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At least 1,027 records · Page 57

A Support Database System for Integrated System Health Management (ISHM)

The development, deployment, operation and maintenance of Integrated Systems Health Management (ISHM) applications require the storage and processing of tremendous amounts of low-level data. This data must be shared in a secure and cost-effective manner between developers, and processed within several heterogeneous architectures. Modern database technology allows this data to be organized efficiently, while ensuring the integrity and security of the data. The extensibility and interoperability of the current database technologies also allows for the creation of an associated support database system. A support database system provides additional capabilities by building applications on top of the database structure. These applications can then be used to support the various technologies in an ISHM architecture. This presentation and paper propose a detailed structure and application description for a support database system, called the Health Assessment Database System (HADS). The HADS provides a shared context for organizing and distributing data as well as a definition of the applications that provide the required data-driven support to ISHM. This approach provides another powerful tool for ISHM developers, while also enabling novel functionality. This functionality includes: automated firmware updating and deployment, algorithm development assistance and electronic datasheet generation. The architecture for the HADS has been developed as part of the ISHM toolset at Stennis Space Center for rocket engine testing. A detailed implementation has begun for the Methane Thruster Testbed Project (MTTP) in order to assist in developing health assessment and anomaly detection algorithms for ISHM. The structure of this implementation is shown in Figure 1. The database structure consists of three primary components: the system hierarchy model, the historical data archive and the firmware codebase. The system hierarchy model replicates the physical relationships between system elements to provide the logical context for the database. The historical data archive provides a common repository for sensor data that can be shared between developers and applications. The firmware codebase is used by the developer to organize the intelligent element firmware into atomic units which can be assembled into complete firmware for specific elements.

FROM↗

Detecting Data-Races in High-Performance Computing

High-performance computing is susceptible to data-race bugs. Data races occur when sequences of computed events do not happen in the intended order, a significant barrier to the integrity of parallel programs using shared-memory architectures. Many approaches to data-race detection are based on traditional static-analysis techniques that typically execute on a program’s source code or control-flow graph (the graphical representation of all possible orders of events in the execution of a program). Similar to classical data-flow analyses, such tools can produce false alarms that report spurious race conditions on error free programs. We have developed a software verification technique that requires as input only a program’s source code and can automatically detect a data-race bug which definitely exists, determine that a program is definitely data-race free, or report that it cannot determine either of the two cases.

97 MATHEMATICS AND COMPUTING↗

An Architecture for Real-Time Interpretation and Visualization of Structural Sensor Data in a Laboratory Environment

A visualization system is being developed out of the need to monitor, interpret, and make decisions based on the information from several thousand sensors during experimental testing to facilitate development and validation of structural health monitoring algorithms. As an added benefit the system will enable complete real-time sensor assessment of complex test specimens. Complex structural specimens are routinely tested that have hundreds or thousands of sensors. During a test, it is impossible for a single researcher to effectively monitor all the sensors and subsequently interesting phenomena occur that are not recognized until post-test analysis. The ability to detect and alert the researcher to these unexpected phenomena as the test progresses will significantly enhance the understanding and utilization of complex test articles. Utilization is increased by the ability to halt a test when the health monitoring algorithm response is not satisfactory or when an unexpected phenomenon occurs, enabling focused investigation potentially through the installation of additional sensors. Often if the test continues, structural changes make it impossible to reproduce the conditions that exhibited the phenomena. The prohibitive time and costs associated with fabrication, sensoring, and subsequent testing of additional test articles generally makes it impossible to further investigate the phenomena. A scalable architecture is described to address the complex computational demands of structural health monitoring algorithm development and laboratory experimental test monitoring. The researcher monitors the test using a photographic quality 3D graphical model with actual sensor locations identified. In addition, researchers can quickly activate plots displaying time or load versus selected sensor response along with the expected values and predefined limits. The architecture has several key features. First, distributed dissimilar computers may be seamlessly integrated into the information flow. Second, virtual sensors may be defined that are complex functions of existing sensors or other virtual sensors. Virtual sensors represent a calculated value not directly measured by particular physical instrument. They can be used, for example, to represent the maximum difference in a range of sensors or the calculated buckling load based on the current strains. Third, the architecture enables autonomous response to preconceived events, where by the system can be configured to suspend or abort a test if a failure is detected in the load introduction system. Fourth, the architecture is designed to allow cooperative monitoring and control of the test progression from multiple stations both remote and local to the test system. To illustrate the architecture, a preliminary implementation is described monitoring the Stitched Composite Wing recently tested at LaRC.

