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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Advances in Distributed Operations and Mission Activity Planning for Mars Surface Exploration

A centralized mission activity planning system for any long-term mission, such as the Mars Exploration Rover Mission (MER), is completely infeasible due to budget and geographic constraints. A distributed operations system is key to addressing these constraints; therefore, future system and software engineers must focus on the problem of how to provide a secure, reliable, and distributed mission activity planning system. We will explain how Maestro, the next generation mission activity planning system, with its heavy emphasis on portability and distributed operations has been able to meet these design challenges. MER has been an excellent proving ground for Maestro's new approach to distributed operations. The backend that has been developed for Maestro could benefit many future missions by reducing the cost of centralized operations system architecture.

Mars Exploration Rover (MER)↗
NASA NTRS2006

Advances in distributed operations and mission activity planning for Mars surface exploration

A centralized mission activity planning system for any long-term mission, such as the Mars Exploration Rover Mission (MER), is completely infeasible due to budget and geographic constraints. A distributed operations system is key to addressing these constraints; therefore, future system and software engineers must focus on the problem of how to provide a secure, reliable, and distributed mission activity planning system. We will explain how Maestro, the next generation mission activity planning system, with its heavy emphasis on portability and distributed operations has been able to meet these design challenges. MER has been an excellent proving ground for Maestro's new approach to distributed operations. The backend that has been developed for Maestro could benefit many future missions by reducing the cost of centralized operations system architecture.

Shams, Khawaja↗
NASA NTRS1990

A development framework for artificial intelligence based distributed operations support systems

Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself.

Adler, Richard M.↗
DOE OSTI2023

Volt/VAR Optimization (VVO) Application on GridAPPS-D Platform

There is a large increment in the distributed energy resources (DERs) installation and deployments of smart sensing devices and communication infrastructure; hence, the power distribution network is swiftly evolving from a passive network to an active network. This motivates the development of advanced applications to operate power distribution systems for higher efficiency and reliability. These advanced applications are model-based and data-driven. This requires an advanced distribution management system (ADMS) to provide required data for the optimal operation of the distribution systems by coordinating various grid controllable devices. In this paper a Volt-VAR optimization (VVO) application to coordinate the grid’s legacy and new voltage control devices for conservation voltage reduction (CVR) is deployed on the GridAPPS-D platform (an open-source platform ) for ADMS application development. The VVO application is validated for various operating conditions on using modified IEEE 8500-node distribution test feeders. Further, the application is successfully deployed on the GridAPPS-D platform.

Jha, Rahul↗
NASA NTRS1993

R and T report: Goddard Space Flight Center

The 1993 Research and Technology Report for Goddard Space Flight Center is presented. Research covered areas such as (1) flight projects; (2) space sciences including cosmology, high energy, stars and galaxies, and the solar system; (3) earth sciences including process modeling, hydrology/cryology, atmospheres, biosphere, and solid earth; (4) networks, planning, and information systems including support for mission operations, data distribution, advanced software and systems engineering, and planning/scheduling; and (5) engineering and materials including spacecraft systems, material and testing, optics and photonics and robotics.

Soffen, Gerald A.↗
NASA NTRS1995

The Telestation: A product for distributed data gathering and operations

Advances in computer, navigation and wireless telecommunication technologies are enabling better electronic devices at reduced costs. Individually, these devices have been applied to increase the performance of many common systems, such as desktop computers, surveying equipment, and modems. However, we believe the convergence of these three technologies will create a product that simultaneously lowers life cycle costs while increasing operational effectiveness. Space Systems/Loral (SS/L) is developing portions of this product, known as the Telestation, for both terrestrial and orbital applications. The Telestation consists of an advanced microprocessor for command and data handling; a GPS receiver for position, time, and attitude information; and a Globalstar Transceiver for two-way digital communications. The Telestation provides the user with real-time command and control of globally distributed hardware elements. This capability can be applied terrestrially for gathering information (e.g., science, environmental, etc.) in remote or inhospitable locations, or where logistical support is inadequate. An in-orbit version can be used for spacecraft or payload operations, allowing principal investigators instant access to their payloads during all phases of a mission. This paper describes some cost effectiveness metrics of the Telestation, its development status, and its utility in both terrestrial and orbital applications.

Cleave, Robert R.↗
DOE OSTI2022

Advanced Metering Infrastructure for Distribution Planning and Operation: Closing the Loop on Grid-Edge Visibility

In the recent history of electric utilities, the potential to have visibility of the grid edge is gaining significance for the reliable planning and operation of a clean energy smart grid. Before the recent large-scale customer adoption of distributed energy resources (DERs), distribution networks were planned with a simpler fit-and-forget philosophy. The importance of customer-sited DERs to achieve climate change goals marks a major shift for utility operations. Changes to traditional fit-and-forget planning paradigms require better availability of grid-edge data. Smart metering is an enterprise-wide tool that is enabling visibility when and where it has been most needed. As of 2020, the rollout of smart metering, or advanced metering infrastructure (AMI), had reached more than 100 million meters in the United States, and nearly half of all electricity customers are now equipped with a smart meter (Figure 1). Smart meters are quickly becoming a ubiquitous data capture feature of smart grids. AMI enables utilities to record and measure electricity usage and power-flow metrics at a minimum of hourly intervals and at least once a day. At a minimum, AMI enables interval metering, automatic meter reading enabling accurate and time-interval billing, and the ability to provide feedback on customer energy consumption.

