Results for “data integration.” — Page 4

DOE OSTI2013

Integrated Data Collection Analysis (IDCA) Program — Ammonium Nitrate

The Integrated Data Collection Analysis (IDCA) program is conducting a proficiency study for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of ammonium nitrate (AN). AN was tested, in most cases, as both received from manufacturer and dried/sieved. The participants found the AN to be: 1) insensitive in Type 12A impact testing (although with a wide range of values), 2) completely insensitive in BAM friction testing, 3) less sensitive than the RDX standard in ABL friction testing, 4) less sensitive than RDX in ABL ESD testing, and 5) less sensitive than RDX and PETN in DSC thermal analyses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Data Integration Aggregated Model For Nuclear Deployment

The data of a nuclear utility or plant are stored in various isolated forms in different systems. These data have different structures and tools and are, therefore, used independently. The integration of data sources is often needed and is performed manually and on an as-needed basis. The integration of the data would enable creating a data warehouse for a single nuclear power plant (NPP) or multiple plants. A data model contains objects that make up a given domain along with their attributes and relationships and could be used as a standard for exchange between applications for simple integration and data aggregation. After a survey of existing models, it was determined that a new model was required to meet the scope of this problem. DIAMOND has been developed in the form of an ontology to meet these needs. An ontology is simply a data model that also acts as a taxonomy for the domain, organizing the objects in a hierarchy with the most general objects at the top.

Browning, JerenM↗

DOE OSTI2020

Detection and Diagnosis of Data Integrity Attacks in Solar Farms Based on Multilayer Long Short-Term Memory Network

Photovoltaic (PV) systems are becoming more vulnerable to cyber threats. In response to this emerging concern, developing cyber-secure power electronics converters has received increased attention from the IEEE Power Electronics Society that recently launched a cyber-physical-security initiative. Here this letter proposes a deep sequence learning based diagnosis solution for data integrity attacks on PV systems in smart grids, including dc–dc and dc–ac converters. The multilayer long short-term memory networks are used to leverage time-series electric waveform data from current and voltage sensors in PV systems. The proposed method has been evaluated in a PV smart grid benchmark model with extensive quantitative analysis. As a comparison, we have evaluated classic data-driven methods, including K-nearest neighbor, decision tree, support vector machine, artificial neural network, and convolutional neural network. Comparison results verify performances of the proposed method for detection and diagnosis of various data integrity attacks on PV systems.

42 ENGINEERING↗

NASA NTRS1992

Flight deck benefits of integrated data link communication

A fixed-base, piloted simulation study was conducted to determine the operational benefits that result when air traffic control (ATC) instructions are transmitted to the deck of a transport aircraft over a digital data link. The ATC instructions include altitude, airspeed, heading, radio frequency, and route assignment data. The interface between the flight deck and the data link was integrated with other subsystems of the airplane to facilitate data management. Data from the ATC instructions were distributed to the flight guidance and control system, the navigation system, and an automatically tuned communication radio. The co-pilot initiated the automation-assisted data distribution process. Digital communications and automated data distribution were compared with conventional voice radio communication and manual input of data into other subsystems of the simulated aircraft. Less time was required in the combined communication and data management process when data link ATC communication was integrated with the other subsystems. The test subjects, commercial airline pilots, provided favorable evaluations of both the digital communication and data management processes.

Waller, Marvin C.↗

NASA NTRS1991

Multisource Data Integration in Remote Sensing

Papers presented at the workshop on Multisource Data Integration in Remote Sensing are compiled. The full text of these papers is included. New instruments and new sensors are discussed that can provide us with a large variety of new views of the real world. This huge amount of data has to be combined and integrated in a (computer-) model of this world. Multiple sources may give complimentary views of the world - consistent observations from different (and independent) data sources support each other and increase their credibility, while contradictions may be caused by noise, errors during processing, or misinterpretations, and can be identified as such. As a consequence, integration results are very reliable and represent a valid source of information for any geographical information system.

