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At least 811 records · Page 45

A pilot's subjective analysis of a Cockpit Display of Traffic Information (CDTI)

Both the advent of electronic displays for cockpit applications and the availability of high-capacity data transmission systems, linking aicraft with ATC ground computers, offer the opportunity of expanding the pilots' role in the distributive management process. A critical element in this process is believed to be the presentation to the pilot of his traffic situation. A representative cockpit display of traffic information (CDTI) system is presented as viewed from the pilot in the cockpit, and the research results from flight tests presented. The use of advanced controls and displays allows for presentation to the pilot, large quantities of information that he has not had before. The real challenge in the design of an operational CDTI system will be the satisfaction of needs for information and the presentation of all necessary information, only in a useable format in order to avoid clutter. Even though a reasonably large display was utilized in these tests, display clutter was the primary problem from the standpoint of information assimilation.

Keyser, G. L., Jr.↗

Aircraft scanner data availability via the version 0 Information Management System

As part of the Earth Observing System Data and Information System (EOSDIS) development, NASA and other government agencies have developed an operational prototype of the Information Management System (IMS). The IMS provides access to the data archived at the Distributed Active Archive Centers (DAAC's) that allows users to search through metadata describing the (image) data. Criteria based on sensor name or type, date and time, and geographic location are used to search the archive. Graphical representations of coverage and browse images are available to further refine a user's selection. previously, the EROS Data Center (EDC) DAAC had identified the Advanced SOlid-state Array Spectrometer (ASAS), Airborne Visible and infrared Imaging Spectrometer (AVIRIS), NS-001, and Thermal Infrared Multispectral Scanner (TIMS) as precursor data sets similar to those the DAAC will handle in the Earth Observing System era. Currently, the EDC DAAC staff, in cooperation with NASA, has transcribed TIMS, NS-001, and Thematic Mapper Simulation (TMS) data from Ames Research Center and also TIMS data from Stennis Space Center. During the transcription process, the IMS metadata and browse images were created to populate the inventory at the EDC DAAC. These data sets are now available in the IMS and may be requested from the any of the DAAC's via the IMS.

Mah, G. R.↗

Pre-Launch GOES-R Risk Reduction Activities for the Geostationary Lightning Mapper

The GOES-R Geostationary Lightning Mapper (GLM) is a new instrument planned for GOES-R that will greatly improve storm hazard nowcasting and increase warning lead time day and night. Daytime detection of lightning is a particularly significant technological advance given the fact that the solar illuminated cloud-top signal can exceed the intensity of the lightning signal by a factor of one hundred. Our approach is detailed across three broad themes which include: Data Processing Algorithm Readiness, Forecast Applications, and Radiance Data Mining. These themes address how the data will be processed and distributed, and the algorithms and models for developing, producing, and using the data products. These pre-launch risk reduction activities will accelerate the operational and research use of the GLM data once GOES-R begins on-orbit operations. The GLM will provide unprecedented capabilities for tracking thunderstorms and earlier warning of impending severe and hazardous weather threats. By providing direct information on lightning initiation, propagation, extent, and rate, the GLM will also capture the updraft dynamics and life cycle of convective storms, as well as internal ice precipitation processes. The GLM provides information directly from the heart of the thunderstorm as opposed to cloud-top only. Nowcasting applications enabled by the GLM data will expedite the warning and response time of emergency management systems, improve the dispatch of electric power utility repair crews, and improve airline routing around thunderstorms thereby improving safety and efficiency, saving fuel and reducing delays. The use of GLM data will assist the Bureau of Land Management (BLM) and the Forest Service in quickly detecting lightning ground strikes that have a high probability of causing fires. Finally, GLM data will help assess the role of thunderstorms and deep convection in global climate, and will improve regional air quality and global chemistry/climate modeling. The GLM has a robust design that benefits and improves upon its strong heritage of NASA-developed LEO predecessors, the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS). GLM will have a substantially larger number of pixels within the focal plane, two lens systems, and multiple Real-Time Event Processors REPS for on-board event detection and data compression to provide continuous observations of the Americas and adjacent oceans.

