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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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NASA NTRS2004

Integrated Risk Management Within NASA Programs/Projects

As NASA Project Risk Management activities continue to evolve, the need to successfully integrate risk management processes across the life cycle, between functional disciplines, stakeholders, various management policies, and within cost, schedule and performance requirements/constraints become more evident and important. Today's programs and projects are complex undertakings that include a myriad of processes, tools, techniques, management arrangements and other variables all of which must function together in order to achieve mission success. The perception and impact of risk may vary significantly among stakeholders and may influence decisions that may have unintended consequences on the project during a future phase of the life cycle. In these cases, risks may be unintentionally and/or arbitrarily transferred to others without the benefit of a comprehensive systemic risk assessment. Integrating risk across people, processes, and project requirements/constraints serves to enhance decisions, strengthen communication pathways, and reinforce the ability of the project team to identify and manage risks across the broad spectrum of project management responsibilities. The ability to identify risks in all areas of project management increases the likelihood a project will identify significant issues before they become problems and allows projects to make effective and efficient use of shrinking resources. By getting a total team integrated risk effort, applying a disciplined and rigorous process, along with understanding project requirements/constraints provides the opportunity for more effective risk management. Applying an integrated approach to risk management makes it possible to do a better job at balancing safety, cost, schedule, operational performance and other elements of risk. This paper will examine how people, processes, and project requirements/constraints can be integrated across the project lifecycle for better risk management and ultimately improve the chances for mission success.

Connley, Warren↗

NASA NTRS1961

A Feasible Approach for an Early Manned Lunar Landing. Part II: Detailed Report of Ad Hoc Task Group

This report, in two parts, presents a program development plan for attempting a first manned lunar landing in 1967. The two parts consist of a Summary Report and a Detailed Report representing the coordinated output of the Ad Hoc Task Group assigned to the study. The study was started in response to the request for such a study by the Associate Administrator in his memorandum of May 2, 1961 establishing the Ad Hoc Task Group. The purpose of the study was to take a first cut at the tasks associated with the design, development and construction of the equipment and facilities as well as the development of the crews, and to show the time phasing 6f these tasks. Included are the space sciences, life science and advanced technology tasks whose data and results are needed for designing and developing the systems required in carrying out the mission. The plan presented in the two reports does not presume to be a firm plan. Its basic purpose is, by choosing one feasible method, to size up the scope, schedule and cost of the job, discover the main problems, pacing items and major decisions and provide a threshold from which a firm and detailed project development plan can be jointly formulated by the various elements of NASA.

Fleming, William A.↗

NASA NTRS1995

A microeconomic scheduler for parallel computers

We describe a scheduler based on the microeconomic paradigm for scheduling on-line a set of parallel jobs in a multiprocessor system. In addition to the classical objectives of increasing the system throughput and reducing the response time, we consider fairness in allocating system resources among the users, and providing the user with control over the relative performances of his jobs. We associate with every user a savings account in which he receives money at a constant rate. When a user wants to run a job, he creates an expense account for that job to which he transfers money from his savings account. The job uses the funds in its expense account to obtain the system resources it needs for execution. The share of the system resources allocated to the user is directly related to the rate at which the user receives money; the rate at which the user transfers money into a job expense account controls the job's performance. We prove that starvation is not possible in our model. Simulation results show that our scheduler improves both system and user performances in comparison with two different variable partitioning policies. It is also shown to be effective in guaranteeing fairness and providing control over the performance of jobs.

Stoica, Ion↗

DOE OSTI2026

AQDrop Quantum Service (AQDrop) v1.0

AQDrop is a job management system designed to streamline access to the Advanced Quantum Testbed (AQT) at NERSC (National Energy Research Scientific Computing Center). It serves as a centralized middleware layer between researchers and quantum processing hardware. Key Features: AQDrop provides a FastAPI-based server backed by PostgreSQL for job submission, queue management, and role-based access control (members, operators, and administrators). Users submit Qiskit circuits via JSON payloads, which are queued, dispatched to the QPU through the Qubic API, and returned as measurement counts. A Python client library and web dashboard round out the interface options. Primary Use: Researchers submit quantum circuit jobs from a laptop or login node; an operator client executes those jobs on the AQT's physical QPU and returns results — all coordinated through the central API. Advantages: Compared to ad-hoc or direct hardware access, AQDrop adds structured queue management, auditable job-status tracking and OAuth2 authentication — reducing scheduling conflicts and unauthorized access. Its containerized deployment also improves reproducibility and scalability. Overall, AQDrop functions as a purpose-built quantum job broker tailored to NERSC's specific hardware and institutional access requirements.

