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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

An IAEA Initiative to Provide Effective Stakeholder Support Services for International Decommissioning and Environmental Remediation - 17341

The International Atomic Energy Agency (IAEA) has initiated a collaborative effort to promote stakeholder support activities through a stakeholder engagement advisory program (SEAP) as part of Phase II of the Constraints to Implementing Decommissioning and Environmental Remediation (CIDER II) program. CIDER II is a collaborative project involving a broad range of Member States, large and small, with ongoing and/or planned decommissioning and environmental remediation (D and ER) programs. The intent of this sub-group of CIDER II is to facilitate better sharing of information and knowledge in areas of stakeholder communication, engagement and participation, and a framework for directly using stakeholder input in the decision making process. The goal is to support trust building in D and ER decisions for radioactive contamination and facilities. A main premise of the CIDER II program is that stakeholder acceptance is necessary for successful D and ER decisions to be made. This paper introduces some of the major challenges to implementing such a broad scale of support for stakeholder engagement, and approaches to overcoming those challenges. Major challenges include the need to address D and ER decision making in different countries with their different languages, cultures, religions, management structures, and politics. For example, in some cases it might be important strategically to first garner support from upper levels of social, management or political hierarchies, including for example, approaching community leaders, and allowing those leaders to directly address their community. Other sites might have more success, for example, if stakeholder interaction starts with the community members. A specific project strategy also probably depends on who makes the request for stakeholder support services. Once the CIDER II SEAP gains traction, there will be a need to prioritize requests from Member States for assistance in connection with specific D and ER projects. A prioritization tool will be developed based on stakeholder engaged structured decision making (SDM). The projects in which support will initially be focused will span a wide range of D and ER problems, types of stakeholder groups, and technical issues such as potential risk to human health and the environment. A database management system will also be designed to capture information from the different proposed projects and will be expanded to house implemented projects for future reference. The case study database will be an integral part of a web-based system that also contains technical approaches for stakeholder involvement depending on the situational environment. A community of practice will be formed that will involve technical experts in stakeholder engagement and structured decision making, and informed representatives from Member States. This will address the need for SEAP to build capacity and provide education for solving D and ER problems. The web-based system will include technical tools for use by the projects, such as: identification of stakeholder groups; social network analysis (how stakeholders are connected); case study forms; best practice forms; information sheets; and 4tools that will directly support optimization of stakeholder guided solutions to D and ER problems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Enabling Data Exchange and Data Integration with the Common Information Model: An Introduction for Power Systems Engineers and Application Developers

The Common Information Model (CIM) is an open-source information model that is used to model an electrical network and the various equipment used on the network. CIM is widely used for data exchange of bulk transmission power systems and is finding increasing use for distribution systems. Use of a non-proprietary information model (such as CIM) that has been agreed upon and adopted by numerous utilities, vendors, and researchers allows significant reduction in the effort and cost of data integration. Likewise, adoption of open data platforms built around the CIM increases available functionalities for managing and optimizing the smart grid of the future. This report is intended as an introduction to CIM for utility engineers, power systems researchers, and application developers, providing a broad view of the CIM and how particular profiles can be adapted for various use cases. Unlike most other CIM introduction documents and the International Electrotechnical Commission (IEC) standards (which are mostly targeted to an audience of data scientists, enterprise database managers, and platform developers), this report is intended for users of traditional power systems analysis software and other readers without any prior experience with canonical information models, data profiles, or UML modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Enabling Efficient Sparse Computations using Linear Algebra Aware Compilers

This project developed the LAPIS compiler framework, built on the Multilevel Intermediate Representation (MLIR), to optimize sparse linear algebra operations and support performance portability across diverse architectures. The main innovation of LAPIS is the Kokkos dialect, which allows for lowering codes from a high productivity language to different architectures in an elegant way. The dialect also allows the conversion of lower-level MLIR code to C++ Kokkos code, facilitating the integration of scientific machine learning (SciML) models into applications. To extend LAPIS for distributed memory architectures, a new partition dialect was created to manage the distribution of sparse tensors and express communication patterns for sparse linear algebra operations. This dialect also supports the distributed execution of operators and includes algorithmic optimizations to minimize communication to improve performance. The project also demonstrates that MLIR can enable effective linear algebra-level optimizations, improving performance on different GPUs for both sparse and dense linear algebra kernels. Key applications of LAPIS include sparse linear algebra and graph kernels, TenSQL, a relational database management solution built on GraphBLAS, and the development of subgraph isomorphism and monomorphism kernels, showcasing performance portability. In summary, the LAPIS framework supports productivity, performance, portability, and distributed memory execution, while also enabling linear algebra-level optimizations that are challenging in traditional programming languages, with successful applications ranging from simple sparse linear algebra to complex graph kernels.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Value added data archiving

