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At least 55 records · Page 3

Improving microstructures segmentation via pretraining with synthetic data

Image analysis of material microstructures through microscopy is an integral capability in the field of materials science. The topological and chemical information obtained through microscopy allow us to draw vital connections between material microstructures, properties, and processing. While scanning electron microscopy (SEM) is able to yield a considerable wealth of information interpretable by the intuition of experts, there has been considerable interest in using machine learning, convolutional neural networks (CNNs) in particular, for such image analysis task. Training CNNs for an image analysis task requires a large annotated dataset. However, in many materials science applications, obtaining a large annotated dataset is cost and labor intensive. In this work, we study the use of synthetic data to enlarge the available annotated experimental data of uranium oxide. We utilize a modified Potts model to simulate uranium oxide particles with morphologies similar to those observed experimentally. We then leverage an image-to-image translation model to synthesize the simulated particles as if they are acquired with SEM. Through this process, we obtain pairs of particle images and their corresponding SEM representations, which corresponds to pairs of annotations and images. Unlike previous works, we leverage synthetic data for pretraining a CNN model prior, and finetune that model further with experimental data. We experimentally demonstrate that using synthetic data as incremental learning process benefits the overall performance compared to training a model on combined synthetic and experimental data.

36 MATERIALS SCIENCE↗

GHEP WIBT (Guidelines for Home Energy Professionals Weatherization Installer Badges Toolkit) [SWR-20-69]

The National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy's (DOE) Weatherization Assistance Program (WAP) are collaborating with the home energy retrofit industry to support the development of skilled workers. The Installer Badges Toolkit provides a flexible, customizable, and voluntary approach to training and skills recognition for WAP implementers, utility programs, private-sector workers, and contractors. In Fiscal Year 2018, DOE, along with the Crew Leader scheme committee, determined the Retrofit Installer Technician (RIT) Job Task Analysis (JTA) could be eliminated and its tasks inserted in the Crew Leader JTA. The RIT tasks became the basis of the Installer Badges. The Badges Toolkit was updated in 2020 to add licensing and copyright agreements. Users must cite the copyright information when using or distributing copies of the Badges Toolkit in any way. The technical content has remained unchanged from previous versions of the Badges Toolkit. The Toolkit for home retrofits consists of 25 Badges, each representing different energy efficiency tasks that an installer could perform on a home. Each Badge defines the desired outcome, criteria to verify, applicable material requirements, and references to Standard Work Specifications (SWS) or other relevant standards. The Badges provide a consistent approach to training by ensuring that installers in different regions are learning the same skills nationwide. Organizations can also customize the Toolkit by choosing only those Badges that are relevant to their program. The Badges Toolkit includes five pieces: "How to Use the Badges Toolkit" provides a brief overview of how a Grantee, Subgrantee, or training provider may approach using the toolkit. The "Badges Toolkit: Worksheet" includes what to consider when determining whether and how to best incorporate the Badges into a weatherization assistance program. The "Crew Leader Job Task Analysis Spreadsheet" indicates how the Badges align with specific areas of the JTA. The "Installer Badges Passport" features separate pages for each Badge, which include places for the installer and the supervisor/trainer to record the number of times a task has been successfully completed. The "Installer Badges Verification Criteria" includes sample inspection checklists for each Badge. These can be modified as needed based on approved variance requests or more stringent requirements. They also provide a basis for consistent inspections and awarding of Badges. Note: All elements of the Badges Toolkit are designed for use by potential program implementers. They are not off-the-shelf products intended for immediate deployment. Program implementers must review and modify as needed, revise verification criteria to match local requirements, complete worksheets, and otherwise define the parameters of their own badging program.

Desai, Jal↗

GeoVision Analysis Supporting Task Force Report: Electric Sector Potential to Penetration

This report describes research and analysis performed in support of the U.S. Department of Energy Geothermal Technologies Office for its Geothermal Vision Study. A summary of the study is captured in DOE’s report, GeoVision: Harnessing the Heat Beneath Our Feet and included ground-breaking, detailed research on geothermal technologies. The study projects and quantifies the future electric and nonelectric deployment potentials of these geothermal technologies within a range of scenarios in addition to their impacts on U.S. jobs, the economy, and environment. Coordinated by the U.S. Department of Energy Geothermal Technologies Office, the Geothermal Vision Study development relied on collecting, modeling, and analyzing robust data sets through seven national laboratory partners that were organized into eight technical task force groups. These task forces and their respective principal leading national laboratory are listed in Table F-1. The table also provides a guide to the final research documents produced by each GeoVision task force. In most cases, these were prepared as laboratory reports, and they are referenced accordingly. Consult these external reports for detailed discussions of the topics contained within, which form the basis of the GeoVision analysis.

