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At least 91 records · Page 5

Compressive Sensing Based Data Acquisition Architecture for Transient Stellar Events in Crowded Star Fields

Compressive sensing is a mathematical technique for simultaneous data acquisition and compression. In this work, we show a CS based architecture for acquiring and reconstructing transient stellar events. This architecture reconstructs a differenced image itself, eliminating the need for any sparse domain transforms, otherwise required for traditional CS reconstruction. The resulting reconstructed differenced image is of critical importance as the information required for generating a time-series photometric light curve is obtained only from a differenced image. Hence, reconstructing a crowded star spatial image, followed by differencing is wasteful. This architecture eliminates the need to 1.) transform an image to a sparse domain, 2.) Reconstruct a dense field, and then apply differencing on the image to obtain the image of critical value. We study the case of microlensing to depict a star source experiencing magnification in time. Our results show that this architecture is able to reconstruct star source magnitudes with magnification factors greater than 1 for clean images with error less than 2% using only 10% of the Nyquist rate samples.

Asmita Korde-Patel

Compressive Sensing Based Data Acquisition Architecture for Transient Stellar Events in Crowded Star Fields

Compressive sensing is a mathematical technique for simultaneous data acquisition and compression. In this work, we show a CS based architecture for acquiring and reconstructing transient stellar events. This architecture recon-structs a differenced image itself, eliminating the need for any sparse domain transforms, otherwise required for traditional CS reconstruction. The resulting reconstructed differenced image is of critical importance as the information required for generating a time-series photometric light curve is obtained only from a differenced image. Hence, reconstructing a crowded star spatial image, followed by differencing is wasteful. This architecture eliminates the need to 1.) transform an image to a sparse domain, 2.) Reconstruct a dense field, and then apply differencing on the image to obtain the image of critical value. We study the case of microlensing to depict a star source experiencing magnification in time. Our results show that this architecture is able to reconstruct star source magnitudes with magnification factors greater than 1 for clean images with error less than 2% using only 10% of the Nyquist rate samples.

Asmita Korde-patel

A Model-based Health Monitoring and Diagnostic System for the UH-60 Helicopter

Model-based reasoning techniques hold much promise in providing comprehensive monitoring and diagnostics capabilities for complex systems. We are exploring the use of one of these techniques, which utilizes multi-signal modeling and the TEAMS-RT real-time diagnostic engine, on the UH-60 Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) flight research aircraft. We focus on the engine and transmission systems, and acquire sensor data across the 1553 bus as well as by direct analog-to-digital conversion from sensors to the QHuMS (Qualtech health and usage monitoring system) computer. The QHuMS computer uses commercially available components and is rack-mounted in the RASCAL facility. A multi-signal model of the transmission and engine subsystems enables studies of system testability and analysis of the degree of fault isolation available with various instrumentation suites. The model and examples of these analyses will be described and the data architectures enumerated. Flight tests of this system will validate the data architecture and provide real-time flight profiles to be further analyzed in the laboratory.

Patterson-Hine, Ann

The Mars 2020 Ground Data System Architecture

The Mars 2020 Mission’s primary objective is to collect 20 geographically unique samples during its prime mission of one and a quarter Martian years, or just over 2 Earth years. Mission planners determined the project needed to develop a system that would enable the operations team to analyze engineering and science data, make science decisions, select viable rover targets at a millimeter resolution and validate an uplink bundle for a car sized rover with more complex science instruments than any previous Mars surface mission. All this had to be done within a five hour time frame. Doing this with a small team would be a challenge, but this had to be accomplished by a large team of engineers and scientists located across North America and Europe. Achieving this level of operational efficiency was unheard of in the prime mission. In addition, the mission had another set of requirements that had nothing to do with surface operations; the Mars 2020 Ground Data System (GDS) was also expected to comply with a new set of security requirements to keep up with the ever changing cybersecurity landscape. The Mars 2020 Ground Data System (GDS) is a re-architected version of the Mars Science Laboratory GDS. The primary goal was to integrate the lessons learned from previous Mars surface missions, accommodate a set of new requirements and capabilities required to ensure mission success, and comply with a new set of cybersecurity controls. The new architecture includes several unique qualities including a data lake, language-agnostic system-wide event-based operations, containerization, automated deployment, network segmentation, infrastructure-as-code, API-driven interfaces, and the first Mars surface GDS to operate primarily in the cloud. The new architecture enabled greater access to the system’s data, tighter integration with the operations team, and a higher level of traceability. The availability of the data also enabled a new set of capabilities previously not possible on surface missions. These new capabilities include an autonomous data to information, pipeline for downlink analysis, horizontal scaling of science data processing capabilities, autonomous round trip data tracking of science and engineering data, integration of flight system state into the tactical planning cycle, high fidelity targeting utilizing kinematic data, and hierarchical image and 3d meshes data representations. This paper will introduce the requirements for the Mars 2020 Mission, the heritage architecture, and the rationale for the changes to achieve the new architecture. The paper will continue to describe the fundamental changes made to the GDS architecture, how these changes enabled a more tightly integrated GDS, and the new capabilities that were enabled by the new architecture. The paper will conclude with the lessons learned from the process of rearchitecting a heritage GDS system and from the first 200 days of operations supporting over 800 users from around the world.