Doggett, William↗

Computing the Properties of Matter with Leadership Computing Resources (Closeout Report for DE-SC0018121)

In order to add more capabilities to Halide, we have designed a new framework called Tiramisu and integrated this framework into Halide. Since Tiramisu enables Halide to target heterogeneous architectures, our development efforts have been refocused on Tiramisu. Most high-performance computer systems today are complex and increasingly heterogeneous; they may have CPUs, GPUs and FPGAs. Achieving best performance requires taking full advantage of all these different architectures. To address this issue, we have designed Tiramisu, an optimization framework that enables Halide (and other DSLs) to target heterogeneous architectures. Tiramisu is an optimization framework that takes as input a high level, architecture-independent representation of code and a set of scheduling and data mapping commands that guide code transformation. The input can either be generated by a domain-specific language (DSL) compiler such as Halide or directly written by a programmer. Tiramisu then applies the user-specified code and data-layout transformations and generates an architecture-specific, low-level intermediate representation (IR) that takes advantage of modern architectural features such as multicore parallelism, non-uniform memory (NUMA) hierarchies, clusters, and accelerators like GPUs and FPGAs. We integrated Tiramisu within Halide and implemented a representative set of benchmarks to evaluate this integration. Tiramisu is now open source and is available for public use (http://tiramisu-compiler.org/). A paper about Tiramisu was published, it shows that Tiramisu extends Halide with many new capabilities and that Tiramisu can generate efficient code for multicores, GPUs, FPGAs and distributed heterogeneous systems. The performance of code generated by the Tiramisu backends matches or exceeds hand optimized reference implementations. For example, the multicore backend matches the highly optimized Intel MKL library on many kernels and shows speedups reaching 4x over the original Halide. In addition to making Tiramisu more robust, we have used Tiramisu to implement a set of representative tensor operation for constructing baryon building blocks required for multi baryon contractions in LQCD. In order to implement this code, we needed to generalize Tiramisu in two ways: first we needed to support indirect array accesses, and second, we needed to add support for complex numbers to Tiramisu. The code generated by Tiramisu is 6x faster than the reference code. Our efforts towards an MPI based multi-node version of tiramisu have matured and the resulting code scales well on multiple nodes (tests up to 512 KNL nodes have been undertaken).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Advanced data structures for the interpretation of image and cartographic data in geo-based information systems

A growing need to usse geographic information systems (GIS) to improve the flexibility and overall performance of very large, heterogeneous data bases was examined. The Vaster structure and the Topological Grid structure were compared to test whether such hybrid structures represent an improvement in performance. The use of artificial intelligence in a geographic/earth sciences data base context is being explored. The architecture of the Knowledge Based GIS (KBGIS) has a dual object/spatial data base and a three tier hierarchial search subsystem. Quadtree Spatial Spectra (QTSS) are derived, based on the quadtree data structure, to generate and represent spatial distribution information for large volumes of spatial data.

Peuquet, D. J.↗

AVIRIS and TIMS data processing and distribution at the land processes distributed active archive center

The U.S. Government has initiated the Global Change Research program, a systematic study of the Earth as a complete system. NASA's contribution of the Global Change Research Program is the Earth Observing System (EOS), a series of orbital sensor platforms and an associated data processing and distribution system. The EOS Data and Information System (EOSDIS) is the archiving, production, and distribution system for data collected by the EOS space segment and uses a multilayer architecture for processing, archiving, and distributing EOS data. The first layer consists of the spacecraft ground stations and processing facilities that receive the raw data from the orbiting platforms and then separate the data by individual sensors. The second layer consists of Distributed Active Archive Centers (DAAC) that process, distribute, and archive the sensor data. The third layer consists of a user science processing network. The EOSDIS is being developed in a phased implementation. The initial phase, Version 0, is a prototype of the operational system. Version 0 activities are based upon existing systems and are designed to provide an EOSDIS-like capability for information management and distribution. An important science support task is the creation of simulated data sets for EOS instruments from precursor aircraft or satellite data. The Land Processes DAAC, at the EROS Data Center (EDC), is responsible for archiving and processing EOS precursor data from airborne instruments such as the Thermal Infrared Multispectral Scanner (TIMS), the Thematic Mapper Simulator (TMS), and Airborne Visible and Infrared Imaging Spectrometer (AVIRIS). AVIRIS, TIMS, and TMS are flown by the NASA-Ames Research Center ARC) on an ER-2. The ER-2 flies at 65000 feet and can carry up to three sensors simultaneously. Most jointly collected data sets are somewhat boresighted and roughly registered. The instrument data are being used to construct data sets that simulate the spectral and spatial characteristics of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument scheduled to be flown on the first EOS-AM spacecraft. The ASTER is designed to acquire 14 channels of land science data in the visible and near-IR (VNIR), shortwave-IR (SWIR), and thermal-IR (TIR) regions from 0.52 micron to 11.65 micron at high spatial resolutions of 15 m to 90 m. Stereo data will also be acquired in the VNIR region in a single band. The AVIRIS and TMS cover the ASTER VNIR and SWIR bands, and the TIMS covers the TIR bands. Simulated ASTER data sets have been generated over Death Valley, California, Cuprite, Nevada, and the Drum Mountains, Utah using a combination of AVIRIS, TIMS, amd TMS data, and existing digital elevation models (DEM) for the topographic information.

