Search NASA⌕ Search

SEARCH · Search NASA

Results for “Automated Strategies”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

A knowledge-based system for controlling automobile traffic

Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.

Maravas, Alexander↗
NASA NTRS1998

Design and implementation of satellite formations and constellations

The direction to develop small low cost spacecraft has led many scientists to recognize the advantage of flying spacecraft in constellations and formations to achieve the correlated instrument measurements formerly possible only by flying many instruments on a single large platform. Yet, constellations and formation flying impose additional complications on orbit selection and orbit maintenance, especially when each spacecraft has its own orbit or science requirements. The purpose of this paper is to develop an operational control method for maintenance of these missions. Examples will be taken from the Earth Observing-1 (EO-1) spacecraft that is part of the New Millennium Program (NMP) and from proposed Earth System Science Program Office (ESSPO) constellations. Results can be used to determine the appropriateness of constellations and formation flying for a particular case as well as the operational impacts. Applications to the ESSPO and NMP are highly considered in analysis and applications. After constellation and formation analysis is completed, implementation of a maneuver maintenance strategy becomes the driver. Advances in technology and automation by GSFC's Guidance, Navigation, and Control Center allow more of the burden of the orbit selection and maneuver maintenance to be automated and ultimately placed onboard the spacecraft, mitigating most of the associated operational concerns. This paper presents the GSFC closed-loop control method to fly in either constellations or formations through the use of an autonomous closed loop three-axis navigation control and innovative orbit maintenance support. Simulation results using AutoCon(TM) and FreeFlyer(TM) with various fidelity levels of modeling and algorithms are presented.

Folta, David↗
NASA NTRS1998

Design and Implementation of Satellite Formations and Constellations

The direction to develop small low cost spacecraft has led many scientists to recognize the advantage of flying spacecraft in constellations and formations to achieve the correlated instrument measurements formerly possible only by flying many instruments on a single large platform. Yet, constellations and formation flying impose additional complications on orbit selection and orbit maintenance, especially when each spacecraft has its own orbit or science requirements. The purpose of this paper is to develop an operational control method for maintenance of these missions. Examples will be taken from the Earth Observing-1 (EO-1) spacecraft that is part of the New Millennium Program (NMP) and from proposed Earth System Science Program Office (ESSPO) constellations. Results can be used to determine the appropriateness of constellations and formation flying for a particular case as well as the operational impacts. Applications to the ESSPO and NMP are highly considered in analysis and applications. After constellation and formation analysis is completed, implementation of a maneuver maintenance strategy becomes the driver. Advances in technology and automation by GSFC's Guidance, Navigation, and Control Center allow more of the burden of the orbit selection and maneuver maintenance to be automated and ultimately placed onboard the spacecraft, mitigating most of the associated operational concerns. This paper presents the GSFC closed-loop control method to fly in either constellations or formations through the use of an autonomous closed loop three-axis navigation control and innovative orbit maintenance support. Simulation results using AutoCon(Trademark) and FreeFlyer(Trademark) with various fidelity levels of modeling and algorithms are presented.

Folta, David↗
NASA NTRS2009

The Contingency of Success: Operations for Deep Impact's Planet Hunt

The Deep Impact Flyby spacecraft completed its prime mission in August 2005. It was reactivated for a mission of opportunity add-on called EPOXI on September 25, 2007. The first portion of EPOXI, called EPOCh (Extra-solar Planetary Observation & CHaracterization), occurred from January 21, 2008 through August 31, 2008. Its purpose was to characterize transiting hot-Jupiters by measuring the effects the planet has on the luminosity of its parent star. These observations entailed using the spacecraft in ways it was never intended. A new green-light, success-oriented operational strategy was devised that entailed high amounts of automation and minimal intervention from the ground. The specifics, techniques, and key challenges to obtaining the 172,209 usable science images from EPOCh are discussed in detail.

observation↗
NASA NTRS1990

The environmental control and life support system advanced automation project. Phase 1: Application evaluation

The Environmental Control and Life Support System (ECLSS) is a Freedom Station distributed system with inherent applicability to advanced automation primarily due to the comparatively large reaction times of its subsystem processes. This allows longer contemplation times in which to form a more intelligent control strategy and to detect or prevent faults. The objective of the ECLSS Advanced Automation Project is to reduce the flight and ground manpower needed to support the initial and evolutionary ECLS system. The approach is to search out and make apparent those processes in the baseline system which are in need of more automatic control and fault detection strategies, to influence the ECLSS design by suggesting software hooks and hardware scars which will allow easy adaptation to advanced algorithms, and to develop complex software prototypes which fit into the ECLSS software architecture and will be shown in an ECLSS hardware testbed to increase the autonomy of the system. Covered here are the preliminary investigation and evaluation process, aimed at searching the ECLSS for candidate functions for automation and providing a software hooks and hardware scars analysis. This analysis shows changes needed in the baselined system for easy accommodation of knowledge-based or other complex implementations which, when integrated in flight or ground sustaining engineering architectures, will produce a more autonomous and fault tolerant Environmental Control and Life Support System.

