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At least 469 records · Page 26

All sources NASA NTRS DOE OSTI

NASA NTRS2002

Science Goal Driven Observing and Spacecraft Autonomy

Spacecraft autonomy will be an integral part of mission operations in the coming decade. While recent missions have made great strides in the ability to autonomously monitor and react to changing health and physical status of spacecraft, little progress has been made in responding quickly to science driven events. For observations of inherently variable targets and targets of opportunity, the ability to recognize early if an observation will meet the science goals of a program, and react accordingly, can have a major positive impact on the overall scientific returns of an observatory and on its operational costs. If the onboard software can reprioritize the schedule to focus on alternate targets, discard uninteresting observations prior to downloading, or download a subset of observations at a reduced resolution, the spacecraft's overall efficiency will be dramatically increased. The science goal monitoring (SGM) system is a proof-of-concept effort to address the above challenge. The SGM will have an interface to help capture higher level science goals from the scientists and translate them into a flexible observing strategy that SGM can execute and monitor. We are developing an interactive distributed system that will use on-board processing and storage combined with event-driven interfaces with ground-based processing and operations, to enable fast re-prioritization of observing schedules, and to minimize time spent on non-optimized observations.

Koratkar, Amuradha↗

NASA NTRS2002

Science Goal Driven Observing and Spacecraft Autonomy

Spacecraft autonomy will be an integral part of mission operations in the coming decade. While recent missions have made great strides in the ability to autonomously monitor and react to changing health and physical status of spacecraft, little progress has been made in responding quickly to science driven events. For observations of inherently variable targets and targets of opportunity, the ability to recognize early if an observation will meet the science goals of a program, and react accordingly, can have a major positive impact on the overall scientific returns of an observatory and on its operational costs. If the onboard software can reprioritize the schedule to focus on alternate targets, discard uninteresting observations prior to downloading, or download a subset of observations at a reduced resolution, the spacecraft's overall efficiency will be dramatically increased. The science goal monitoring (SGM) system is a proof- of-concept effort to address the above challenge. The SGM will have an interface to help capture higher-level science goals from the scientists and translate them into a flexible observing strategy that SGM can execute and monitor. We are developing an interactive distributed system that will use on-board processing and storage combined with event-driven interfaces with ground-based processing and operations, to enable fast re-prioritization of observing schedules, and to minimize time spent on non-optimized observations. This paper will focus on our strategy for developing SGM and the technical challenges that we have encountered. We will discuss the SGM architecture as it applies to the proposed MIDEX-class mission Kronos. However, the architecture and interfaces will also be designed for easy adaptability to other observing platforms, including ground-based systems and to work with different scheduling and pipeline processing systems.

Jones, Jeremy↗

DOE OSTI2023

Power system restoration incorporating diverse distributed energy resources

An example system includes an aggregator configured to receive a service collaboration request and iteratively determine, based on minimum and maximum power values for DERs under its management, an optimized operation schedule. The aggregator may also be configured to iteratively determine, based on the optimized operation schedule, an estimated flexibility range for devices under its management and output an indication thereof. The system may also include a power management unit (PMU) configured to iteratively receive the indication and determine, based on a network model that includes the estimated flexibility range, a reconfiguration plan and an overall optimized operation schedule for the network. The PMU may also be configured to iteratively cause reconfiguration of the network based on the plan. The PMU and aggregator may also be configured to iteratively, at a fast timescale, cause energy resources under their management to modify operation based on the overall optimized operation schedule.

Ding, Fei↗

DOE OSTI2022

Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant

A hybrid PV plant (HPP) combines a photovoltaic (PV) plant with a battery energy storage system (BESS), which is considered a promising step towards the future of renewable power plants by the U.S. Department of Energy. When the renewable penetration reaches a significant level, a hybrid PV plant can bid in as a controllable thermal plant in the future electricity market. In this study, a bidding and BESS scheduling model is proposed for the HPP. The robust optimization (RO) technique has been utilized to identify the worst-case scenario of uncertainties during the bidding process. To address the overly conservative issue of the single-stage RO, we have decoupled the BESS schedule for arbitrage and PV capacity firming by a two-stage RO formulation. By comparing the output of single-stage RO and two-stage RO, the two-stage RO bids and schedules in a more aggressive manner, which increases the income of HPP. Also, the penalty of under-generation is considered in our model so that the day-ahead bidding decision and arbitrage schedules can be adjusted based on the potential UNDER-GENERATION penalty. Because the proposed model is non-convex and contains multi-stages, the Column-and-Constraint Generation (C&CG) algorithm is applied to the model as the solution. The proposed model has shown better economic performance compared to a state-of-art single-stage bidding method in case studies.

