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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Automated Work Packages: Radio Frequency Identification, Bluetooth Beacons, and Video Applications in the Nuclear Power Industry

The need to move conventional paper-based work packages into an electronic state motivated the development of a large span of electronic work package forms that ranged from simple Portable Document Format (PDF) files to adaptive and intelligent electronic forms. In parallel to this development, the Department of Energy Light Water Reactor Sustainability Program (LWRS) initiated the automated work package as a pilot project to evaluate implementing state of the art automation techniques into the work package process to improve the economic and safety of the work process. Through a multiple year’s effort, the automated work package project have developed a vision of the future work package that relies on automation in all critical and human factor challenging tasks. The vision identified gaps in the work process, the means to automate them, and evaluated the implementation, feasibility and benefits of these means. This was conducted through continues engagement with the nuclear power industry. The aim of this report is to study the potential of three automation technologies, which have been advancing in various industries, in the current work process of nuclear power plants. The study is to determine the feasibility and benefits of incorporating the technologies and determine potential gaps, if any, that need to be addressed to facilitate deployment of the studied technologies. The three automation technologies identified for this effort are ultra-high frequency (UHF) radio frequency identification (RFID), Bluetooth low energy (BLE) beacons, and video monitoring and recording. As part of this effort, the Idaho National Laboratory (INL) collaborated with Xcel Energy Inc. to evaluate these technologies. During the research and development scope of the effort, INL engaged Xcel Energy Inc. periodically and exchanged valuable insight on the means to implement these technologies in a nuclear power plant. Multiple pilot prototypes were developed and tested in a user study conducted at Xcel Energy Inc. in Minneapolis, Minnesota. The outcome of this effort resulted in significant findings that included the detailed means to custom fit the technologies to fit the nuclear power industry need, and identifying and evaluating several applications of high economic or safety potential. The limitations and obstacles that could impact deployment of the technologies were also identified, and the means of how to address these limitations and obstacles were studied.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

The good, the bad, and the ugly: Data-driven load profile discord identification in a large building portfolio

Reducing the overall energy consumption and associated greenhouse gas emissions in the building sector is essential for meeting our future sustainability goals. Recently, smart energy metering facilities have been deployed to enable monitoring of energy consumption data with hourly or subhourly temporal resolution. This unprecedented data collection has created various opportunities for advanced data analytics involving load profiles (e.g., building energy benchmarking programs, building-to-grid integration, and calibration of urban-scale energy models). These applications often need preprocessing steps to detect daily load profile discords, such as: 1) outliers due to system malfunctions (the bad) and 2) irregular energy consumption patterns, such as those resulting from holidays (the ugly) compared to normal consumption patterns (the good). However, current preprocessing methods predominantly focus on filtering using statistical threshold values, which fail to capture the contextual discords of daily profiles. In addition, discord detection algorithms in building research are often aimed at finding individual building-level discords, which are not suitable at a large scale. Thus, here, we develop a method for automated load profile discord identification (ALDI) in a large portfolio of buildings (more than 100 buildings). Specifically, ALDI 1) uses the matrix profile (MP) method to quantify the similarities of daily subsequences in time series meter data, 2) compares daily MP values with typical-day MP distributions using the Kolmogorov-Smirnov test, and 3) identifies daily load profile discords in a large building portfolio. We evaluate ALDI using the metering data of both an academic campus and a residential neighborhood. Our results demonstrate that ALDI efficiently discovers measurement errors by system malfunctions and low energy consumption days in the academic campus portfolio, and it detects unique load shape patterns likely driven by occupant behavior and extreme weather conditions in the residential neighborhood.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Managing complexity in simulations of land surface and near-surface processes

Increasing computing power and the growing role of simulation in Earth systems science have led to an increase in the number and complexity of processes in modern simulators. We present a multiphysics framework that specifies interfaces for coupled processes and automates weak and strong coupling strategies to manage this complexity. Process management is enabled by viewing the system of equations as a tree, where individual equations are associated with leaf nodes and coupling strategies with internal nodes. A dynamically generated dependency graph connects a variable to its dependencies, streamlining and automating model evaluation, easing model development, and ensuring models are modular and flexible. Additionally, the dependency graph is used to ensure that data requirements are consistent between all processes in a given simulation. Here we discuss the design and implementation of these concepts within the Arcos framework, and demonstrate their use for verification testing and hypothesis evaluation in numerical experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Toward digital design at the exascale: An overview of project ICECap

High performance computing has entered the Exascale Age. Capable of performing over 1018 floating point operations per second, exascale computers, such as El Capitan, the National Nuclear Security Administration's first, have the potential to revolutionize the detailed in-depth study of highly complex science and engineering systems. However, in addition to these kind of whole machine “hero” simulations, exascale systems could also enable new paradigms in digital design by making petascale hero runs routine. Currently, untenable problems in complex system design, optimization, model exploration, and scientific discovery could all become possible. Motivated by the challenge of uncovering the next generation of robust high-yield inertial confinement fusion (ICF) designs, project ICECap (Inertial Confinement on El Capitan) attempts to integrate multiple advances in machine learning (ML), scientific workflows, high performance computing, GPU-acceleration, and numerical optimization to prototype such a future. Built on a general framework, ICECap is exploring how these technologies could broadly accelerate scientific discovery on El Capitan. In addition to our requirements, system-level design, and challenges, we describe some of the key technologies in ICECap, including ML replacements for multiphysics packages, tools for human-machine teaming, and algorithms for multifidelity design optimization under uncertainty. As a test of our prototype pre-El Capitan system, we advance the state-of-the art for ICF hohlraum design by demonstrating the optimization of a 17-parameter National Ignition Facility experiment and show that our ML-assisted workflow makes design choices that are consistent with physics intuition, but in an automated, efficient, and mathematically rigorous fashion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Performance Monitoring using Pecos (V.0.1)

Advances in sensor technology have rapidly increased our ability to monitor natural and human-made physical systems. In many cases, it is critical to process the resulting large volumes of data on a regular schedule and alert system operators when the system has changed. Automated quality control and performance monitoring can allow system operators to quickly detect performance issues. Pecos is an open source python package designed to address this need. Pecos includes built-in functionality to monitor performance of time series data. The software can be used to automatically run a series of quality control tests and generate customized reports which include performance metrics, test results, and graphics. The software was developed specifically for solar photovoltaic system monitoring, and is intended to be used by industry and the research community. The software can easily be customized for other applications. The following Pecos documentation includes installation instructions and examples, description of software features, and software license. It is assumed that the reader is familiar with the Python Programming Language. References are included for additional background on software components.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Agilent AgileBioFoundry CRADA (Final Report)

The mission of this CRADA with Agilent was to couple powerful MS platforms (QQQ, IM-QTOF-MS) with Agilent’s novel Ultra-High-Performance Liquid Chromatography (UHPLC) fast metabolomic workflows and perform ABF Machine Learning (ML) to generated datasets. Agilent transferred UHPLC methods to PNNL and LBNL and methods were implemented and demonstrated in both labs, achieving total acquisition times of < 10 min. Metabolites analyzed using Agilent’s shared methods included metabolites from central carbon metabolism, common across hosts, and metabolites unique to engineered strains. Standards were acquired in an UHPLC-Drift Tube Ion Mobility Mass Spectrometer (DTIMS) system for the first time within the context of ABF and methods were optimized based on Agilent’s protocols. Samples from ABF hosts Pseudomonas putida, Aspergillus pseudoterreus, Aspergillus niger and Rhodosporidium toruloides were analyzed using the UHPLC-DTIMS platform for a total of 276 runs. A data analysis workflow compatible with the Experimental Data Depot (EDD) and completely shareable was developed for the acquired UHPLC-DTIMS data. Samples were analyzed using a Data Independent Acquisition Approach (DIA), which for most of the standards provided more transitions therefore increasing detection confidence. Using the data acquired by PNNL, LBNL, and Agilent’s specifications from previous ML projects, SNL applied an ensemble ML strategy to pick the best performing model for automated LC-method selection. Finally, with the contribution of the participant labs and Agilent, SNL developed an Automated Method Selection (AMS) software tool to predict the best liquid chromatography method for analysis of any new molecules of interest. Samples with novel pathways and new metabolite targets of interest are generated at a high pace in the ABF. Therefore, our accomplishment in this CRADA improved the efficiency and accuracy of strain testing by developing and implementing fast analytical methods, robust processing tools, and software for predicting the best methods for UHPLC analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data Management for Digital Twin Implementation: Enhancing Existing SCADA Architecture for INL's CITRC Test Distribution System

The United States power grid will continue to experience stress from aging infrastructure, extreme weather, and increasing loads. In order to strengthen resiliency, researchers need to run tests and simulations that model real-life infrastructure. Idaho National Laboratory (INL) is creating a digital twin of its Critical Infrastructure Test Range Complex (CITRC). CITRC is an at-scale grid testbed which can be configured in utility-realistic distribution scenarios for a variety of tests, such as advanced grid protection and control. A digital twin of this infrastructure would support in-depth tests/simulations without risking physical consequences, before trialing devices under test at-scale. This project focuses on the data acquisition part of constructing a digital twin. It investigates the Supervisory Data Acquisition and Control (SCADA) system of CITRC and explores ways to utilize this system for the twin. Future “ideal” at-scale implementations such as upgraded equipment, modern communication protocols, and automation applications are also explored.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Microfluidic-Based Robotic Sampling System for Radioactive Solutions

A novel microfluidic based robotic sampling system has been developed for sampling and analysis of liquid solutions in nuclear processes. This system couples the use of a microfluidic sample chip with a robotic system designed to allow remote, automated sampling of process solutions in-cell and facilitates direct coupling of the microfluidic sample chip with analytical instrumentation. This system provides the capability for near real time analysis, reduces analytical waste, and minimizes the potential for personnel exposure associated with traditional sampling methods. A prototype sampling system was designed, built and tested. System testing demonstrated operability of the microfluidic based sample system and identified system modifications to optimize performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Protein identification from electron cryomicroscopy maps by automated model building and side-chain matching

Using single-particle electron cryo-microscopy (cryo-EM), it is possible to obtain multiple reconstructions showing the 3D structures of proteins imaged as a mixture. Here, it is shown that automatic map interpretation based on such reconstructions can be used to create atomic models of proteins as well as to match the proteins to the correct sequences and thereby to identify them. This procedure was tested using two proteins previously identified from a mixture at resolutions of 3.2 Å, as well as using 91 deposited maps with resolutions between 2 and 4.5 Å. The approach is found to be highly effective for maps obtained at resolutions of 3.5 Å and better, and to have some utility at resolutions as low as 4 Å.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Robot-Powered Reliability Testing at NREL's ESIF

With auto manufacturers expected to roll out fuel cell electric vehicles in the 2015 to 2017 timeframe, the need for a reliable hydrogen fueling infrastructure is greater than ever. That's why the National Renewable Energy Laboratory (NREL) is using a robot in its Energy Systems Integration Facility (ESIF) to assess the durability of hydrogen fueling hoses, a largely untested-and currently costly-component of hydrogen fueling stations. The automated machine mimics the repetitive stress of a human bending and twisting the hose to refuel a vehicle-all under the high pressure and low temperature required to deliver hydrogen to a fuel cell vehicle's onboard storage tank.

08 HYDROGEN↗
DOE OSTI2016

Streamlining the Design-to-Build Transition with Build-Optimization Software Tools

Scaling-up capabilities for the design, build, and test of synthetic biology constructs holds great promise for the development of new applications in fuels, chemical production, or cellular-behavior engineering. Construct design is an essential component in this process; however, not every designed DNA sequence can be readily manufactured, even using state-of-the-art DNA synthesis methods. Current biological computer-aided design and manufacture tools (bioCAD/CAM) do not adequately consider the limitations of DNA synthesis technologies when generating their outputs. Designed sequences that violate DNA synthesis constraints may require substantial sequence redesign or lead to price-premiums and temporal delays, which adversely impact the efficiency of the DNA manufacturing process. In this paper, we have developed a suite of build-optimization software tools (BOOST) to streamline the design-build transition in synthetic biology engineering workflows. BOOST incorporates knowledge of DNA synthesis success determinants into the design process to output ready-to-build sequences, preempting the need for sequence redesign. The BOOST web application is available at https://boost.jgi.doe.gov and its Application Program Interfaces (API) enable integration into automated, customized DNA design processes. Finally, the herein presented results highlight the effectiveness of BOOST in reducing DNA synthesis costs and timelines.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Development of a liquid-helium free cryogenic sample holder with mK temperature control for autonomous electron microscopy

The automated and autonomous cryogenic transmission electron microscopy (Cryo-EM) demands a sample holder capable of maintaining temperatures below 10 K with precise control, long holding times, and minimal helium use. Rising to this challenge, we initiated an ambitious project to develop a novel closed-cycle cryocooler-based cryogenic sample holder that operates without the use of liquid helium and the consumption of gaseous helium. Here, this article presents the design, construction, and experimental testing of the initial prototype, which achieves an ultimate temperature of 5.6 K with exceptional stability close to 1mK, while providing a wide temperature control range from 295 K to 5.6 K, marking a clear advancement in cryo-EM holder development. While the prototype was not designed for atomic resolution imaging and thus lacks a sturdy support system to mitigate mechanical vibrations from the cryocooler's pulsed tube, this innovative approach successfully demonstrates proof of concept. It offers unprecedented capabilities for state-of-the-art cryogenic microscopy and microanalysis in materials and biological sciences.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Dual-Zone Solar Control Indoor Shade: Demonstration at the Ronald V. Dellums Federal Building and U.S. Courthouse, 1301 Clay Street, Oakland, California and the Lawrence Berkeley National Laboratory Advanced Windows Testbed, Berkeley, California

Standard window shades are used to control sunlight, glare, window heat gains, and daylight. The challenge with conventional shades is that once the shades are lowered to reduce discomfort, daylight is reduced, which, in turn, increases the need for electric lighting. View is also obstructed, reducing the occupants’ connection to the outdoors. The strategy of subdividing the window wall and admitting daylight from above and controlling sunlight and view through the lower aperture can yield significant energy and peak demand savings over conventional shading systems, and improve the daylight quality of the indoor environment. This study evaluated a dual zone solar control (DZSC) shade with an upper, automated, horizontal, venetian blind with concave-up, matte white slats and a lower, manually operated, roller shade made of a transparent, reflective film. The automatic controls were designed to adjust the upper slat angle to maximize daylight to the room interior. The lower shade, when lowered, provided an unobstructed view to the outdoors. For the qualitative analysis, the DZSC shades were installed on windows in the southeast half of one floor in the Ronald V. Dellums Federal Building and U.S. Courthouse or hereafter referred to as the Oakland Federal Building (OFB) in Oakland, California. The position of the DZSC shades were observed and recorded periodically. Surveys were issued to occupants in the private offices and open plan workstations affected by the shades. For the quantitative analysis, the DZSC shades were installed in the south-facing windows of thermally isolated, fully instrumented, test chambers in the Advanced Windows Testbed at the Lawrence Berkeley National Laboratory (LBNL) in Berkeley, California. Measurements of window heat loads, daylight illuminance and environmental conditions related to visual and thermal comfort were collected over a six-month, solstice-to-solstice period. The performance of the DZSC shade was compared to fabric roller shades and venetian blinds since these are the two most common types of shades used in both commercial and Federal buildings. Several DZSC design permutations were evaluated: 1) manual or automated control of the upper louver system (“man” or “auto”) and 2) tinted or silvered reflective film for the lower shade (“Gray-Gray (GG)” or “Gray-Silver (GS)”1). The automated, reflective shade (auto-GS) reduced dimmable fluorescent lighting energy use by 51% and window cooling load by 13-15% compared to a conventional fabric roller shade with dual-pane, spectrally selective, low-e windows during the summer period (winter period was not measured). Qualitative analysis revealed that the auto-GS shade was preferred by 80% of the survey respondents compared to the existing vertical fabric blinds with single-pane, tinted windows in the occupied building. Survey results indicated that visual discomfort was reduced and thermal discomfort was also reduced during warm or hot weather. Occupants expressed greater satisfaction with the unobstructed view. Installation and commissioning of the DZSC shades was fairly straightforward with some minor problems due to inadequate installation instructions and improper wiring. A few occupants expressed dissatisfaction with the automatic controls for the upper louvers due to visual discomfort, erroneous control, and motor noise.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

3D camera assisted fully automated calibration of scanning laser Doppler vibrometers

Scanning laser Doppler vibrometers (LDV) are used to measure full-field vibration shapes of products and structures. In most commercially available scanning laser Doppler vibrometer systems the user manually draws a grid of measurement locations on a 2D camera image of the product. The determination of the correct physical measurement locations can be a time consuming and diffcult task. In this paper we present a new methodology for product testing and quality control that integrates 3D imaging techniques with vibration measurements. This procedure allows to test prototypes in a shorter period because physical measurements locations will be located automatically. The proposed methodology uses a 3D time-of-flight camera to measure the location and orientation of the test-object. The 3D image of the time-of-flight camera is then matched with the 3D-CAD model of the object in which measurement locations are pre-defined. A time of flight camera operates strictly in the near infrared spectrum. To improve the signal to noise ratio in the time-of-flight measurement, a time-of-flight camera uses a band filter. As a result of this filter, the laser spot of most laser vibrometers is invisible in the time-of-flight image. Therefore a 2D RGB-camera is used to find the laser-spot of the vibrometer. The laser spot is matched to the 3D image obtained by the time-of-flight camera. Next an automatic calibration procedure is used to aim the laser at the (pre)defined locations. Another benefit from this methodology is that it incorporates automatic mapping between a CAD model and the vibration measurements. This mapping can be used to visualize measurements directly on a 3D CAD model. Secondly the orientation of the CAD model is known with respect to the laser beam. This information can be used to find the direction of the measured vibration relatively to the surface of the object. With this direction, the vibration measurements can be compared more precisely with numerical experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Machine-learning-assisted insight into spin ice Dy 2 Ti 2 O 7

Complex behavior poses challenges in extracting models from experiment. An example is spin liquid formation in frustrated magnets like Dy 2 Ti 2 O 7 . Understanding has been hindered by issues including disorder, glass formation, and interpretation of scattering data. Here, we use an automated capability to extract model Hamiltonians from data, and to identify different magnetic regimes. This involves training an autoencoder to learn a compressed representation of three-dimensional diffuse scattering, over a wide range of spin Hamiltonians. The autoencoder finds optimal matches according to scattering and heat capacity data and provides confidence intervals. Validation tests indicate that our optimal Hamiltonian accurately predicts temperature and field dependence of both magnetic structure and magnetization, as well as glass formation and irreversibility in Dy 2 Ti 2 O 7 . The autoencoder can also categorize different magnetic behaviors and eliminate background noise and artifacts in raw data. Our methodology is readily applicable to other materials and types of scattering problems.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Apartment Compartmentalization With an Aerosol-Based Sealing Process

Air sealing of building enclosures is a difficult and time-consuming process. Current methods in new construction require laborers to physically locate small and sometimes large holes in multiple assemblies and then manually seal each of them. The innovation demonstrated under this research study was the automated air sealing and compartmentalization of buildings through the use of an aerosolized sealant, developed by the Western Cooling Efficiency Center at University of California Davis. CARB sought to demonstrate this new technology application in a multifamily building in Queens, NY. The effectiveness of the sealing process was evaluated by three methods: air leakage testing of overall apartment before and after sealing, point-source testing of individual leaks, and pressure measurements in the walls of the target apartment during sealing.

42 ENGINEERING↗