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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Gaia: segmented germanium detector for high-energy X-ray fluorescence and spectroscopic imaging

We present Gaia, a monolithic array of 96 high-purity germanium pixel detectors integrated with a custom low-noise application-specific integrated circuit (ASIC) and a field-programmable gate array (FPGA)-based data acquisition system. The sensor operates at ∼100 K using a commercial closed-cycle cryocooler, with the in-vacuum electronics thermally isolated from the cold finger to ensure thermal stability. The system demonstrates an average energy resolution of 711 eV at 122 keV, measured using a 57 Co source, and 253 eV at 5.89 keV, measured with 55 Fe across all channels. The readout architecture incorporates a high-performance FPGA paired with a dual-core ARM processor, forming a complete embedded Linux-based computing platform. Communication between the processor and FPGA is handled via memory-mapped I/O, and data are streamed over high-speed gigabit Ethernet. A full-scale 384-pixel Gaia detector, based on this 96-element module, is currently under fabrication.

36 MATERIALS SCIENCE↗
DOE OSTI2013

High speed, multi-channel, user programmable digital data acquisition system.

As applications for radiation detection become more demanding, and in turn improvements are made in the technology of radiation detection, there is a need for high speed digital detector readout electronics matching these improvements. Specifically, full control over the on-line processing resources of modern digital electronics is desirable so that researchers can develop custom algorithms for special applications.In the proposed effort, the 500 MHz digital readout electronics previously developed by our company will be redesigned to allow user access to the on-line processing resources. In Phase I, the division of online processing into vendor and user firmware sections has been studied on existing hardware. In Phase II, the hardware will be upgraded to better facilitate the division, and the firmware will be restructured into a robust vendor logic block (providing standard functions such as host I/O, on-board memory I/O, energy computation, MCA spectra, timestamps, waveform capture, run statistics, and triggering and timing) and a user logic block for custom algorithms (with templates and examples for frequently used functions). Investigating several options to divide online processing, it was determined that the most promising approach is to “partition” a single FPGA integrated circuit into a vendor and user section, which is supported in newer devices. The analog front end of the existing electronics proved suitable for most applications, in particular high rate measurements with germanium detectors. The design architecture for new electronics was developed, combining one of the new FPGA device with the analog front end.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

WE-AB-303-09: Rapid Projection Computations for On-Board Digital Tomosynthesis in Radiation Therapy

Purpose: To facilitate fast and accurate iterative volumetric image reconstruction from limited-angle on-board projections. Methods: Intrafraction motion hinders the clinical applicability of modern radiotherapy techniques, such as lung stereotactic body radiation therapy (SBRT). The LIVE system may impact clinical practice by recovering volumetric information via Digital Tomosynthesis (DTS), thus entailing low time and radiation dose for image acquisition during treatment. The DTS is estimated as a deformation of prior CT via iterative registration with on-board images; this shifts the challenge to the computational domain, owing largely to repeated projection computations across iterations. We address this issue by composing efficient digital projection operators from their constituent parts. This allows us to separate the static (projection geometry) and dynamic (volume/image data) parts of projection operations by means of pre-computations, enabling fast on-board processing, while also relaxing constraints on underlying numerical models (e.g. regridding interpolation kernels). Further decoupling the projectors into simpler ones ensures the incurred memory overhead remains low, within the capacity of a single GPU. These operators depend only on the treatment plan and may be reused across iterations and patients. The dynamic processing load is kept to a minimum and maps well to the GPU computational model. Results: We have integrated efficient, pre-computable modules for volumetric ray-casting and FDK-based back-projection with the LIVE processing pipeline. Our results show a 60x acceleration of the DTS computations, compared to the previous version, using a single GPU; presently, reconstruction is attained within a couple of minutes. The present implementation allows for significant flexibility in terms of the numerical and operational projection model; we are investigating the benefit of further optimizations and accurate digital projection sub-kernels. Conclusion: Composable projection operators constitute a versatile research tool which can greatly accelerate iterative registration algorithms and may be conducive to the clinical applicability of LIVE. National Institutes of Health Grant No. R01-CA184173; GPU donation by NVIDIA Corporation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Connect the Dots: In Situ 4-D Seismic Monitoring of CO 2 Storage With Spatio-Temporal CNNs

