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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

State-based scheduling: An architecture for telescope observation scheduling

The applicability of constraint-based scheduling, a methodology previously developed and validated in the domain of factory scheduling, is extended to problem domains that require attendance to a wider range of state-dependent constraints. The problem of constructing and maintaining a short-term observation schedule for the Hubble Space Telescope (HST), which typifies this type of domain is the focus of interest. The nature of the constraints encountered in the HST domain is examined, system requirements are discussed with respect to utilization of a constraint-based scheduling methodology in such domains, and a general framework for state-based scheduling is presented.

Muscettola, Nicola↗
NASA NTRS1991

Polynomial optimization techniques for activity scheduling. Optimization based prototype scheduler

Polynomial optimization techniques for activity scheduling (optimization based prototype scheduler) are presented in the form of the viewgraphs. The following subject areas are covered: agenda; need and viability of polynomial time techniques for SNC (Space Network Control); an intrinsic characteristic of SN scheduling problem; expected characteristics of the schedule; optimization based scheduling approach; single resource algorithms; decomposition of multiple resource problems; prototype capabilities, characteristics, and test results; computational characteristics; some features of prototyped algorithms; and some related GSFC references.

Reddy, Surender↗
NASA NTRS1996

A Generic Expert Scheduling System Architecture and Toolkit: GUESS (Generically Used Expert Scheduling System)

Scheduling has become an increasingly important element in today's society and workplace. Within the NASA environment, scheduling is one of the most frequently performed and challenging functions. Towards meeting NASA's scheduling needs, a research version of a generic expert scheduling system architecture and toolkit has been developed. This final report describes the development and testing of GUESS (Generically Used Expert Scheduling System).

Liebowitz, Jay↗
NASA NTRS2011

Scheduling Results for the THEMIS Observation Scheduling Tool

We describe a scheduling system intended to assist in the development of instrument data acquisitions for the THEMIS instrument, onboard the Mars Odyssey spacecraft, and compare results from multiple scheduling algorithms. This tool creates observations of both (a) targeted geographical regions of interest and (b) general mapping observations, while respecting spacecraft constraints such as data volume, observation timing, visibility, lighting, season, and science priorities. This tool therefore must address both geometric and state/timing/resource constraints. We describe a tool that maps geometric polygon overlap constraints to set covering constraints using a grid-based approach. These set covering constraints are then incorporated into a greedy optimization scheduling algorithm incorporating operations constraints to generate feasible schedules. The resultant tool generates schedules of hundreds of observations per week out of potential thousands of observations. This tool is currently under evaluation by the THEMIS observation planning team at Arizona State University.

Thermal Emission Imaging System (THEMIS)↗
NASA NTRS1975

An algorithm for a single machine scheduling problem with sequence dependent setup times and scheduling windows

An enumeration algorithm is presented for solving a scheduling problem similar to the single machine job shop problem with sequence dependent setup times. The scheduling problem differs from the job shop problem in two ways. First, its objective is to select an optimum subset of the available tasks to be performed during a fixed period of time. Secondly, each task scheduled is constrained to occur within its particular scheduling window. The algorithm is currently being used to develop typical observational timelines for a telescope that will be operated in earth orbit. Computational times associated with timeline development are presented.

Moore, J. E.↗
NASA NTRSDate not supplied

Crew Autonomy through Self-Scheduling: Guidelines for Crew Scheduling Performance Envelope and Mitigation Strategies

Future long duration exploration missions (LDEMs) bring new challenges to astronaut crews in deep space, one of which is increased communication latencies with ground stations. As a result, crews will have to behave more autonomously by self-scheduling their own operational timelines in an efficient and effective manner. To support crew autonomy, our team has spent the last few years developing Playbook, a mission planning and scheduling tool. Our research focuses on investigating scheduling performance using Playbook to inform the deployment of novel aids that streamline the timeline creation process and proposing relevant standards and guidelines for autonomous crews in LDEMs. Summarizing yearly progress of research analysis and experiment in HERA.

user experience↗
NASA NTRSDate not supplied

Crew Autonomy Through Self-Scheduling: Guidelines for Crew Scheduling Performance Envelope and Mitigation Strategies

NASA’s future long duration exploration missions (LDEMs) will encounter increasing communication transmission delays as they move farther from Earth-based ground stations. Because crews can no longer rely on real-time support from ground planners, they will have to self-schedule their own operational timelines effectively and efficiently. To enable this, our team develops Playbook, a mission planning and scheduling tool. Our research focuses on quantifying scheduling performance using Playbook to inform the design and development of future features aimed at streamlining timeline creation. We also aim to propose standards and guidelines for autonomous crews in LDEMs. This year, we discuss preliminary results from HERA Campaign 6.