advanced metering infrastructure↗
NASA NTRS2013

Integrated Ground Operations Demonstration for Responsive Space Access

Integrated Ground Operations Demonstration Units (IGODU) project developed to mature, integrate and demonstrate advancements in cryogenics, system health management and command and control technologies. Two Distinct Testing Environments: a) GODU Integrated Refrigeration and Storage - GODU LH2; b) GODU Autonomous Control - GODU LO2. Scope: I. GODU LH2: a) Investigate alternative storage and distribution architecture for future cryogenic propellant operations. b) Demonstrate advanced cryogenic propellant handling operations (liquefaction, storage and distribution) of normal boiling point and sub-cooled cryogenic propellants. II. GODU L02: a) Develop and demonstrate advanced control and health management technologies and techniques to autonomously control cryogenic propellant servicing operations. b) Investigate modern COTS hardware and control systems in an effort to reduce the "standing army" of engineers associated with maintaining and operating ground systems through the use of health management and autonomous control technologies. Goals: a) Raise Technology Readiness Levels (TRL) and Integration Readiness Levels (IRL) of several key technology development areas. b) Reduce operations lifecycle costs of future test programs and launch complexes. c) Demonstrate technologies for future exploration beyond low earth orbit. d) Serve as test environments for extraterrestrial surface operations.

Johnson, Robert G.↗
DOE OSTI2023

Distribution Grid Management in the Presence of Distributed Energy Resources

The global concerns over climate change, government policies, and incentives in support of distributed energy resources (DERs) are accelerating the growth of DERs in distribution networks. The growth in DER penetration levels can create various issues such as over/under voltages, reverse power flows, overloading, and protection miscoordination. State-of-the-art grid automation solutions such as advanced distribution management systems (ADMS) and distributed energy resource management systems (DERMS) can leverage the DERs to improve distribution grid operations. The ADMS offers advanced grid management functions such as Volt-VAR optimization (VVO), fault management, and outage management to the distribution operator to improve situational awareness and optimize network operations. The DERMS solutions aggregate the small-scale BTM DERs to provide grid services including demand response, voltage regulation, and situational awareness. In this presentation, distribution grid management approaches in the presence of DERs using ADMS and DERMS will be discussed.

ADMS↗
NASA NTRS1993

Distributed science operations for JPL planetary missions

Advances in spacecraft, flight instruments, and ground systems provide an impetus and an opportunity for scientific investigation teams to take direct control of their instruments' operations and data collection while at the same time, providing a cost effective and flexible approach in support of increasingly complex science missions. Operations of science instruments have generally been integrated into planetary flight and ground systems at a very detailed level. That approach has been successful, but the cost of incorporating instrument expertise into the central mission operations system has been high. This paper discusses an approach to simplify planetary science operations by distributing instrument computing and data management tasks from the central mission operations system to each investigator's home center of observational expertise. Some early results of this operations concept will be presented based on the Mars Observer (MO) Project experience and Cassini Project plans.

Benson, Richard D.↗
DOE OSTI2022

A Simple and Accurate Energy-Detector-Based Transient Waveform Detection for Smart Grids: Real-World Field Data Performance

Integration of distributed energy sources, advanced meshed operation, sensors, automation, and communication networks all contribute to autonomous operations and decision-making processes utilized in the grid. Therefore, smart grid systems require sophisticated supporting structures. Furthermore, rapid detection and identification of disturbances and transients are a necessary first step towards situationally aware smart grid systems. This way, high-level monitoring is achieved and the entire system kept operational. Even though smart grid systems are unavoidably sophisticated, low-complexity algorithms need to be developed for real-time sensing on the edge and online applications to alert stakeholders in the event of an anomaly. In this study, the simplest form of anomaly detection mechanism in the absence of any a priori knowledge, namely, the energy detector (also known as radiometer in the field of wireless communications and signal processing), is investigated as a triggering mechanism, which may include automated alerts and notifications for grid anomalies. In contrast to the mainstream literature, it does not rely on transform domain tools; therefore, utmost design and implementation simplicity are attained. Performance results of the proposed energy detector algorithm are validated by real power system data obtained from the DOE/EPRI National Database of power system events and the Grid Signature Library.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Inverter Reliability Estimation for Advanced Inverter Functionality