4-D seismic imaging has been widely used in CO 2 sequestration projects to monitor the fluid flow in the volumetric subsurface region that is not sampled by wells. Ideally, real-time monitoring and near-future forecasting would provide site operators with great insights to understand the dynamics of the subsurface reservoir and assess any potential risks. However, due to obstacles such as high deployment cost, availability of acquisition equipment, exclusion zones around surface structures, only very sparse seismic imaging data can be obtained during monitoring. That leads to an unavoidable and growing knowledge gap over time. The operator needs to understand the fluid flow throughout the project lifetime and the seismic data are only available at a limited number of times. This is insufficient for understanding reservoir behavior. To overcome those challenges, we have developed spatio-temporal neural-network-based models that can produce high-fidelity interpolated or extrapolated images effectively and efficiently. Specifically, our models are built on an autoencoder, and incorporate the long short-term memory (LSTM) structure with a new loss function regularized by optical flow. We validate the performance of our models using real 4-D post-stack seismic imaging data acquired at the Sleipner CO 2 sequestration field. We employ two different strategies in evaluating our models. Numerically, we compare our models with different baseline approaches using classic pixel-based metrics. We also conduct a blind survey and collect a total of 20 responses from domain experts to evaluate the quality of data generated by our models. Finally, via both numerical and expert evaluation, we conclude that our models can produce high-quality 2-D/3-D seismic imaging data at a reasonable cost, offering the possibility of real-time monitoring or even near-future forecasting of the CO 2 storage reservoir.

4-D seismic imaging↗
DOE OSTI2017

On the Origin of Reverse Transcriptase-Using CRISPR-Cas Systems and Their Hyperdiverse, Enigmatic Spacer Repertoires

Cas1 integrase is the key enzyme of the clustered regularly interspaced short palindromic repeat (CRISPR)-Cas adaptation module that mediates acquisition of spacers derived from foreign DNA by CRISPR arrays. In diverse bacteria, the cas1 gene is fused (or adjacent) to a gene encoding a reverse transcriptase (RT) related to group II intron RTs. An RT-Cas1 fusion protein has been recently shown to enable acquisition of CRISPR spacers from RNA. Phylogenetic analysis of the CRISPR-associated RTs demonstrates monophyly of the RT-Cas1 fusion, and coevolution of the RT and Cas1 domains. Nearly all such RTs are present within type III CRISPR-Cas loci, but their phylogeny does not parallel the CRISPR-Cas type classification, indicating that RT-Cas1 is an autonomous functional module that is disseminated by horizontal gene transfer and can function with diverse type III systems. To compare the sequence pools sampled by RT-Cas1-associated and RT-lacking CRISPR-Cas systems, we obtained samples of a commercially grown cyanobacterium— Arthrospira platensis . Sequencing of the CRISPR arrays uncovered a highly diverse population of spacers. Spacer diversity was particularly striking for the RT-Cas1-containing type III-B system, where no saturation was evident even with millions of sequences analyzed. In contrast, analysis of the RT-lacking type III-D system yielded a highly diverse pool but reached a point where fewer novel spacers were recovered as sequencing depth was increased. Matches could be identified for a small fraction of the non-RT-Cas1-associated spacers, and for only a single RT-Cas1-associated spacer. Thus, the principal source(s) of the spacers, particularly the hypervariable spacer repertoire of the RT-associated arrays, remains unknown. IMPORTANCE While the majority of CRISPR-Cas immune systems adapt to foreign genetic elements by capturing segments of invasive DNA, some systems carry reverse transcriptases (RTs) that enable adaptation to RNA molecules. From analysis of available bacterial sequence data, we find evidence that RT-based RNA adaptation machinery has been able to join with CRISPR-Cas immune systems in many, diverse bacterial species. To investigate whether the abilities to adapt to DNA and RNA molecules are utilized for defense against distinct classes of invaders in nature, we sequenced CRISPR arrays from samples of commercial-scale open-air cultures of Arthrospira platensis , a cyanobacterium that contains both RT-lacking and RT-containing CRISPR-Cas systems. We uncovered a diverse pool of naturally occurring immune memories, with the RT-lacking locus acquiring a number of segments matching known viral or bacterial genes, while the RT-containing locus has acquired spacers from a distinct sequence pool for which the source remains enigmatic. While the majority of CRISPR-Cas immune systems adapt to foreign genetic elements by capturing segments of invasive DNA, some systems carry reverse transcriptases (RTs) that enable adaptation to RNA molecules. From analysis of available bacterial sequence data, we find evidence that RT-based RNA adaptation machinery has been able to join with CRISPR-Cas immune systems in many, diverse bacterial species. To investigate whether the abilities to adapt to DNA and RNA molecules are utilized for defense against distinct classes of invaders in nature, we sequenced CRISPR arrays from samples of commercial-scale open-air cultures of Arthrospira platensis , a cyanobacterium that contains both RT-lacking and RT-containing CRISPR-Cas systems. We uncovered a diverse pool of naturally occurring immune memories, with the RT-lacking locus acquiring a number of segments matching known viral or bacterial genes, while the RT-containing locus has acquired spacers from a distinct sequence pool for which the source remains enigmatic.