15 GEOTHERMAL ENERGY↗

A General Framework for Progressive Data Compression and Retrieval

In scientific simulations, observations, and experiments, the transfer of data to and from disk and across networks has become a major bottleneck for data analysis and visualization. Compression techniques have been employed to tackle this challenge, but traditional lossy methods often demand conservative error tolerances to meet the numerical accuracy requirements of both anticipated and unknown data analysis tasks. Progressive data compression and retrieval has emerged as a promising solution, where each analysis task dictates its own accuracy needs. However, few analysis algorithms inherently support progressive data processing, and adapting compression techniques, file formats, client/server frameworks, and APIs to support progressivity can be challenging. Here, this paper presents a framework that enables progressive-precision data queries for any data compressor or numerical representation. Our strategy hinges on a multi-component representation that successively reduces the error between the original and compressed field, allowing each field in the progressive sequence to be expressed as a partial sum of components. We have implemented this approach with four established scientific data compressors and assessed its effectiveness using real-world data sets from the SDRBench collection. The results show that our framework competes in accuracy with the standalone compressors it is based upon. Additionally, (de)compression time is proportional to the number of components requested by the user. Finally, our framework allows for fully lossless compression using lossy compressors when a sufficient number of components are employed.

97 MATHEMATICS AND COMPUTING↗

ABF Past Accomplishments - TEA/LCA

The Integrated Analysis task in the Agile BioFoundry (ABF) conducts techno-economic analysis (TEA) and life cycle assessment (LCA) to quantify the economics and environmental impacts of bioprocesses under development. The team from Argonne National Laboratory (ANL) and the National Renewable Energy Laboratory (NREL) develops TEA and LCA models of selected compound targets and hosts of interest to the ABF in an effort to provide an analysis-based foundation to the R&D. To date, the Integrated Analysis task has performed process modeling and analyses on multiple pairings of bioproducts and hosts, centered around major metabolic "beachheads" and "exemplar" molecules chosen for each of the metabolic pathways of interest. This presentation provides an overview of the approach used for TEA and LCA in the ABF and of the progress, outcomes, and impacts of TEA and LCA to support ABF goals, with a focus towards developing bio-based products that are both environmentally and economically viable.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

North American Board of Certified Energy Practitioners Final Report

The U.S. DOE’s Office of EERE National Solar Energy Technology Program (SETP) calls for a “National Accreditation and Certification Program for Installation and Acceptance of Photovoltaic Systems.” A near-term goal listed in the U.S. Photovoltaic Industry’s Roadmap, 2000 - 2020 is to work to establish standards, codes, and certifications which are essential for consumer protection and acceptance as part of the goal of building toward a viable future PV industry. This program paves the way for a voluntary national certification program for PV system practitioners and installers, initiation of the first steps toward certification of hardware, and reinforcement of all five of the technical objectives in the Systems category of SETPs Multi-Year technical Plan. Through this project, NABCEP will direct the continued initiation of and sustained implementation and administration of the NABCEP Solar PV Installer Certification Program (hereafter the “Program”). The NABCEP Program is a national, voluntary program designed to provide certification for those PV installers who demonstrate the requisite skills, abilities and knowledge typically required to install and maintain PV systems. The core document upon which the Program was developed and upon which the national exam is based, is referred to as the (Program) Task Analysis. It is a thorough descriptive document containing specific psychomotor and cognitive tasks for the purposes of identifying the types of training/assessment methods that apply. Psychomotor skills require measuring, assembling, fastening and related activities. Cognitive skills require knowledge processing, decision-making and computations. NABCEP effectively evaluates an applicant’s psychomotor skills through review of a candidate’s PV installations and hands-on training received. NABCEP evaluates the candidate’s cognitive skills through administration of its national Program exam. By first qualifying for and then obtaining the required passing score, NABCEP certificants receive an accreditation that upholds NABCEP’s standards of quality, compliance to applicable codes and safety in PV installation. The objectives of DOE’s National Solar Energy Technology Program (SETP) are intrinsic to NABCEP. As detailed in the PV Roadmap, the lifespan of a PV system is a function of reliability and value. PV system reliability is directly dependent upon the quality of components and, design, installation and maintenance of a system. The latter three are all core components of the NABCEP Task Analysis - accordingly NABCEP certified installers will be instrumental in improving reliability of systems through safe, code and manufacturer-compliant installation and necessary post-installation maintenance of PV systems. This will have the effect of ensuring and increasing the performance of installed systems and, as consumers realize the benefits of well-installed and maintained systems, increased demand will follow and manufacturers will respond - supporting further growth in the PV industry. Furthermore, as more NABCEP certified installers perform these installations and maintenance competently, additional installations (whole system re-installations) and unnecessary repairs can be avoided. This will drive down system costs. This combined with creation/enhancement of the DE-FG36-04GO14348/005 NABCEP Central Data Base of Installers – providing consumers with installation/maintenance service options will further reduce system costs and help meet the overall goal of reducing life cycle costs. As consumers receive more value from PV systems which are providing longer, trouble free, renewable energy, they will join the ranks of professionals and enthusiasts calling for reduced technological barriers to installation (particularly for grid-tied systems). States and utilities will react to pressure and begin easing onerous net-metering and other technological restrictions. The benefits of NABCEP’s Program will be evident to consumers, manufacturers, distributors, state energy officials and solar academic institutions. Consumers benefit through increased system performance and reduced costs. Manufacturers of PV and balance of system components as well as distributors support and benefit from NABCEP because of assurances that systems are installed in accordance to code (i.e., NEC) and their specifications, resulting in longer life. Collaborators including state energy officials (i.e., New York State Energy Research and Development Authority) benefit by knowing that rebate funds are spent on systems whose benefits will far exceed system costs. Program Objectives The improvements and advantages offered by a national voluntary certification program can only expand the horizons for photovoltaic applications.