In the near future, grid operators are expected to regularly use advanced distributed energy resource (DER) functions, defined in IEEE 1547-2018, to perform a range of grid-support operations. Many of these functions adjust the active and reactive power of the device through commanded or autonomous modes, which will produce new stresses on the grid-interfacing power electronics components, such as DC/AC inverters. In previous work, multiple DER devices were instrumented to evaluate additional component stress under multiple reactive power setpoints. We utilize quasi-static time-series simulations to determine voltage-reactive power mode (volt-var) mission profile of inverters in an active power system. Mission profiles and loss estimates are then combined to estimate the reduction of the useful life of inverters from different reactive power profiles. It was found that the average lifetime reduction was approximately 0.15% for an inverter between standard unity power factor operation and the IEEE 1547 default volt-var curve based on thermal damage due to switching in the power transistors. For an inverter with an expected 20-year lifetime, the 1547 volt-var curve would reduce the expected life of the device by 12 days. This framework for determining an inverter's useful life from experimental and modeling data can be applied to any failure mechanism and advanced inverter operation.

component degradation↗
NASA NTRS2023

Distributed Ground Sensor Fusion Based Object Tracking for Autonomous Advanced Air Mobility Operations

Autonomous operations are a crucial aspect in the context of Advanced Air Mobility and other emerging aviation markets. In order to enable this autonomy, an accurate and detailed understanding of the positions of the various vehicles in the air is necessary. Full localization independent of on-board sensors makes the system suitable for noncooperative vehicles. This paper focuses on the object tracking part that relies on distributed ground-based sensor fusion, considering specific properties and limitations of different sensor types. Results show satisfactory performance in nominal scenarios with full coverage. Dropouts of individual sensors affect the accuracy of the tracking results, which agrees with expectations for partial coverage, when full localization is not achievable anymore. Finally, a study is performed to identify which parameters have the largest impact on the fit error.

Autonomous↗
NASA NTRS2004

Balanced Expertise Distribution in Remote Ultrasound Imaging Aboard The International Space Station (ISS)

Astronaut training for ISS operations usually ensures independent performance. With small crew size same crews also conduct all science work onboard. With diverse backgrounds, a good "match" between the existing and required skills can only be anecdotal. Furthermore, full proficiency in most of the complex tasks can be attained only through long training and practice, which may not be justified and may be impossible given the scarcity of training time. To enable a number of operational and science advancements, authors have developed a new approach to expertise distribution in time and among the space and ground personnel. Methods: As part of NASA Operational Ultrasound Project (1998-2003) and the NASA-solicited experiment "Advanced Diagnostic Ultrasound in Microgravity-ADUM" (P.I. -S.D., ongoing), the authors have created a "Balanced Expertise Distribution" approach to perform complex ultrasound imaging tasks on ISS for both operational and science use. The four components of expertise are a) any pre-existing pertinent expertise; b) limited preflight training c) adaptive onboard proficiency enhancement tools; d) real-time ' guidance from the ground. Throughout the pre-flight training and flight time preceding the experiments, the four components are shaped in a dynamic fashion to meet in an optimum combination during the experiment sessions. Results: Procedure validation sessions and feasibility studies have given encouraging results. While several successful real-time remote guidance sessions have been conducted on ISS, Expedition 8 is the first to use an "on-orbit proficiency enhancement" tool. Conclusions: In spite of severely limited training time, daring peer-reviewed research and operational enhancements are feasible through a balanced distribution of expertise in time, as well as among the crewmembers and ground personnel. This approach shows great promise for biomedical research, but may be applicable for other areas of micro gravity-based science

Sargsyan, Ashot↗
DOE OSTI2024

A framework to enhance disaster debris estimation with AI and aerial photogrammetry

This study addresses the critical need to enhance disaster preparedness and response, focusing on hurricane impact assessment and debris estimation. Accurate assessments in this context are critical for post-event search-and-rescue (SAR) operations and resource distribution. Recent computing advancements are revealing the potential of unmanned aerial vehicles (UAVs) and artificial intelligence (AI) technologies in collecting data and assisting with post-hurricane reconnaissance. However, the use of AI and UAV photogrammetry for accurate disaster impact analysis remains underexplored. To this end, this study proposes a damage and debris analysis framework harnessing reality capture through aerial imagery and photogrammetry. Within this framework, a region-based neural network is leveraged to detect debris locations in aerial imagery with favorable performance. In a testbed within the Beaumont-Port Arthur region, in Southeast Texas, this study performs 3D reality captures of the built environment. Since the accuracy of the 3D reality capture is of importance in research areas associated with time-sensitive disaster response, we further investigate the optimal 2D aerial imagery overlap ratio required to generate a sufficiently accurate 3D model for disaster impact analysis and debris volume estimation. Results indicate that, in the case of aerial imagery for infrastructure systems, a minimum of 60 % overlap is recommended for damage assessment and debris analysis. In contrast, for flat green areas, a minimum of 50 % overlap is adequate. Overall, for disaster response applications, our study reveals that an overlap ratio between 60 % and 70 % is optimal for achieving a balance between time efficiency and data quality in aerial data collection. Furthermore, these quantitative recommendations are crucial for enabling efficient disaster response efforts. Additionally, our study outcomes will improve disaster impact analysis and facilitating timely and effective response strategies.

Artificial intelligence↗