Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Adaptive Scheduling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Phase-shifting human circadian rhythms: influence of sleep timing, social contact and light exposure

1. Both the timing of behavioural events (activity, sleep and social interactions) and the environmental light-dark cycle have been reported to contribute to entrainment of human circadian rhythms to the 24 h day. Yet, the relative contribution of those putative behavioural synchronizers to that of light exposure remains unclear. 2. To investigate this, we inverted the schedule of rest, sedentary activity and social contact of thirty-two young men either with or without exposure to bright light. 3. On this inverted schedule, the endogenous component of the core temperature rhythm of subjects who were exposed to bright light showed a significant phase shift, demonstrating that they were adapting to the new schedule. In contrast, the core temperature rhythm of subjects who were not exposed to bright light moved on average 0.2 h later per day and after 10 days had not significantly adapted to the new schedule. 4. The direction of phase shift in the groups exposed to bright light was dependent on the time of bright light exposure, while control subjects drifted to a later hour regardless of the timing of their schedule of sleep timing, social contact and meals. 5. These results support the concept that the light-dark cycle is the most important synchronizer of the human circadian system. They suggest that inversion of the sleep-wake, rest-activity and social contact cycles provides relatively minimal drive for resetting the human circadian pacemaker. 6. These data indicate that interventions designed to phase shift human circadian rhythms for adjustment to time zone changes or altered work schedules should focus on properly timed light exposure.

Non-NASA Center↗
DOE OSTI2025

Decentralized Distributed Proximal Policy Optimization (DD-PPO) for High Performance Computing Scheduling on Multi-User Systems

Resource allocation in High Performance Computing (HPC) environments presents a complex and multifaceted challenge for job scheduling algorithms. Beyond the efficient allocation of system resources, schedulers must account for and optimize multiple performance metrics, including job wait time and system throughput. Traditional heuristic-based scheduling algorithms increasingly struggle and lack the efficiency needed to meet the demands and address the complexity and scale of modern HPC systems. Consequently, recent research efforts have focused on leveraging advancements in Artificial Intelligence (AI) and Deep Learning (DL), particularly Reinforcement Learning (RL), to develop more adaptable and intelligent scheduling strategies. Previous RL-based scheduling approaches have explored a range of algorithms, from Deep Q-Networks (DQN) to Proximal Policy Optimization (PPO), and more recently, hybrid methods that integrate Graph Neural Networks (GNNs) with RL techniques. However, a common limitation across these methods is their reliance on relatively small datasets, with few methods being evaluated using large-scale, multi-million-job trace datasets representative of real-world HPC workloads. Moreover, existing RL schedulers face scalability issues due to centralized policy updates, which hinder training efficiency and performance when applied to large datasets. This study introduces a novel RL-based scheduler utilizing Decentralized Distributed Proximal Policy Optimization (DD-PPO) algorithm, which supports large-scale distributed training across multiple workers without requiring parameter synchronization at every step. By eliminating reliance on centralized updates to a shared policy, the DD-PPO scheduler enhances scalability, training efficiency, and sample utilization. Experimental validation using a large real-world dataset containing over 11.5 million job traces collected from petascale HPC systems over six years assesses the influence of dataset scale on training effectiveness and compares DD-PPO performance to traditional and advanced scheduling approaches. The experimental results demonstrate improved scheduling performance in comparison to both heuristic-based schedulers and existing RL-based scheduling algorithms.

AI↗
NASA NTRS1991

Shiftwork in space - Bright light as a chronobiologic countermeasure

The potential of timed exposures to bright light as a countermeasure to the changes in the work/rest schedules during space missions was investigated. In the experiments, four human subjects were exposed to two sessions of eleven days of simulated weightlessness (6-deg head-down-tilt bedrest) with 6-hr extensions of the scheduled wake time on days 3 and 4 (a 12-hr phase delay). In a blind crossover design, subjects were exposed to bright light (greater than 3500 lux) for 5 hrs on each of the two shift days and on the following day, at times expected to accelerate adaptation to the phase delay (experimental group), or have no phase shifting effect (control group). Results indicate that bright light may accelerate the rate of adaptation to work/rest schedule delays under simulated weightlessness conditions. However, such effect was found to be largely independent of the timing of the light exposure.