Goodman, S. J.↗

DISTRI: Distributed Multi-Facility HPC Simulator (DISTRI) v2.1

DISTRI is an advanced network simulator designed for multi-facility computational infrastructures with agentic behavior. It simulates HPC facilities where computational resources act as autonomous agents, making intelligent decisions about job scheduling, load balancing, and resource allocation. The simulator focuses on developing and testing decentralized algorithms that promote resilience and efficiency in multi-facility environments. Key Features: - Agentic Resource Behavior: Processors and DTNs act as autonomous agents with decision-making capabilities - Pheromone-Based Load Balancing: Decentralized load balancing inspired by ant colony optimization - Dual Topology Support: Mesh (normal operations) and Dumbell (network testing) topologies - Comprehensive TCP Simulation: Realistic TCP implementations with multiple congestion control algorithms - Failure Resilience Testing: Processor failure simulation with automatic job reassignment - Extensive Visualization: Detailed performance analysis and metrics collection - Research-Ready: Designed for algorithm development and benchmarking

Bez, Jean Luca [Lawrence Berkeley National Laborat↗

Proof-of-Concept of a Networked Validation Environment for Distributed Air/Ground NextGen Concepts

The National Airspace System (NAS) must be improved to increase capacity, reduce flight delays, and minimize environmental impacts of air travel. NASA has been tasked with aiding the Federal Aviation Administration (FAA) in NAS modernization. Automatic Dependent Surveillance-Broadcast (ADS-B) is an enabling technology that is fundamental to realization of the Next Generation Air Transportation System (NextGen). Despite the 2020 FAA mandate requiring ADS-B Out equipage, airspace users are lacking incentives to equip with the requisite ADS-B avionics. A need exists to validate in flight tests advanced concepts of operation (ConOps) that rely on ADS-B and other data links without requiring costly equipage. A potential solution is presented in this paper. It is possible to emulate future data link capabilities using the existing in-flight Internet and reduced-cost test equipment. To establish proof-of-concept, a high-fidelity traffic operations simulation was modified to include a module that simulated Internet transmission of ADS-B messages. An advanced NASA ConOp, Flight Deck Interval Management (FIM), was used to evaluate technical feasibility. A preliminary assessment of the effects of latency and dropout rate on FIM was performed. Flight hardware that would be used by proposed test environment was connected to the simulation so that data transfer from aircraft systems to test equipment could be verified. The results indicate that the FIM ConOp, and therefore, many other advanced ConOps with equal or lesser response characteristics and data requirements, can be evaluated in flight using the proposed concept.

Grisham, James↗

Enabling Advanced Automation in Spacecraft Operations with the Spacecraft Emergency Response System

