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This presentation provides updates to the SEPA cybersecurity working group related to IEEE 1547.3 Guide for DER Cybersecurity, DOE Laboratory Coordination Committee, and other standards development efforts.
Building simulations are increasingly used in various applications related to energy efficient buildings. For individual buildings, applications include: design of new buildings, prediction of retrofit savings, ratings, performance path code compliance and qualification for incentives. Beyond individual building applications, larger scale applications (across the stock of buildings at various scales: national, regional and state) include: codes and standards development, utility program design, regional/state planning, and technology assessments. For these sorts of applications, a set of representative buildings are typically simulated to predict performance of the entire population of buildings. Focusing on the U.S. single-family residential building stock, this paper will describe how multiple data sources for building characteristics are combined into a highly-granular database that preserves the important interdependencies of the characteristics. We will present the sampling technique used to generate a representative set of thousands (up to hundreds of thousands) of building models. We will also present results of detailed calibrations against building stock consumption data.
¦1: Data, Design Methodology and Construction 1.1: Graphite Selection and Acquisition Strategy (Original tasks completed) 1.2: Graphite Properties (Virgin Materials) 1.3: Graphite Fracture Behaviour(Original tasks completed) 1.4: Graphite Oxidation Behaviour(Original tasks completed) 1.5: Graphite Component Testing 1.6: Graphite Irradiation Effects 1.7: Graphite Irradiation Induced Creep 1.8: Graphite Codes and Standards Development (ASME & ASTM) 1.9: Graphite BehaviourModels Development 1.10: Links to Existing Graphite Irradiation BehaviourDatabases 1.11: Materials Database ¦2: Operation and Inspection 2.1: Methodologies for determining requirements for inspection of graphite cores 2.2: Methodologies for ISI of graphite cores ¦3: Decommissioning and Disposal (New task added 2021) 3.1: Technical data for decommissioning and disposal issues
Developing new insulation materials having a thermal resistivity greater than 69 m K/W (10 hr ft2 °F/Btu/inch) can be appealing for building envelope retrofit and construction of new buildings. Multiple institutions are involved in the development of innovative insulation materials with high thermal resistivity. However, these projects have struggled in the development of new materials due to the difficulty associated with the measurement of small sections of high thermal resistivity materials. As new materials are being developed, the size of each test specimen impacts the cost of development. Given the lack of a reliable method to measure the thermal resistivity on small samples of such materials, we evaluated experimental techniques that can be improved to satisfy the need for testing small sections of high thermal resistivity materials and developed standardized test methods to enable the rapid thermal evaluation of advanced insulation materials. This paper presents the study results and potential techniques for fast, accurate, and reliable effective thermal resistivity measurement on small samples of insulation materials.
In this session at the SETO Peer Review, several solar cybersecurity projects will be discussed. INL will provide an overview of the multi-lab Securing Solar for the Grid (S2G) project. We will highlight the focus areas of standards development and best practices, cybersecurity tool kits and supply chain analysis, and education and workforce development.
Graph neural networks (GNNs) have emerged as one of the most effective Machine learning (ML) techniques for drug effect prediction from drug molecular graphs. Despite having immense potential, GNN models lack performance when using data sets that contain high dimensional asymmetrically co-occurrent drug effects as targets with complex correlations between them. Training individual learning models for each drug effect and incorporating every prediction result for a wide spectrum of drug effects is beyond practicality. Such an implication provides a testbed to address this challenge as multi-target prediction problems, aiming to predict all drug effects at a time. We develop standard and hybrid graph neural networks (GNNs)to perform two separate tasks that are multi-regression for continuous values and multi-label classification for categorical values contained in our data sets. Since this step makes the target data even more sparse and introduces asymmetric label co-occurrence, the learning of multi-label classification models becomes difficult and heavily impacts the GNN's performance. To address these challenges, we propose a new data oversampling technique to improve multi-label classification performances on all the given imbalanced molecular graph data sets. Using the technique, we improve the data imbalance ratio of the drug effects better than before while protecting the data set's integrity. Finally, we evaluate multi-label classification performance using the best-performant hybrid GNN model on all the oversampled data sets obtained from the proposed oversampling technique. These results outperform those of other ML models including GNN models when they are trained on the original data sets or oversampled data sets using MLSMOTE (a well-known oversampling technique) in all evaluation metrics precision, recall, and F1 score by a significant margin.