BESS scheduling↗

NASA NTRS1980

A solar encounter mission - Starprobe

Accurate measurements of the internal mass distribution and dynamics of the sun as well as in situ observations of its environs are proposed through a JPL-designed satellite, STARPROBE. Scheduled for launch in 1988 under NASA's five-year plan, the probe will conduct radiometric experiments to determine the solar quadrupole moment (J2), fields-and-particles experiments (evaluating such phenomena as heating, acceleration, and peak random velocity of solar wind), and optical experiments potentially superior to those of the Earth-orbiting Solar Optical Telescope (SOT). With flight times ranging from 2.7 to 5.9 years, present delivery options comprise planetary gravity-assist trajectories that will give the spacecraft a perihelion of four solar radii at a 90 deg-inclination. Owing to science- and mission requirements, the thermal shield of the craft should tolerate a solar flux 3000 times greater than that at earth, radioisotope thermoelectric generators supplying 700 watts of power, and a three-axis stabilization system with reaction wheels providing control torque. Implementation concepts now under study may change some of the details of the design.

Randolph, J. E.↗

NASA NTRS1985

Space Station Power System Advanced Development

The objectives of the Space Station Advanced Development Program are related to the development of a set of design options and/or new capabilities to support Space Station development and operation, taking into account also a quantification of the performance and risk of key state-of-the-art technologies, and a reduction of the cost and schedule risk in Space Station development. Attention is given to the photovoltaic power system, a solar dynamic system, and aspects of power management and distribution. A major issue will be the selection of the power generation system. In view of the advantages of the solar dynamic system, it is attempted to resolve issues associated with this system.

Forestieri, A. F.↗

NASA NTRS2004

Schedule Risk Assessment

Schedule Risk Assessment (SRA) determines the probability of finishing on or before a given point in time. This viewgraph presentation introduces the prerequisites, probability distribution curves, special conditions, calculations, and results analysis for SRA.

Smith, Grego↗

NASA NTRS2008

Reducing NPR 7120.5D to Practice: Preparing for a Life-Cycle Review

In March 2007, NASA issued revised rules for space flight project management, NPR 7120.5D, 'NASA Space Flight Program and Project Management Requirements.' Central to the new rules was the construct of Key Decision Points, maturity gates that the project team must pass in order to continue development. In order that the KDP decision be fully informed, the NPR required, as entrance criteria for the gate, the generation and delivery of specified planning, technical, and cost/schedule documents (gate products) and a life-cycle review, the Preliminary Design Review. Building on JPL experience on the Prometheus and Juno projects, the team successfully organized for and conducted these reviews on an aggressive schedule. Key actions were taken to proactively interact with the SRB, produce high-quality gate products with stakeholder review, generate review presentation materials, and handle a myriad of supporting logistical functions. A review preparation team was established, including a Review Captain and leads for documentation, information systems, and logistics, and their roles, responsibilities and task assignments were identified. Aids were produced, including a detailed review preparation schedule and a comprehensive gate products production table. Institutional support was leveraged early and often. Implementation strategy reflected the needs of a nationally-distributed team, as well as applicable export control and IT security requirements. This paper gives a brief overview of the GRAIL mission and its project management challenges, provides a detailed description of project PMSR and PDR preparation and execution activities, including positive and negative lessons learned, and identifies recommendations for future NASA (and non-NASA) project teams.