14 SOLAR ENERGY↗

Analytic Steering: Inserting Context into the Information Dialog

An analyst’s intrinsic domain knowledge is a primary asset in almost any analysis task. Unstructured text analysis systems that apply un-supervised content analysis approaches can be more effective if they can leverage this domain knowledge in a manner that augments the information discovery process without obfuscating new or unexpected content. Current unsupervised approaches rely upon the prowess of the analyst to submit the right queries or observe generalized document and term relationships from ranked or visual results. We propose a new approach which allows the user to control or steer the analytic view within the unsupervised space. This process is controlled through the data characterization process via user supplied context in the form of a collection of key terms. We show that steering with an appropriate choice of key terms can provide better relevance to the analytic domain and still enable the analyst to uncover un-expected relationships; this paper discusses cases where various analytic steering approaches can provide enhanced analysis results and cases where analytic steering can have a negative impact on the analysis process.

Steering↗

GeoVision Analysis Supporting Task Force Report: Thermal Applications-Quantifying Technical, Economic, and Market Potential of Geothermal District Heating Systems in the United States

This report describes research and analysis performed in support of the U.S. Department of Energy Geothermal Technologies Office for its Geothermal Vision Study. A summary of the study is captured in DOE’s report, GeoVision: Harnessing the Heat Beneath Our Feet and included ground-breaking, detailed research on geothermal technologies. The study projects and quantifies the future electric and nonelectric deployment potentials of these geothermal technologies within a range of scenarios in addition to their impacts on U.S. jobs, the economy, and environment. Coordinated by the U.S. Department of Energy Geothermal Technologies Office, the Geothermal Vision Study development relied on collecting, modeling, and analyzing robust data sets through seven national laboratory partners that were organized into eight technical task force groups. These task forces and their respective principal leading national laboratory are listed in Table F-1. The table also provides a guide to the final research documents produced by each GeoVision task force. In most cases, these were prepared as laboratory reports, and they are referenced accordingly. Consult these external reports for detailed discussions of the topics contained within, which form the basis of the GeoVision analysis.

15 GEOTHERMAL ENERGY↗

Empirical Study of Focus-Plus-Context and Aggregation Techniques for the Visualization of Streaming Data

Analysis of streaming data often involves both real-time monitoring of incoming data as well as contextual awareness of data history. A focus-plus-context approach can support both goals, with variable levels of visual aggregation making it possible to provide a high level of detail for incoming and recent data while providing contextual information about recent history. Visual aggregation reduces data resolution in order to show the context of data over large periods of time within a limited display space. With a controlled experiment, we evaluated the effectiveness of different types of aggregation for four types of stream-analysis tasks. Overall, the results show that a focus-plus-context design has little negative impact on the ability to successfully monitor and analyze streaming data, making it possible to show longer periods of time than other approaches. However, visual aggregation can be problematic for trend recognition tasks. This research demonstrates how the effectiveness of the visualization depends on the specifics of the analysis task.