Tilton, James C.↗

DOE OSTI2013

Integrated Data Collection Analysis (IDCA) Program — Bullseye ® Smokeless Powder

The Integrated Data Collection Analysis (IDCA) program is conducting a proficiency study for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of Bullseye ® smokeless powder (Gunpowder). The participants found the Gunpowder: 1) to have a range of sensitivity to impact, from less than RDX to almost as sensitive as PETN, 2) to be moderately sensitive to BAM and ABL friction, 3) have a range for ESD, from insensitive to more sensitive than PETN, and 4) to have thermal sensitivity about the same as PETN and RDX.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Integrated Data Collection Analysis (IDCA) Program - SSST Testing Methods

The Integrated Data Collection Analysis (IDCA) program is conducting a proficiency study for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the methods used for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis during the IDCA program. These methods changed throughout the Proficiency Test and the reasons for these changes are documented in this report. The most significant modifications in standard testing methods are: 1) including one specified sandpaper in impact testing among all the participants, 2) diversifying liquid test methods for selected participants, and 3) including sealed sample holders for thermal testing by at least one participant. This effort, funded by the Department of Homeland Security (DHS), is putting the issues of safe handling of these materials in perspective with standard military explosives. The study is adding SSST testing results for a broad suite of different HMEs to the literature. Ultimately the study will suggest new guidelines and methods and possibly establish the SSST testing accuracies needed to develop safe handling practices for HMEs. Each participating testing laboratory uses identical test materials and preparation methods wherever possible. The testing performers involved are Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), Indian Head Division, Naval Surface Warfare Center, (NSWC IHD), Sandia National Laboratories (SNL), and Air Force Research Laboratory (AFRL/RXQL). These tests are conducted as a proficiency study in order to establish some consistency in test protocols, procedures, and experiments and to compare results when these testing variables cannot be made consistent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Integrated Data Analysis (IDCA) Program - PETN Class 4 Standard

The Integrated Data Collection Analysis (IDCA) program is conducting a proficiency study for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of PETN Class 4. The PETN was found to have: 1) an impact sensitivity (DH 50 ) range of 6 to 12 cm, 2) a BAM friction sensitivity (F 50 ) range 7 to 11 kg, TIL (0/10) of 3.7 to 7.2 kg, 3) a ABL friction sensitivity threshold of 5 or less psig at 8 fps, 4) an ABL ESD sensitivity threshold of 0.031 to 0.326 j/g, and 5) a thermal sensitivity of an endothermic feature with T min = ~ 141 °C, and a exothermic feature with a T max = ~205°C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

An integrated data analysis tool for improving measurements on the MST RFP

Many plasma diagnostics contain complementary information. For example, the double-foil soft x-ray system (SXR) and the Thomson Scattering diagnostic (TS) on the Madison Symmetric Torus both measure electron temperature. The complementary information from these diagnostics can be combined using a systematic method based on integrated data analysis techniques, leading to more accurate and sensitive results. An integrated data analysis tool based on Bayesian probability theory was able to estimate electron temperatures that are consistent with both the SXR and TS diagnostics and more precise than either. A Markov Chain Monte Carlo analysis to increase the flexibility of the tool was implemented and benchmarked against a grid search method.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2012