True autonomy is the Holy Grail of spacecraft mission operations. The goal of launching a satellite and letting it manage itself throughout its useful life is a worthy one. With true autonomy, the cost of mission operations would be reduced to a negligible amount. Under full autonomy, any problems (no matter the severity or type) that may arise with the spacecraft would be handled without any human intervention via some combination of smart sensors, on-board intelligence, and/or smart automated ground system. Until the day that complete autonomy is practical and affordable to deploy, incremental steps of deploying ever-increasing levels of automation (computerization of once manual tasks) on the ground and on the spacecraft are gradually decreasing the cost of mission operations. For example, NASA's Goddard Space Flight Center (NASA-GSFC) has been flying spacecraft with low cost operations for several years. NASA-GSFC's SMEX (Small Explorer) and MIDEX (Middle Explorer) missions have effectively deployed significant amounts of automation to enable the missions to fly predominately in 'light-out' mode. Under light-out operations the ground system is run without human intervention. Various tools perform many of the tasks previously performed by the human operators. One of the major issues in reducing human staff in favor of automation is the perceived increased in risk of losing data, or even losing a spacecraft, because of anomalous conditions that may occur when there is no one in the control center. When things go wrong, missions deploying advanced automation need to be sure that anomalous conditions are detected and that key personal are notified in a timely manner so that on-call team members can react to those conditions. To ensure the health and safety of its lights-out missions, NASA-GSFC's Advanced Automation and Autonomy branch (Code 588) developed the Spacecraft Emergency Response System (SERS). The SERS is a Web-based collaborative environment that enables secure distributed fault and resource management. The SERS incorporates the use of intelligent agents, threaded discussions, workflow, database connectivity, and links to a variety of communications devices (e.g., two-way paging, PDA's, and Internet phones) via commercial gateways. When the SERS detects a problem, it notifies on-call team members, who then can remotely take any necessary actions to resolve the anomalies.The SERS goes well beyond a simple '911' system that sends out an error code to everyone with a pager. Instead, SERS' software agents send detailed data (i.e., notifications) to the most appropriate team members based on the type and severity of the anomaly and the skills of the on-call team members. The SERS also allows the team members to respond to the notifications from their wireless devices. This unique capability ensures rapid response since the team members no longer have to go to a PC or the control center for every anomalous event. Most importantly, the SERS enables safe experimentation with various techniques for increasing levels of automation, leading to robust autonomy. For the MIDEX missions at NASA GSFC, the SERS is used to provide 'human-in-the-loop' automation. During lights-out operations, as greater control is given to the MIDEX automated systems, the SERS can be configured to page remote personnel and keep them informed regarding actions taking place in the control center. Remote off-duty operators can even be given the option of enabling or inhibiting a specific automated response in near real time via their two-way pagers. The SERS facilitates insertion of new technology to increase automation, while maintaining the safety and security of mission resources. This paper will focus on SERS' overall functionality and how SERS has been designed to handle the monitoring and emergency response for missions with varying levels of automation. The paper will also convey some of the key lessons learned from SERS' deployment across of variety of missions, highlighting this incremental approach to achieving 'robust autonomy'.

Breed, Julie↗

Artificial Intelligence/Machine Learning Technology in Power System Applications

The primary purpose of this report is to provide an overview of the advancement in artificial intelligence and machine learning (AI/ML) technologies and their applications in power systems. It offers a foundation for understanding the transformative role of AI/ML in power systems and aims to stimulate further research and development in this area. This report begins with a historical perspective of AI/ML technologies, then explores their advancement to today’s prominence. The document highlights key contributors to the success of AI/ML technologies, including increased computational power, greater data availability, innovative algorithms, and advanced tools. It further introduces various AI/ML techniques, including supervised, unsupervised and reinforcement learning, graph neural networks, and generative AI. It also emphasizes the critical importance of ensuring the safety, security, and trustworthiness of these AI/ML techniques within this sector. The report reviews the recent representative advancements in various power system applications enhanced by AI/ML techniques, underscoring key developments and their transformative impact as evidenced by numerous studies. It also explores both the opportunities and challenges associated with the application of AI/ML technologies to improve power system applications. While the report extensively covers AI/ML applications in power systems, focusing primarily on the technical and operational aspects, it may not thoroughly explore the sociopolitical, economic, and broader regulatory implications of AI/ML integration in power systems. AI/ML techniques hold significant potential for enhancing power system applications; however, they are not omnipotent. It is crucial to acknowledge their limitations and understand that they may not be able to address all challenges in the power system domain. Various factors must be considered that influence the implementation, adoption, and effectiveness of AI/ML solutions, including but not limited to safety, security, transparency, and trustworthiness. Additionally, the incorporation of advanced human–machine interfaces is essential, as it enables humans to validate the effectiveness of AI/ML solutions while remaining actively engaged, fostering trust in AI/ML deployment. Finally, the report summarizes AI/ML research activities supported by the Department of Energy (DOE) Office of Electricity (OE) through the Advanced Grid Modeling (AGM) program. The work aligns with the interests and mission of DOE-OE AGM, with the report serving as a resource for identifying existing progress and for pinpointing future applications within AI/ML that need further exploration and support.