Process-oriented diagnostics (PODs) aim to provide feedback for model developers through model analysis based on physical hypotheses. However, the step from a diagnostic based on relationships among variables, even when hypothesis driven, to specific guidance for revising model formulation or parameterizations can be substantial. The POD may provide more information than a purely performance-based metric, but a gap between POD principles and providing actionable information for specific model revisions can remain. Furthermore, in coordinating diagnostics development, there is a trade-off between freedom for the developer, aiming to capture innovation, and near-term utility to the modeling center. Best practices that allow for the former, while conforming to specifications that aid the latter, are important for community diagnostics development that leads to tangible model improvements. Promising directions to close the gap between principles and practice include the interaction of PODs with perturbed physics experiments and with more quantitative process models as well as the inclusion of personnel from modeling centers in diagnostics development groups for immediate feedback during climate model revisions. Examples are provided, along with best-practice recommendations, based on practical experience from the NOAA Model Diagnostics Task Force (MDTF). Common standards for metrics and diagnostics that have arisen from a collaboration between the MDTF and the Department of Energy’s Coordinated Model Evaluation Capability are advocated as a means of uniting community diagnostics efforts.
The nuclear criticality safety (NCS) consensus standards are developed as using rigorous procedures of the Standards Board of the American Nuclear Society. These procedures have been accredited by the American National Standards Institute, Inc., as meeting the criteria for American National Standards. The Nuclear Criticality Safety Consensus Committee (NCSCC) that approved all 18 NCS consensus standards is balanced to ensure that competent, concerned, and varied interests have had an opportunity to participate. The ANS-8 subcommittee (ANS-8) consists of 17 NCS experts with many years of experience as end users of ANS standards who serve on standard working groups to develop and maintain standards. ANS-8 ensures that the technical content of the standards is adequate for NCS community use. Attempts are made to ensure that ANS-8 consists of NCS professionals with a diverse range of experience such that all standards are applicable to as many sites as possible. ANS-8 is a very active subcommittee, and some active projects in progress are discussed in this paper: basis statement development for all standards, development of a glossary for consistency of definitions across all ANS-8 standards, and Considering the Criticality Safety Support Group (CSSG) Recommendation 2016-04 to the ANS Standards Board for changes in several ANS-8 standards.
This report describes the development of two standard test methods: one for evaluating PM2.5 sensors; and the other for evaluating CO 2 Sensors. The standards were developed to provide a pathway for the use of reliable, low-cost indoor air quality sensors as occupant feedback, ventilation control, and overall indoor air quality improvement. This paper describes the development process and technical issues involved.
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Abstract Data standardization combined with descriptive metadata facilitate data reuse, which is the ultimate goal of the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. Community data or metadata standards are increasingly created through an approach that emphasizes collaboration between various stakeholders. Such an approach requires platforms for collaboration on the development process that centers on sharing information and receiving feedback. Our objective in this study was to conduct a systematic review to identify data standards and reporting formats that use version control for developing data standards and to summarize common practices, particularly in earth and environmental sciences. Out of 108 data standards and reporting formats identified in our review, 32 used GitHub as the version control platform, and no other platforms were used. We found no universally accepted methodology for developing and publishing data standards. Many GitHub repositories did not use key features that could help developers to gather user feedback, or to create and revise standards that build on previous work. We provide guidance for community‐driven standard development and associated documentation on GitHub based on a systematic review of existing practices.
This presentation provides an overview of consensus international solar resource standards and best practices development.
Electric two-wheelers (E2Ws) and electric three-wheelers (E3Ws) have reached upfront cost price parity as compared to their conventional counterparts in many markets (IEA 2022). Therefore, Pakistan has embraced E2Ws and E3Ws in their National Electric Vehicle Policy (Government of Pakistan 2019b). Specifically, this policy targets 50% of new two- and three-wheeler sales to be electric by 2030. In the short term, this policy targets five times as many E2Ws and E3Ws as cars, vans, and pickups. In order to meet these goals in a safe, reliable, and efficient manner, Pakistan needs to develop and implement standards related to E2W and E3W vehicles and charging infrastructure, including battery swap stations. Without standards, E2Ws and E3Ws can be dangerous, unreliable, incompatible with charging stations, or diminish the grid’s electricity quality (Goel and Singh 2019; Sasidharan 2020). Fortunately, there are several global and local efforts to establish standards that Pakistan can learn from or adopt. This document explains the purpose and process of standards development and introduces the international standards development organizations involved and relevant classification and testing systems. It then introduces and lists many standards related to the vehicles, batteries, and charging equipment so that Pakistan can adopt or reference these standards when developing its own.