Researchers in the Molecular Sciences Research Center (MSRC) of Pacific Northwest Laboratory (PNL) currently generate massive amounts of scientific data. The amount of data that will need to be managed by the turn of the century is expected to increase significantly. Automated tools that support the management, maintenance, and sharing of this data are minimal. Researchers typically manage their own data by physically moving datasets to and from long term storage devices and recording a dataset's historical information in a laboratory notebook. Even though it is not the most efficient use of resources, researchers have tolerated the process. The solution to this problem will evolve over the next three years in three phases. PNL plans to add sophistication to existing multilevel file system (MLFS) software by integrating it with an object database management system (ODBMS). The first phase in the evolution is currently underway. A prototype system of limited scale is being used to gather information that will feed into the next two phases. This paper describes the prototype system, identifies the successes and problems/complications experienced to date, and outlines PNL's long term goals and objectives in providing a permanent solution.

Berard, Peter R.↗
DOE OSTI2022

Development of a Cloud-based Application to Enable a Scalable Risk-informed Predictive Maintenance Strategy at Nuclear Power Plants

Light-water reactor operations and maintenance (O&M) costs are prohibitively high, thus contributing to the premature decommissioning of nuclear power plants (NPPs). This is partly due to how the equipment is monitored. In recent years, cloud computing has emerged as a dominant technology by virtue of its low costs, computing and storage adaptability, and ability to host applications over numerous types of virtual infrastructures. Cloud computing can be a cost-effective alternative to onsite storage and diagnostics. This paper conducts a techno-economic assessment of a provisional cloud deployment architecture for a NPP predictive monitoring (PdM) system. The cloud-based monitoring system would enable maintenance and diagnostics (M&D) analysts and other authorized plant users to remotely monitor equipment functionality so as to enable PdM practices and early detection of faults. The Microsoft Azure cloud platform is included in the proposed cloud architecture to provide data processing and storage, sensor device networking, and database management; however, this analysis could be extended to other cloud computing service providers as well. For the techno-economic assessment, technical feasibility is measured in terms of network performance metrics such as response time, latency, and throughput, whereas economic feasibility is measured in terms of operational costs and capital expenditures. Finally, this report covers certain regulatory and security aspects that may concern licensees looking to implement cloud computing. The report focuses on the integration of sensor database storage, the application of cloud resources to PdM, and the identification of technological and economic hurdles associated with moving to a cloud-computing-based architecture.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1992

STARBASE: Database software for the automated plate scanner

The Automated Plate Scanner (APS) of the University of Minnesota, a unique high speed 'flying spot' laser scanner, is currently being used to scan and digitize the 936 O and E plate pairs of the first epoch Palomar Sky Survey. The resultant database will be used to produce a catalog of approximately a billion stars and several million galaxies. The authors describe the ongoing development of a dedicated APS database management system which will be made available to the astronomical community via INTERNET. A specialized DBMS called STARBASE has been written to provide fast access to the hundreds of millions of images collected by the APS. This system provides an initial reduction mode for parameterizing APS images and classifying image types using a novel set of neural network image classifiers. A second analysis mode, which will be that commonly used by the general user, provides for searches of the database which may be constrained by any combination of physical and positional parameters. Through the use of pointer hash trees, the system has been optimized for extremely fast positional searches using either right ascension and declination on the sky or linear X and Y positions on the POSS field. In addition to fast data retrieval, the system provides a graphical interface for displaying scatter plots or histograms of the collected data. In addition, a specialized image display system is being developed to allow the user to view densitometric data for all objects classified as extended by the neural network system. Finally, STARBASE has a flexible programmable interface which allows other programs to access information in the database. This allows users to write applications suited to their particular needs to process APS data.

