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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Asynchronous data change notification between database server and accelerator controls system

Database data change notification (DCN) is a commonly used feature. Not all database management systems (DBMS) provide an explicit DCN mechanism. Even for those DBMS's which support DCN (such as Oracle and MS SQL server), some server side and/or client side programming may be required to make the DCN system work. This makes the setup of DCN between database server and interested clients tedious and time consuming. In accelerator control systems, there are many well established software client/server architectures (such as CDEV, EPICS, and ADO) that can be used to implement data reflection servers that transfer data asynchronously to any client using the standard SET/GET API. This paper describes a method for using such a data reflection server to set up asynchronous DCN (ADCN) between a DBMS and clients. This method works well for all DBMS systems which provide database trigger functionality. Asynchronous data change notification (ADCN) between database server and clients can be realized by combining the use of a database trigger mechanism, which is supported by major DBMS systems, with server processes that use client/server software architectures that are familiar in the accelerator controls community (such as EPICS, CDEV or ADO). This approach makes the ADCN system easy to set up and integrate into an accelerator controls system. Several ADCN systems have been set up and used in the RHIC-AGS controls system.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Conceptual Architecture of Building Energy Management Open Source Software (BEMOSS)

The objective of this paper is to present a conceptual architecture of a Building Energy Management Open Source Software (BEMOSS) platform. The proposed BEMOSS platform is expected to improve sensing and control of equipment in small- and medium-sized buildings, reduce energy consumption and help implement demand response (DR). It aims to offer: scalability, robustness, plug and play, open protocol, interoperability, cost-effectiveness, as well as local and remote monitoring. In this paper, four essential layers of BEMOSS software architecture -- namely User Interface, Application and Data Management, Operating System and Framework, and Connectivity layers -- are presented. A laboratory test bed to demonstrate the functionality of BEMOSS located at the Advanced Research Institute of Virginia Tech is also briefly described.

agents↗
NASA NTRS1992

RT-Syn: A real-time software system generator

This paper presents research into providing highly reusable and maintainable components by using automatic software synthesis techniques. This proposal uses domain knowledge combined with automatic software synthesis techniques to engineer large-scale mission-critical real-time software. The hypothesis centers on a software synthesis architecture that specifically incorporates application-specific (in this case real-time) knowledge. This architecture synthesizes complex system software to meet a behavioral specification and external interaction design constraints. Some examples of these external constraints are communication protocols, precisions, timing, and space limitations. The incorporation of application-specific knowledge facilitates the generation of mathematical software metrics which are used to narrow the design space, thereby making software synthesis tractable. Success has the potential to dramatically reduce mission-critical system life-cycle costs not only by reducing development time, but more importantly facilitating maintenance, modifications, and extensions of complex mission-critical software systems, which are currently dominating life cycle costs.

Setliff, Dorothy E.↗
NASA NTRS1992

Software Management Environment (SME) concepts and architecture, revision 1

This document presents the concepts and architecture of the Software Management Environment (SME), developed for the Software Engineering Branch of the Flight Dynamic Division (FDD) of GSFC. The SME provides an integrated set of experience-based management tools that can assist software development managers in managing and planning flight dynamics software development projects. This document provides a high-level description of the types of information required to implement such an automated management tool.

Hendrick, Robert↗
NASA NTRS2009

Complex Event Recognition Architecture

Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.

Fitzgerald, William A.↗
NASA NTRS2025

OnAIR: Applications of The NASA On-Board Artificial Intelligence Research Platform

Infusing artificial intelligence algorithms into production aerospace systems can be challenging due to costs, timelines, and a risk averse industry. We introduce the Onboard Artificial Intelligence Research (OnAIR) platform, an open source software pipeline and cognitive architecture tool which enables full life cycle AI research for on-board intelligent systems. We begin a description and user walk-through of the OnAIR tool. Next we describe four use cases of OnAIR for both research and deployed onboard applications, detailing their use of OnAIR and the benefits it provided to development and function of each respective scenario. We conclude with remarks on future work, future planned deployments and goals for forward progression of OnAIR as a tool to enable larger AI and aerospace research community.