horizontal gene transfer↗
DOE OSTI2025

Distributed Cross-Channel Hierarchical Aggregation for Foundation Models

Vision-based scientific foundation models hold significant promise for advancing scientific discovery and innovation. This potential stems from their ability to aggregate images from diverse sources—such as varying physical groundings or data acquisition systems—and to learn spatio-temporal correlations using transformer architectures. However, tokenizing and aggregating images can be compute-intensive, a challenge not fully addressed by current distributed methods. In this work, we introduce the Distributed Cross-Channel Hierarchical Aggregation (D-CHAG) approach designed for datasets with a large number of channels across image modalities. Our method is compatible with any model-parallel strategy and any type of vision transformer architecture, significantly improving computational efficiency. We evaluated D-CHAG on hyperspectral imaging and weather forecasting tasks. When integrated with tensor parallelism and model sharding, our approach achieved up to a 75% reduction in memory usage and more than doubled sustained throughput on up to 1,024 AMD GPUs on the Frontier Supercomputer.

Tsaris, Aristeidis (aris) [ORNL] (ORCID:0000000277↗
DOE OSTI2016

Testing of the Authenticatable Container Tracking System (ACTS)

The Authenticatable Container Tracking System (ACTS) is being designed to provide a secure container tag that can be used to optimize chain-of-custody monitoring for packaged nuclear materials as they are being stored, processed, and transported. ACTS is an active device that uses an almost-universal core platform that can be appropriately configured to provide the necessary data acquisition, data logging, and communications functions needed for 21st century material accountancy, monitoring, and tracking applications. The core design supports active monitoring of containment, movement, and location and provides secure data transmission via selectable communication methods that can be used throughout the world. This core architecture enables appropriately designed modules to be easily interfaced to the basic system, thus providing an integration path for current and new technologies. ACTS contains a built-in set of sensors but also supports an expansion bus for up to six additional communications, tracking, or sensing modules that may enhance monitoring and tracking of particular containers for specific applications. ACTS stores events in memory, communicates activity to Argonne National Laboratory’s ARG-US TransPort tracking and information server, and provides options for data encryption and authentication. We are currently beginning a testing phase that will field five devices outdoors in a controlled environment to allow evaluation of the functionality of the systems and the hardness of the devices to outdoor conditions. Partners for this system are Oak Ridge National Laboratory, Argonne National Laboratory, Savannah River National Laboratory, Pacific Northwest National Laboratory, and commercialization partner The Aquila Group.

Britton Jr, Chuck↗
DOE OSTI2026

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRSDate not supplied

Delay Tolerant, Radio Frequency Identification (RFID )-enabled Sensing

Radio Frequency Identification (RFID) technology offers a completely passive method to transmit fixed data sequences from an RFID tag, which typically doesn’t have its own power supply, to an interrogator. Radio frequency (RF) energy harvested from the interrogator is rectified by the tag and used to charge an integrated circuit (IC). The IC then modulates the received signal with the data stored on the tag and reflects the energy back to the interrogator. RFID has seen great proliferation in terrestrial inventory management applications, and it has recently made the jump to spaceflight applications onboard the International Space Station, augmenting an existing optical bar‐code infrastructure for tracking supplies. A number of advanced automated logistics management (ALM) concepts employing RFID are currently being developed and evaluated, including so‐called “smart” shelves, cubbies, and trash receptacles using low‐power, embeddable RFID interrogators. An infrastructure where both crew members and robotic assistants, such as autonomous free flyers, are similarly equipped with small RFID interrogators seems likely. It therefore behooves us to consider extending this infrastructure beyond ALM to applications such as low power, embedded sensing. Typically, data on an RFID tag can only be written by an RFID interrogator, using interrogator energy. In recent years, however, a few efforts have focused on using that energy to drive data acquisition from the tag IC, allowing the tag to modify its stored data sequence with sensor data before replying to an interrogator. In this way, the tag can act as a completely passive sensing device. One problem exists with this approach, however: the tag cannot gather data when an interrogator is not present. Thus, strictly passive RFID sensing tags cannot gather data at regular intervals, in the manner of a typical wireless sensor network, without careful, and impractical, planning of mobile interrogator movements. To address this shortcoming, we look to a recent advance in RFID technology which allows an external microprocessor to power the tag IC and write directly into its RFID memory using a wired serial interface. In this paradigm, data gathering is driven by a small, on‐board power supply (using batteries or harvested energy), and data transfer is provided passively through the RFID interrogation service. Since communication typically consumes the lion’s share of power in WSNs, such a technique has the potential to enable extremely long‐lived, embedded wireless sensing when used with extremely low‐current microcontrollers. Since the communication channel is only open when an interrogator is present and actively interrogating the RFID sensing tag, transport of periodically‐sampled sensor data presents itself as a delay/disruption‐tolerant networking (DTN) problem. In this paper, we present the design of a DTN‐like overlay on the common EPC Global, Class 1, Generation 2 RFID standard. This overlay allows seamless, guaranteed data transfer using the EPC Global protocol, supporting extremely low‐power, embedded sensing using an infrastructure likely to be already in place for ALM applications. We evaluate a prototype implementation of a complete end‐to‐end system using a robotic RFID interrogation agent, and we present future directions for the development of this sensing technique.