Ragan, Eric↗

GeoVision Analysis Supporting Task Force Report: Impacts-The Employment Opportunities, Water Impacts, Emission Reductions, and Air Quality Improvements of Achieving High Penetrations of Geothermal Power in the United States

This report describes research and analysis performed in support of the U.S. Department of Energy Geothermal Technologies Office for its Geothermal Vision Study. A summary of the study is captured in DOE’s report, GeoVision: Harnessing the Heat Beneath Our Feet and included ground-breaking, detailed research on geothermal technologies. The study projects and quantifies the future electric and nonelectric deployment potentials of these geothermal technologies within a range of scenarios in addition to their impacts on U.S. jobs, the economy, and environment. Coordinated by the U.S. Department of Energy Geothermal Technologies Office, the Geothermal Vision Study development relied on collecting, modeling, and analyzing robust data sets through seven national laboratory partners that were organized into eight technical task force groups. These task forces and their respective principal leading national laboratory are listed in Table F-1. The table also provides a guide to the final research documents produced by each GeoVision task force. In most cases, these were prepared as laboratory reports, and they are referenced accordingly. Consult these external reports for detailed discussions of the topics contained within, which form the basis of the GeoVision analysis.

15 GEOTHERMAL ENERGY↗

GeoVision Analysis: Exploration Task Force Report

The GeoVision study effort included ground-breaking, detailed research on current and future market conditions and geothermal technologies in order to forecast and quantify the electric and non-electric deployment potentials under a range of scenarios, in addition to their impacts on the Nation’s jobs, economy and environment. Coordinated by the U.S. Department of Energy’s (DOE’s) Geothermal Technologies Office (GTO), the GeoVision study development relied on the collection, modeling, and analysis of robust datasets through seven national laboratory partners, which were organized into eight technical Task Force groups. The purpose of this report is to provide a central repository for the research conducted by the Exploration Task Force. The Exploration Task Force consists of four individuals representing three national laboratories: Patrick Dobson (task lead) and Christine Doughty of Lawrence Berkeley National Laboratory, Anna Wall of National Renewable Energy Laboratory, Travis McLing of Idaho National Laboratory, and Chester Weiss of Sandia National Laboratories. As part of the GeoVision analysis, our team conducted extensive scientific and financial analyses on a number of topics related to current and future geothermal exploration methods. The GeoVision Exploration Task Force complements the drilling and resource technology investigations conducted as part of the Reservoir Maintenance and Development Task Force. The Exploration Task Force however has focused primarily on early stage R&D technologies in exploration and confirmation drilling, along with an evaluation of geothermal financing challenges and assumptions, and innovative “blue-sky” technologies. This research was used to develop geothermal resource supply curves (through the use of GETEM) for use in the ReEDS capacity expansion modeling that determines geothermal technology deployment potential. It also catalogues and explores the large array of early-stage R&D technologies with the potential to dramatically reduce exploration and geothermal development costs, forming the basis of the GeoVision Technology Improvement (TI) scenario. These modeling topics are covered in detail in Potential to Penetration task force report. Most of the research contained herein has been published in peer-reviewed papers or conference proceedings and are cited and referenced accordingly. The sections that follow provide a central repository for all of the research findings of the Exploration and Confirmation Task Force. In summary, it provides a comprehensive discussion of Engineered Geothermal Systems (EGS) and associated technology challenges, the risks and costs of conducting geothermal exploration, a review of existing government efforts to date in advancing early-stage R&D in both exploration and EGS technologies, as well as a discussion of promising and innovative technologies and implementation of blue-sky concepts that could significantly reduce costs, lower risks, and shorten the time needed to explore and develop geothermal resources of all types.

15 GEOTHERMAL ENERGY↗

Near real-time streaming analysis of big fusion data

Experiments on fusion plasmas produce high-dimensional data time series with ever-increasing magnitude and velocity, but turn-around times for analysis of this data have not kept up. For example, many data analysis tasks are often performed in a manual, ad-hoc manner some time after an experiment. In this article, we introduce the Delta framework that facilitates near real-time streaming analysis of big and fast fusion data. By streaming measurement data from fusion experiments to a high-performance compute center, Delta allows computationally expensive data analysis tasks to be performed in between plasma pulses. This article describes the modular and expandable software architecture of Delta and presents performance benchmarks of individual components as well as of an example workflow. Focusing on a streaming analysis workflow where electron cyclotron emission imaging (ECEi) data is measured at KSTAR on the National Energy Research Scientific Computing Center's (NERSC's) supercomputer we routinely observe data transfer rates of about 4 Gigabit per second. In NERSC, a demanding turbulence analysis workflow effectively utilizes multiple nodes and graphical processing units and executes them in under 5 min. We further discuss how Delta uses modern database systems and container orchestration services to provide web-based real-time data visualization. For the case of ECEi data we demonstrate how data visualizations can be augmented with outputs from machine learning models. Here, by providing session leaders and physics operators, results of higher-order data analysis using live visualizations may make more informed decisions on how to configure the machine for the next shot.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Top-down and bottom-up definitions of human failure events in human reliability analysis