Lopez-Roig, Reynaldo

Data system architecture considerations for a space station

The functions that a space station could serve are outlined and details of the data systems requirements are discussed. The data system design will be guided by an overall space systems plan, and will feature distributed, layered architecture, user friendliness, hierarchical control, technology transparency, standard interfaces, and automated engineering tools. The station would begin with a limited core capability and evolve to serve functions defined thereafter. The automation of the engineering tools will be necessary to permit an optimized, minimized crew to control all functions of the space station, while at the same time freeing the crew from being actively involved in maintaining the nominal life support functions of the equipment. One major criterion is that the software must be error free, while another is adaptibility to changing space station configurations and demands.

Connell, E. B.

DAQ: Software Architecture for Data Acquisition in Sounding Rockets

A multithreaded software application was developed by Jet Propulsion Lab (JPL) to collect a set of correlated imagery, Inertial Measurement Unit (IMU) and GPS data for a Wallops Flight Facility (WFF) sounding rocket flight. The data set will be used to advance Terrain Relative Navigation (TRN) technology algorithms being researched at JPL. This paper describes the software architecture and the tests used to meet the timing and data rate requirements for the software used to collect the dataset. Also discussed are the challenges of using commercial off the shelf (COTS) flight hardware and open source software. This includes multiple Camera Link (C-link) based cameras, a Pentium-M based computer, and Linux Fedora 11 operating system. Additionally, the paper talks about the history of the software architecture's usage in other JPL projects and its applicability for future missions, such as cubesats, UAVs, and research planes/balloons. Also talked about will be the human aspect of project especially JPL's Phaeton program and the results of the launch.

Ahmad, Mohammad

Alaska Synthetic Aperture Radar (SAR) Facility science data processing architecture

The paper describes the architecture of the Alaska SAR Facility (ASF) at Fairbanks, being developed to generate science data products for supporting research in sea ice motion, ice classification, sea-ice-ocean interaction, glacier behavior, ocean waves, and hydrological and geological study areas. Special attention is given to the individual substructures of the ASF: the Receiving Ground Station (RGS), the SAR Processor System, and the Interactive Image Analysis System. The SAR data will be linked to the RGS by the ESA ERS-1 and ERS-2, the Japanese ERS-1, and the Canadian Radarsat.

Hilland, Jeffrey E.

Detector architecture and data flow of the CMS HGCAL Phase-2 Endcap Calorimeter Upgrade

The CMS High Granularity Calorimeter (HGCAL) is the Phase-2 endcap calorimeter upgrade for the High-Luminosity Large Hadron Collider, designed to provide precise spatial, energy, and timing measurements in a high-radiation, high-pileup environment. This work presents an overview of the HGCAL assembly process, detector architecture, and end-to-end data flow. The data flow goes from signal generation in silicon sensors and scintillator tiles through front-end electronics, optical transmission, and back-end data acquisition. The study highlights how the integrated detector, electronics, and readout systems enable efficient event reconstruction and support the physics objectives of the HL-LHC.

Osei Boakye, Prince [Grambling State U.]

The Geostationary Operational Satellite R Series SpaceWire Based Data System Architecture

The GOES-R program selected SpaceWire as the best solution to satisfy the desire for simple and flexible instrument to spacecraft command and telemetry communications. Data generated by GOES-R instruments is critical for meteorological forecasting, public safety, space weather, and other key applications. In addition, GOES-R instrument data is provided to ground stations on a 24/7 basis. GOES-R requires data errors be detected and corrected from origin to final destination. This paper describes GOES-R developed strategy to satisfy this requirement

Krimchansky, Alexander

A Data System Architecture for Measurement Based Systems: Precipitation Processing System

NASA s Earth Science Enterprise (ESE) is changing focus from single satellite missions to measurement oriented programs. An example of this paradigm shift is the Global Precipitation Measurement (GPM) project. GPM is conceptualized as a rolling-wave of measurement possibilities all focused on the key precipitation parameter. In response to this shift to measurement programs and also integral to the ESE s new strategy for processing and management its data, a measurement based approach is also critical for data processing system that support measurement programs like GPM. This paper provides an overview of the paradigm shift from mission to measurement. It also presents a summary of the ESE s new strategy for its data systems. Building on this background the paper details the architectural, design and implementation aspects of the Precipitation Processing System (PPS). The PPS is an evolution of a single point system developed for the Tropical Rainfall Measurement Mission to a generic precipitation data system. The paper provides the context within which PPS will support the GPM program.