Gander, Philippa H.↗
NASA NTRSDate not supplied

NASA's Space Launch System Begins Integration, Stacking in Preparation for Artemis I Launch

The Artemis era of human lunar exploration is nearing take-off as NASA’s new super heavy-lift launch vehicle, the Space Launch System (SLS), begins stack-ing and integration operations in mid-2020 at Kennedy Space Center (KSC) in Florida. With a planned upgrade path to progressively more powerful vehicles and availability in crew and cargo configurations, SLS provides a unique and flexible launch solution to send crew, large-scale infrastructure and robotic probes to deep space. The SLS Block 1 vehicle, the initial variant to fly, is optimized for lunar missions with a proven propulsion system consisting of four liquid hydrogen (LH2)/liquid oxygen (LOX)-fed RS-25 engines and twin five-segment solid rocket boosters (SRBs). The Block 1 vehicle can also be outfitted with an industry-standard 5 m-class payload fairing (the “cargo” configuration) and will launch at least 27 metric tons (t) of mass to trans-lunar injection (TLI). SLS is the backbone of NASA’s Artemis program, which will return the agency’s human spaceflight program to the Moon for the first time since 1972. For the Artemis I mission, SLS will send an uncrewed Orion spacecraft to TLI, where it will enter a distant retrograde lunar orbit and fly 38,000 nmi past the Moon – farther than any spacecraft built for humans has ever traveled. The SLS Block 1 vehicle for Artemis I completed manufacturing in 2019. Several elements, including the upper stage, have been delivered to the Exploration Ground Systems (EGS) program at KSC and are being prepped for integration and stack-ing. The five-segment solid rocket boosters – the largest and most powerful ever built for flight – are also complete. The booster motor segments for the Artemis I flight are scheduled to ship from prime contractor Northrop Grumman’s Utah facilities and begin stacking and integration at KSC in June 2020. The SLS core stage is the largest rocket stage NASA has ever built in terms of volume and height, and includes the avionics and the tanks that feed cryogenic propellant to the four RS-25s (formerly Space Shuttle Main Engines [SSMEs]). They have been modified with an updated controller and nozzle insulation to protect them from the hotter launch environment. The SLS core stage is currently being test-ed at NASA’s Stennis Space Center (SSC) in a series of “green run” tests to verify it meets design and performance requirements. Following the green run test series, which is scheduled to culminate with a full-duration hot-fire of the four RS-25 engines, the core stage will ship to KSC and be stacked between the sol-id rocket boosters in the Vehicle Assembly Building (VAB). Integration of the vehicle will continue with the upper stage, known as the Interim Cryogenic Propulsion Stage (ICPS) and the Launch Vehicle Stage Adapter (LVSA) on the core stage. Another adapter, the Orion Stage Adapter (OSA), connects SLS to Orion and provides housing for 13 6U CubeSat payloads manifested on Artemis I. The CubeSats will be released in deep space after Orion separates from the vehicle, and the flight marks the first ride share opportunity for independent small-sats to deep space. The second major SLS variant to come online, Block 1B, replaces the single-engine ICPS with a four-engine LH2/LOX Exploration Upper Stage (EUS). This more powerful upper stage, along with other vehicle up-grades, will enable the Block 1B vehicle to launch 38-42 t to TLI, depending on crew or cargo configuration. The final evolution of the vehicle, Block 2, will onramp evolved solid rocket boosters to increase mass to TLI to 43-46 t, de-pending on crew or cargo configuration. The Block 1B/Block 2 vehicles can be outfitted with an 8.4 m-diameter payload fairing in 19.1 m or 27.4 m lengths, to provide unprecedented volume for payloads. With the initial Block 1 vehicle completely manufactured and the core stage in final testing before shipping to KSC, the SLS Program and its industry partners have made significant progress manufacturing subsequent vehicles. For the second Block 1 vehicle, the solid rocket motor segments are complete, as are the RS-25 engines with controllers. All five major components of the Artemis II core stage – the forward skirt, LOX and LH2 tanks, intertank and engine section – are manufactured and technicians are installing subsystems at NASA’s rocket factory, Michoud Assembly Facility. The RL-10 engine for the Artemis II ICPS is complete and panels have been machined for its LH2 tank. In addition, panels are machined for the vehicle’s two adapters, with welding scheduled to begin in summer 2020. Flight hard-ware is also in production for the third SLS vehicle, with several booster motor segments cast. The pace of development on the EUS has increased, with the goal to complete Critical Design Review (CDR) in December 2020. Several EUS test rings have been machined at Michoud. The EUS is designed to exe-cute a variety of missions – human spaceflight, deployment of deep-space infra-structure, or high-C3 missions to the outer solar system – with crew and cargo configurations available beginning in the mid-2020s. The near-term goal for the nation’s powerful new space exploration asset, however, is to launch the Arte-mis program, and send the first woman and the next man to the lunar surface. At the Astrodynamics Specialist Conference, the SLS program will update the community on the progress of the initial Block 1 vehicle in final green run test-ing, integration and stacking. In addition, this paper will provide an update to the community on the manufacturing status of subsequent Block 1 and Block 1B vehicles.