Mah, G. R.↗

A Systems Engineering Approach to Architecture Development

Architecture development is conducted prior to system concept design when there is a need to determine the best-value mix of systems that works collectively in specific scenarios and time frames to accomplish a set of mission area objectives. While multiple architecture frameworks exist, they often require use of unique taxonomies and data structures. In contrast, this presentation characterizes architecture development using terminology widely understood within the systems engineering community. Using a notional civil space architecture example, it employs a multi-tier framework to describe the enterprise level architecture and illustrates how results of lower tier, mission area architectures integrate into the enterprise architecture. It also presents practices for conducting effective mission area architecture studies, including establishing the trade space, developing functions and metrics, evaluating the ability of potential design solutions to meet the required functions, and expediting study execution through the use of iterative design cycles.

Architecture Development↗

A Systems Engineering Approach to Architecture Development

Architecture development is often conducted prior to system concept design when there is a need to determine the best-value mix of systems that works collectively in specific scenarios and time frames to accomplish a set of mission area objectives. While multiple architecture frameworks exist, they often require use of unique taxonomies and data structures. In contrast, this paper characterizes architecture development using terminology widely understood within the systems engineering community. Using a notional civil space architecture example, it employs a multi-tier framework to describe the enterprise level architecture and illustrates how results of lower tier, mission area architectures integrate into the enterprise architecture. It also presents practices for conducting effective mission area architecture studies, including establishing the trade space, developing functions and metrics, evaluating the ability of potential design solutions to meet the required functions, and expediting study execution through the use of iterative design cycles.

Multi-tier Framework↗

A Systems Engineering Approach to Architecture Development

Architecture development is often conducted prior to system concept design when there is a need to determine the best-value mix of systems that works collectively in specific scenarios and time frames to accomplish a set of mission area objectives. While multiple architecture frameworks exist, they often require use of unique taxonomies and data structures. In contrast, this paper characterizes architecture development using terminology widely understood within the systems engineering community. Using a notional civil space architecture example, it employs a multi-tier framework to describe the enterprise level architecture and illustrates how results of lower tier, mission area architectures integrate into the enterprise architecture. It also presents practices for conducting effective mission area architecture studies, including establishing the trade space, developing functions and metrics, evaluating the ability of potential design solutions to meet the required functions, and expediting study execution through the use of iterative design cycles

Architecture Development↗

SeaWiFS technical report series. Volume 20: The SeaWiFS bio-optical archive and storage system (SeaBASS), part 1

This document provides an overview of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-Optical Archive and Storage System (SeaBASS), which will serve as a repository for numerous data sets of interest to the SeaWiFS Science Team and other approved investigators in the oceanographic community. The data collected will be those data sets suitable for the development and evaluation of bio-optical algorithms which include results from SeaWiFS Intercalibration Round-Robin Experiments (SIRREXs), prelaunch characterization of the SeaWiFS instrument by its manufacturer -- Hughes/Santa Barbara Research Center (SBRC), Marine Optical Characterization Experiment (MOCE) cruises, Marine Optical Buoy (MOBY) deployments and refurbishments, and field studies of other scientists outside of NASA. The primary goal of the data system is to provide a simple mechanism for querying the available archive and requesting specific items, while assuring that the data is made available only to authorized users. The design, construction, and maintenance of SeaBASS is the responsibility of the SeaWiFS Calibration and Validation Team (CVT). This report is concerned with documenting the execution of this task by the CVT and consists of a series of chapters detailing the various data sets involved. The topics presented are as follows: 1) overview of the SeaBASS file architecture, 2) the bio-optical data system, 3) the historical pigment database, 4) the SIRREX database, and 5) the SBRC database.