Cognitive Architecture↗
NASA NTRS2008

Open Architecture Standard for NASA's Software-Defined Space Telecommunications Radio Systems

NASA is developing an architecture standard for software-defined radios used in space- and ground-based platforms to enable commonality among radio developments to enhance capability and services while reducing mission and programmatic risk. Transceivers (or transponders) with functionality primarily defined in software (e.g., firmware) have the ability to change their functional behavior through software alone. This radio architecture standard offers value by employing common waveform software interfaces, method of instantiation, operation, and testing among different compliant hardware and software products. These common interfaces within the architecture abstract application software from the underlying hardware to enable technology insertion independently at either the software or hardware layer. This paper presents the initial Space Telecommunications Radio System (STRS) Architecture for NASA missions to provide the desired software abstraction and flexibility while minimizing the resources necessary to support the architecture.

Reinhart, Richard C.↗
NASA NTRS1989

Study of a unified hardware and software fault-tolerant architecture

A unified architectural concept, called the Fault Tolerant Processor Attached Processor (FTP-AP), that can tolerate hardware as well as software faults is proposed for applications requiring ultrareliable computation capability. An emulation of the FTP-AP architecture, consisting of a breadboard Motorola 68010-based quadruply redundant Fault Tolerant Processor, four VAX 750s as attached processors, and four versions of a transport aircraft yaw damper control law, is used as a testbed in the AIRLAB to examine a number of critical issues. Solutions of several basic problems associated with N-Version software are proposed and implemented on the testbed. This includes a confidence voter to resolve coincident errors in N-Version software. A reliability model of N-Version software that is based upon the recent understanding of software failure mechanisms is also developed. The basic FTP-AP architectural concept appears suitable for hosting N-Version application software while at the same time tolerating hardware failures. Architectural enhancements for greater efficiency, software reliability modeling, and N-Version issues that merit further research are identified.

Lala, Jaynarayan↗
NASA NTRS1992

Software design by reusing architectures

Abstraction fosters reuse by providing a class of artifacts that can be instantiated or customized to produce a set of artifacts meeting different specific requirements. It is proposed that significant leverage can be obtained by abstracting software system designs and the design process. The result of such an abstraction is a generic architecture and a set of knowledge-based, customization tools that can be used to instantiate the generic architecture. An approach for designing software systems based on the above idea are described. The approach is illustrated through an implemented example, and the advantages and limitations of the approach are discussed.

Bhansali, Sanjay↗
DOE OSTI2020

Using Neural Architecture Search for Improving Software Flaw Detection in Multimodal Deep Learning Models

Software flaw detection using multimodal deep learning models has been demonstrated as a very competitive approach on benchmark problems. In this work, we demonstrate that even better performance can be achieved using neural architecture search (NAS) combined with multimodal learning models. We adapt a NAS framework aimed at investigating image classification to the problem of software flaw detection and demonstrate improved results on the Juliet Test Suite, a popular benchmarking data set for measuring performance of machine learning models in this problem domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Track reconstruction as a service for collider physics

Optimizing charged-particle track reconstruction algorithms is crucial for efficient event reconstruction in Large Hadron Collider (LHC) experiments due to their significant computational demands. Existing track reconstruction algorithms have been adapted to run on massively parallel coprocessors, such as graphics processing units (GPUs), to reduce processing time. Nevertheless, challenges remain in fully harnessing the computational capacity of coprocessors in a scalable and non-disruptive manner. This paper proposes an inference-as-a-service approach for particle tracking in high energy physics experiments. To evaluate the efficacy of this approach, two distinct tracking algorithms are tested: Patatrack, a rule-based algorithm, and Exa.TrkX, a machine learning-based algorithm. The as-a-service implementations show enhanced GPU utilization and can process requests from multiple CPU cores concurrently without increasing per-request latency. The impact of data transfer is minimal and insignificant compared to running on local coprocessors. This approach greatly improves the computational efficiency of charged particle tracking, providing a solution to the computing challenges anticipated in the High-Luminosity LHC era.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic materials