Raymond S. Wagner↗
NASA NTRS2011

Onboard Radar Processing Development for Rapid Response Applications

We are developing onboard processor (OBP) technology to streamline data acquisition on-demand and explore the potential of the L-band SAR instrument onboard the proposed DESDynI mission and UAVSAR for rapid response applications. The technology would enable the observation and use of surface change data over rapidly evolving natural hazards, both as an aid to scientific understanding and to provide timely data to agencies responsible for the management and mitigation of natural disasters. We are adapting complex science algorithms for surface water extent to detect flooding, snow/water/ice classification to assist in transportation/ shipping forecasts, and repeat-pass change detection to detect disturbances. We are near completion of the development of a custom FPGA board to meet the specific memory and processing needs of L-band SAR processor algorithms and high speed interfaces to reformat and route raw radar data to/from the FPGA processor board. We have also developed a high fidelity Matlab model of the SAR processor that is modularized and parameterized for ease to prototype various SAR processor algorithms targeted for the FPGA. We will be testing the OBP and rapid response algorithms with UAVSAR data to determine the fidelity of the products.

dual polarized data↗
NASA NTRS1984

Photographic memory: The storage and retrieval of data

The concept of density encoding digital data in a mass-storage computer peripheral is proposed. This concept requires that digital data be encoded as distinguishable density levels (DDLS) of the film to be used as the storage medium. These DDL's are then recorded on the film in relatively large pixels. Retrieval of the data would be accomplished by scanning the photographic record using a relatively small aperture. Multiplexing of the pixels is used to store data of a range greater than the number of DDL's supportable by the film in question. Although a cartographic application is used as an example for the photographic storage of data, any digital data can be stored in a like manner. When the data is inherently spatially-distributed, the aptness of the proposed scheme is even more evident. In such a case, human-readability is an advantage which can be added to those mentioned earlier: speed of acquisition, ease of implementation, and cost effectiveness.

Horton, J.↗
DOE OSTI2022

Hardware-Based Randomized Encoding for Sensor Authentication in Power Grid SCADA Systems

Supervisory Control and Data Acquisition (SCADA) systems are utilized extensively in critical power grid infrastructures. Modern SCADA systems have been proven to be susceptible to cyber-security attacks and require improved security primitives in order to prevent unwanted influence from an adversarial party. One section of weakness in the SCADA system is the integrity of field level sensors providing essential data for control decisions at a master station. In this paper we propose a lightweight hardware scheme providing inferred authentication for SCADA sensors by combining an analog to digital converter and a permutation generator as a single integrated circuit. Through this method we encode critical sensor data at the time of sensing, so that unencoded data is never stored in memory, increasing the difficulty of software attacks. We show through experimentation how our design stops both software and hardware false data injection attacks occurring at the field level of SCADA systems.

42 ENGINEERING↗
NASA NTRS2012

Lunar Reconnaissance Orbiter (LRO) Command and Data Handling Flight Electronics Subsystem

A document describes a high-performance, modular, and state-of-the-art Command and Data Handling (C&DH) system developed for use on the Lunar Reconnaissance Orbiter (LRO) mission. This system implements a complete hardware C&DH subsystem in a single chassis enclosure that includes a processor card, 48 Gbytes of solid-state recorder memory, data buses including MIL-STD-1553B, custom RS-422, SpaceWire, analog collection, switched power services, and interfaces to the Ka-Band and S-Band RF communications systems. The C&DH team capitalized on extensive experience with hardware and software with PCI bus design, SpaceWire networking, Actel FPGA design, digital flight design techniques, and the use of VxWorks for the real-time operating system. The resulting hardware architecture was implemented to meet the LRO mission requirements. The C&DH comprises an enclosure, a backplane, a low-voltage power converter, a single-board computer, a communications interface board, four data storage boards, a housekeeping and digital input/output board, and an analog data acquisition board. The interfaces between the C&DH and the instruments and avionics are connected through a SpaceWire network, a MIL-STD-1553 bus, and a combination of synchronous and asynchronous serial data transfers over RS-422 and LVDS (low-voltage differential-signaling) electrical interfaces. The C&DH acts as the spacecraft data system with an instrument data manager providing all software and internal bus scheduling, ingestion of science data, distribution of commands, and performing science operations in real time.