NPR 7120.5D↗

DOE OSTI2022

Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant: Preprint

BESS scheduling↗

DOE OSTI2023

Conquering Data Chaos: Research Data Management with Kubernetes

Managing massive volumes of data and effectively making it accessible to researchers poses significant challenges and is a barrier to scientific discovery. In many cases, critical data is locked up in unwieldy file formats or one-off databases and is too large to effectively process on a single machine. This talk explores the role of Kubernetes, an open-source container orchestration platform, in addressing research data management challenges. I will discuss how we are using a set of publicly available open-source and home-grown tools in the National Renewable Energy Lab (NREL) Data, Analysis, and Visualization (DAV) group to help researchers overcome data-related bottlenecks. The talk will begin by providing an overview of the data challenges faced in research data management, including data storage, processing, and analysis. I will highlight Kubernetes' ability to handle large-scale data by leveraging containerization and distributed computing, including distributed storage. Kubernetes allows researchers to encapsulate data processing infrastructure and workflows into portable containers, enabling reproducibility and ease of deployment. Kubernetes can then schedule and manage the resource allocation of these containers to enable efficient utilization of limited computing resources, leading to more efficient data processing and analysis. I will discuss some limitations of traditional, siloed approaches to dealing with data and emphasize the need for solutions which foster collaboration. I will highlight how we are using Kubernetes at NREL to facilitate data sharing and cooperation among research teams. Kubernetes' flexible architecture enables the deployment of shared computing environments, such as Apache Superset, where researchers can seamlessly access and analyze shared datasets. Providing the ability to have one research team easily consume data generated by another, utilizing Kubernetes' as a central data platform, is one of the major wins we've encountered by adopting the platform. Finally, I will showcase real-world use cases from NREL where we have used Kubernetes to solve some persistent data challenges involving large volumes of sensor and monitoring data. I will discuss the challenges we encountered when creating our cluster and making it available as a production-ready resource. I will also discuss the specific suite of tools, including Postgres and Apache Druid for columnar and timeseries data, and Redpanda Kafka for streaming data we have deployed in our infrastructure, and the process that went into the selection of these tools.

collaborative environment↗

DOE OSTI2025

CGSim: A Simulation Framework for Large Scale Distributed Computing Environment

Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new algorithms, and optimizing resource allocation strategies. However, existing simulators suffer from limited scalability, hardwired algorithms, lack of real-time monitoring, and inability to generate datasets suitable for modern machine learning approaches. We present CGSim, a simulation framework for large-scale distributed computing environments that addresses these limitations. Built upon the validated SimGrid simulation framework, CGSim provides high-level abstractions for modeling heterogeneous grid environments while maintaining accuracy and scalability. Key features include a modular plugin mechanism for testing custom workflow scheduling and data movement policies, interactive real-time visualization dashboards, and automatic generation of event-level datasets suitable for AI-assisted performance modeling. We demonstrate CGSim’s capabilities through a comprehensive evaluation using production ATLAS PanDA workloads, showing significant calibration accuracy improvements across WLCG computing sites. Scalability experiments show near-linear scaling for multi-site simulations, with distributed workloads achieving 6 × better performance compared to single-site execution. The framework enables researchers to simulate WLCG-scale infrastructures with hundreds of sites and thousands of concurrent jobs within practical time budget constraints on commodity hardware.

Vatsavai, Sairam Sri [Brookhaven National Laborato↗

DOE OSTI2024

Preventive Power Outage Estimation Based on a Novel Scenario Clustering Strategy

The increasing occurrence of extreme weather events is challenging power grid operation. For extreme weather events, the system operator is responsible for estimating the power outages and scheduling the restoration resources. This paper proposes an outage evaluation framework to identify the possible unserved load profiles, vulnerable areas, and mobile energy adequacy. The outputs of an outage prediction model tool are used to generate numerous faulted line scenarios. Next, each scenario's nodal unserved load profile is obtained by solving a three-phase restoration model that considers repair crews and mobile energy resources (MERs). Then, a novel scenario clustering strategy is developed to cluster the unserved load profiles into multiple representative profiles which the system operator can focus on. Finally, case studies on a distribution system evaluate the damage caused by an extreme weather event and verify the effectiveness of the proposed scenario clustering strategy.

MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND D↗

NASA NTRS1973

Joint US/Soviet docking mission.

The purpose and objectives of the joint Apollo/Soyuz experimental test flight, the technical requirements and anticipated solutions necessary to meet the objectives, the mission plan, the flight vehicles, the schedule, and the expected results of successfully completing such a project are discussed. The androgynous feature of the docking system is provided by a symmetrical distribution of all elements which are directly connected during docking, relative to the axis of reverse symmetry. Both the American and Russian systems are designed to serve as either the active or passive system for docking and undocking.