24 POWER TRANSMISSION AND DISTRIBUTION↗

On the Efficient Evaluation of the Exchange Correlation Potential on Graphics Processing Unit Clusters

The predominance of Kohn–Sham density functional theory (KS-DFT) for the theoretical treatment of large experimentally relevant systems in molecular chemistry and materials science relies primarily on the existence of efficient software implementations which are capable of leveraging the latest advances in modern high-performance computing (HPC). With recent trends in HPC leading toward increasing reliance on heterogeneous accelerator-based architectures such as graphics processing units (GPU), existing code bases must embrace these architectural advances to maintain the high levels of performance that have come to be expected for these methods. In this work, we purpose a three-level parallelism scheme for the distributed numerical integration of the exchange-correlation (XC) potential in the Gaussian basis set discretization of the Kohn–Sham equations on large computing clusters consisting of multiple GPUs per compute node. In addition, we purpose and demonstrate the efficacy of the use of batched kernels, including batched level-3 BLAS operations, in achieving high levels of performance on the GPU. We demonstrate the performance and scalability of the implementation of the purposed method in the NWChemEx software package by comparing to the existing scalable CPU XC integration in NWChem.

97 MATHEMATICS AND COMPUTING↗

The revolution in data gathering systems

This paper gives a review of the data-acquisition systems used in NASA's wind tunnels from the 1950's to the present as a basis for assessing the impact of minicomputers and microcomputers on data acquisition and processing. The operation and disadvantages of wind-tunnel data systems are summarized for the period before 1950, the early 1950's, the early and late 1960's, and the early 1970's. Some significant advances discussed include the use or development of solid-state components, minicomputer systems, large central computers, on-line data processing, autoranging DC amplifiers, MOS-FET multiplexers, MSI and LSI logic, computer-controlled programmable amplifiers, solid-state remote multiplexing, integrated circuits, and microprocessors. The distributed system currently in use with the 40-ft by 80-ft wind tunnel at Ames Research Center is described in detail. The expected employment of distributed systems and microprocessors in the next decade is noted.

Cambra, J. M.↗

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

Dubovik, O↗

Extending the Capabilities of Closed-loop Distributed Engine Control Simulations Using LAN Communication

Distributed Engine Control (DEC) is an enabling technology that has the potential to advance the state-of-the-art in gas turbine engine control. To analyze the capabilities that DEC offers, a Hardware-In-the-Loop (HIL) test bed is being developed at NASA Glenn Research Center. This test bed will support a systems-level analysis of control capabilities in closed-loop engine simulations. The structure of the HIL emulates a virtual test cell by implementing the operator functions, control system, and engine on three separate computers. This implementation increases the flexibility and extensibility of the HIL. Here, a method is discussed for implementing these interfaces by connecting the three platforms over a dedicated Local Area Network (LAN). This approach is verified using the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k), which is typically implemented on one computer. There are marginal differences between the results from simulation of the typical and the three-computer implementation. Additional analysis of the LAN network, including characterization of network load, packet drop, and latency, is presented. The three-computer setup supports the incorporation of complex control models and proprietary engine models into the HIL framework.

propulsion simulation↗

Communications for the Future Electric Grid: Systems and Implications

As the operation of the electric grid continues to become more automated, the associated increase in sensors and systems places increasing demands for fast response, cybersecure communications. This paper presents a review of advances underway in communications and networking technologies that may be implemented to meet these future electric grid requirements.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Simulation Technology at NASA

