SEARCH · Engineering Papers

Results for “Distributed 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.

SourceResearch connectionFrom yearThrough year

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

At least 901 records · Page 50

All sources NASA NTRS DOE OSTI

NASA NTRS2005

Robotic and Human-Tended Collaborative Drilling Automation for Subsurface Exploration

Future in-situ lunar/martian resource utilization and characterization, as well as the scientific search for life on Mars, will require access to the subsurface and hence drilling. Drilling on Earth is hard - an art form more than an engineering discipline. Human operators listen and feel drill string vibrations coming from kilometers underground. Abundant mass and energy make it possible for terrestrial drilling to employ brute-force approaches to failure recovery and system performance issues. Space drilling will require intelligent and autonomous systems for robotic exploration and to support human exploration. Eventual in-situ resource utilization will require deep drilling with probable human-tended operation of large-bore drills, but initial lunar subsurface exploration and near-term ISRU will be accomplished with lightweight, rover-deployable or standalone drills capable of penetrating a few tens of meters in depth. These lightweight exploration drills have a direct counterpart in terrestrial prospecting and ore-body location, and will be designed to operate either human-tended or automated. NASA and industry now are acquiring experience in developing and building low-mass automated planetary prototype drills to design and build a pre-flight lunar prototype targeted for 2011-12 flight opportunities. A successful system will include development of drilling hardware, and automated control software to operate it safely and effectively. This includes control of the drilling hardware, state estimation of both the hardware and the lithography being drilled and state of the hole, and potentially planning and scheduling software suitable for uncertain situations such as drilling. Given that Humans on the Moon or Mars are unlikely to be able to spend protracted EVA periods at a drill site, both human-tended and robotic access to planetary subsurfaces will require some degree of standalone, autonomous drilling capability. Human-robotic coordination will be important, either between a robotic drill and humans on Earth, or a human-tended drill and its visiting crew. The Mars Analog Rio Tinto Experiment (MARTE) is a current project that studies and simulates the remote science operations between an automated drill in Spain and a distant, distributed human science team. The Drilling Automation for Mars Exploration (DAME) project, by contrast: is developing and testing standalone automation at a lunar/martian impact crater analog site in Arctic Canada. The drill hardware in both projects is a hardened, evolved version of the Advanced Deep Drill (ADD) developed by Honeybee Robotics for the Mars Subsurface Program. The current ADD is capable of 20m, and the DAME project is developing diagnostic and executive software for hands-off surface operations of the evolved version of this drill. The current drill automation architecture being developed by NASA and tested in 2004-06 at analog sites in the Arctic and Spain will add downhole diagnosis of different strata, bit wear detection, and dynamic replanning capabilities when unexpected failures or drilling conditions are discovered in conjunction with simulated mission operations and remote science planning. The most important determinant of future 1unar and martian drilling automation and staffing requirements will be the actual performance of automated prototype drilling hardware systems in field trials in simulated mission operations. It is difficult to accurately predict the level of automation and human interaction that will be needed for a lunar-deployed drill without first having extensive experience with the robotic control of prototype drill systems under realistic analog field conditions. Drill-specific failure modes and software design flaws will become most apparent at this stage. DAME will develop and test drill automation software and hardware under stressful operating conditions during several planned field campaigns. Initial results from summer 2004 tests show seven identifi distinct failure modes of the drill: cuttings-removal issues with low-power drilling into permafrost, and successful steps at executive control and initial automation.

Glass, Brian↗

NASA NTRS2002

Airborne Use of Traffic Intent Information in a Distributed Air-Ground Traffic Management Concept: Experiment Design and Preliminary Results

This paper presents initial findings of a research study designed to provide insight into the issue of intent information exchange in constrained en-route air-traffic operations and its effect on pilot decision making and flight performance. The piloted simulation was conducted in the Air Traffic Operations Laboratory at the NASA Langley Research Center. Two operational modes for autonomous operations were compared under conditions of low and high operational complexity. The tactical mode was characterized primarily by the use of state information for conflict detection and resolution and an open-loop means for the pilot to meet operational constraints. The strategic mode involved the combined use of state and intent information, provided the pilot an additional level of alerting, and allowed a closed-loop approach to meeting operational constraints. Operational constraints included separation assurance, schedule adherence, airspace hazard avoidance, flight efficiency, and passenger comfort. Potential operational benefits of both modes are illustrated through several scenario case studies. Subjective pilot ratings and comments comparing the tactical and strategic modes are presented.