Odewahn, S. C.↗
NASA NTRS1986

ADAMS: AIRLAB data management system user's guide

The AIRLAB Data Management System (ADAMS) is an online environment that supports research at NASA's AIRLAB. ADAMS provides an easy to use interactive interface that eases the task of documenting and managing information about experiments and improves communication among project members. Data managed by ADAMS includes information about experiments, data sets produced, software and hardware available in AIRLAB as well as that used in a particular experiment, and an on-line engineer's notebook. The User's Guide provides an overview of the ADAMS system as well as details of the operations available within ADAMS. A tutorial section takes the user step-by-step through a typical ADAMS session. ADAMS runs under the VAX/VMS operating system and uses the ORACLE database management system and DEC/FMS (the Forms Management System). ADAMS can be run from any VAX connected via DECnet to the ORACLE host VAX. The ADAMS system is designed for simplicity, so interactions within the underlying data management system and communications network are hidden from the user.

Conrad, C. L.↗
NASA NTRS1993

Exercise countermeasure protocol management expert system

Exercise will be used primarily to countermeasure against deconditioning on extended space flight. In this paper we describe the development and evaluation of an expert system for exercise countermeasure protocol management. Currently, the system includes two major subsystems: baseline prescription and prescription adjustment. The baseline prescription subsystem is designed to provide initial exercise prescriptions while prescription adjustment subsystem is designed to modify the initial prescription based on the exercised progress. The system runs under three different environments: PC, SUN workstation, and Symbolic machine. The inference engine, baseline prescription module, prescription adjustment module and explanation module are developed under the Symbolic environment by using the ART (Automated Reasoning Tool) software. The Sun environment handles database management features and interfaces with PC environment to obtain physical and physiological data from exercise units on-board during the flight. Eight subjects' data have been used to evaluate the system performance by comparing the prescription of nine experienced exercise physiologists and the one prescribed by the expert system. The results of the validation test indicated that the performance of the expert system was acceptable.

NASA Discipline Data Analysis↗
DOE OSTI2018

Adaptation of Commercially Available Robots for Conditioning and Packaging ILW at Sellafield - 18282

The Legacy Ponds and Silos at Sellafield site contain some of the most hazardous Intermediate Level Waste (ILW) in the UK. As part of a multi-billion pound decommissioning programme, this waste will be retrieved and transported across the site for conditioning and packaging in the Box Encapsulation Plant (BEP). Current plans are to commence plant active commissioning in 2022, which will represent a major milestone in the UK nuclear decommissioning programme. Within the plant, skips of waste will be transferred from the shielded transport package into standard 3 cubic metre ILW containers. Waste from the Pile Fuel Storage Pond and First Generation Magnox Storage Pond will be immobilised in cementitious grout before being transferred to an adjacent store. Waste from the Magnox Swarf Storage Silo will not be immobilised in grout, but will be packaged, providing multi-barrier containment. During the concept design, the project team selected commercially available robots as the most viable technology for carrying out the numerous dexterous and repetitive tasks involved in characterising, conditioning and packaging the waste within the shielded 'hot' cells. Significant technical challenges had to be overcome during the design to adapt a commercially available robot for use within a high radiation / high contamination environment, where human access is not safe even for short periods of time. These challenges included: - Designing robot assemblies that could be retrofitted into the existing cell structure that was constructed as part of an earlier project but never completed; - Designing robot assemblies that could be recovered to their 'transport' position without requiring manual intervention; - Designing robot assemblies that could be remotely removed and replaced with new ones if they failed part way through the plant operational life; - Designing through-wall service and power connections that allow maintenance and recovery; - Designing control systems and human-machine interfaces that enable both manual and automated operation of the robot, whilst avoiding collisions with the in-cell cranes and other in cell furniture; - Assessing the radiation tolerance of all items. Bespoke computer simulations and full-scale development trials have been carried out, using non-active test materials, in order to demonstrate the Technology Readiness Level (TRL) required by Sellafield Limited (SL) at each stage of the project [1]. The results of these trials have been recorded in both video and written form so that they can form part of the project's Knowledge Management database. Detailed designs and specifications for the robot assemblies have been updated to incorporate the recommendations from the development trials. Procurement and manufacture of robot assemblies has already commenced to deliver two waste handling robots, two waste container lidding / swabbing robots and associated critical spares. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2009

