and assign routes to a known set of vehicles at the depot. We propose a heuristic solution to the problem by borrowing techniques from Mixed Integer Linear Programming (MILP), Constraint Programming, and Monte Carlo Tree Search (MCTS). The resulting hybrid framework is MCTS with Bound-and-Prune (BP) and rapid simulated updates (U), or MCTS-BP-U. This approach is able to quickly provide a feasible solution for MRWPDP, even for large problem instances up to 1000 vehicles. We provide a MILP formulation of MRWPDP and compare its performance against MCTS-BP-U in terms of solution quality. An agent-based model simulation is conducted as a final step to validate the efficacy of our approach.

air traffic scheduling↗
NASA NTRSDate not supplied

Aerial Vehicle Routing and Scheduling for UAS Traffic Management: A Hybrid Monte Carlo Tree Search Approach

We present the Multi-Route Weighted Package Delivery Problem (MRWPDP) and a scalable solution methodology as a major step towards enabling an airspace deconfliction service for drone delivery operations. The problem is motivated by Strategic deconfliction under the FAA’s “Unmanned Aircraft Systems Traffic Management” Concept of Operations. MRWPDP falls under a class of vehicle routing and scheduling problems, and as such is NP-Hard. In MRWPDP, a graph network is given which consists of depots, drop-off sites, and multiple routes connecting the two. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is to optimally schedule the departure time and assign routes to a known set of vehicles at the depot. We propose a heuristic solution to the problem by borrowing techniques from Mixed Integer Linear Programming (MILP), Constraint Programming, and Monte Carlo Tree Search (MCTS). The resulting hybrid framework is MCTS with Bound-and-Prune (BP) and rapid simulated updates (U), or MCTS-BP-U. This approach is able to quickly provide a feasible solution for MRWPDP, even for large problem instances up to 1000 vehicles. We provide a MILP formulation of MRWPDP and compare its performance against MCTS-BP-U in terms of solution quality. An agent-based model simulation is conducted as a final step to validate the efficacy of our approach.

air traffic scheduling↗
NASA NTRS1990

Space communications scheduler: A rule-based approach to adaptive deadline scheduling

Job scheduling is a deceptively complex subfield of computer science. The highly combinatorial nature of the problem, which is NP-complete in nearly all cases, requires a scheduling program to intelligently transverse an immense search tree to create the best possible schedule in a minimal amount of time. In addition, the program must continually make adjustments to the initial schedule when faced with last-minute user requests, cancellations, unexpected device failures, quests, cancellations, unexpected device failures, etc. A good scheduler must be quick, flexible, and efficient, even at the expense of generating slightly less-than-optimal schedules. The Space Communication Scheduler (SCS) is an intelligent rule-based scheduling system. SCS is an adaptive deadline scheduler which allocates modular communications resources to meet an ordered set of user-specified job requests on board the NASA Space Station. SCS uses pattern matching techniques to detect potential conflicts through algorithmic and heuristic means. As a result, the system generates and maintains high density schedules without relying heavily on backtracking or blind search techniques. SCS is suitable for many common real-world applications.

Straguzzi, Nicholas↗
NASA NTRS2019

Rising Above the Cloud - Toward High-Rate Delay-Tolerant Networking in Low-Earth Orbit

The High Data Rate Architecture (HiDRA) project is implementing a High-rate Delay Tolerant Networking (HDTN) capability that can support Low Earth Orbit (LEO) applications and environments. The present state of the effort, future work, and other elements of the work to date are described in this paper. This implementation is intended to support applications that run at 1+ Gbps, per the requirements of modern optical and high-frequency RF links. Uniquely, this implementation is also tuned to support relay and data trunking applications, which might require support for large numbers of small bundles per second. The design for this platform is based entirely on commercial-off-the-shelf (COTS) components, and possesses buffering capabilities in the 5 TB range. This document takes results from previous individual tests and integrates them to demonstrate results in the presence of a coherent use-case: consider a network aboard the ISS which intends to utilize an upcoming optical communications capability. For this use-case, orbital analysis software is used to analyze orbital dynamics, from which a list of access times are generated that might take in to account weather, schedule competition, etc. A variant of Contact Graph Routing (CGR) is applied to these windows to determine an optimal schedule. This schedule is then loaded into the HDTN prototype and, in conjunction with various measurement tools, a complete end-to-end analysis of HDTN's performance is conducted. Various bottlenecks (including storage) are identified: these bottlenecks are expected to help us focus our future work on the elements of the system that are most likely to present issues moving forward. Finally, we discuss possible paths for evolution beyond the present rates supported by the system, including (but not limited to) hardware acceleration.