Wing, David J.↗

NASA NTRS2001

Airborne Use of Traffic Intent Information in a Distributed Air-Ground Traffic Management Concept: Experiment Design and Preliminary Results

Wing, David J.↗

NASA NTRS1993

Decision theory for computing variable and value ordering decisions for scheduling problems

Heuristics that guide search are critical when solving large planning and scheduling problems, but most variable and value ordering heuristics are sensitive to only one feature of the search state. One wants to combine evidence from all features of the search state into a subjective probability that a value choice is best, but there has been no solid semantics for merging evidence when it is conceived in these terms. Instead, variable and value ordering decisions should be viewed as problems in decision theory. This led to two key insights: (1) The fundamental concept that allows heuristic evidence to be merged is the net incremental utility that will be achieved by assigning a value to a variable. Probability distributions about net incremental utility can merge evidence from the utility function, binary constraints, resource constraints, and other problem features. The subjective probability that a value is the best choice is then derived from probability distributions about net incremental utility. (2) The methods used for rumor control in Bayesian Networks are the primary way to prevent cycling in the computation of probable net incremental utility. These insights lead to semantically justifiable ways to compute heuristic variable and value ordering decisions that merge evidence from all available features of the search state.

Linden, Theodore A.↗

DOE OSTI2019

Systems and methods for regulating a microgrid

A microgrid system includes one or more power generators configured to provide electrical energy. The microgrid system also includes a localized distribution network coupled to the one or more power generators, coupled to the one or more loads, and coupled to an external grid. The microgrid system further includes a microgrid controller configured to predict microgrid demand for the one or more loads for a predetermined period of time. The microgrid controller is also configured to receive demand information for the external grid for the predetermined period of time. The microgrid controller is further configured to determine an operation plan for the one or more power generators based on the predicted microgrid demand and the received demand information. Moreover, the microgrid controller is configured to determine a schedule to transmit electrical energy to the external grid based on the operation plan.