Work Coordination Engine

The Work Coordination Engine (WCE) is a Java application integrated into the Service Management Database (SMDB), which coordinates the dispatching and monitoring of a work order system. WCE de-queues work orders from SMDB and orchestrates the dispatching of work to a registered set of software worker applications distributed over a set of local, or remote, heterogeneous computing systems. WCE monitors the execution of work orders once dispatched, and accepts the results of the work order by storing to the SMDB persistent store. The software leverages the use of a relational database, Java Messaging System (JMS), and Web Services using Simple Object Access Protocol (SOAP) technologies to implement an efficient work-order dispatching mechanism capable of coordinating the work of multiple computer servers on various platforms working concurrently on different, or similar, types of data or algorithmic processing. Existing (legacy) applications can be wrapped with a proxy object so that no changes to the application are needed to make them available for integration into the work order system as "workers." WCE automatically reschedules work orders that fail to be executed by one server to a different server if available. From initiation to completion, the system manages the execution state of work orders and workers via a well-defined set of events, states, and actions. It allows for configurable work-order execution timeouts by work-order type. This innovation eliminates a current processing bottleneck by providing a highly scalable, distributed work-order system used to quickly generate products needed by the Deep Space Network (DSN) to support space flight operations. WCE is driven by asynchronous messages delivered via JMS indicating the availability of new work or workers. It runs completely unattended in support of the lights-out operations concept in the DSN.

Zendejas, Silvino↗
NASA NTRS1989

Knowledge-based control of an adaptive interface

The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations.

Lachman, Roy↗
DOE OSTI2013

A Workflow-based Intelligent Network Data Movement Advisor with End-to-end Performance Optimization

Next-generation eScience applications often generate large amounts of simulation, experimental, or observational data that must be shared and managed by collaborative organizations. Advanced networking technologies and services have been rapidly developed and deployed to facilitate such massive data transfer. However, these technologies and services have not been fully utilized mainly because their use typically requires significant domain knowledge and in many cases application users are even not aware of their existence. By leveraging the functionalities of an existing Network-Aware Data Movement Advisor (NADMA) utility, we propose a new Workflow-based Intelligent Network Data Movement Advisor (WINDMA) with end-to-end performance optimization for this DOE funded project. This WINDMA system integrates three major components: resource discovery, data movement, and status monitoring, and supports the sharing of common data movement workflows through account and database management. This system provides a web interface and interacts with existing data/space management and discovery services such as Storage Resource Management, transport methods such as GridFTP and GlobusOnline, and network resource provisioning brokers such as ION and OSCARS. We demonstrate the efficacy of the proposed transport-support workflow system in several use cases based on its implementation and deployment in DOE wide-area networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Managing code transformations for better performance portability

Code optimization is an intricate task that is getting more complex as computing systems evolve. Managing the program optimization process, including the implementation and evaluation of code variants, is tedious, inefficient, and errors are likely to be introduced in the process. Moreover, because each platform typically requires a different sequence of transformations to fully harness its computing power, the optimization process complexity grows as new platforms are adopted. To address these issues, systems and frameworks have been proposed to automate the code optimization process. They, however, have not been widely adopted and are primarily used by experts with deep knowledge about underlying architecture and compiler intricacies. This article describes the requirements that we believe necessary for making automatic performance tuning more broadly used, especially in complex, long-lived high-performance computing applications. Besides discussing limitations of current systems and strategies to overcome these, we describe the design of a system that is able to semi-automatically generate efficient platform-specific code. In the proposed system, the code optimization is programmer-guided, separately from application code, on an external file in what we call optimization programming. The language to program the optimization process is able to represent complex collections of transformations and, as a result, generate efficient platform-specific code. A database manages different optimized versions of code regions, providing a pragmatic approach to performance portability, and the framework itself has separate components, allowing the optimized code to be used on systems without installing all of the modules required for the code generation. We present experiments on two different platforms to illustrate the generation of efficient platform-specific code that performs comparable to hand-optimized, vendor-provided code.