Hylton, Alan↗
NASA NTRS2021

Romie: A Domain-Independent Tool for Computer-Aided Robust Operations Management

Romie is a decision support tool based on AI's latest advances in the domain of robust scheduling. Unlike all its predecessors, the tool allows to (i) visually model the operational problem and context entirely (ii) optimize to find near-optimal schedules while taking uncertainty into account and deals with (iii) a combination of various {key performance indicators (KPIs). It comes with a web user interface. Part or all of the modelled activities may be associated to random variables describing their stochastic durations, in order to produce schedules that are robust w.r.t. temporal uncertainty. Hence, depending on the pursued KPIs, the schedules maximize a combination of the following terms: the probability of satisfying the problem constraints, the expected return/efficiency, the expected outcome quality, and even the operators' wellness by minimizing its expected extra-hours. Initially developed for spatial exploration and demonstration in the context of Mars analog missions, this versatile tool is here applied to operations management in both biotechnology manufacturing and robots parametrization in a cave exploration context.

Chien, Steve A.↗
NASA NTRS1990

Evaluating scheduling algorithms for traffic with heterogeneous performance objectives

Two types of network traffic are considered: traffic with deadlines, for which the most important performance objective is based on loss rate, and packets without deadlines, for which the most important performance objective is based on mean delay. An optimal scheduling algorithm is presented to minimize weighted loss rate and weighted mean delay in the queues that form at the switches and at the network access points of a packet-switched network, where weights reflect the relative importance of packets. Although not practical for implementation, the algorithm is intended as a standard for the comparison of the performance of other scheduling algorithms. The algorithm is more general and lower computational complexity than previously published algorithms, enabling performance evaluation of some important scenarios that could not previously have been considered. Using the optimal performance results of this algorithm, the performance of the first-come-first-served, static priority, and earliest deadline first scheduling algorithms is evaluated. The results suggest that network efficiency could be improved by using a more sophisticated heuristic scheduling algorithm rather than one of the aforementioned algorithms.

Peha, Jon M.↗
NASA NTRS1993

A Genetic Algorithm Tool (splicer) for Complex Scheduling Problems and the Space Station Freedom Resupply Problem

The Space Station Freedom will require the supply of items in a regular fashion. A schedule for the delivery of these items is not easy to design due to the large span of time involved and the possibility of cancellations and changes in shuttle flights. This paper presents the basic concepts of a genetic algorithm model, and also presents the results of an effort to apply genetic algorithms to the design of propellant resupply schedules. As part of this effort, a simple simulator and an encoding by which a genetic algorithm can find near optimal schedules have been developed. Additionally, this paper proposes ways in which robust schedules, i.e., schedules that can tolerate small changes, can be found using genetic algorithms.

Wang, Lui↗
NASA NTRS2002

A System for Planning Ahead

A software system that uses artificial intelligence techniques to help with complex Space Shuttle scheduling at Kennedy Space Center is commercially available. Stottler Henke Associates, Inc.(SHAI), is marketing its automatic scheduling system, the Automated Manifest Planner (AMP), to industries that must plan and project changes many different times before the tasks are executed. The system creates optimal schedules while reducing manpower costs. Using information entered into the system by expert planners, the system automatically makes scheduling decisions based upon resource limitations and other constraints. It provides a constraint authoring system for adding other constraints to the scheduling process as needed. AMP is adaptable to assist with a variety of complex scheduling problems in manufacturing, transportation, business, architecture, and construction. AMP can benefit vehicle assembly plants, batch processing plants, semiconductor manufacturing, printing and textiles, surface and underground mining operations, and maintenance shops. For most of SHAI's commercial sales, the company obtains a service contract to customize AMP to a specific domain and then issues the customer a user license.

Source record↗
NASA NTRS1992

Design and scheduling for periodic concurrent error detection and recovery in processor arrays

Periodic application of time-redundant error checking provides the trade-off between error detection latency and performance degradation. The goal is to achieve high error coverage while satisfying performance requirements. We derive the optimal scheduling of checking patterns in order to uniformly distribute the available checking capability and maximize the error coverage. Synchronous buffering designs using data forwarding and dynamic reconfiguration are described. Efficient single-cycle diagnosis is implemented by error pattern analysis and direct-mapped recovery cache. A rollback recovery scheme using start-up control for local recovery is also presented.

Wang, Yi-Min↗