Baone, Chaitanya Ashok↗

NASA NTRS2014

International Space Station Data Collection for Disaster Response

Natural disasters - including such events as tropical storms, earthquakes, floods, volcanic eruptions, and wildfires -effect hundreds of millions of people worldwide, and also cause billions of dollars (USD) in damage to the global economy. Remotely sensed data acquired by orbital sensor systems has emerged as a vital tool to identify the extent of damage resulting from a natural disaster, as well as providing near-real time mapping support to response efforts on the ground and humanitarian aid efforts. The International Space Station (ISS) is a unique terrestrial remote sensing platform for acquiring disaster response imagery. Unlike automated remote-sensing platforms it has a human crew; is equipped with both internal and externally-mounted remote sensing instruments; and has an inclined, low-Earth orbit that provides variable views and lighting (day and night) over 95 percent of the inhabited surface of the Earth. As such, it provides a useful complement to free-flyer based, sun-synchronous sensor systems in higher altitude polar orbits. While several nations have well-developed terrestrial remote sensing programs and assets for data collection, many developing nations do not have ready access to such resources. The International Charter, Space and Major Disasters (also known as the "International Disaster Charter", or IDC; http://www.disasterscharter.org/home) addresses this disparity. It is an agreement between agencies of several countries to provide - on a best-effort basis - remotely sensed data of natural disasters to requesting countries in support of disaster response. The lead US agency for interaction with the IDC is the United States Geological Survey (USGS); when an IDC request or "activation" is received, the USGS notifies the science teams for NASA instruments with targeting information for data collection. In the case of the ISS, the Earth Sciences and Remote Sensing (ESRS) Unit, part of the Astromaterials Research and Exploration Science Directorate and supporting the ISS Program Science Office at NASA's Johnson Space Center, receives notification from the USGS and coordinates targeting and data collection with the NASA ISS sensor teams. If data is collected, it is passed back to the USGS for posting on their Hazards Data Distribution System and made available for download. The ISS International Partners (CSA, ESA, JAXA, Roscosmos/Energia) have their own procedures for independently supporting IDC activations using their assets on ISS, and there is currently no joint coordination with NASA ISS sensor teams. Following completion of ISS assembly, NASA remote sensing assets began collecting IDC response data in May 2012. The initial NASA ISS sensor systems available to respond to IDC activations included the ISS Agricultural Camera (ISSAC), an internal multispectral visible-near infrared wavelength system mounted in the Window Observational Research Facility, or WORF; the Crew Earth Observations (CEO) Facility, where the crew collects imagery through Station windows using off-the-shelf handheld digital visible-wavelength cameras; and the Hyperspectral Imager for the Coastal Oceans (HICO), a visible to near-infrared system mounted externally on the Japan Experiment Module Exposed Facility. The ISSAC completed its primary mission and was removed from the WORF in January 2013. It was replaced by the very high resolution ISS SERVIR Environmental Research and Visualization System (ISERV) Pathfinder, a visible-wavelength digital camera, telescope, and pointing system. Since the start of IDC response by NASA sensors on the ISS in May 2012 and as of this report, there have been eighty IDC activations; NASA sensor systems have collected data for twenty-three of these events. Of the twenty-three successful data collections, five involved 2 or more ISS sensor systems responding to the same event. Data has also been collected by International Partners in response to natural disasters, most notably JAXA and Roscosmos/Energia through the Urugan program. Data collected in response to IDC activations is delivered by the ISS sensor teams to the ESRS for quality review and transfer to the USGS, where it is ingested into the Hazards Data Distribution System, or HDDS (https://hdds.usgs.gov/hdds2/; figure 1). This system allows the local agencies that issued the IDC activation request to review and download data. The data is then used to develop secondary products useful for humanitarian response such as flood maps. As of this report, approximately 1000 images collected by NASA ISS sensor systems have been downloaded from the HDDS, indicating that the ISS has assumed a valuable role in disaster response efforts. The ISS is also a unique platform in that it will have multiple users over its lifetime, and that no single remote sensing system has a permanent internal or external berth. This scheduled turnover provides for development of new remote sensing capabilities relevant to disaster response -as well as both research and applied science-and represents a significant contribution to continuance and enhancement of the NASA mission to investigate changes on our home planet.