The Abisko project aims to develop an energy-efficient spiking neural network (SNN) computing architecture and software system capable of autonomous learning and operation. The SNN architecture explores novel neuromorphic devices that are based on resistive-switching materials, such as memristors and electrochemical RAM. Equally important, Abisko uses a deep codesign approach to pursue this goal by engaging experts from across the entire range of disciplines: materials, devices and circuits, architectures and integration, software, and algorithms. Here, the key objectives of our Abisko project are threefold. First, we are designing an energy-optimized high-performance neuromorphic accelerator based on SNNs. This architecture is being designed as a chiplet that can be deployed in contemporary computer architectures and we are investigating novel neuromorphic materials to improve its design. Second, we are concurrently developing a productive software stack for the neuromorphic accelerator that will also be portable to other architectures, such as field-programmable gate arrays and GPUs. Third, we are creating a new deep codesign methodology and framework for developing clear interfaces, requirements, and metrics between each level of abstraction to enable the system design to be explored and implemented interchangeably with execution, measurement, a model, or simulation. As a motivating application for this codesign effort, we target the use of SNNs for an analog event detector for a high-energy physics sensor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

SDN-NGenIA, a Software Defined Next Generation Integrated Architecture for HEP and Data Intensive Science

This project aims to enable the LHC and other leading programs in high energy physics and other global science domains funded by the DOE to operate with a new level of efficiency and control, through the development of a Next Generation Integrated Architecture (NGenIA) based on intelligent software defined network (SDN)-driven network systems coupled to high throughput applications. While the initial focus is on the challenging LHC use case, the systems and products being developed are general, and apply to many fields of data intensive science ranging from astrophysical sky surveys to bioinformatics and earth observation, as well as other organizations facing the challenges of extracting knowledge from distributed multi-petabyte data stores. A central concept in this development program is a new paradigm ‘consistent network operations’ among widely distributed computing and storage facilities, where stable high throughput flows, at set rates, cross load-balanced network paths, up to flexible high water marks that are adjusted in real time to accommodate other network traffic. The large smooth flows are launched and managed by SDN services that act in concert with the experiments’ site-resident data distribution and management systems, to meet the expanding needs of the science programs. The technical goals include the construction of autonomous, intelligent site-resident services that interact dynamically with network-resident services, and with the science programs’ principal data distribution and management tools, to request or command network resources in support of high throughput petascale to exascale workflow Specific work items include: 1. Developing compact Data Transfer Nodes (DTNs) with auto-tuning functions that support data transfer rates in the 100 Gbps to the 1 Tbps range when used with high throughput data transfer applications 2. Deep site orchestration among virtualized clusters, storage subsystems and subnets to successfully coschedule CPU, storage and network resources 3. Science-program designed site architectures, operational modes, and policy and resource usage priorities, adjudicated across multiple network domains and virtual organizations, using the orchestration functions and methods 4. Seamlessly extending end-to-end operation across both extra-site and intra-site boundaries through the use of Open vSwitch (OVS), FireQoS + next generation Science DMZs 5. Novel methods of system integration that enable granular control of extreme scale long distance transfers through flow matching of scattered source-destination address pairs to multi-domain dynamic circuits 6. Funneling massive sets of streams to DTNs at the site edge hosting petascale buffer pools configured for flows of 100 Gbps and up, exploiting state of the art data transfers 7. Adaptive scheduling based on pervasive end-to-end monitoring, including DTN or compute-node resident agents providing comprehensive end-system profiling 8. Developing unsupervised and supervised machine learning and modeling methods to optimize the workflow involving terabyte to multi-petabyte datasets.