NASA Ames Research Center is home to several high-fidelity research flight and air-traffic control simulation facilities which, together with an experienced workforce, produce high-quality research data and findings that have proven to be applicable in the real world. These assets include the Vertical Motion Simulator (VMS), Crew Vehicle Systems Research Facility (CVSRF), Future Flight Central (FFC) air traffic control tower simulator, and several air-traffic control (ATC) simulators. The VMS combines a high-fidelity simulation capability with an adaptable simulation environment, enabling customization for numerous human-in-the-loop research applications. The distinctive feature of the VMS is its unparalleled large amplitude, high-fidelity motion capability. In over 30 years of continuous operation, the VMS has contributed significantly to the body of knowledge in a range of disciplines directly benefiting several aerospace programs and flight safety, including the design and development of flight control systems for the Joint Strike Fighter, Space Shuttle Orbiter, and rotorcraft. It continues to be used for researching new vehicle configurations, vehicle control and safety, transfer-of-training, etc., by NASA, other government agencies, and Industry.The CVSRF includes two motion-based flight simulators: a Boeing 747-400 full flight simulator and the reconfigurable Advanced Concepts Flight Simulator (ACFS). These simulators are primarily used to research air-traffic management concepts and procedures, advanced navigation and avionics concepts, and cockpit human factors. FFC is a full-sized control tower simulator with a 360-degree external field-of-view display system and reconfigurable system architecture. FFC and the ATC simulators are used for testing air-traffic management automation and decision support tools and demonstrate their feasibility in a realistic environment prior to technology transfer for implementation in the National Airspace System (NAS).To support integrated simulations and flight-tests for NASA's Unmanned Aircraft Systems (UAS) in the National Airspace System (NAS) Project, NASA developed a distributed test environment incorporating Live, Virtual, Constructive, (LVC) concepts. Development of the software enabling the LVC is conducted primarily at the Distributed Simulation Research Lab (DSRL) at NASA Ames. The LVC components provide the core infrastructure supporting simulation of UAS operations by integrating live and virtual aircraft in a realistic air traffic environment. This provides the ability to conduct tests more efficiently by promoting the use of existing distributed assets. The LVC infrastructure was used in several human-in-the-loop simulations to evaluate acceptance of Detect and Avoid (DAA) advisories used by UAS pilots to maintain well clear of other virtual traffic and to negotiate maneuvers with air traffic control. It is currently being used to support testing of self-separation algorithms between unmanned and manned aircraft in live flight. Further simulations with more comprehensive air traffic scenarios mixing live and virtual aircraft is planned.In the current fiscal environment, maintaining and upgrading these high-fidelity simulation assets and retaining the skilled workforce necessary to meet future research needs is the primary non-technical challenge.

CVSRF↗

Rotor Wake Vortex Definition: Initial Evaluation of 3-C PIV Results of the Hart-II Study

An initial evaluation is made of extensive three-component (3C) particle image velocimetry (PIV) measurements within the wake across a rotor disk plane. The model is a 40 percent scale BO-105 helicopter main rotor in forward flight simulation. This study is part of the HART II test program conducted in the German-Dutch Wind Tunnel (DNW). Included are wake vortex field measurements over the advancing and retreating sides of the rotor operating at a typical descent landing condition important for impulsive blade-vortex interaction (BVI) noise. Also included are advancing side results for rotor angle variations from climb to steep descent. Using detailed PIV vector maps of the vortex fields, methods of extracting key vortex parameters are examined and a new method was developed and evaluated. An objective processing method, involving a center-of-vorticity criterion and a vorticity 'disk' integration, was used to determine vortex core size, strength, core velocity distribution characteristics, and unsteadiness. These parameters are mapped over the rotor disk and offer unique physical insight for these parameters of importance for rotor noise and vibration prediction.

Burley, Casey L.↗

Using X-Ray Computed Tomography as a Tool for Preliminary Examination Tool of Current and Future Extraterrestrial Sample Return Missions