Stefanov, William L.↗

NASA NTRS2014

Lunar Flashlight: Mapping Lunar Surface Volatiles Using a Cubesat

Water ice and other volatiles may be located in the Moon's polar regions, with sufficient quantities for in situ extraction and utilization by future human and robotic missions. Evidence from orbiting spacecraft and the LCROSS impactor suggests the presence of surface and/or nearsurface volatiles, including water ice. These deposits are of interest to human exploration to understand their potential for use by astronauts. Understanding the composition, quantity, distribution, and form of water/H species and other volatiles associated with lunar cold traps is identified as a NASA Strategic Knowledge Gap (SKG) for Human Exploration. These polar volatile deposits could also reveal important information about the delivery of water to the Earth- Moon system, so are of scientific interest. The scientific exploration of the lunar polar regions was one of the key recommendations of the Planetary Science Decadal Survey. In order to address NASA's SKGs, the Advanced Exploration Systems (AES) program selected three lowcost 6-U CubeSat missions for launch as secondary payloads on the first test flight (EM1) of the Space Launch System (SLS) scheduled for 2017. The Lunar Flashlight mission was selected as one of these missions, specifically to address the SKG associated with lunar volatiles. Development of the Lunar Flashlight CubeSat concept leverages JPL's Interplanetary Nano- Spacecraft Pathfinder In Relevant Environment (INSPIRE) mission, MSFC's intimate knowledge of the Space Launch System and EM-1 mission, small business development of solar sail and electric propulsion hardware, and JPL experience with specialized miniature sensors. The goal of Lunar Flashlight is to determine the presence or absence of exposed water ice and its physical state, and map its concentration at the kilometer scale within the permanently shadowed regions of the lunar south pole. After being ejected in cislunar space by SLS, Lunar Flashlight deploys its solar panels and solar sail and maneuvers into a low-energy transfer to lunar orbit. The solar sail and attitude control system work to bring the satellite into an elliptical polar orbit spiraling down to a perilune of 30-10 km above the south pole for data collection. Lunar Flashlight uses its solar sail to shine reflected sunlight into permanently shadowed regions, measuring surface albedo with a four-filter point spectrometer at 1.1, 1.5 1.9, and 2.0 microns. Water ice will be distinguished from dry regolith from these measurements in two ways: 1) spatial variations in absolute reflectance (water ice is much brighter in the continuum channels), and 2) reflectance ratios between absorption and continuum channels. Derived reflectance and reflectance ratios will be mapped onto the lunar surface in order to distinguish the composition of the PSRs from that of the sunlit terrain. Lunar Flashlight enables a low-cost path to in-situ resource utilization (ISRU) by identifying operationally useful deposits (if there are any), which is a game-changing capability for expanded human exploration.

Cohen, B. A.↗

NASA NTRSDate not supplied

Human Factors Research Considerations for Terminal Area Urban Air Mobility Operations

In this presentation, we discuss the human factors research challenges from introducing greater levels of automation in a future air transportation concept called Urban Air Mobility (UAM). UAM is an air transportation concept that aims to provide air transportation services to the daily commuter, as well as emergency response and package delivery. The principal innovation over current day large air transport system is the greater distribution of important safety functions to automated and human agents; these functions include air traffic management, traditionally an air traffic controller responsibility. A central aspect of UAM is the development of an automated air traffic manager, whose primary responsibility is to approve airspace access for vehicle operators. Vehicle operator roles may include onboard and remote pilots, as well as a human manager who will supervise an entire fleet. Alternatively, both fleet manager and vehicle operators can be merged into a single role – a feasible option if UAM aircraft are autonomous. In lieu of tower controllers, vertiport managers, with the assistance of automation, will manage arrival and departure schedules between vertiports, as well as supervise surface operations. Our approach here will be to introduce use cases currently being developed by NASA, and then provide preliminary definitions for each of the roles introduced above and how coordination between them can be configured to support the operations within the use cases described. Subsequently, we review the tools and interfaces being developed to support the various roles. To conclude, we present current human factors work related to defining the roles above and suggest future work to advance the UAM concept.

trial planning↗

NASA NTRS2001

Parametric Data from a Wind Tunnel Test on a Rocket-Based Combined-Cycle Engine Inlet

A 40-percent scale model of the inlet to a rocket-based combined-cycle (RBCC) engine was tested in the NASA Glenn Research Center 1- by 1-Foot Supersonic Wind Tunnel (SWT). The full-scale RBCC engine is scheduled for test in the Hypersonic Tunnel Facility (HTF) at NASA Glenn's Plum Brook Station at Mach 5 and 6. This engine will incorporate the configuration of this inlet model which achieved the best performance during the present experiment. The inlet test was conducted at Mach numbers of 4.0, 5.0, 5.5, and 6.0. The fixed-geometry inlet consists of an 8 deg.. forebody compression plate, boundary layer diverter, and two compressive struts located within 2 parallel sidewalls. These struts extend through the inlet, dividing the flowpath into three channels. Test parameters investigated included strut geometry, boundary layer ingestion, and Reynolds number (Re). Inlet axial pressure distributions and cross-sectional Pitot-pressure surveys at the base of the struts were measured at varying back-pressures. Inlet performance and starting data are presented. The inlet chosen for the RBCC engine self-started at all Mach numbers from 4 to 6. Pitot-pressure contours showed large flow nonuniformity on the body-side of the inlet. The inlet provided adequate pressure recovery and flow quality for the RBCC cycle even with the flow separation.