Computer Science↗
NASA NTRS2011

An Analysis of Database Replication Technologies with Regard to Deep Space Network Application Requirements

The Deep Space Network (DSN) has three communication facilities which handle telemetry, commands, and other data relating to spacecraft missions. The network requires these three sites to share data with each other and with the Jet Propulsion Laboratory for processing and distribution. Many database management systems have replication capabilities built in, which means that data updates made at one location will be automatically propagated to other locations. This project examines multiple replication solutions, looking for stability, automation, flexibility, performance, and cost. After comparing these features, Oracle Streams is chosen for closer analysis. Two Streams environments are configured - one with a Master/Slave architecture, in which a single server is the source for all data updates, and the second with a Multi-Master architecture, in which updates originating from any of the servers will be propagated to all of the others. These environments are tested for data type support, conflict resolution, performance, changes to the data structure, and behavior during and after network or server outages. Through this experimentation, it is determined which requirements of the DSN can be met by Oracle Streams and which cannot.

Oracle Database File System↗
DOE OSTI2019

Highly interactive, steered scientific workflows on HPC systems: optimizing design solutions

Scientific workflows are becoming increasingly important in high performance computing (HPC) settings, as the feasibility and appeal of many simultaneous heterogeneous tasks increases with increasing hardware capabilities. Currently no HPC-based workflow platform supports a dynamically adaptable workflow with interactive steering and analysis at run-time. Furthermore, for most workflow programs, compute resources are fixed for a given instance, resulting in a possible waste of expensive allocation resources when tasks are spawned and killed. Here we describe the design and testing of a run-time-interactive, adaptable, steered workflow tool capable of executing thousands of parallel tasks without an MPI programming model, using a database management system to facilitate task management through multiple live connections. We find that on the Oak Ridge Leadership Computing Facility pre-exascale Summit supercomputer it is possible to launch and interactively steer workflows with thousands of simultaneous tasks with negligible latency. For the case of particle simulation and analysis tasks that run for minutes to hours, this paradigm offers the prospect of a robust and efficient means to perform simulation-space exploration with on-the-fly analysis and adaptation.

Ossyra, John R↗
DOE OSTI2015

A spatial DB model to simulate the road network efficiency in hydrogeological emergency

We deal with the theme of the simulation of risk analysis using a technological approach based on the integration of exclusively free and open source tools: PostgreSQL as Database Management System (DBMS) and Quantum GIS-GRASS as Geographic Information System (GIS) platform. The case study is represented by a seismic land in Sicily characterized by steep slopes and frequent instability phenomena. This area includes a city of about 30.000 inhabitants (Enna) that lies on the top of a mountain at about 990 m a.s.l.. The access to the city is assured by few and very winding roads that are also highly vulnerable to seismic and hydrogeological hazards. When exceptional rainfall events occur, the loss of efficiency of these roads should compromise timeliness and effectiveness of rescue operations. The data of the sample area have been structured into the adopted DBMS, and the connection to the GIS functionalities allows simulating the exceptional events. We analyzed the hazard, vulnerability and exposure related to these events and calculated the final risk defining three classes for each scenario: low (L), medium (M) and high (H). This study can be a valuable tool to prioritize risk levels and set priorities for intervention to the main road networks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Active learning for robust, high-complexity reactive atomistic simulations

Machine learned reactive force fields based on polynomial expansions have been shown to be highly effective for describing simulations involving reactive materials. Nevertheless, the highly flexible nature of these models can give rise to a large number of candidate parameters for complicated systems. In these cases, reliable parameterization requires a well-formed training set, which can be difficult to achieve through standard iterative fitting methods. In this paper, we present an active learning approach based on cluster analysis and inspired by Shannon information theory to enable semi-automated generation of informative training sets and robust machine learned force fields. The use of this tool is demonstrated for development of a model based on linear combinations of Chebyshev polynomials explicitly describing up to four-body interactions, for a chemically and structurally diverse system of C/O under extreme conditions. We show that this flexible training database management approach enables development of models exhibiting excellent agreement with Kohn–Sham density functional theory in terms of structure, dynamics, and speciation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