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At least 757 records · Page 42

Efficient data extraction from neutron time-of-flight spin-echo raw data

Neutron spin-echo spectrometers with a position-sensitive detector and operating with extended time-of-flight-tagged wavelength frames are able to collect a comprehensive set of data covering a large range of wavevector and Fourier time space with only a few instrumental settings in a quasi-continuous way. Extracting all the information contained in the raw data and mapping them to a suitable physical space in the most efficient way is a challenge. This article reports algorithms employed in dedicated software, DrSpine (data reduction for spin echo), that achieves this goal and yields reliable representations of the intermediate scattering function S(Q, t) independent of the selected `binning'.

36 MATERIALS SCIENCE↗

Data-driven Cyberattack Detection for Photovoltaic (PV) Systems through Analyzing Micro-PMU Data

With increasing exposure to software-based sensing and control, Photovoltaic (PV) systems are facing higher risks of cyber attacks. Here, to ensure the system stability and minimize potential economic losses, it is imperative to monitor operating states and detect attacks at the early stage. To meet this demand, Micro-Phasor Measurement Units (μPMU) are increasingly popular in monitoring distribution networks. However, due to the relatively low sampling rate, μPMU has not yet been used to detect and classify cyber-attacks in power electronics enabled smart grid. To our knowledge, this is one of the first attempts to use μPMU to detect cyber attacks that degrade the performance of power electronics systems. We propose to apply data-driven methods on micro-PMU data to implement attack detection. We have evaluated data-driven methods, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), long short-term memory (LSTM) and convolutional neural network (CNN). The proposed CNN model achieves the required performances with the highest 99.23% accuracy and 0.9963 F 1 score.

14 SOLAR ENERGY↗

New generation of data acquisition and data storage systems of the IBR-2 reactor spectrometers complex

The paper presents an overview of works on the creation of data acquisition and data storage systems, which have been carried out in the Department of the IBR-2 spectrometers complex (DCS) of the Frank Laboratory of Neutron Physics (FLNP) over the past 15 years (before, during, and after the modernization of the IBR-2 reactor). These systems represent a unified set of identical (from the viewpoint of hardware) modules limited in type but functionally complete, wherein distinctions in parameters, functional capabilities, encoding, correction and preliminary data processing procedures specific to each spectrometer are realized on the level of microprograms, electronic tables, and integrated software control system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

CIRFT Data Update and Data Analyses for Spent Nuclear Fuel Vibration Reliability Study

The objective of this research is to collect experimental data on spent nuclear fuel (SNF) from pressurized water reactors (PWRs), including the H. B. Robinson Nuclear Power Station (HBR), Catawba Nuclear Station, North Anna Nuclear Power Station (NA), and the Limerick Nuclear Power Station (LMK) boiling water reactor (BWR). Data will be collected under simulated transportation environments using the cyclic integrated reversible-bending fatigue tester (CIRFT), an enabling hot-cell testing technology developed at Oak Ridge National Laboratory (ORNL). These data will be used to support ongoing SNF modeling activities and to address regulatory issues associated with SNF transport.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Scalable Data Center Capacity for DOE's AI Prototype: A Rapidly Available Gigawatt Data Center for DOE

The multilaboratory Gigawatt Data Center working group was commissioned to identify approaches to rapidly establish federal data centers with scalable capacities up to 1,000 MW. These state-of-the-art facilities will serve as hubs for interdisciplinary collaboration, industry partnerships, and transformative applications of artificial intelligence. The proposed strategic shift includes facilitating multilaboratory collaboration, prioritizing operational efficiency, expanding public–private partnerships, optimizing investments, ensuring long-term contractual flexibility, supporting open science and secure data enclaves, and exploiting high-speed national networks. Owing to their extensive experience and best practices, the US Department of Energy national laboratories are uniquely positioned to lead this initiative. We recommend conducting a feasibility analysis to rapidly identify the optimal sites for this initiative, and the effort will likely involve private industry for design, construction, financing, and operational integration. We also propose establishing multiple geographically diverse sites to ensure energy resilience, high operational reliability, and a diverse user base, thereby effectively addressing the nation’s critical needs.

42 ENGINEERING↗

Community Choice Aggregation(CCA) Data Collection Webinar for Status and Trends in the Voluntary Market Report (2024 Data) [Slides]

We have subcontracted LEAN Energy US, to help us improve our CCA data collection effort for the Annual Voluntary Energy Markets Data Report. LEAN Energy US (Local Energy Aggregation Network) is a national 501(c)3 non-profit organization dedicated to accelerating the country's transition to clean and renewable power, supporting competition and customer choice in the energy sector, and maintaining affordable electricity rates. We work in partnership with a range of organizations to actively support the formation and operational success of Community Choice Aggregation (CCA) programs around the country. This webinar, hosted in partnership with LEAN Energy US, is intended to introduce their members to our data collection effort and encourage CCAs in their network to participate.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Hybrid statistical testing for nuclear material accounting data and/or process monitoring data in nuclear safeguards

The aim of nuclear safeguards is to ensure that special nuclear material is used for peaceful purposes. Historically, nuclear material accounting (NMA) has provided the quantitative basis for monitoring for nuclear material loss or diversion, and process monitoring (PM) data is collected by the operator to monitor the process. PM data typically support NMA in various ways, often by providing a basis to estimate some of the in-process nuclear material inventory. We develop options for combining PM residuals and NMA residuals (residual = measurement - prediction), using a hybrid of period-driven and data-driven hypothesis testing. The modified statistical tests can be used on time series of NMA residuals (the NMA residual is the familiar material balance), or on a combination of PM and NMA residuals. The PM residuals can be generated on a fixed time schedule or as events occur.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Integral Benchmark Data for Nuclear Data Testing Through the ICSBEP & IRPhEP

The status of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and International Reactor Physics Experiment Evaluation Project (IRPhEP) was last discussed directly with the nuclear data community at ND2007. Since ND2007, integral benchmark data that are available for nuclear data testing have increased significantly. The status of the ICSBEP and the IRPhEP is discussed and selected benchmark configurations that have been added to the ICSBEP and IRPhEP Handbooks since ND2007 are highlighted.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

India Solar Resource Data: Enhanced Data for Accelerated Deployment (Fact Sheet)

Identifying potential locations for solar photovoltaic (PV) and concentrating solar power (CSP) projects requires an understanding of the underlying solar resource. Under a bilateral partnership between the United States and India - the U.S.-India Energy Dialogue - the National Renewable Energy Laboratory has updated Indian solar data and maps using data provided by the Ministry of New and Renewable Energy (MNRE) and the National Institute for Solar Energy (NISE). This fact sheet overviews the updated maps and data, which help identify high-quality solar energy projects. This can help accelerate the deployment of solar energy in India.

14 SOLAR ENERGY↗

India Solar Resource Data: Enhanced Data for Accelerated Deployment

Identifying potential locations for solar photovoltaic (PV) and concentrating solar power (CSP) projects requires an understanding of the underlying solar resource. Under a bilateral partnership between the United States and India - the U.S.-India Energy Dialogue - the National Renewable Energy Laboratory has updated Indian solar data and maps using data provided by the Ministry of New and Renewable Energy (MNRE) and the National Institute for Solar Energy (NISE). This fact sheet overviews the updated maps and data, which help identify high-quality solar energy projects. This can help accelerate the deployment of solar energy in India.

14 SOLAR ENERGY↗