Fernandez, Rene↗

DOE OSTI2019

Incorporating energy storage and user experience in isolated microgrid dispatch using a multi-objective model

In order to coordinate multiple different scheduling objectives from the perspectives of economy, environment, and users, a practical multi-objective dynamic optimal dispatch model incorporating energy storage and user experience is proposed for isolated microgrids. In this model, besides microturbine units, energy storage is employed to provide spinning reserve services for microgirds; and furthermore, from the perspective of demand side management, a consumer satisfaction indicator is developed to measure the quality of user experience. A two-step solution methodology incorporating multi-objective optimisation and decision analysis is put forward to address this model. First, a powerful heuristic optimisation algorithm, called the -dominance based evolutionary algorithm, is used to find a well-distributed set of Pareto-optimal solutions of the problem. Thereby, the best compromise solutions are identified from the entire solutions with the use of decision analysis by integrating fuzzy C-means clustering and grey relation projection. The simulation results on the modified Oak Ridge National Laboratory Distributed Energy Control and Communication lab microgrid test system demonstrate the effectiveness of the proposed approach.

Li, Yang↗

DOE OSTI2022

E-transit-bench: simulation platform for analyzing electric public transit bus fleet operations

When electrified transit systems make grid aware choices, improved social welfare is achieved by reducing grid stress, reducing system loss, and minimizing power quality issues. Electrifying transit fleet has numerous challenges like non availability of buses during charging, varying charging costs and so on, that are related the electric grid behavior. However, transit systems do not have access to the information about the co-evolution of the grid's power flow and therefore cannot account for the power grid's needs in its day-to-day operation. In this paper we propose a framework of transportation-grid co-simulation, analyzing the spatio-temporal interaction between the transit operations with electric buses and the power distribution grid. Real-world data for a day's traffic from Chattanooga city's transit system is simulated in SUMO and integrated with a realistic distribution grid simulation (using GridLAB-D) to understand the grid impact due to transit electrification. Charging information is obtained from the transportation simulation to feed into grid simulation to assess the impact of charging. We also discuss the impact to the grid with higher degree of transit electrification that further necessitates such an integrated transportation-grid co-simulation to operate the integrated system optimally. Our future work includes extending the platform for optimizing the charging and trip assignment operations.

Sen, Rishav↗

NASA NTRS2007

Computational Support for Technology- Investment Decisions

Strategic Assessment of Risk and Technology (START) is a user-friendly computer program that assists human managers in making decisions regarding research-and-development investment portfolios in the presence of uncertainties and of non-technological constraints that include budgetary and time limits, restrictions related to infrastructure, and programmatic and institutional priorities. START facilitates quantitative analysis of technologies, capabilities, missions, scenarios and programs, and thereby enables the selection and scheduling of value-optimal development efforts. START incorporates features that, variously, perform or support a unique combination of functions, most of which are not systematically performed or supported by prior decision- support software. These functions include the following: Optimal portfolio selection using an expected-utility-based assessment of capabilities and technologies; Temporal investment recommendations; Distinctions between enhancing and enabling capabilities; Analysis of partial funding for enhancing capabilities; and Sensitivity and uncertainty analysis. START can run on almost any computing hardware, within Linux and related operating systems that include Mac OS X versions 10.3 and later, and can run in Windows under the Cygwin environment. START can be distributed in binary code form. START calls, as external libraries, several open-source software packages. Output is in Excel (.xls) file format.