Stocker, Erich Franz

Custom Integration of Multiple Medical Functionalities

INTRODUCTION: Previous spaceflight experience and results from probabilistic risk assessment of spaceflight medical risk have highlighted the need for vital sign measurements, medical scopes, and clinical imaging tools for managing medical conditions during spaceflight. The Human Research Program’s Exploration Medical Capability (ExMC) Element and the Mars Campaign Office’s Exploration Medical Integrated Product Team (XMIPT) have performed ground-based evaluations of two Commercial-off-the-Shelf (COTS) Multi-functional Integrated Medical (MIM) devices, which integrate various medical capabilities together in one device. The key findings from these evaluations are presented in a complementary presentation, leaving this presentation to focus on forward recommendations for customized integration of multiple medical functionalities. KEY COMPONENTS: The key features of a custom integration of multiple medical functionalities includes devices and capabilities that optimally reduce medical risk. The COTS MIM devices incorporated functionality for best supporting Earth-based, emergency, pre-hospital care. Our custom integration will use probabilistic risk assessment tools, such as the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT), to determine the optimal functionality to include based on medical risk minimization. An additional feature of custom integration includes the ability to adapt to different requirements within different vehicles and/or missions. The COTS MIM devices store data in patient specific records, however, the format of the records is not modifiable, and data are not easily transferred from the MIM device to a central data architecture outside of the manufacturer’s established system. Our concept for custom integration will use devices that have an open application programming interface, which can easily connect to independent data architectures and third-party visualization software. The ultrasound capabilities included within the COTS MIM devices did not satisfy many of the Artemis Research and Operations Working Group’s ultrasound functional needs, and therefore, incorporation of higher quality ultrasound capabilities within a customized integration will be beneficial. The COTS MIM devices included minimal procedural guidance and clinical decision support tools. Supplemental tools of this type would need to be supplied along with the COTS MIM devices if they were to be used operationally, so another advantage of customization is the ability to integrate these support tools along with the medical functionality, for a more streamlined user experience. CONCLUSION: Investigation of a customized integration of medical functionality provides a method for further understanding the needs of a long-term exploration spaceflight medical system. The crew members of these exploration missions will need to operate more and more independently from Earth-based ground support. Therefore, having an optimized, streamlined medical system, which contains the functionality and supporting information needed, while remaining within mission and vehicle constraints, will help to maintain crew health and performance, which is necessary for achieving high levels of mission success.

B E Lewandowski

Functional language and data flow architectures

This is a tutorial article about language and architecture approaches for highly concurrent computer systems based on the functional style of programming. The discussion concentrates on the basic aspects of functional languages, and sequencing models such as data-flow, demand-driven and reduction which are essential at the machine organization level. Several examples of highly concurrent machines are described.

Ercegovac, M. D.

A comparison of multiprocessor scheduling methods for iterative data flow architectures

A comparative study is made between the Algorithm to Architecture Mapping Model (ATAMM) and three other related multiprocessing models from the published literature. The primary focus of all four models is the non-preemptive scheduling of large-grain iterative data flow graphs as required in real-time systems, control applications, signal processing, and pipelined computations. Important characteristics of the models such as injection control, dynamic assignment, multiple node instantiations, static optimum unfolding, range-chart guided scheduling, and mathematical optimization are identified. The models from the literature are compared with the ATAMM for performance, scheduling methods, memory requirements, and complexity of scheduling and design procedures.

Storch, Matthew

Data base architecture for instrument characteristics critical to spacecraft conceptual design

Spacecraft designs are driven by the payloads and mission requirements that they support. Many of the payload characteristics, such as mass, power requirements, communication requirements, moving parts, and so forth directly affect the choices for the spacecraft structural configuration and its subsystem design and component selection. The conceptual design process, which translates mission requirements into early spacecraft concepts, must be tolerant of frequent changes in the payload complement and resource requirements. A computer data base was designed and implemented for the purposes of containing the payload characteristics pertinent for spacecraft conceptual design, tracking the evolution of these payloads over time, and enabling the integration of the payload data with engineering analysis programs for improving the efficiency in producing spacecraft designs. In-house tools were used for constructing the data base and for performing the actual integration with an existing program for optimizing payload mass locations on the spacecraft.