self-scheduling↗
DOE OSTI2024

Tools And Methods to Analyze Plant Outage Schedule and Assist Schedulers in Improving Outage Resilience

Refueling outages of nuclear power plants (NPPs) are considered one of the most critical phases throughout the plant lifetime. In such instances, tens of thousands of activities (e.g., maintenance, surveillance) are performed in a short amount of time (typically 2-3 weeks unless major backfitting or modernization projects are carried out) by a large number of crews (e.g., electricians, mechanics) that are hired as contractors. As a consequence, a plant outage can be expensive not only in terms of costs (e.g., contractor labor, material), but also in terms of loss generation since the plant is taken off the grid during the full outage duration (an indicative metric is about 1.2M$/day of loss of revenue). Thus, there is a continuous need to decrease the economic impact of outages on plant finances. This can be done by: decreasing the frequency of plant outages (e.g., from 18 to 24 months), reducing the time to complete the outage, and reducing the risk of outage delays. The Optimization of Outage Activities project under the Risk Informed Systems Analysis Pathway (RISA) sponsored by Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program focuses on developing tools and methods to support NPPs with outage schedule optimization. The developed tools and methods are designed to analyze plant outage schedule with the goal of identify critical elements in the schedule that might pose a high risk of delays. These methods and tools can be considered resource-centric in the sense that they address outage challenges as a resource optimization problem. In this context, resources are either time and crews; outage delays occurs when either (or both) resources are insufficient to complete the set of tasks assigned at a specific time instant of the outage. This report provides details on how plant resources (time and crews) can be allocated in such a way that delays are minimized. In this respect, two classes of methods have been developed: the first one focuses on the time resource and how variability of the time to complete outage tasks may impact outage delays. The second one integrates available resources to assess when dailies activities should be performed such that the risk of outage delays are minimized.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Scheduling techniques in the Request Oriented Scheduling Engine (ROSE)

Scheduling techniques in the ROSE are presented in the form of the viewgraphs. The following subject areas are covered: agenda; ROSE summary and history; NCC-ROSE task goals; accomplishments; ROSE timeline manager; scheduling concerns; current and ROSE approaches; initial scheduling; BFSSE overview and example; and summary.

Zoch, David R.↗
NASA NTRS1992

Requirements for the implementation of schedule repair technology in the Experiment Scheduling Program

The following list of requirements specifies the proposed revisions to the Experiment Scheduling Program (ESP2) which deal with schedule repair. These requirements are divided into those which are general in nature, those which relate to measurement and analysis functions of the software, those which relate specifically to conflict resolution, and those relating directly to the user interface. (This list is not a complete list of requirements for the user interface, but only a list of those schedule repair requirements which relate to the interface.) Some of the requirements relate only to uses of the software in real-time operations. Others are clearly for future versions of the software, beyond the upcoming revision. In either case, the fact will be clearly stated.

Bullington, Stanley F.↗
NASA NTRS2021

Utilizing Schedule Constraints to Improve Automated Scheduling in NASA's Deep Space Network

NASA’s Deep Space Network (DSN) is a mission critical facility that supports many different space missions,from LEO to deep space exploration. In recent years, as the network has suffered from increasing oversubscription, more restrictions have been added to reduce the amount of manual scheduling labor necessary to come to consensus. In this paper, we describe a new auto-mated scheduling tool which takes advantage of these restrictions to bring the scheduling problem closer to feasibility. In addition, we describe an algorithm to reduce problem inputs given a partially-solved problem,thereby bringing the problem even closer to feasibility

Johnston, Mark↗
NASA NTRSDate not supplied

Crew Autonomy through Self-Scheduling: Guidelines for Crew Scheduling Performance Envelope and Mitigation Strategies

As NASA considers long-duration exploration missions, it is envisioned that crews will behave more autonomously as compared to low-Earth orbit missions. When considering long duration exploration missions, Flight Operations Directorate (FOD) identified the following benefits and challenges presented on this slide. As missions operate further from Earth, the communication latency between the spacecraft and Mission Control Center will increase requiring the crew to take a more active role in reacting to daily planning. However, one of the key challenges for crew self-scheduling is that we do not want to overwhelm astronauts who are not expert mission planners. This leads to our primary research objective: to first, characterize the human performance envelope for the task of planning and scheduling in the context of human spaceflight operations, then, develop countermeasure aids to mitigate adverse performance effects due to plan complexity, and finally, inform performance standards and guidelines based on research results. Our next steps are to finish summarizing our findings from the experiment in conference papers and our upcoming yearly report. In the upcoming year, we will continue to collect data in analog missions and begin summarizing our recommended standards and guidelines.

user experience↗
NASA NTRS2015

Assessing Resilience of Scheduled Performance-Based Navigation Arrival Operations