In the probabilistic risk assessments (PRAs) used in the nuclear industry, human failure events (HFEs) are determined as a subset of hardware failures, namely those hardware failures that could be triggered by human action or inaction. This approach is top-down, starting with hardware faults and deducing human contributions to those faults. Elsewhere, more traditionally human factors driven approaches would tend to look at opportunities for human errors first in a task analysis and then identify which of those errors is risk significant. The intersection of top-down and bottom-up approaches to defining HFEs has not been carefully studied. Ideally, both approaches should arrive at the same set of HFEs. This question is crucial, however, as human reliability analysis (HRA) methods are generalized to new domains like oil and gas. The HFEs used in nuclear PRAs tend to be top-down—defined as a subset of the PRA—whereas the HFEs used in petroleum quantitative risk assessments (QRAs) often tend to be bottom-up—derived from a task analysis conducted by human factors experts. The marriage of these approaches is necessary in order to ensure that HRA methods developed for top-down HFEs are also sufficient for bottom-up applications.

02 PETROLEUM↗

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation and data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.

97 MATHEMATICS AND COMPUTING↗

Home Energy Professionals Certifications ISO/IEC 17024: 2021 Policies and Procedures Manual

The U.S. Department of Energy (DOE) enlisted its National Renewable Energy Laboratory (NREL) to coordinate the development of a framework for new certifications in the weatherization and home performance industry. The Home Energy Professional certifications support DOE's Weatherization Assistance Program (WAP) and the broader residential home performance industry through the credentialing process of defined job task analysis for energy auditors and quality control inspectors. The HEP certifications are not intended to supplant or infringe upon any existing industry-recognized credentials, however, the WAP and the home performance industry have utilized the advanced HEP certifications to promote quality work and standardized job task analysis since 2010. On an ongoing basis, NREL brings industry practitioners and subject matter experts together to develop, review, and revise the certification schemes in accordance with the International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC) 17024 standard, "Conformity assessment - General requirements for bodies operating certification of persons" (ISO/IEC 17024). This handbook covers the policies and procedures for the process of developing, maintaining, and validating the certification schemes. Each policy and procedure includes the relevant ISO/IEC 17024 section at the beginning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Expediting Scientific Data Analysis with Reorganization of Data

Data producers typically optimize the layout of data files to minimize the write time. In most cases, data analysis tasks read these files in access patterns different from the write patterns causing poor read performance. In this paper, we introduce Scientific Data Services (SDS), a framework for bridging the performance gap between writing and reading scientific data. SDS reorganizes data to match the read patterns of analysis tasks and enables transparent data reads from the reorganized data. We implemented a HDF5 Virtual Object Layer (VOL) plugin to redirect the HDF5 dataset read calls to the reorganized data. To demonstrate the effectiveness of SDS, we applied two parallel data organization techniques: a sort-based organization on a plasma physics data and a transpose-based organization on mass spectrometry imaging data. We also extended the HDF5 data access API to allow selection of data based on their values through a query interface, called SDS Query. We evaluated the execution time in accessing various subsets of data through existing HDF5 Read API and SDS Query. We showed that reading the reorganized data using SDS is up to 55X faster than reading the original data.

97 MATHEMATICS AND COMPUTING↗

Intrusion Detection System Alarm Station Operator Interface Improvements

To address Alarm Station operator performance, Portable Intrusion Detection System team gathered information concerning AS operator data needs when assessing alarms. The purpose was to improve the Portable Intrusion Detection System operator interface to ensure that critical information was quickly presented and easily accessible. To gather the data, the team used a Goal Directed Task Analysis approach. The method of analysis was to prepare a set of interview questions, interview selected AS operator experts, conduct the interviews, create a goal/decision/information hierarchy based on information gathered, and then apply the results to the operator interface. In applying the results, the team had to consider not only the Goal Directed Task Analysis -determined information needs of the Alarm Station operator end-user population, but also account for customer requirements and differences in domain. The constraints in implementing all situation awareness recommendations are summarized and initial potential solutions presented.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