Rowell, Lawrence F.

Machine-Protection System for the PIP-II Linear Accelerator: Architecture and Data Processing Schemes

PIP-II at Fermilab features a brand-new, 800 MeV leading-edge Linear Accelerator (Linac) that will enable the Fermilab complex to deliver more than a megawatt of beam power to the Long Base-line Neutrino Facility (LBNF), requiring a robust Machine Protection System (MPS) to prevent beam-induced damage to delicate cryomodules and vacuum components. Signals in various accelerator components, in both analog and digital format, are collected and processed to assest the operating conditions of the accelerator. In the situation a potential damage is foreseen, the beam permit signal will be drop. A critical element of this system is the fast Analog Machine Protection System, a high-bandwidth platform designed for real-time beam loss monitoring. The system utilizes a modular, FPGA-based architecture to digitize signals from beam-sensing devices, such as AC Current Transformers (ACCTs), non-invasive Ring Pickups (RPUs) and beam scrapers. To eliminate both high frequency as well as 60 Hz noise that might be picked up in the industrial environment, data processing schemes beyond regular digital filtering are planned and implemented.

Wu, Jinyuan [Fermilab] (ORCID:0000000344329521)

Moving Towards a Common Ground and Flight Data Systems Architecture for NASA's Exploration Missions

The National Aeronautics and Space Administration has embarked on an ambitious effort to return man to the moon and then on to Mars. The Exploration Vision requires development of major new space and ground assets and poses challenges well beyond those faced by many of NASA's recent programs. New crewed vehicles must be developed. Compatible supply vehicles, surface mobility modules and robotic exploration capabilities will supplement the manned exploration vehicle. New launch systems will be developed as well as a new ground communications and control infrastructure. The development must take place in a cost-constrained environment and must advance along an aggressive schedule. Common solutions and system interoperability and will be critical to the successful development of the Exploration data systems for this wide variety of flight and ground elements. To this end, NASA has assembled a team of engineers from across the agency to identify the key challenges for Exploration data systems and to establish the most beneficial strategic approach to be followed. Key challenges and the planned NASA approach for flight and ground systems will be discussed in the paper. The described approaches will capitalize on new technologies, and will result in cross-program interoperability between spacecraft and ground systems, from multiple suppliers and agencies.

Rader. Steve

Holistic energy analysis method for thermal management architectures of data centers

Modern high-performance computing (HPC) data centers (DCs), particularly those supporting energy-intensive artificial intelligence (AI) workloads, face escalating thermal management challenges that degrade performance through thermal throttling and drive up cooling power consumption and operational costs. To address this challenge, many have developed a wide variety of thermal management solutions (single-phase, two-phase, direct, indirect, hybrid, and more) which attempt to cool HPC DCs effectively while attempting to minimize overall system power consumption. However, the analysis of these solutions and methods to effectively compare one with another is lacking. Overall power usage effectiveness (PUE) and total-power usage effectiveness (TUE) provide a metric to quantify power consumption but fail to identify components in the system which require further optimization. To address this, we propose a holistic analytical framework – the waterfall diagram (WFD) – which leverages a waterfall chart methodology, offering a comprehensive visualization of both the thermal management system loop and heat flow pathways from individual server components to the outdoor ambient. Use of the WFD enables graphical estimations of power efficiency and cooling performance across each component of a DC cooling system and complements Sankey-style energy flow visualizations by additionally resolving stage-wise temperature changes and incremental TUE contributions. The framework is used in conjunction with simulation-based approaches, to conduct a detailed pressure drop and flow distribution analysis aimed at identifying the optimal coolant distribution architecture for a single-phase direct-to-chip water-cooled DC, which serves as the baseline for subsequent WFD analysis. Among the evaluated architectures, the 3 U modular coolant distribution architecture is found to demonstrate the best performance, considering minimal pressure drop and uniform flow distribution. In addition, TUE is calculated for each cooling loop component based on its associated pressure drop and corresponding pumping power, which are integrated into the WFD. This correlation between TUE and local temperature offers immediate insight into the power efficiency and thermal performance contributions of individual components, facilitating further development and optimization. Examples of WFD applications are presented under varying thermal loads and ambient conditions, demonstrating reasonable cooling strategies. Notably, the 3 U modular architecture maintains a consistent chip case temperature of 85°C, achieving a TUE of 1.016 at ambient temperature of 47°C, and a TUE of 1.026 at ambient temperature of 52°C. The WFD methodology provides an efficient, holistic, and streamlined framework for DC thermal management architecture assessment and enables design optimization which is important for addressing the thermal-fluidic energy challenges of current and next-generation DCs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI