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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 613 records · Page 34

Case Study of the Space Shuttle Cockpit Avionics Upgrade Software

The purpose of the Space Shuttle Cockpit Avionics Upgrade project was to reduce crew workload and improve situational awareness. The upgrade was to augment the Shuttle avionics system with new hardware and software. An early version of this system was used to gather human factor statistics in the Space Shuttle Motion Simulator of the Johnson Space Center for one month by multiple teams of astronauts. The results were compiled by NASA Ames Research Center and it was was determined that the system provided a better than expected increase in situational awareness and reduction in crew workload. Even with all of the benefits nf the system, NASA cancelled the project towards the end of the development cycle. A major success of this project was the validation of the hardware architecture and software design. This was significant because the project incorporated new technology and approaches for the development of human rated space software. This paper serves as a case study to document knowledge gained and techniques that can be applied for future space avionics development efforts. The major technological advances were the use of reflective memory concepts for data acquisition and the incorporation of Commercial off the Shelf (COTS) products in a human rated space avionics system. The infused COTS products included a real time operating system, a resident linker and loader, a display generation tool set, and a network data manager. Some of the successful design concepts were the engineering of identical outputs in multiple avionics boxes using an event driven approach and inter-computer communication, a reconfigurable data acquisition engine, the use of a dynamic bus bandwidth allocation algorithm. Other significant experiences captured were the use of prototyping to reduce risk, and the correct balance between Object Oriented and Functional based programming.

Ferguson, Roscoe C.↗

Verification and Validation of Hybridspectral Radiometry Obtained from an Unmanned Surface Vessel (USV) in the Open and Coastal Oceans

The hardware and software capabilities of the compact-profiling hybrid instrumentation for radiometry and ecology (C-PHIRE) instruments on an unmanned surface vessel (USV) are evaluated. Both the radiometers and USV are commercial-off-the-shelf (COTS) products, with the latter being only minimally modified to deploy the C-PHIRE instruments. The hybridspectral C-PHIRE instruments consist of an array of 18 multispectral microradiometers with 10 nm wavebands spanning 320–875 nm plus a hyperspectral compact grating spectrometer (CGS) with 2048 pixels spanning 190–1000 nm. The C-PHIRE data were acquired and processed using two architecturally linked software packages, thereby allowing lessons learned in one to be applied to the other. Using standard data products and unbiased statistics, the C-PHIRE data were validated with those from the well-established compact-optical profiling system (C-OPS) and verified with the marine optical buoy (MOBY). Agreement between algorithm variables used to estimate colored dissolved organic matter (CDOM) absorption and chlorophyll a concentration were also validated. Developing and operating novel technologies, such as the C-PHIRE series of instruments, deployed on a USV increase the frequency and coverage of optical observations, which are required to fully support the present and next-generation validation exercises in radiometric remote sensing of aquatic ecosystems.

Hybridspectral↗

Architectural Implementation of NASA Space Telecommunications Radio System Specification

This software demonstrates a working implementation of the NASA STRS (Space Telecommunications Radio System) architecture specification. This is a developing specification of software architecture and required interfaces to provide commonality among future NASA and commercial software-defined radios for space, and allow for easier mixing of software and hardware from different vendors. It provides required functions, and supports interaction with STRS-compliant simple test plug-ins ("waveforms"). All of it is programmed in "plain C," except where necessary to interact with C++ plug-ins. It offers a small footprint, suitable for use in JPL radio hardware. Future NASA work is expected to develop into fully capable software-defined radios for use on the space station, other space vehicles, and interplanetary probes.

Peters, Kenneth J.↗

The Application of Coordination to Magnetic Measurement Automation: An SSW System Example

Magnetic measurements are an integral part of the development cycle of accelerator magnets, a part which provides necessary feedback to drive design and manufacturing improvements and corrections. Automation of these measurements allows for reduction of human errors and reproducibility of measurements. Realization of automation via coordination that is separated at the architectural level from the functional code provides flexibility in defining measurement procedures and substantial extensibility. The described Single Stretched Wire (SSW) system herein is an implementation of such a solution with the use of a component-based framework designed to build a family of measurement systems.

43 PARTICLE ACCELERATORS↗

Applying Service-Oriented Architecture to Archiving Data in Control and Monitoring Systems

Current trends in the architecture of software systems focus our attention on building systems using a set of loosely coupled components, each providing a specific functionality known as service. It is not much different in control and monitoring systems, where a functionally distinct sub-system can be identified and independently designed, implemented, deployed and maintained. One functionality that renders itself perfectly to becoming a service is archiving the history of the system state. The design of such a service and our experience of using it are the topic of this article. The service is built with responsibility segregation in mind, therefore, it provides for reducing data processing on the data viewer side and separation of data access and modification operations. The service architecture and the details concerning its data store design are discussed. An implementation of a service client capable of archiving EPICS process variables (PV) and LabVIEW shared variables is presented. Data access tools, including a browser-based data viewer and a mobile viewer, are also presented.

Nogiec, J. M.↗

FAIR AI models in high energy physics

Abstract The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, and improving how data is shared to facilitate scientific discovery. Generalizing these principles to research software and other digital products is an active area of research. Machine learning models—algorithms that have been trained on data without being explicitly programmed—and more generally, artificial intelligence (AI) models, are an important target for this because of the ever-increasing pace with which AI is transforming scientific domains, such as experimental high energy physics (HEP). In this paper, we propose a practical definition of FAIR principles for AI models in HEP and describe a template for the application of these principles. We demonstrate the template’s use with an example AI model applied to HEP, in which a graph neural network is used to identify Higgs bosons decaying to two bottom quarks. We report on the robustness of this FAIR AI model, its portability across hardware architectures and software frameworks, and its interpretability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Discovery and Synchronization Service Architectural Notes

This is a short architectural note for a critical component of safely scaling drone operations. The primary motivation for this note is to collect language and terminology around the Discovery and Synchronization Service (DSS) as it is currently implemented for Uncrewed Aircraft System (UAS) Traffic Management. The major driver for this document was frequent miscommunication about DSS. Often there have been multiple informed and invested stakeholders in the same room making statements about “multiple DSSs” and each of them meaning something slightly different.

uas traffic management↗

Exploring performance and energy tradeoffs for irregular applications: A case study on the Tilera many-core architecture

High performance, parallel applications with irregular data accesses are becoming a critical workload class for modern systems. In particular, the execution of such workloads on emerging many-core systems is expected to be a significant component of applications in data mining, machine learning, scientific computing and graph analytics. However, power and energy constraints limit the capabilities of individual cores, memory hierarchy and on-chip interconnect of such systems, thus leading to architectural and software trade-os that must be understood in the context of the intended application’s behavior. Irregular applications are notoriously hard to optimize given their data-dependent access patterns, lack of structured locality and complex data structures and code patterns. We have ported two irregular applications, graph community detection using the Louvain method (Grappolo) and high-performance conjugate gradient (HPCCG), to the Tilera many-core system and have conducted a detailed study of platform-independent and platform-specific optimizations that improve their performance as well as reduce their overall energy consumption. To conduct this study, we employ an auto-tuning based approach that explores the optimization design space along three dimensions - memory layout schemes, GCC compiler flag choices and OpenMP loop scheduling options. We leverage MIT’s OpenTuner auto-tuning framework to explore and recommend energy optimal choices for different combinations of parameters. We then conduct an in-depth architectural characterization to understand the memory behavior of the selected workloads. Finally, we perform a correlation study to demonstrate the interplay between the hardware behavior and application characteristics. Using auto-tuning, we demonstrate whole-node energy savings and performance improvements of up to 49:6% and 60% relative to a baseline instantiation, and up to 31% and 45:4% relative to manually optimized variants.

auto tuning↗

High speed packet switching

This document constitutes the final report prepared by Proteon, Inc. of Westborough, Massachusetts under contract NAS 5-30629 entitled High-Speed Packet Switching (SBIR 87-1, Phase 2) prepared for NASA-Greenbelt, Maryland. The primary goal of this research project is to use the results of the SBIR Phase 1 effort to develop a sound, expandable hardware and software router architecture capable of forwarding 25,000 packets per second through the router and passing 300 megabits per second on the router's internal busses. The work being delivered under this contract received its funding from three different sources: the SNIPE/RIG contract (Contract Number F30602-89-C-0014, CDRL Sequence Number A002), the SBIR contract, and Proteon. The SNIPE/RIG and SBIR contracts had many overlapping requirements, which allowed the research done under SNIPE/RIG to be applied to SBIR. Proteon funded all of the work to develop new router interfaces other than FDDI, in addition to funding the productization of the router itself. The router being delivered under SBIR will be a fully product-quality machine. The work done during this contract produced many significant findings and results, summarized here and explained in detail in later sections of this report. The SNIPE/RIG contract was completed. That contract had many overlapping requirements with the SBIR contract, and resulted in the successful demonstration and delivery of a high speed router. The development that took place during the SNIPE/RIG contract produced findings that included the choice of processor and an understanding of the issues surrounding inter processor communications in a multiprocessor environment. Many significant speed enhancements to the router software were made during that time. Under the SBIR contract (and with help from Proteon-funded work), it was found that a single processor router achieved a throughput significantly higher than originally anticipated. For this reason, a single processor router was developed and the final delivery under this contract will include a single processor CNX-500 router. The router and its interface boards (2 FDDIs and 2 dual-ethernets) are all product-quality components.

Source record↗

Blockchain-Based Smart Contracts Use for Photovoltaic Energy Trade Transactions

In recent decades, interest in renewable energy via solar energy has increased, especially in California and Nevada. In a region that can produce enough solar power for self-use, prosumers must use or sell surplus energy. Solar energy self-consumption is essential in modern energy transactions in the grid. This paper proposes an approach towards grid services that includes photovoltaic hardware to store the excess energy in battery storage. Such energy can then be sold to power companies while the transaction is handled using blockchain. Software, security architecture and data flow requirements based on the Ethereum Blockchain are included. Furthermore, this solution protects the private information of seller and buyer and secures transactions.