Scott, D. R.↗

NASA NTRS1986

COFS 1 Guest Investigator Program

The process for selecting guest investigators for participation in the Control of Flexible Structures (COFS)-1 program is described. Contracts and grants will be awarded in late CY87. A straw-man list of types of experiments and a distribution of the experiments has been defined to initiate definition of an experiments package which supports development and validation of control structures interaction technology. A schedule of guest investigator participation has been developed.

Fontana, Anthony↗

NASA NTRS1988

Machine intelligence and autonomy for aerospace systems

The present volume discusses progress toward intelligent robot systems in aerospace applications, NASA Space Program automation and robotics efforts, the supervisory control of telerobotics in space, machine intelligence and crew/vehicle interfaces, expert-system terms and building tools, and knowledge-acquisition for autonomous systems. Also discussed are methods for validation of knowledge-based systems, a design methodology for knowledge-based management systems, knowledge-based simulation for aerospace systems, knowledge-based diagnosis, planning and scheduling methods in AI, the treatment of uncertainty in AI, vision-sensing techniques in aerospace applications, image-understanding techniques, tactile sensing for robots, distributed sensor integration, and the control of articulated and deformable space structures.

Heer, Ewald↗

NASA NTRS1993

Integration of domain and resource-based reasoning for real-time control in dynamic environments

A real-time software controller that successfully integrates domain-based and resource-based control reasoning to perform task execution in a dynamically changing environment is described. The design of the controller is based on the concept of partitioning the process to be controlled into a set of tasks, each of which achieves some process goal. It is assumed that, in general, there are multiple ways (tasks) to achieve a goal. The controller dynamically determines current goals and their current criticality, choosing and scheduling tasks to achieve those goals in the time available. It incorporates rule-based goal reasoning, a TMS-based criticality propagation mechanism, and a real-time scheduler. The controller has been used to build a knowledge-based situation assessment system that formed a major component of a real-time, distributed, cooperative problem solving system built under DARPA contract. It is also being employed in other applications now in progress.

Morgan, Keith↗

NASA NTRS2006

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗

NASA NTRS2018

The Integrated Impact of Diet on Human Immune Response, the Gut Microbiota, and Nutritional Status During Adaptation to a Spaceflight Analog

Spaceflight impacts human physiology, including well documented immune system dysregulation. Diet, immune function, and the microbiome are interlinked, but diet is the only one of these factors that we have the ability to easily, and significantly, alter on Earth or during flight. As we understand dietary impacts on physiology more thoroughly, we may then improve the spaceflight diet to improve crew health and potentially reduce spaceflight-associated physiological alterations. It is expected that increasing the consumption of fruits and vegetables and bioactive compounds (e.g., omega-3 fatty acids, lycopene, flavonoids) and therefore enhancing overall nutritional intake from the nominal shelf-stable, fully-processed space food system could serve as a countermeasure to improve human immunological profiles, the taxonomic profile of the gut microbiota, and nutritional status, especially where currently dysregulated during spaceflight. This interdisciplinary study will determine the effect of the current shelf-stable spaceflight diet compared to an "enhanced" shelf-stable spaceflight diet (25% more foods rich in omega-3 fatty acids, lycopene, flavonoids, and more fruits, and vegetables in general). The NASA Human Exploration Research Analog (HERA) 2017 missions, consisting of four 45-day missions with closed chamber confinement and realistic mission simulation in a high-fidelity mock space vehicle, will serve as a platform to replicate mission stressors and the effects on crew biochemistry, immunology, and the gut microbiome. Bio sampling of crewmembers is scheduled for selected intervals pre- and in-mission. Data collection also includes dietary intake recording. Outcome measures will include immune markers (e.g., peripheral leukocyte distribution, inflammatory cytokine profiles, T cell function), the taxonomic and metatranscriptomic profile of the gut microbiome, and nutritional status biomarkers and metabolites. Statistical evaluations will determine physiological and biochemical shifts in relation to nutrient intake and study phase. To date, sample collection has been completed for 2 crewmembers from the first mission, aka Campaign 4 Mission 1. Mission 2 was terminated after 22 days due to effects of Hurricane Harvey, and sample collection was not completed. Sample collection will continue for Campaign 4 Mission 3 and 4 prior to comprehensive sample analysis. Beneficial improvements will provide evidence of the impact of diet on crew health and adaptation to this spaceflight analog, and will aid in the design and development of more-efficient targeted dietary interventions for exploration missions.

Douglas, G. L.↗