Abstract Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR). The SSSOM specification can be found at http://w3id.org/sssom/spec. Database URL: http://w3id.org/sssom/spec
Measurements on samples of calcined uranyl fluoride (UO 2 F 2 ) using Raman spectroscopy, electron microscopy with elemental analysis, and secondary ion mass spectrometry (SIMS) indicate four facts. First, UO 2 F 2 undergoes a previously unreported oxidation reaction beginning around 350 °C in air. The resulting oxidation compound is likely similar to U 3 O 8 /UO 3 , but presently represents a novel chemical species. Second, variations in F/U ratio across samples as measured by electron microscopy with x-ray spectroscopy correlate with variations in F/U ratio as measured with the NanoSIMS 50L instrument. Third, simple mixed powders of LaF 3 +U 3 O 8 are not sufficiently homogeneous to act as a high F+U content standard material. Fourth, additional method development for determining the bulk F/U ratio using an alternative technique is necessary to further develop analytical standards.
This guide describes the structure and setup of the standard VERA development environment (VERA Dev Env) and standard VERA Third Party Libraries (TPLs) that need to be in place before installing many of the VERA simulation components. It describes everything from the initial setup on a new machine to the final build, testing, and installation of VERA components. The goal of this document is to describe how to create the directories and contents outlined in 'Standard VERA Dev Env Directory Structure' and then obtain the remaining VERA source and build, test, and install any of the necessary VERA components on a given system. This document describes the process both for a development version of VERA and for a released tarball of the VERA sources.
This paper surveys the existing landscape of standards relevant to heliostats, identifies their gaps, and proposes a path forward to a comprehensive set of heliostat guidelines, technical specifications, and standards under the framework of International Electrotechnical Commission (IEC) TC 117. Gaps in existing guidelines and standards are surveyed using a three-tiered taxonomy: component-level, heliostat-level, and field-level. At each level, the gap analysis is followed by a proposal for a coordinated path forward on the development of standards. At the component level, advances in the understanding of wind loading should inform a technical specification for drives and structures. Reflectors require consolidation of measurement guidelines into existing standards documents. Communications & controls require technical standards to inform their selection and secure implementation. At the heliostat level, IEC 62817 (solar trackers) adequately characterizes drive systems, structures, and electronics, but requires adaptation to heliostats' use patterns, operating modes, and expected life cycles. IEC 62817 does not address heliostat beam quality and pointing accuracy, but the process for determining both is elaborated in the SolarPACES Guideline for Heliostat Performance Testing. This SolarPACES document requires two main modifications: adaptation to IEC language and inclusion of testing after heliostats which have undergone accelerated weathering and mechanical cycling (to understand performance degradation). At the field level, IEC 62862-4-2 addresses the function and control of heliostat fields but does not cover the statistically rigorous testing of heliostat groups, or field performance factors like security and soiling. The addition of documents under IEC-62862-4 is proposed to address this gap.
Since 2009, the U.S. Department of Energy (DOE) Office of Nuclear Energy's Nuclear Energy University Program (NEUP) has been at the forefront of nuclear research, specifically concentrating on advancing high-temperature gas-cooled reactor (HTGR) technologies. By Fiscal Year 2023, NEUP has authorized 35 projects dedicated to HTGR research, each contributing significantly to the enhancement of our understanding of this technology. The outcomes of these diverse projects have been disseminated through final NEUP reports, peer-reviewed journal articles, and presentations at academic conferences, forming a comprehensive tapestry of knowledge. Despite the substantial value of these findings, their dissemination has been fragmented, posing challenges for accessibility to researchers and policymakers and leading to underutilization of DOE investments. Recognizing this critical gap and its potential consequences for the future of nuclear research, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program conducted an extensive survey of completed and ongoing HTGR NEUP projects. This survey enabled the compilation of crucial data, resulting in the development of a specialized public-access database tailored for computational fluid dynamics and system code validation, specifically designed for HTGR applications. However, the data collection process revealed a significant challenge in central data organization due to individual researchers from different institutes employing varying logics and preferences for recording and documenting experimental data. Consequently, an urgent need has been identified to establish a standardized reporting format for HTGR experimental projects. Addressing this issue is essential for enhancing collaboration, maximizing the impact of DOE investments, and ensuring the seamless advancement of HTGR technologies in nuclear research.