The Astromaterials Acquisition and Curation Office at the Johnson Space Center is the past, present, and future home of all of NASA’s astromaterials sample collections. The primary goals of the curation office are to maintain the long-term integrity of the samples and ensure that the samples are distributed for scientific study in a fair, timely, and responsible manner, thus maximizing the return on each sample. Part of the curation process is planning for the future. To this end, we perform fundamental research in advanced curation initiatives to better prepared for future sample return missions. Advanced Curation is tasked with developing procedures, technology, and data sets necessary for curating new sample collections, or getting new results from existing sample collections. As part of these advanced curation efforts, we have installed and are operating a Nikon XTH 320 X-ray Computed Tomography(XCT) system in the JSC curation office with four interchangeable X-ray sources, a large-area detector, and a heavy-duty stage. These instrument characteristics allow us exceptional flexibility to analyze a wide range of sample sizes, from sub-mm soil particles to rocks >10 cm in diameter. The penetrative nature of the XCT scans allows for astromaterials samples to be analyzed within sealed low-density containers (e.g., Teflon bags), preserving the pristinity of the samples. We have begun scanning of the Apollo and Antarctic Meteorite sample suites in order to non-destructively map out lithic clasts (and other features) within the samples. The data from these scans will be made available to scientists via the JSC curation website and the Astromaterials Curation Newsletter. We anticipate sample requests from these “new” lithic clasts identified in these “old” samples. We also anticipate that XCT analyses like these would be useful for future sample return missions, like the OSIRIS REx mission, as well as future sample return missions.

Zeigler, Ryan↗

Data Driven UAM Flight Energy Consumption Prediction and Risk Assessment

With the current technological advancements revolutionizing the concept of Urban Air Mobility (UAM) and package delivery, there is also, a concurrent need to quantify the operational safety of these vehicles in terms of their associated risk. Conducting safe flight operations is critical for UAM vehicles which are electrically Vertical Takeoff and Landing (eVTOL) vehicles, to operate in current Air traffic control. In this paper, a data-driven method for UAM vehicle energy consumption prediction and risk quantification with conditional value-at-risk based on energy consumption distribution is presented. Significant factors affecting energy consumption, such as density altitude, aircraft design, airspeed, and collision avoidance algorithms, are considered in the data-driven based energy consumption prediction of different eVTOL

Data-driven↗

Enhancing Responsiveness and Resilience with Distributed Applications in the Grid

A number of trends are increasing the variability in electric power systems resulting in a need for new approaches in control. The increased variability is originating from distributed energy resources and an increasing demand for personalized energy choice from customers grid-edge. Electricity distribution systems continue to incorporate increasing numbers of intelligent end devices, automated switchgear, and sensing and measurement devices which are providing more visibility and control at the grid-edge. Traditional distribution system planning and operations techniques must evolve to meet the new complexity while continuing to deliver safe, reliable, and cost-effective energy. New technologies are enabling new capabilities at the grid-edge to respond to these needs. Distributed applications can deploy intelligence across the distribution grid with peer-to-peer communications and a shared data context for their local environment. These applications can cooperate with each other to respond quickly to changing grid conditions. This enables a layered coordination framework spanning the centralized Advanced Distribution Management System functions with wide area visibility to these new distributed applications running at intelligent devices and meters throughout the distribution system. This paper describes an open-architecture, open-source system approach for commercial scale integration of devices and intelligence at the grid-edge.

Ogle, James P.↗

Evaluating the Impact of Managed EV Charging for Reliable Operation of Bulk Power Systems with High Non-Dispatchable Generation

The growth of electric vehicles (EVs) and variable-generation (VG) sources introduces new challenges for power-system operations. This study introduces a modeling framework and evaluates five EV charging strategies under projected 2040 grid conditions in the Evergy service territory with high non-dispatchable generation. Using realistic EV behavior and generation models, their impacts on system peak demand, ramp rate, and reserve capacity are evaluated. Results show that only the peak-avoidance strategy effectively reduces system peak demand, while decentralized strategies-particularly cost based dynamic charging-can exacerbate peaks due to synchronized user behavior. However, ramp-rate minimization strategy significantly reduce the stress on dispatchable generation achieving the lowest maximum absolute ramp rate (MARR) (56.81 MW) and lowest reserve requirement (2.39 GW). In contrast, unmanaged and TOU random strategies increase the stress on dispatchable generation sources with increased MARR and reserve requirements. These findings highlight the importance of coordinated, system-aware managed charging strategies to ensure reliable and affordable grid operation in the presence of EVs and VG sources.

14 - SOLAR ENERGY↗