Steve Creech↗
NASA NTRS1972

A fast acting electrical servo for the actuation of full span, Fowler-type wing flaps in DLC applications: A detail design study

The philosophy and detail design of an electro-mechanical actuator for Fowler-type wing flaps which have a response time constant of 0.025 seconds are described. A conventional electrical servomotor with a power rating twice the maximum power delivered to the load is employed along with adaptive, gain-scheduled feedback and various logic circuits, including one to remove electrical excitation from the motor during extended periods when no motion of the flap is desired.

Smetana, F. O.↗
NASA NTRS1995

Performance and policy dimensions in internet routing

The Internet Routing Project, referred to in this report as the 'Highball Project', has been investigating architectures suitable for networks spanning large geographic areas and capable of very high data rates. The Highball network architecture is based on a high speed crossbar switch and an adaptive, distributed, TDMA scheduling algorithm. The scheduling algorithm controls the instantaneous configuration and swell time of the switch, one of which is attached to each node. In order to send a single burst or a multi-burst packet, a reservation request is sent to all nodes. The scheduling algorithm then configures the switches immediately prior to the arrival of each burst, so it can be relayed immediately without requiring local storage. Reservations and housekeeping information are sent using a special broadcast-spanning-tree schedule. Progress to date in the Highball Project includes the design and testing of a suite of scheduling algorithms, construction of software reservation/scheduling simulators, and construction of a strawman hardware and software implementation. A prototype switch controller and timestamp generator have been completed and are in test. Detailed documentation on the algorithms, protocols and experiments conducted are given in various reports and papers published. Abstracts of this literature are included in the bibliography at the end of this report, which serves as an extended executive summary.

Mills, David L.↗
NASA NTRS1996

Mission simulation as an approach to develop requirements for automation in Advanced Life Support Systems

This paper examines mission simulation as an approach to develop requirements for automation and robotics for Advanced Life Support Systems (ALSS). The focus is on requirements and applications for command and control, control and monitoring, situation assessment and response, diagnosis and recovery, adaptive planning and scheduling, and other automation applications in addition to mechanized equipment and robotics applications to reduce the excessive human labor requirements to operate and maintain an ALSS. Based on principles of systems engineering, an approach is proposed to assess requirements for automation and robotics using mission simulation tools. First, the story of a simulated mission is defined in terms of processes with attendant types of resources needed, including options for use of automation and robotic systems. Next, systems dynamics models are used in simulation to reveal the implications for selected resource allocation schemes in terms of resources required to complete operational tasks. The simulations not only help establish ALSS design criteria, but also may offer guidance to ALSS research efforts by identifying gaps in knowledge about procedures and/or biophysical processes. Simulations of a planned one-year mission with 4 crewmembers in a Human Rated Test Facility are presented as an approach to evaluation of mission feasibility and definition of automation and robotics requirements.