Nguyen, Quang↗
DOE OSTI2020

CRADA Final Report: Open Microgrid Platform

Current microgrid control technology is mostly proprietary, expensive, and inflexible. An open-source, vendor-neutral, publish-subscribe controller will significantly lower the barrier to entry for new technologies and market entrants: inverter, battery, and load control manufacturers; cloud and services providers; and energy aggregators. An OpenFMB controller can significantly reduce the acquisition, integration, and ongoing operating and maintenance costs and increase revenue opportunities for energy producers and consumers. It allows distributed energy resource (DER) owners to replace individual DER components as richer-function, lower-cost devices become available or to incorporate new forecast and optimization algorithms as they are developed. A standard, secure, full-function DER field controller will also provide a low-cost means for grid operators to effectively manage the variability and uncertainty of solar photovoltaics (PV). Under the terms of this CRADA, ORNL has worked with Open Energy Solutions (OES) to advance the transition of ORNL’s existing open-source microgrid controller into a platform geared toward mainstream implementation. Using a more prevalent and memory-safe programming language, Rust, OES has converted ORNL’s current generation on-grid optimization into an application more suitable for industry use. The results of the ported optimization were analyzed by inputting the same arguments in both the current-generation and next-generation optimizers and verifying that the results were equivalent.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1994

Expert system technologies for Space Shuttle decision support: Two case studies

This paper addresses the issue of integrating the C Language Integrated Production System (CLIPS) into distributed data acquisition environments. In particular, it presents preliminary results of some ongoing software development projects aimed at exploiting CLIPS technology in the new mission control center (MCC) being built at NASA Johnson Space Center. One interesting aspect of the control center is its distributed architecture; it consists of networked workstations which acquire and share data through the NASA/JSC-developed information sharing protocol (ISP). This paper outlines some approaches taken to integrate CLIPS and ISP in order to permit the development of intelligent data analysis applications which can be used in the MCC. Three approaches to CLIPS/IPS integration are discussed. The initial approach involves clearly separating CLIPS from ISP using user-defined functions for gathering and sending data to and from a local storage buffer. Memory and performance drawbacks of this design are summarized. The second approach involves taking full advantage of CLIPS and the CLIPS Object-Oriented Language (COOL) by using objects to directly transmit data and state changes from ISP to COOL. Any changes within the object slots eliminate the need for both a data structure and external function call thus taking advantage of the object matching capabilities within CLIPS 6.0. The final approach is to treat CLIPS and ISP as peer toolkits. Neither is embedded in the other; rather the application interweaves calls to each directly in the application source code.

Ortiz, Christopher J.↗
NASA NTRS2011

Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.

Figueroa, Fernando↗
DOE OSTI2011

The Global Trigger Processor: A VXS Switch Module for Triggering Large Scale Data Acquisition Systems

The 12 GeV upgrade for Jefferson Lab's Continuous Electron Beam Accelerator Facility requires the development of a new data acquisition system to accommodate the proposed 200 kHz Level 1 trigger rates expected for fixed target experiments at 12 GeV. As part of a suite of trigger electronics comprised of VXS switch and payload modules, the Global Trigger Processor (GTP) will handle up to 32,768 channels of preprocessed trigger information data from the multiple detector systems that surround the beam target at a system clock rate of 250 MHz. The GTP is configured with user programmable Physics trigger equations and when trigger conditions are satisfied, the GTP will activate the storage of data for subsequent analysis. The GTP features an Altera Stratix IV GX FPGA allowing interface to 16 Sub-System Processor modules via 32 5-Gbps links, DDR2 and flash memory devices, two gigabit Ethernet interfaces using Nios II embedded processors, fiber optic transceivers, and trigger output signals. The GTP's high-bandwidth interconnect with the payload modules in the VXS crate, the Ethernet interface for parameter control, status monitoring, and remote update, and the inherent nature of its FPGA give it the flexibility to be used large variety of tasks and adapt to future needs. This paper details the responsibilities of the GTP, the hardware's role in meeting those requirements, and elements of the VXS architecture that facilitated the design of the trigger system. Also presented will be the current status of development including significant milestones and challenges.

Kaneta, Scott↗