Adumitroaie, Virgil↗

DOE OSTI2020

Integrating Electric Vehicle Charging Infrastructure into Commercial Buildings and Mixed-Use Communities: Design, Modeling, and Control Optimization Opportunities: Preprint

This paper discusses modeling and field studies of controlled EV charging that have been performed with the goal of minimizing requirements for infrastructure upgrades, minimizing building peak demand charges, and maximizing the use of on-site generation. We present a large-scale workplace charging pilot of a demand-controlled scheduled EV charging system with over 250 active daily commuters, successfully demonstrating management of aggregate charging power to avoid new infrastructure investments, mitigate peak demand charges, and provide cost-effective workplace charging to users. In addition to understanding opportunities for demand management, integrating these controllable loads into the energy modeling process for new buildings will also be necessary. This paper then presents an example energy modeling process that evaluates the potential effects of EV charging on building load profiles and infrastructure requirements for a mixed-use community. Finally, we discuss an illustration of how EV charging can be controlled to be synergistic with other building loads and distributed generation.

buildings↗

NASA NTRS2021

Lila: Optimal Dispatching in Probabilistic Temporal Networks using Monte Carlo Tree Search

Executing a Probabilistic Simple Temporal Network (PSTN) amounts at scheduling, i.e. \textit{dispatch}, a set of events under time uncertainty. This constitutes a NP-hard online optimization problem. The right execution time must be dynamically assigned to each event of the PSTN such that the temporal constraints are met, whereas activity durations are progressively observed as the execution unfolds. We propose a dispatching algorithm based on Monte Carlo Tree Search, called Lila, with the following characteristics: (i) it is an anytime algorithm, both offline and online, proven asymptotically optimal; (ii) it returns the current probability of success, either before or at any moment during operations; (iii) it handles any possible continuous or discrete, even non-parametric, probability distributions, as well as inter-dependencies between random variables, exogenous and endogenous uncertainty; and (iv) can be easily extended to handle probabilistic external events, PSTNs with resources, PSTNs with cutoff times and precondition chains, etc. Lila is universal in the sense that it can handle any dispatching protocol, simply by specifying it to the algorithm. It has the unlimited flexibility offered by the simulation paradigm, whilst it asymptotically converges to optimal decisions and/or robustness approximations.

Chien, Steve A.↗

DOE OSTI2022

Implementation of a practical Markov chain Monte Carlo sampling algorithm in PyBioNetFit

Abstract Summary Bayesian inference in biological modeling commonly relies on Markov chain Monte Carlo (MCMC) sampling of a multidimensional and non-Gaussian posterior distribution that is not analytically tractable. Here, we present the implementation of a practical MCMC method in the open-source software package PyBioNetFit (PyBNF), which is designed to support parameterization of mathematical models for biological systems. The new MCMC method, am, incorporates an adaptive move proposal distribution. For warm starts, sampling can be initiated at a specified location in parameter space and with a multivariate Gaussian proposal distribution defined initially by a specified covariance matrix. Multiple chains can be generated in parallel using a computer cluster. We demonstrate that am can be used to successfully solve real-world Bayesian inference problems, including forecasting of new Coronavirus Disease 2019 case detection with Bayesian quantification of forecast uncertainty. Availability and implementation PyBNF version 1.1.9, the first stable release with am, is available at PyPI and can be installed using the pip package-management system on platforms that have a working installation of Python 3. PyBNF relies on libRoadRunner and BioNetGen for simulations (e.g. numerical integration of ordinary differential equations defined in SBML or BNGL files) and Dask.Distributed for task scheduling on Linux computer clusters. The Python source code can be freely downloaded/cloned from GitHub and used and modified under terms of the BSD-3 license (https://github.com/lanl/pybnf). Online documentation covering installation/usage is available (https://pybnf.readthedocs.io/en/latest/). A tutorial video is available on YouTube (https://www.youtube.com/watch?v=2aRqpqFOiS4&t=63s). Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1999