Caplinger, Evan [Lawrence Berkeley National Labora↗

NASA NTRS1971

A simple executive for a fault-tolerant, real-time multiprocessor.

Description of a simple executive for operation with a fault-tolerant multiprocessor that is oriented toward application in an environment where the primary function is to provide real-time control. The primary executive function is to accept requests for jobs placed by other jobs or from peripheral equipment and then schedule their initiation in accordance with the request parameters. The executive is also brought into action when a processor fails, so that appropriate disposition may be made of the job that was running on the failed processor. Many architectural features intended to support this executive concept are included.

Filene, R. J.↗

NASA NTRS1979

Performance and economy of a fault-tolerant multiprocessor

The FTMP (Fault-Tolerant Multiprocessor) is one of two central aircraft fault-tolerant architectures now in the prototype phase under NASA sponsorship. The intended application of the computer includes such critical real-time tasks as 'fly-by-wire' active control and completely automatic Category III landings of commercial aircraft. The FTMP architecture is briefly described and it is shown that it is a viable solution to the multi-faceted problems of safety, speed, and cost. Three job dispatch strategies are described, and their results with respect to job-starting delay are presented. The first strategy is a simple First-Come-First-Serve (FCFS) job dispatch executive. The other two schedulers are an adaptive FCFS and an interrupt driven scheduler. Three failure modes are discussed, and the FTMP survival probability in the face of random hard failures is evaluated. It is noted that the hourly cost of operating two FTMPs in a transport aircraft can be as little as one-to-two percent of the total flight-hour cost of the aircraft.

Lala, J. H.↗

NASA NTRS1984

Operational numerical weather prediction on the CYBER 205 at the National Meteorological Center

The Development Division of the National Meteorological Center (NMC), having the responsibility of maintaining and developing the numerical weather forecasting systems of the center, is discussed. Because of the mission of NMC data products must be produced reliably and on time twice daily free of surprises for forecasters. Personnel of Development Division are in a rather unique situation. They must develop new advanced techniques for numerical analysis and prediction utilizing current state-of-the-art techniques, and implement them in an operational fashion without damaging the operations of the center. With the computational speeds and resources now available from the CYBER 205, Development Division Personnel will be able to introduce advanced analysis and prediction techniques into the operational job suite without disrupting the daily schedule. The capabilities of the CYBER 205 are discussed.

Deaven, D.↗

NASA NTRS1992

Generating effective project scheduling heuristics by abstraction and reconstitution

A project scheduling problem consists of a finite set of jobs, each with fixed integer duration, requiring one or more resources such as personnel or equipment, and each subject to a set of precedence relations, which specify allowable job orderings, and a set of mutual exclusion relations, which specify jobs that cannot overlap. No job can be interrupted once started. The objective is to minimize project duration. This objective arises in nearly every large construction project--from software to hardware to buildings. Because such project scheduling problems are NP-hard, they are typically solved by branch-and-bound algorithms. In these algorithms, lower-bound duration estimates (admissible heuristics) are used to improve efficiency. One way to obtain an admissible heuristic is to remove (abstract) all resources and mutual exclusion constraints and then obtain the minimal project duration for the abstracted problem; this minimal duration is the admissible heuristic. Although such abstracted problems can be solved efficiently, they yield inaccurate admissible heuristics precisely because those constraints that are central to solving the original problem are abstracted. This paper describes a method to reconstitute the abstracted constraints back into the solution to the abstracted problem while maintaining efficiency, thereby generating better admissible heuristics. Our results suggest that reconstitution can make good admissible heuristics even better.

Janakiraman, Bhaskar↗

NASA NTRS1984

Standardization in software conversion of (ROM) estimating

Technical problems and their solutions comprise by far the majority of work involved in space simulation engineering. Fixed price contracts with schedule award fees are becoming more and more prevalent. Accurate estimation of these jobs is critical to maintain costs within limits and to predict realistic contract schedule dates. Computerized estimating may hold the answer to these new problems, though up to now computerized estimating has been complex, expensive, and geared to the business world, not to technical people. The objective of this effort was to provide a simple program on a desk top computer capable of providing a Rough Order of Magnitude (ROM) estimate in a short time. This program is not intended to provide a highly detailed breakdown of costs to a customer, but to provide a number which can be used as a rough estimate on short notice. With more debugging and fine tuning, a more detailed estimate can be made.

Roat, G. H.↗

DOE OSTI2025

Exascale workflow applications and middleware: An ExaWorks retrospective

Exascale computers offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific discovery and insight. However, these software combinations and integrations are difficult to achieve due to the challenges of coordinating and deploying heterogeneous software components on diverse and massive platforms. Here, we present the ExaWorks project, which addresses many of these challenges. We developed a workflow Software Development Toolkit (SDK), a curated collection of workflow technologies that can be composed and interoperated through a common interface, engineered following current best practices, and specifically designed to work on HPC platforms. ExaWorks also developed PSI/J, a job management abstraction API, to simplify the construction of portable software components and applications that can be used over various HPC schedulers. The PSI/J API is a minimal interface for submitting and monitoring jobs and their execution state across multiple and commonly used HPC schedulers. We also describe several leading and innovative workflow examples of ExaWorks tools used on DOE leadership platforms. Furthermore, we discuss how our project is working with the workflow community, large computing facilities, and HPC platform vendors to address the requirements of workflows sustainably at the exascale.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2003

Requirements: The More the Better?

Nothing ever, ever, becomes a requirement until two things happen: (1) there is a solid understanding and acceptance of the requirement's cost and schedule implications; and (2) knowledgeable technical people are so confident that the program can meet the requirement within the cost and schedule that they are willing to bet their jobs on it. Yikes!! Does this mean that we never undertake high-risk projects? No. what it does mean is that when you undertake high-risk activities, you agree on an expectation or requirement that includes failure, or falling short, as a real possibility, and your cost and schedule reflect the risk. The other thing that it means is that you may have to start a project with some requirements open until after the work progresses to a point where the requirement meets the two criteria above. The process is also flawed because there are usually too many requirements. Something about the engineering or designer mentality seems to demand hosts of requirements as an input to the technical process.

Little, Terry↗

DOE OSTI2024

Exploring Enhanced Dominant Resource Fairness Using Linear Programming Calculated Weights

Maintaining resource fairness while achieving optimization for various performance metrics such as resource utilization, turnaround time and job latency is a well-known resource scheduling challenge in cloud computing. Despite the significant progress made with the introduction of dominant resource fairness by Ghodsi et al., which ensures major allocation properties such as sharing incentive, strategy-proofness, envy-freeness and Pareto efficiency to be achieved

Yan, Bo [Binghamton University]↗

NASA NTRS2011

Meta-RaPS Algorithm for the Aerial Refueling Scheduling Problem

The Aerial Refueling Scheduling Problem (ARSP) can be defined as determining the refueling completion times for each fighter aircraft (job) on multiple tankers (machines). ARSP assumes that jobs have different release times and due dates, The total weighted tardiness is used to evaluate schedule's quality. Therefore, ARSP can be modeled as a parallel machine scheduling with release limes and due dates to minimize the total weighted tardiness. Since ARSP is NP-hard, it will be more appropriate to develop a ppro~imate or heuristic algorithm to obtain solutions in reasonable computation limes. In this paper, Meta-Raps-ATC algorithm is implemented to create high quality solutions. Meta-RaPS (Meta-heuristic for Randomized Priority Search) is a recent and promising meta heuristic that is applied by introducing randomness to a construction heuristic. The Apparent Tardiness Rule (ATC), which is a good rule for scheduling problems with tardiness objective, is used to construct initial solutions which are improved by an exchanging operation. Results are presented for generated instances.

Kaplan, Sezgin↗

NASA NTRS2005

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↗

NASA NTRS2003

A Hierarchical and Distributed Approach for Mapping Large Applications to Heterogeneous Grids using Genetic Algorithms

In this paper, we propose a distributed approach for mapping a single large application to a heterogeneous grid environment. To minimize the execution time of the parallel application, we distribute the mapping overhead to the available nodes of the grid. This approach not only provides a fast mapping of tasks to resources but is also scalable. We adopt a hierarchical grid model and accomplish the job of mapping tasks to this topology using a scheduler tree. Results show that our three-phase algorithm provides high quality mappings, and is fast and scalable.