Integrated Data Collection Analysis (IDCA) program--KClO 4 /Dodecane Mixture

The Integrated Data Collection Analysis (IDCA) program is conducting a proficiency study for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of a mixture of KClO 4 and dodecane—KClO 4 /dodecane mixture. This material was selected because of the challenge of performing SSST testing of a mixture of solid and liquid materials. The mixture was found to: 1) be less sensitive to impact than RDX, and PETN, 2) less sensitive to friction than RDX and PETN, and 3) less sensitive to spark than RDX and PETN. The thermal analysis showed little or no exothermic features suggesting that the dodecane volatilized at low temperatures. A prominent endothermic feature was observed and assigned to a phase transition of KClO 4 . This effort, funded by the Department of Homeland Security (DHS), ultimately will put the issues of safe handling of these materials in perspective with standard military explosives. The study is adding SSST testing results for a broad suite of different HMEs to the literature. Ultimately the study has the potential to suggest new guidelines and methods and possibly establish the SSST testing accuracies needed to develop safe handling practices for HMEs. Each participating testing laboratory uses identical test materials and preparation methods wherever possible. Note, however, the test procedures differ among the laboratories. The results are compared among the laboratories and then compared to historical data from various sources. The testing performers involved for the KClO 4 /dodecane mixture are Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), Indian Head Division, Naval Surface Warfare Center, (NSWC IHD), and Air Force Research Laboratory (AFRL/RXQL). These tests are conducted as a proficiency study in order to establish some consistency in test protocols, procedures, and experiments and to understand how to compare results when these testing variables cannot be made consistent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Integrated Data Collection Analysis (IDCA) Program - KClO 4 /Carbon Mixture

The Integrated Data Collection Analysis (IDCA) program is conducting a proficiency study for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of a mixture of KClO 4 and activated carbon—KClO 4 /C mixture. This material was selected because of the challenge of performing SSST testing of a mixture of two solids. The mixture was found to be insensitive to impact, friction, and thermal stimulus, and somewhat sensitive to spark discharge. This effort, funded by the Department of Homeland Security (DHS), ultimately will put the issues of safe handling of these materials in perspective with standard military explosives. The study is adding SSST testing results for a broad suite of different HMEs to the literature. Ultimately the study has the potential to suggest new guidelines and methods and possibly establish the SSST testing accuracies needed to develop safe handling practices for HMEs. Each participating testing laboratory uses identical test materials and preparation methods wherever possible. Note, however, the test procedures differ among the laboratories. The results are compared among the laboratories and then compared to historical data from various sources. The testing performers involved for the KClO 4 /carbon mixture are Lawrence Livermore National Laboratory (LLNL), Los Alamos National Laboratory (LANL), Indian Head Division, Naval Surface Warfare Center, (NSWC IHD), and Air Force Research Laboratory (AFRL/RXQL). These tests are conducted as a proficiency study in order to establish some consistency in test protocols, procedures, and experiments and to understand how to compare results when these testing variables cannot be made consistent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Integrated Data Collection Analysis (IDCA) Program - KClO 4 /Aluminum Mixture

The Integrated Data Collection Analysis (IDCA) program is conducting a Proficiency Test for Small-Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of a mixture of KClO 4 and aluminum—KClO 4 /Al mixture. This material was selected because of the challenge of performing SSST testing of a mixture of two solids. The mixture was found to be: 1) much less sensitive to impact than RDX, (LLNL being the exception) and PETN, 2) more sensitive to friction than RDX and PETN, and 3) extremely sensitive to spark. The thermal analysis showed little or no exothermic character. One prominent endothermic feature was observed in the temperature range studied and identified as a phase transition of KClO 4 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Integrated Data Collection Analysis (IDCA) Program - NaClO 3 /Icing Sugar

The Integrated Data Collection Analysis (IDCA) program is conducting a proficiency study for Small- Scale Safety and Thermal (SSST) testing of homemade explosives (HMEs). Described here are the results for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of a mixture of NaClO 3 and icing sugar—NaClO 3 /icing sugar mixture. The mixture was found to: be more sensitive than RDX but less sensitive than PETN in impact testing (180-grit sandpaper); be more sensitive than RDX and about the same sensitivity as PETN in BAM fiction testing; be less sensitive than RDX and PETN except for one participant found the mixture more sensitive than PETN in ABL ESD testing; and to have one to three exothermic features with the lowest temperature event occurring at ~ 160°C always observed in thermal testing. Variations in testing parameters also affected the sensitivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Carbon Storage Data Integration, Visualization and Application via EDX and GeoCube

Barkhurst, Aaron A.↗

DOE OSTI2020

Near-Real-Time Forecast of Satellite-Based Soil Moisture Using Long Short-Term Memory with an Adaptive Data Integration Kernel