Industrial Hygiene Issues

This breakout session is a traditional conference instrument used by the NASA industrial hygiene personnel as a method to convene personnel across the Agency with common interests. This particular session focused on two key topics, training systems and automation of industrial hygiene data. During the FY 98 NASA Occupational Health Benchmarking study, the training system under development by the U.S. Environmental Protection Agency (EPA) was deemed to represent a "best business practice." The EPA has invested extensively in the development of computer based training covering a broad range of safety, health and environmental topics. Currently, five compact disks have been developed covering the topics listed: Safety, Health and Environmental Management Training for Field Inspection Activities; EPA Basic Radiation Training Safety Course; The OSHA 600 Collateral Duty Safety and Health Course; and Key program topics in environmental compliance, health and safety. Mr. Chris Johnson presented an overview of the EPA compact disk-based training system and answered questions on its deployment and use across the EPA. This training system has also recently been broadly distributed across other Federal Agencies. The EPA training system is considered "public domain" and, as such, is available to NASA at no cost in its current form. Copies of the five CD set of training programs were distributed to each NASA Center represented in the breakout session. Mr. Brisbin requested that each NASA Center review the training materials and determine whether there is interest in using the materials as it is or requesting that EPA tailor the training modules to suit NASA's training program needs. The Safety, Health and Medical Services organization at Ames Research Center has completed automation of several key program areas. Mr. Patrick Hogan, Safety Program Manager for Ames Research Center, presented a demonstration of the automated systems, which are described by the following: (1) Safety, Health and Environmental Training. This system includes an assessment of training needs for every NASA Center organization, course descriptions, schedules and automated course scheduling, and presentation of training program metrics; (2) Safety and Health Inspection Information. This system documents the findings from each facility inspection, tracks abatement status on those findings and presents metrics on each department for senior management review; (3) Safety Performance Evaluation Profile. The survey system used by NASA to evaluate employee and supervisory perceptions of safety programs is automated in this system; and (4) Documentation Tracking System. Electronic archive and retrieval of all correspondence and technical reports generated by the Safety, Health and Medical Services Office are provided by this system.

Brisbin, Steven G.↗

NASA NTRS2005

Ground System for Solar Dynamics Observatory (SDO) Mission

NASA s Goddard Space Flight Center (GSFC) has recently completed its Critical Design Review (CDR) of a new dual Ka and S-band ground system for the Solar Dynamics Observatory (SDO) Mission. SDO, the flagship mission under the new Living with a Star Program Office, is one of GSFC s most recent large-scale in-house missions. The observatory is scheduled for launch in August 2008 from the Kennedy Space Center aboard an Atlas-5 expendable launch vehicle. Unique to this mission is an extremely challenging science data capture requirement. The mission is required to capture 99.99% of available science over 95% of all observation opportunities. Due to the continuous, high volume (150 Mbps) science data rate, no on-board storage of science data will be implemented on this mission. With the observatory placed in a geo-synchronous orbit at 36,000 kilometers within view of dedicated ground stations, the ground system will in effect implement a "real-time" science data pipeline with appropriate data accounting, data storage, data distribution, data recovery, and automated system failure detection and correction to keep the science data flowing continuously to three separate Science Operations Centers (SOCs). Data storage rates of approx. 45 Tera-bytes per month are expected. The Mission Operations Center (MOC) will be based at GSFC and is designed to be highly automated. Three SOCs will share in the observatory operations, each operating their own instrument. Remote operations of a multi-antenna ground station in White Sands, New Mexico from the MOC is part of the design baseline.

Tann, Hun K.↗

DOE OSTI2023

Reducing Urban Traffic Congestion Using Deep Learning and Model Predictive Control

This article proposes a deep learning (DL)-based control algorithm—DL velocity-based model predictive control (VMPC)—for reducing traffic congestion with slowly time-varying traffic signal controls. This control algorithm consists of system identification using DL and traffic signal control using VMPC. For the training process of DL, we established a modeling error entropy loss as the criteria inspired by the theory of stochastic distribution control (SDC) originated by the fourth author. Herein, simulation results show that the proposed algorithm can reduce traffic congestion with a slowly varying traffic signal control input. Results of an ablation study demonstrate that this algorithm compares favorably to other model-based controllers in terms of prediction error, signal varying speed, and control effectiveness.

97 MATHEMATICS AND COMPUTING↗