This paper assesses the resilience of scheduled Performance-Based Navigation (PBN) arrival operations. Resilience is defined as an ability to return to nominal operations following a schedule perturbation. Results from a Human-in-the- Loop (HITL) experiment that included off-nominal events to perturb the schedule are described. The schedule comes from a precision trajectory-based arrival manager. The experiment collected data regarding the response to perturbed schedules in three conditions, where: 1) a disturbance rejection algorithm made schedule adjustments automatically, 2) a Traffic Management Coordinator (TMC) participant made schedule adjustments manually, or 3) no schedule adjustments were made. Analyses showed that the simulation’s scheduled PBN operations have inherent resilience, recovering from more than half of the perturbed schedules even with no schedule adjustments. Resilience to the same off-nominal events improved with schedule adjustments; an increased proportion of perturbed schedules recovered within the length of operation run, and the average duration of the schedule’s perturbed state decreased. Compared to the manual schedule adjustments condition, a greater number of schedule adjustments occurred for the same off-nominal events in the automated condition. However, perturbed schedules were recovered more frequently and perturbations were less severe in the automated condition. Subjective and objective workload in the manual and the automated schedule adjustment conditions were similar to the no schedule adjustment condition.

Resilience↗
NASA NTRS2020

Using Explainable Scheduling for the Mars 2020 Rover Mission

Understanding the reasoning behind the behavior of an auto- mated scheduling system is essential to ensure that it will be trusted and consequently used to its full capabilities in critical applications. In cases where a scheduler schedules activities in an invalid location, it is usually easy for the user to infer the missing constraint by inspecting the schedule with the in- valid activity to determine the missing constraint. If a sched- uler fails to schedule activities because constraints could not be satisfied, determining the cause can be more challenging. In such cases it is important to understand which constraints caused the activities to fail to be scheduled and how to al- ter constraints to achieve the desired schedule. In this pa- per, we describe such a scheduling system for NASA’s Mars 2020 Perseverance Rover, as well as Crosscheck, an explain- able scheduling tool that explains the scheduler behavior. The scheduling system and Crosscheck are the baseline for oper- ational use to schedule activities for the Mars 2020 rover. As we describe, the scheduler generates a schedule given a set of activities and their constraints and Crosscheck: (1) provides a visual representation of the generated schedule; (2) analyzes and explains why activities failed to schedule given the con- straints provided; and (3) provides guidance on potential con- straint relaxations to enable the activities to schedule in future scheduler runs.

Chien, Steve↗
NASA NTRS2004

An Enabling Technology for New Planning and Scheduling Paradigms

The Night Projects Directorate at NASA's Marshall Space Flight Center is developing a new planning and scheduling environment and a new scheduling algorithm to enable a paradigm shift in planning and scheduling concepts. Over the past 33 years Marshall has developed and evolved a paradigm for generating payload timelines for Skylab, Spacelab, various other Shuttle payloads, and the International Space Station. The current paradigm starts by collecting the requirements, called ?ask models," from the scientists and technologists for the tasks that are to be scheduled. Because of shortcomings in the current modeling schema, some requirements are entered as notes. Next, a cadre with knowledge of vehicle and hardware modifies these models to encompass and be compatible with the hardware model; again, notes are added when the modeling schema does not provide a better way to represent the requirements. Finally, the models are modified to be compatible with the scheduling engine. Then the models are submitted to the scheduling engine for automatic scheduling or, when requirements are expressed in notes, the timeline is built manually. A future paradigm would provide a scheduling engine that accepts separate science models and hardware models. The modeling schema would have the capability to represent all the requirements without resorting to notes. Furthermore, the scheduling engine would not require that the models be modified to account for the capabilities (limitations) of the scheduling engine. The enabling technology under development at Marshall has three major components: (1) A new modeling schema allows expressing all the requirements of the tasks without resorting to notes or awkward contrivances. The chosen modeling schema is both maximally expressive and easy to use. It utilizes graphical methods to show hierarchies of task constraints and networks of temporal relationships. (2) A new scheduling algorithm automatically schedules the models without the intervention of a scheduling expert. The algorithm is tuned for the constraint hierarchies and the complex temporal relationships provided by the modeling schema. It has an extensive search algorithm that can exploit timing flexibilities and constraint and relationship options. (3) An innovative architecture allows multiple remote users to simultaneously model science and technology requirements and other users to model vehicle and hardware characteristics. The architecture allows the remote users to submit scheduling requests directly to the scheduling engine and immediately see the results. These three components are integrated so that science and technology experts with no knowledge of the vehicle or hardware subsystems and no knowledge of the internal workings of the scheduling engine have the ability to build and submit scheduling requests and see the results. The immediate feedback will hone the users' modeling skills and ultimately enable them to produce the desired timeline. This paper summarizes the three components of the enabling technology and describes how this technology would make a new paradigm possible.

Jaap, John↗