NASA Discipline Number 61-10↗
NASA NTRS2015

Integrated Test and Evaluation Flight Test 3 Flight Test Plan

The desire and ability to fly Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) is of increasing urgency. The application of unmanned aircraft to perform national security, defense, scientific, and emergency management are driving the critical need for less restrictive access by UAS to the NAS. UAS represent a new capability that will provide a variety of services in the government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized due to the lack of a common understanding of what is required to safely operate UAS in the NAS. NASA's UAS Integration into the NAS Project is conducting research in the areas of Separation Assurance/Sense and Avoid Interoperability, Human Systems Integration (HSI), and Communication to support reducing the barriers of UAS access to the NAS. This research is broken into two research themes namely, UAS Integration and Test Infrastructure. UAS Integration focuses on airspace integration procedures and performance standards to enable UAS integration in the air transportation system, covering Sense and Avoid (SAA) performance standards, command and control performance standards, and human systems integration. The focus of Test Infrastructure is to enable development and validation of airspace integration procedures and performance standards, including the integrated test and evaluation. In support of the integrated test and evaluation efforts, the Project will develop an adaptable, scalable, and schedulable relevant test environment capable of evaluating concepts and technologies for unmanned aircraft systems to safely operate in the NAS. To accomplish this task, the Project will conduct a series of Human-in-the-Loop and Flight Test activities that integrate key concepts, technologies and/or procedures in a relevant air traffic environment. Each of the integrated events will build on the technical achievements, fidelity and complexity of the previous tests and technical simulations, resulting in research findings that support the development of regulations governing the access of UAS into the NAS.

Unmanned↗
NASA NTRS2015

UAS Integration in the NAS Project: Integrated Test and Evaluation (IT&E) Flight Test 3

The desire and ability to fly Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) is of increasing urgency. The application of unmanned aircraft to perform national security, defense, scientific, and emergency management are driving the critical need for less restrictive access by UAS to the NAS. UAS represent a new capability that will provide a variety of services in the government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized due to the lack of a common understanding of what is required to safely operate UAS in the NAS. NASA's UAS Integration into the NAS Project is conducting research in the areas of Separation Assurance/Sense and Avoid Interoperability, Human Systems Integration (HSI), and Communication to support reducing the barriers of UAS access to the NAS. This research is broken into two research themes namely, UAS Integration and Test Infrastructure. UAS Integration focuses on airspace integration procedures and performance standards to enable UAS integration in the air transportation system, covering Sense and Avoid (SAA) performance standards, command and control performance standards, and human systems integration. The focus of Test Infrastructure is to enable development and validation of airspace integration procedures and performance standards, including the integrated test and evaluation. In support of the integrated test and evaluation efforts, the Project will develop an adaptable, scalable, and schedulable relevant test environment capable of evaluating concepts and technologies for unmanned aircraft systems to safely operate in the NAS. To accomplish this task, the Project will conduct a series of Human-in-the-Loop and Flight Test activities that integrate key concepts, technologies and/or procedures in a relevant air traffic environment. Each of the integrated events will build on the technical achievements, fidelity and complexity of the previous tests and technical simulations, resulting in research findings that support the development of regulations governing the access of UAS into the NAS.

interoperability↗
NASA NTRS2015

UAS-NAS Integrated Human in the Loop: Test Environment Report

The desire and ability to fly Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) is of increasing urgency. The application of unmanned aircraft to perform national security, defense, scientific, and emergency management are driving the critical need for less restrictive access by UAS to the NAS. UAS represent a new capability that will provide a variety of services in the government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized due to the lack of a common understanding of what is required to safely operate UAS in the NAS. NASA's UAS Integration in the NAS Project is conducting research in the areas of Separation Assurance/Sense and Avoid Interoperability (SSI), Human Systems Integration (HSI), and Communication to support reducing the barriers of UAS access to the NAS. This research was broken into two research themes namely, UAS Integration and Test Infrastructure. UAS Integration focuses on airspace integration procedures and performance standards to enable UAS integration in the air transportation system, covering Sense and Avoid (SAA) performance standards, command and control performance standards, and human systems integration. The focus of the Test Infrastructure theme was to enable development and validation of airspace integration procedures and performance standards, including the execution of integrated test and evaluation. In support of the integrated test and evaluation efforts, the Project developed an adaptable, scalable, and schedulable relevant test environment incorporating live, virtual, and constructive elements capable of validating concepts and technologies for unmanned aircraft systems to safely operate in the NAS. To accomplish this task, the Project planned to conduct three integrated events: a Human-in-the-Loop simulation and two Flight Test series that integrated key concepts, technologies and/or procedures in a relevant air traffic environment. Each of the integrated events were built on the technical achievements, fidelity and complexity of previous simulations and tests, resulting in research findings that support the development of regulations governing the access of UAS into the NAS. The purpose of this document is to describe how well the system under test was representative

Human in the Loop↗
NASA NTRS2016

UAS-NAS Flight Test Series 3: Test Environment Report

The desire and ability to fly Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) is of increasing urgency. The application of unmanned aircraft to perform national security, defense, scientific, and emergency management are driving the critical need for less restrictive access by UAS to the NAS. UAS represent a new capability that will provide a variety of services in the government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized due to the lack of a common understanding of what is required to safely operate UAS in the NAS. NASA's UAS Integration in the NAS Project is conducting research in the areas of Separation Assurance/Sense and Avoid Interoperability (SSI), Human Systems Integration (HSI), and Communications (Comm), and Certification to support reducing the barriers of UAS access to the NAS. This research is broken into two research themes namely, UAS Integration and Test Infrastructure. UAS Integration focuses on airspace integration procedures and performance standards to enable UAS integration in the air transportation system, covering Detect and Avoid (DAA) performance standards, command and control performance standards, and human systems integration. The focus of Test Infrastructure is to enable development and validation of airspace integration procedures and performance standards, including integrated test and evaluation. In support of the integrated test and evaluation efforts, the Project will develop an adaptable, scalable, and schedulable relevant test environment capable of evaluating concepts and technologies for unmanned aircraft systems to safely operate in the NAS. To accomplish this task, the Project is conducting a series of human-in-the-loop (HITL) and flight test activities that integrate key concepts, technologies and/or procedures in a relevant air traffic environment. Each of the integrated events will build on the technical achievements, fidelity, and complexity of the previous tests and technical simulations, resulting in research findings that support the development of regulations governing the access of UAS into the NAS. The integrated events started with two initial flight test used to develop and test early integrations and components of the test environment. Test subjects and a relevant test environment were brought in for the integrated HITL (or IHITL) conducted in 2014. The IHITL collected data to evaluate the effectiveness of DAA Well Clear (DWC) algorithms and the acceptability of UAS concepts integrated into the NAS. The first integrated flight test (and the subject of this report) followed the IHITL by replacing the simulation components with live aircraft. The project finishes the integrated events with a final flight test to be conducted in 2016 that provides the researchers with an opportunity to collect DWC and Collision Avoidance (CA) interoperability data during flight encounters.

flight test↗
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 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 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 NTRS1995

Planning Complex Projects Automatically

Automated Manifest Planner (AMP) computer program applies combination of artificial-intelligence techniques to assist both expert and novice planners, reducing planning time by orders of magnitude. Gives planners flexibility to modify plans and constraints easily, without need for programming expertise. Developed specifically for planning space shuttle missions 5 to 10 years ahead, with modifications, applicable in general to planning other complex projects requiring scheduling of activities depending on other activities and/or timely allocation of resources. Adaptable to variety of complex scheduling problems in manufacturing, transportation, business, architecture, and construction.

Henke, Andrea L.↗