47 OTHER INSTRUMENTATION↗
NASA NTRS2008

Hardware Architecture Study for NASA's Space Software Defined Radios

This study defines a hardware architecture approach for software defined radios to enable commonality among NASA space missions. The architecture accommodates a range of reconfigurable processing technologies including general purpose processors, digital signal processors, field programmable gate arrays (FPGAs), and application-specific integrated circuits (ASICs) in addition to flexible and tunable radio frequency (RF) front-ends to satisfy varying mission requirements. The hardware architecture consists of modules, radio functions, and and interfaces. The modules are a logical division of common radio functions that comprise a typical communication radio. This paper describes the architecture details, module definitions, and the typical functions on each module as well as the module interfaces. Trade-offs between component-based, custom architecture and a functional-based, open architecture are described. The architecture does not specify the internal physical implementation within each module, nor does the architecture mandate the standards or ratings of the hardware used to construct the radios.

Reinhart, Richard C.↗
NASA NTRS2012

Space Telecommunications Radio System (STRS) Architecture Standard. Release 1.02.1

This document contains the NASA architecture standard for software defined radios used in space- and ground-based platforms to enable commonality among radio developments to enhance capability and services while reducing mission and programmatic risk. Transceivers (or transponders) with functionality primarily defined in software (e.g., firmware) have the ability to change their functional behavior through software alone. This radio architecture standard offers value by employing common waveform software interfaces, method of instantiation, operation, and testing among different compliant hardware and software products. These common interfaces within the architecture abstract application software from the underlying hardware to enable technology insertion independently at either the software or hardware layer.

Reinhart, Richard C.↗
NASA NTRS2018

IV&V Planning & Execution Initiative

Independent verification and validation (IV&V) is a systems engineering discipline which seeks to provide confidence that mission-critical software-dependent systems will operate safely and achieve all mission objectives. In order to optimize application of IV&V resources, it is necessary to identify specific assurance objectives that are most likely to reveal difficulty and therefore to increase confidence. Software assurance literature deals predominantly with the code itself. However, our experience is that the most significant software-related issues are discovered via analysis of other system artifacts such as operations concepts, requirements and design. Consequently, it is desirable to, when assessing risk and defining assurance objectives, consider all facets of the software system architecture. We describe in this presentation progress and lessons learned from an IV&V capability development initiative to enhance the IV&V project planning process using all available architecture information.

Risk↗
DOE OSTI2020

Using Neural Architecture Search for Improving Software Flaw Detection in Multimodal Deep Learning Models

Software flaw detection using multimodal deep learning models has been demonstrated as a very competitive approach on benchmark problems. In this work, we demonstrate that even better performance can be achieved using neural architecture search (NAS) combined with multimodal learning models. We adapt a NAS framework aimed at investigating image classification to the problem of software flaw detection and demonstrate improved results on the Juliet Test Suite, a popular benchmarking data set for measuring performance of machine learning models in this problem domain.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2018

A Concept for Civil Space Traffic Management

As technology has improved, operators have sought to use cubesats, as well as smallsats more generally, to perform increasingly more ambitious and sophisticated functions. Despite this, practical concerns associated with cubesat infant mortality, conjunctions, limited maneuverability, and debris generation have been relatively muted because most cubesats have been launched to lower orbits that limit both their orbital lifetime and consequences should a collision occur. NASA ARC has developed a concept for a highly-automated and distributed space traffic management (STM) architecture, drawing on similar work done to provide traffic management for small unmanned aerial systems (UAS) operating at low altitudes. The system proposes a strategy to accommodate growing space traffic volume safely, as well as pave the way for a transition of civil STM authority to a civilian governmental entity. The architecture envisions an open-access software platform architecture of data and service suppliers, consumers, and regulators, connected via a set of application programming interfaces (APIs). The platform would build on, rather than replicate existing integration and coordination efforts within the space situational awareness ecosystem, using existing standards for data message formats from organizations like the Consultative Committee for Space Data Systems and wrapping, rather than replacing existing integrations. We will present an initial STM architecture in this presentation, with a few examples showing how stakeholders can interact structurally, but flexibly, within this architecture.

Space Situational Awareness↗