Nowcasts, or near-real-time (NRT) forecasts, of soil moisture based on the Soil Moisture Active and Passive (SMAP) mission could provide substantial value for a range of applications including hazards monitoring and agricultural planning. To provide such a NRT forecast with high fidelity, we enhanced a time series deep learning architecture, long short-term memory (LSTM), with a novel data integration (DI) kernel to assimilate the most recent SMAP observations as soon as they become available. The kernel is adaptive in that it can accommodate irregular observational schedules. Testing over the CONUS, this NRT forecast product showcases predictions with unprecedented accuracy when evaluated against subsequent SMAP retrievals. It showed smaller error than NRT forecasts reported in the literature, especially at longer forecast latency. The comparative advantage was due to LSTM’s structural improvements, as well as its ability to utilize more input variables and more training data. The DI-LSTM was compared to the original LSTM model that runs without data integration, referred to as the projection model here. We found that the DI procedure removed the autocorrelated effects of forcing errors and errors due to processes not represented in the inputs, for example, irrigation and floodplain/lake inundation, as well as mismatches due to unseen forcing conditions. The effects of this purely data-driven DI kernel are discussed for the first time in the geosciences. Furthermore, this work presents an upper-bound estimate for the random component of the SMAP retrieval error.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Differential and Integral Data Evaluation for Titanium: An Application to Criticality Safety

The intent of this work is to highlight the role of differential and integral data evaluation to address issues in connection with criticality safety applications. Demonstration is made by using, as an example, differential data measurements and evaluation, and the benchmark integral experiments for titanium. Energy differential data are measured analyzed and evaluated to produce nuclear data libraries for criticality safety applications. Alternatively, integral experiments are performed at critical facilities, small experimental reactors, and play an important part in the validation of the differential nuclear data. The demonstration provided here for titanium gives its importance to criticality safety. Titanium is an effective neutron absorber that serves as baseline material for chemical separation in high-activity waste solutions in US. Titanium has not been considered for use in nuclear applications such as reactor design and analysis. Rather, it appears as a structural material that may be present in fuel cycle facilities or canisters for transport and disposition of nuclear waste. Criticality safety evaluations of systems in which titanium is present require an understanding of the nuclear data and its uncertainty.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

Nationwide Buildings Energy Research enabled through an integrated Data Intensive Scientific Workflow and Advanced Analysis Environment

Modern workflow systems enable scientists to run ensemble simulations at unprecedented scales and levels of complexity, allowing them to study system sizes previously impossible to achieve, due to the inherent resource requirements needed for the modeling work. However as a result of these new capabilities the science teams suddenly also face unprecedented data volumes that they are unable to analyze with their existing tools and methodologies in a timely fashion. In this paper we will describe the ongoing development work to create an integrated data intensive scientific workflow and analysis environment that offers researchers the ability to easily create and execute complex simulation studies and provides them with different scalable methods to analyze the resulting data volumes. The integration of simulation and analysis environments is hereby not only a question of ease of use, but supports fundamental functions in the correlated analysis of simulation input, execution details and derived results for multi-variant, complex studies. To this end the team extended and integrated the existing capabilities of the Velo data management and analysis infrastructure, the MeDICi data intensive workflow system and RHIPE the R for Hadoop version of the well-known statistics package, as well as developing a new visual analytics interface for the result exploitation by multi-domain users. The capabilities of the new environment are demonstrated on a use case that focusses on the Pacific Northwest National Laboratory (PNNL) building energy team, showing how they were able to take their previously local scale simulations to a nationwide level by utilizing data intensive computing techniques not only for their modeling work, but also for the subsequent analysis of their modeling results. As part of the PNNL research initiative PRIMA (Platform for Regional Integrated Modeling and Analysis) the team performed an initial 3 year study of building energy demands for the US Eastern Interconnect domain, which they are now planning to extend to predict the demand for the complete century. The initial study raised their data demands from a few GBs to 400GB for the 3year study and expected tens of TBs for the full century.

99 GENERAL AND MISCELLANEOUS↗

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↗