Hooker, Stanford B.↗

FPA Depot - Web Application

Lines of code (LOC) analysis is one of the methods used to measure programmer productivity and estimate schedules of programming projects. The Launch Control System (LCS) had previously used this method to estimate the amount of work and to plan development efforts. The disadvantage of using LOC as a measure of effort is that one can only measure 30% to 35% of the total effort of software projects involves coding [8]. In the application, instead of using the LOC we are using function point for a better estimation of hours in each software to develop. Because of these disadvantages, Jamie Szafran of the System Software Branch of Control And Data Systems (NE-C3) at Kennedy Space Canter developed a web application called Function Point Analysis (FPA) Depot. The objective of this web application is that the LCS software architecture team can use the data to more accurately estimate the effort required to implement customer requirements. This paper describes the evolution of the domain model used for function point analysis as project managers continually strive to generate more accurate estimates.

Avila, Edwin M. Martinez↗

Interoperability format translation and transformation between IFC architectural design file and simulation file formats

Automatically translating a building architecture file format (Industry Foundation Class) to a simulation file, in one aspect, may extract data and metadata used by a target simulation tool from a building architecture file. Interoperability data objects may be created and the extracted data is stored in the interoperability data objects. A model translation procedure may be prepared to identify a mapping from a Model View Definition to a translation and transformation function. The extracted data may be transformed using the data stored in the interoperability data objects, an input Model View Definition template, and the translation and transformation function to convert the extracted data to correct geometric values needed for a target simulation file format used by the target simulation tool. The simulation file in the target simulation file format may be generated.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Interoperability format translation and transformation between IFC architectural design file and simulation file formats

Automatically translating a building architecture file format (Industry Foundation Class) to a simulation file, in one aspect, may extract data and metadata used by a target simulation tool from a building architecture file. Interoperability data objects may be created and the extracted data is stored in the interoperability data objects. A model translation procedure may be prepared to identify a mapping from a Model View Definition to a translation and transformation function. The extracted data may be transformed using the data stored in the interoperability data objects, an input Model View Definition template, and the translation and transformation function to convert the extracted data to correct geometric values needed for a target simulation file format used by the target simulation tool. The simulation file in the target simulation file format may be generated.

97 MATHEMATICS AND COMPUTING↗

Transformer-powered surrogates close the ICF simulation-experiment gap with extremely limited data

Abstract Recent advances in machine learning, specifically transformer architecture, have led to significant advancements in commercial domains. These powerful models have demonstrated superior capability to learn complex relationships and often generalize better to new data and problems. This paper presents a novel transformer-powered approach for enhancing prediction accuracy in multi-modal output scenarios, where sparse experimental data is supplemented with simulation data. The proposed approach integrates transformer-based architecture with a novel graph-based hyper-parameter optimization technique. The resulting system not only effectively reduces simulation bias, but also achieves superior prediction accuracy compared to the prior method. We demonstrate the efficacy of our approach on inertial confinement fusion experiments, where only 10 shots of real-world data are available, as well as synthetic versions of these experiments.

97 MATHEMATICS AND COMPUTING↗

The development of a post-test diagnostic system for rocket engines

An effort was undertaken by NASA to develop an automated post-test, post-flight diagnostic system for rocket engines. The automated system is designed to be generic and to automate the rocket engine data review process. A modular, distributed architecture with a generic software core was chosen to meet the design requirements. The diagnostic system is initially being applied to the Space Shuttle Main Engine data review process. The system modules currently under development are the session/message manager, and portions of the applications section, the component analysis section, and the intelligent knowledge server. An overview is presented of a rocket engine data review process, the design requirements and guidelines, the architecture and modules, and the projected benefits of the automated diagnostic system.

Zakrajsek, June F.↗

The development of a post-test diagnostic system for rocket engines

An effort was undertaken by NASA to develop an automated post-test, post-flight diagnostic system for rocket engines. The automated system is designed to be generic and to automate the rocket engine data review process. A modular, distributed architecture with a generic software core was chosen to meet the design requirements. The diagnostic system is initially being applied to the Space Shuttle Main Engine data review process. The system modules currently under development are the session/message manager, and portions of the applications section, the component analysis section, and the intelligent knowledge server. An overview is presented of a rocket engine data review process, the design requirements and guidelines, the architecture and modules, and the projected benefits of the automated diagnostic system.

Zakrajsek, June F.↗

1D-Convolutional Neural Network Architecture for Generalized Time-series Segmentation

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D convolutional neural net (CNN) architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization will be described as well as the results of application to three separate data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation. In all three test cases the 1D-CNN performs better than tailored integral/derivative/thresholding algorithms across a range of signal-to-noise levels.

CNN↗

1D-Convolutional Neural Network Architecture for Generalized Time-series Segmentation

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D convolutional neural net (CNN) architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization will be described as well as the results of application to three separate data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation. In all three test cases the 1D-CNN performs better than tailored integral/derivative/thresholding algorithms across a range of signal-to-noise levels.

CNN↗