Sanyal, Soumya↗

NASA NTRS2022

Fatigue, Schedules, Sleep, and Sleepiness in U.S. Commercial Pilots During COVID-19

Introduction: COVID-19 has had a significant impact on the aviation industry. While reduced flying capacity may intuitively translate to reduced fatigue risk by way of fewer flights and duty hours, the actual impact of the pandemic on pilot fatigue is unknown. Methods: We surveyed US commercial airline pilots in late 2020 (n = 669) and early 2021 (n = 156) to assess the impact of COVID-19 on schedules and fatigue during the pandemic. Results: Overall, pilots reported reduced flight and duty hours compared to pre-pandemic. Average sleep on workdays was slightly shorter in late 2020 (6.88 h) and recovered to pre-pandemic levels in early 2021 (6.95 h). Similarly, the frequency of sleepiness on days off and in-flight increased in late 2020, with 54% of pilots reporting an increase in in-flight sleepiness, then returned to pre-pandemic levels in early 2021. The use of in-flight sleepiness countermeasures remained the same across assessed time points. Pilots highlighted several factors which impacted their sleep and job performance, including limited access to nutritional food during duty days and layovers, reduced access to exercise facilities during layovers, increased stress due to job insecurity and health concerns, increased distractions and workload, and changes to scheduling. Discussion: Despite a reduction in flights and duty days, COVID-19 led to increased sleepiness on days off and in-flight, potentially due to the negative impact of lack of access to essential needs and heightened stress on sleep. Operators need to monitor the change in these COVID-19 related risks as the industry returns to full service.

sleep↗

NASA NTRS2007

In-Space Crew-Collaborative Task Scheduling

For all past and current human space missions, the final scheduling of tasks to be done in space has been devoid of crew control, flexibility, and insight. Ground controllers, with minimal input from the crew, schedule the tasks and uplink the timeline to the crew or uplink the command sequences to the hardware. Prior to the International Space Station (ISS), the crew could make requests about tomorrow s timeline, they could omit a task, or they could request that something in the timeline be delayed. This lack of control over one's own schedule has had negative consequences. There is anecdotal consensus among astronauts that control over their own schedules will mitigate the stresses of long duration missions. On ISS, a modicum of crew control is provided by the job jar. Ground controllers prepare a task list (a.k.a. "job jar") of non-conflicting tasks from which jobs can be chosen by the in space crew. Because there is little free time and few interesting non-conflicting activities, the task-list approach provides little relief from the tedium of being micro-managed by the timeline. Scheduling for space missions is a complex and laborious undertaking which usually requires a large cadre of trained specialists and suites of complex software tools. It is a giant leap from today s ground prepared timeline (with a job jar) to full crew control of the timeline. However, technological advances, currently in-work or proposed, make it reasonable to consider scheduling a collaborative effort by the ground-based teams and the in-space crew. Collaboration would allow the crew to make minor adjustments, add tasks according to their preferences, understand the reasons for the placement of tasks on the timeline, and provide them a sense of control. In foreseeable but extraordinary situations, such as a quick response to anomalies and extended or unexpected loss of signal, the crew should have the autonomous ability to make appropriate modifications to the timeline, extend the timeline, or even start over with a new timeline. The Vision for Space Exploration (VSE), currently being pursued by the National Aeronautics and Space Administration (NASA), will send humans to Mars in a few decades. Stresses on the human mind will be exacerbated by the longer durations and greater distances, and it will be imperative to implement stress-reducing innovations such as giving the crew control of their daily activities.

Jaap, John↗

NASA NTRS1992

Uncertainty management by relaxation of conflicting constraints in production process scheduling

Mathematical-analytical methods as used in Operations Research approaches are often insufficient for scheduling problems. This is due to three reasons: the combinatorial complexity of the search space, conflicting objectives for production optimization, and the uncertainty in the production process. Knowledge-based techniques, especially approximate reasoning and constraint relaxation, are promising ways to overcome these problems. A case study from an industrial CIM environment, namely high-grade steel production, is presented to demonstrate how knowledge-based scheduling with the desired capabilities could work. By using fuzzy set theory, the applied knowledge representation technique covers the uncertainty inherent in the problem domain. Based on this knowledge representation, a classification of jobs according to their importance is defined which is then used for the straightforward generation of a schedule. A control strategy which comprises organizational, spatial, temporal, and chemical constraints is introduced. The strategy supports the dynamic relaxation of conflicting constraints in order to improve tentative schedules.

Dorn, Juergen↗