14 SOLAR ENERGY↗

Data Center Facility Monitoring with Physics Aware Approach

U.S. Department of Energy's National Renewable Energy Laboratory (NREL) hosts one of the world's most energy-efficient HPC data centers; this system uses component-level warm-water liquid cooling to efficiently remove heat from the data center and capture it for reuse in the building or rejection to the atmosphere. Given the complexity of this system, building data-driven tools for holistically monitoring and operating the entire data center is a priority for ensuring maximal efficiency and resiliency. In this advanced smart facility, over one million metrics are recorded per minute using state-of-the-art streaming data architecture and software to capture and process the state of the system in real time. Here we detail two efforts to effectively analyze, visualize, and interpret this large volume streaming data. We have developed a novel, flexible system for identifying and visualizing individual metric anomalies and component performance across the data center through automatic metadata extraction and physically-motivated visualization for quick interpretation. Additionally, to directly connect system maintenance to data stream processing we explore a physics informed multi-metric drift and anomaly detection application to detect scale-build up in heat exchangers.

anomaly detection↗

Geant4Reweight: a framework for evaluating and propagating hadronic interaction uncertainties in Geant4

Geant4Reweight is an open-source C++ framework that allows users to weight tracks produced by the Geant4 particle transport Monte Carlo simulation according to hadron interaction cross section variations and estimate uncertainties in Geant4 interaction models by comparing the simulation’s hadron interaction cross section predictions to data. The ability to weight hadron transport as simulated by Geant4 is crucial to the propagation of systematic uncertainties related to secondary hadronic interactions in current and upcoming neutrino oscillation experiments, including MicroBooNE, NOvA, and DUNE, aswell as hadron test beam experiments such as ProtoDUNE. Here, we provide motivation for weighting hadron tracks in Geant4 in the context of systematic uncertainty propagation, a description of Geant4’s transport simulation technique, and a description of our weighting technique and fitting framework in the momentum range 0–10 GeV/c, which is typical for the hadrons produced by neutrino interactions in these experiments.

97 MATHEMATICS AND COMPUTING↗

Modeling of advanced accelerator concepts

Computer modeling is essential to research on Advanced Accelerator Concepts (AAC), as well as to their design and operation. This paper summarizes the current status and future needs of AAC systems and reports on several key aspects of (i) high-performance computing (including performance, portability, scalability, advanced algorithms, scalable I/Os and In-Situ analysis), (ii) the benefits of ecosystems with integrated workflows based on standardized input and output and with integrated frameworks developed as a community, and (iii) sustainability and reliability (including code robustness and usability).

47 OTHER INSTRUMENTATION↗

AI for nuclear physics: the EXCLAIM project

An overview of the recent activity of the newly funded EXCLusives with AI and Machine learning (EXCLAIM) collaboration is presented. The main goal of the collaboration is to develop a framework to implement AI and machine learning techniques in problems emerging from the phenomenology of high energy exclusive scattering processes from nucleons and nuclei, maximizing the information that can be extracted from various sets of experimental data, while implementing theoretical constraints from lattice QCD. A specific perspective embraced by EXCLAIM is to use the methods of theoretical physics to understand the working of ML, beyond its standardized applications to physics analyses which most often rely on industrially provided tools, in an automated way.

Analysis and statistical methods↗

Automated Generation of Integrated Digital and Spiking Neuromorphic Machine Learning Accelerators

The growing numbers of application areas for artificial intelligence (AI) methods have led to an explosion of domain-specific accelerators that could support every new machine learning (ML) algorithm advancement, clearly highlighting the need for a capability to quickly and automatically transition from algorithm definition to hardware implementation and explore design space along a variety of SWaP (size, weight and Power). The software defined architectures (SODA) synthesizer implements a compiler-based modular infrastructure for the end-to-end generation of machine learning accelerators from high-level frameworks to hardware description language. At the same time, neuromorphic computing, by mimicking how the brain operates, promises to perform artificial intelligence tasks at efficiencies orders of magnitude higher than the current conventional tensor-processing based accelerators, as demonstrated by a variety of specialized designs leveraging Spiking Neural Networks (SNNs). Nevertheless, the mapping of an artificial neural network (ANN) to solutions supporting SNNs is still a non-trivial and very device-specific task, and completely lack the possibility to design hybrid systems that integrate conventional and spiking neural models. In this paper we discuss the support for such an integrated generation leveraging the SODA Synthesizer framework and its modular structure. In particular, we present a new MLIR dialect (part of the SODA frontend) that allows expressing spiking neural network features (e.g., available resources, spiking sequences, analog signal reading, etc.) and illustrate how it enables mapping to Spiking Neurons and deployment to the related specialized hardware (which, in the digital domain, could be generated through the other existing layers of the SODA Synthesizer). We then discuss the opportunities for even deeper integration afforded by the hardware compilation infrastructure, providing a path towards the generation of complex heterogeneous artificial intelligence systems.

Curzel, Serena↗

Cyber Dumpster Diving: Creating New Software Systems for Less

Modern scientific software is daunting in its breadth and complexity. From massively parallel simulations running on the world’s largest supercomputers to visualizations and user support environments that manage ever-growing, complex data collections, the challenges for software engineers are plentiful indeed.

software architecture↗