Dewberry, Brandon S.↗
DOE OSTI2024

Condition-Based Maintenance of a Circulating Water System of a Canadian Nuclear Power Plant using Machine Learning and Statistical Tools

Canada Deuterium Uranium pressurized-heavy-water reactors (PHWR) are a type of nuclear power plant that generate clean and reliable energy. The scope of this work is to automate data analysis methodologies to inform a condition-based maintenance strategy of a circulating water system (CWS) of a PHWR. The multiunit CWS provides a continuous supply of water to cool steam condensers, even during transient scenarios, thereby improving the thermal efficiency. This work aims to develop a machine learning (ML) based approach to detect anomalies in heterogeneous data of a CWS in a PHWR to help inform a predictive maintenance strategy. The heterogeneous data include textual and numeric time series data for a PHWR. Natural-language-processing (NLP)-based models are used to analyze textual data contained in work orders and operator logs and an event-timeseries correlation detection method is applied to assist anomalies diagnoses for CWS. An ML model Robust Linear Model (RLM) is also used to remove the seasonal variations in the system variable distributions based on distributions of environmental variables. A machine learning model, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), trained on both original data and data without any seasonal variations will then be used to detect if an anomaly exists. Thus, by moving to an automated methodology to detect, classify, and forecast anomalies, the maintenance strategy would be based on component condition instead of a time-based schedule.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS2024

Automated Detection of Spurious Signals in VLBI Phase Calibration Data

In this memorandum, a set of processing strategies for automatic masking of phase calibration tones is outlined as implemented in the software package PIMA in the task Generate Phase Calibration Mask, or GEPM. The task relies on a robust procedure of cleaning phase calibration data before employing several mathematical strategies designed to selectively identify spurious signals from phase calibration tones. These strategies were derived as more rigorous implementations of heuristics traditionally used by analysts in manually identifying problematic phase calibration data. The task is intended to automate the process of generating a phase calibration mask and in so doing increase the speed and regularity of VLBI analysis. At the outset of the project, a series of goals were identified to evaluate the success of this mask generation. This included the development of an algorithm to identify and mask short-term (defined as less than 10 seconds in length) spurious signals affecting phase calibration data, the development of an algorithm to identify and mask phase calibration tones affected by constant radio-frequency interference, the implementation of a detection scheme for identifying large jumps in phase calibration phase caused by clock breaks, and finally a method of reporting phase calibration health metrics to the user. Processing of over 10 experiments has demonstrated that the final form of the task GEPM as detailed in this technical memorandum satisfies each of these conditions and satisfactorily performs the task of automatic phase calibration data masking, although the wide variety in quality and characteristics of phase calibration data makes a single solution to the problem quite difficult. A series of user inputs have therefore been defined to assist analysts in tailoring automatic masking to specific stations and phase calibration generators. The vast majority of applicable code was written in FORTRAN to increase execution speed and ease of interfacing with the existing code base in PIMA, but a wrapper function in Python was also written to allow for a simpler method of interacting with GEPM and inputting relevant parameters. In addition to this report, thorough documentation was added to the already existing repositories associated with PIMA as a whole.

Geodesy↗
DOE OSTI2021

Heuristic Dispatch Based on Price Signals for Behind-the-Meter PV-Battery Systems in the System Advisor Model

The economic potential of a behind-the-meter (BTM) PV-battery system depends greatly on how the battery is dispatched. Different utility rates, system sizes, generation and load profiles can all require different dispatch strategies. This paper presents price signals dispatch, a new algorithm for automated economic dispatch of BTM PV-battery systems, which utilizes 24-hour PV and load forecasts, degradation data, and utility rates. The algorithm is integrated with the System Advisor Model (SAM) tool and is tested with a nonlinear generic electrochemical battery model. Price signals dispatch outperforms SAM's existing algorithms in cases requiring a balance between demand charge management and energy arbitrage, and in cases where battery degradation imposes a significant cost.

batteries↗
NASA NTRS1977

The automation of remote vehicle control

The automation of remote vehicles is becoming necessary to overcome the requirement of having man present as a controller. By removing man, remote vehicles can be operated in areas where the environment is too hostile for man, his reaction times are too slow, time delays are too long, and where his presence is too costly, or where system performance can be improved. This paper addresses the development of automated remote vehicle control for nonspace and space tasks from warehouse vehicles to proposed Mars rovers. The state-of-the-art and the availability of new technology for implementing automated control are reviewed and the major problem areas are outlined. The control strategies are divided into those where the path is planned in advance or constrained, or where the system is a teleoperator, or where automation or robotics have been introduced.

Paine, G.↗
NASA NTRS2002

Spatial learning and memory is preserved in rats after early development in a microgravity environment

This study evaluated the cognitive mapping abilities of rats that spent part of their early development in a microgravity environment. Litters of male and female Sprague-Dawley rat pups were launched into space aboard the National Aeronautics and Space Administration space shuttle Columbia on postnatal day 8 or 14 and remained in space for 16 days. These animals were designated as FLT groups. Two age-matched control groups remained on Earth: those in standard vivarium housing (VIV) and those in housing identical to that aboard the shuttle (AGC). On return to Earth, animals were tested in three different tasks that measure spatial learning ability, the Morris water maze (MWM), and a modified version of the radial arm maze (RAM). Animals were also tested in an open field apparatus to measure general activity and exploratory activity. Performance and search strategies were evaluated in each of these tasks using an automated tracking system. Despite the dramatic differences in early experience, there were remarkably few differences between the FLT groups and their Earth-bound controls in these tasks. FLT animals learned the MWM and RAM as quickly as did controls. Evaluation of search patterns suggested subtle differences in patterns of exploration and in the strategies used to solve the tasks during the first few days of testing, but these differences normalized rapidly. Together, these data suggest that development in an environment without gravity has minimal long-term impact on spatial learning and memory abilities. Any differences due to development in microgravity are quickly reversed after return to earth normal gravity.

NASA Discipline Neuroscience↗
NASA NTRS2016

Synergistic Allocation of Flight Expertise on the Flight Deck (SAFEdeck): A Design Concept to Combat Mode Confusion, Complacency, and Skill Loss in the Flight Deck

This paper presents a new design and function allocation philosophy between pilots and automation that seeks to support the human in mitigating innate weaknesses (e.g., memory, vigilance) while enhancing their strengths (e.g., adaptability, resourcefulness). In this new allocation strategy, called Synergistic Allocation of Flight Expertise in the Flight Deck (SAFEdeck), the automation and the human provide complementary support and backup for each other. Automation is designed to be compliant with the practices of Crew Resource Management. The human takes a more active role in the normal operation of the aircraft without adversely increasing workload over the current automation paradigm. This designed involvement encourages the pilot to be engaged and ready to respond to unexpected situations. As such, the human may be less prone to error than the current automation paradigm.

Schutte, Paul↗
DOE OSTI2020

Long-Term Vehicle Speed Prediction via Historical Traffic Data Analysis for Improved Energy Efficiency of Connected Electric Vehicles

Connected and automated vehicles (CAVs) are expected to provide enhanced safety, mobility, and energy efficiency. While abundant evidence has been accumulated showing substantial energy saving potentials of CAVs through eco-driving, traffic condition prediction has remained to be the main challenge in capitalizing the gains. The coupled power and thermal subsystems of CAVs necessitate the use of different speed preview windows for effective and integrated power and thermal management. Real-time vehicle-to-infrastructure (V2I) communications can provide an accurate speed prediction over a short prediction horizon (e.g., 30 s to 60 s), but not for a long range (e.g., over 180 s). Therefore, advanced approaches are required to develop detailed speed prediction for robust optimization-based energy management of CAVs. This paper presents an integrated speed prediction framework based on historical traffic data classification and real-time V2I communications for efficient energy management of electrified CAVs. The proposed framework provides multi-range speed predictions with different fidelity over short and long horizons. The proposed multi-range speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs). The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the proposed data classification strategy over a long prediction horizon. Despite the uncertainty in long-range CAVs’ speed predictions, the vehicle-level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal driving (i.e., human driver) and conventional BTM strategy.

Engineering↗
DOE OSTI2026

Flame Chemistry Workshop: a perspective on challenges and strategic actions in combustion experiments and chemical kinetics modeling

Continued progress in the development of predictive models for combustion chemistry—including ignition and flame behavior, species evolution, and combustion system performance—relies on overcoming enduring and emerging challenges in experimental measurements, theoretical formulations, and chemical kinetics mechanism construction. As combustion science continues to coincide with advances in sustainable fuels development, plasma technologies, and automated modeling capabilities, the need for coordinated, community-driven strategies is essential. The Flame Chemistry Workshop (FCWS), held biennially before the International Symposium on Combustion, serves as a dedicated platform to identify, consolidate, and address these challenges in a structured and collaborative manner. This perspective arises from discussions at the 7th FCWS in Milan, Italy (2024), and presents a collective view of the critical barriers currently limiting progress. Across the five technical domains discussed during the 7th FCWS – sustainable fuels combustion, advanced diagnostics for combustion measurements, experiments and modeling in plasma combustion, artificial intelligence and automated methods for theory and mechanisms generation, and chemical kinetic models—a series of persistent and emerging scientific challenges were identified, highlighting the need for deeper integration between three areas: theory, experiments, and modeling. In conclusion, the present article concisely describes present challenges that were identified in each of the technical domains in an effort to streamline and coordinate solutions to accelerate progress in combustion science.

Chemical kinetics↗
DOE OSTI2026

Automated Signal Timing Plan Reconstruction Using High-Resolution Event-Based Controller Data for Digital Twins

Transportation digital twins are essential tools for evaluating emerging technologies such as connected and automated vehicles, adaptive traffic signal control, and mobility optimization strategies. Realistic digital twins require accurate emulation of real-world signal controllers and detailed signal timing plans. However, signal timing plans are often unavailable or difficult to access, forcing researchers and modelers to rely on assumed fixed timings or halt their analysis. To overcome this challenge, we present a method that directly estimates signal timing plan parameters using high-resolution, event-based data from traffic signal controllers. The proposed method extracts key parameters, including cycle length, offset, phase sequence, coordinated phases, phase-specific minimum and maximum green durations, vehicle extensions, and splits under coordination. A rule-based deterministic signal timing reconstruction algorithm based on traffic signal operation rules, such as those outlined in the Signal Timing Manual, is developed and validated. We evaluate this method, which uses high-resolution controller event logs and verified signal timing plans, on 94 signalized intersections in Nashville, Tennessee, demonstrating their ability to generate accurate, simulation-ready signal timing plans for tools such as SUMO and Vissim.

Saroj, Abhilasha [ORNL] (ORCID:0000000191178063)↗
DOE OSTI2021

A Study of Cost-Saving Potential of Load Flexibility Measures in Grid-Interactive Multifamily Buildings

With recent advances in smart technologies, more and more smart devices are penetrating the residential and commercial buildings market. The introduction of these smart devices is also helping IoT companies emerge with load aggregator roles in the sector. With more utility companies on the track of supporting OpenADR protocols, the aggregators could play a significant role in providing load flexibilities by automatically responding to demand response (DR) events and coordinating load flexibility measures between customers. This would benefit utility companies by reducing stress on the grid during critical peak demand hours as well as customers by allowing them to utilize utility rate structures advantageous to those able to reduce electric usage during high-demand hours. This study evaluates cost and energy savings from adopting multiple load flexibility measures in multifamily buildings. Combinations of different load flexibility measures, including space temperature floating, light dimming, automatic window shading, and water heater temperature floating, are considered. The simulations are performed using OpenStudio®, an open-source U.S. Department of Energy (DOE) simulation platform. For the case study, we used a midrise apartment building with weather conditions from Denver, Colorado. To compare climate zone differences, simulations were also performed for Los Angeles, California, and Chicago, Illinois. Initial results indicate that the application of automated load flexibility measures without careful consideration of dispatching strategies and DR program enrollments could significantly affect the savings. To get meaningful cost savings, aggregators need to encourage tenant awareness to curtail energy usage through occupant behavior in addition to dispatching automatic load flexibility measures. The outcomes from this study are believed to help load aggregators understand the risks and benefits of load flexibility opportunities.

building energy modeling↗
NASA NTRS1988

Automated satellite control in Ada

The Advanced Ground Segment, a prototype satellite/payload operations control center workstation, which represents an evolutionary effort to improve the automation of control centers while improving software practices and supporting distributed control center functions, is described. Multiple levels of automation are supported through a rule-based control strategy. The architecture provides the necessary interfaces and modularity for future inclusion of more sophisticated control strategies.

Jaworski, Allan↗
NASA NTRS1989

Computational Methods for Structural Mechanics and Dynamics, part 1

The structural analysis methods research has several goals. One goal is to develop analysis methods that are general. This goal of generality leads naturally to finite-element methods, but the research will also include other structural analysis methods. Another goal is that the methods be amenable to error analysis; that is, given a physical problem and a mathematical model of that problem, an analyst would like to know the probable error in predicting a given response quantity. The ultimate objective is to specify the error tolerances and to use automated logic to adjust the mathematical model or solution strategy to obtain that accuracy. A third goal is to develop structural analysis methods that can exploit parallel processing computers. The structural analysis methods research will focus initially on three types of problems: local/global nonlinear stress analysis, nonlinear transient dynamics, and tire modeling.

Stroud, W. Jefferson↗
NASA NTRS1990

Time-based operations in an advanced ATC environment

Information on time-based operations in an advanced air traffic control (ATC) environment is given in viewgraph form. The objectives are to develop and evaluate procedures and clearances for 4D equipped aircraft, study the effect of dissimilar airborne and ground based speed strategies, and evaluate the effectiveness and acceptability of ATC automation tools. Information is given on ATC simulation, ATC automation tools, Denver arrival airspace, time-based ATC procedures, and future plans.

Green, Steven M.↗