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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 901 records · Page 50

Exploring Quantized Axion Electrodynamics in Magnetic Topological Insulator Multilayer Heterostructures (Final Technical Report)

The current program is focusing on investigating the properties of the high Chern number quantum anomalous Hall (QAH) effect in magnetic topological insulator (TI) multilayer heterostructures and the exploration of the topological magnetoelectric effect in thick magnetic TI films/heterostructures. Our program includes both experimental and theoretical efforts on this topic.

36 MATERIALS SCIENCE↗

Lessons learned from nitrogen doping at JLab - Exploration of surface resistance and quench field trade-offs with varied interstitial atom diffusion of niobium cavity surfaces

Interstitial diffusion of atomic species into the surface of niobium has been found to yield significantly reduced srf surface resistance and lowered quench fields. This talk summarizes systematic efforts to explore the trade-offs of these phenomena with a goal of learning how to maximize Q0 in the 30 MV/m regime. The talk also summarizes N-doped cavity progress at JLab for LCLS-II. This work is supported by the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under contract DE-AC05-06OR23177 and by the LCLS-II Project under DE-AC02-76SF00515.

Palczewski, Ari↗

Exploring induced mechanical vibrations in superconducting magnets

Controlled mechanical oscillations are not part of superconducting magnet toolkit except for diagnostics/quench detection purposes. However, significant potential exists to use them to affect operational conditions in magnets. There is also the possibility to explore them in terms of magnet protection. As none of these is known to had been investigated in past an effort is made here to address viability, use cases and benefits of such developments. Both appear to be valid and promising subjects and the magnet community can only gain with further investigations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Exploring the 3D nucleon structure with CLAS and CLAS12 at JLAB

Exploring the 3 dimensional structure of the nucleon can help to understand several fundamental questions of nature, such as the origin of the nucleon spin and the charge and density distributions inside the nucleon. In QCD, the 3-dimensional structure of the nucleon is described by Wigner functions. However, experimentally momentum and coordinate space have to be assessed independently. The momentum distribution can be accessed by transverse momentum dependent distribution functions (TMDs) measured in semi-inclusive deep inelastic scattering (SIDIS) or Drell-Yan processes while the distribution in transverse coordinate and longitudinal momentum space is described by generalized parton distributions (GPDs) which can be accessed for example by deeply virtual Compton scattering (DVCS) and hard exclusive meson production (DVMP). Based on the high quality data of CLAS and the recently upgraded CLAS12 detector at Jefferson Laboratory (JLAB), a detailed study of these distribution functions is being performed. With the new CLAS12 data, multidimensional, high precision studies in an extended kinematic range become possible for the first time. The talk will present the results of recent SIDIS, DVCS and DVMP studies with CLAS and CLAS12 and their impact on the understanding of the 3D nucleon structure.

Diehl, Stefan↗

An Integrated Framework for Risk Assessment of Safety-related Digital Instrumentation and Control Systems in Nuclear Power Plants: Methodology Refinement and Exploration

This report documents activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2023 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a technical basis to support effective, and secure DI&C technologies for digital upgrades/designs. A risk assessment-informed framework was proposed for this strategy, which aims to (1) provide a best-estimate, risk informed capability to quantitatively estimate the safety margin obtained from plant modernization, especially for safety-related DI&C systems, (2) support and supplement existing risk informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems, (4) assure the long-term safety and reliability of safety-related DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals, the LWRS-developed framework provides a means to address relevant technical issues by: (1) defining a risk informed analysis process for DI&C upgrade that integrates hazard analysis, reliability analysis, and consequence analysis, (2) applying risk informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development and deployment of advanced DI&C technologies in nuclear power plants (NPPs). Adding diversity within a system or components is the primary means to eliminate and mitigate CCFs, but diversity also increases system complexity and may not address all sources of systematic failures. Optimization of diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in safety-related DI&C systems of NPPs and supporting relevant design optimization, the proposed framework provides: (a) A best-estimate, risk informed capability to address new technical digital issues quantitatively, focusing on software CCFs in safety-related DI&C systems of NPPs; (b) A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to predict and prevent risk in the early design stage of DI&C systems; (c) Technical bases and risk informed insights to assist users address the risk informed alternatives for evaluation of CCFs in safety-related DI&C systems of NPPs; and (d) A risk informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The research and development efforts of this project in FY 2023 are focused on refining current methods on software CCF modeling and estimation and exploring additional innovative approaches to risk assessment of DI&C systems to enable a more comprehensive and complete assessment of various safety-related DI&C design architectures. The primary audience of this report are DI&C designers, engineers, and probabilistic risk assessment (PRA) practitioners. This includes stakeholders, such as the nuclear utilities and regulators who consider the deployment and upgrade of DI&C systems, DI&C software developers and reviewers, and cybersecurity specialists. It should be noted that all the analyses are performed for the demonstration of the methodology, not for the evaluation of an actual digital control system. Results are obtained based on limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Exploring Dark Sector Physics in MicroBooNE with e+e- Final States

Neutrinos are the second most abundant massive particle in the universe, but because of their small mass and weak interactions with matter, they are still not well understood. Due to their pervasive nature and unique properties, neutrinos make great probes to explore fundamental questions about the universe such as what is the composition of dark matter? The MiniBooNE experiment, designed to study neutrino oscillations, detected what has become a longstanding anomaly – an excess of low energy electromagnetic events from accelerator neutrino interactions. A possible explanation of the anomaly comes from neutrino interactions with nuclei that create heavier, sterile neutrinos that will decay quickly into electron-positron pairs. Complementing this is the MicroBooNE experiment, a liquid argon time projection chamber, that can reconstruct events well in both two and three dimensions and can distinguish electrons from photons. This reconstruction ability enables us to select dark sector neutrino interactions from other possible interactions using machine learning techniques such as graph neural networks (GNNs) which is the primary focus of this project.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Exploration of Domain Aware Machine Learning for Grid Analytics: Transfer-Learnt Energy Models to Assist Buildings Control with Sparse Field Data

Buildings are a primary consumer of energy in the United States and are also increasingly being perceived as providers of grid services such as load shifting, shedding and modulation. High fidelity models of building energy consumption are needed to set appropriate baselines for measurement and verification (M&V) of controllers designed for energy efficient operation of buildings and to enable buildings to provide grid services via. participation in demand response programs. State-of-the-art building energy modeling techniques either rely on Physics based models, or extensive instrumentation of the building envelope to gather “big” data to train machine learning based models such as deep neural networks. While Physics based models are often limited by their accuracy, it is not always feasible to gather a significant amount of field data required to train machine learning based models with sufficient accuracy. In this paper, we explore the use of transfer learning-based strategies to address unsatisfactory accuracy of models for estimating building energy consumption when available field data for training is sparse or of unacceptable quality. In particular, we transfer knowledge in the form of data and parameters, from Physics based simulation frameworks to the field to improve the model accuracy, thus resulting in a Physics-informed Machine Learning framework. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that the proposed transfer learning based models provide comparative (and in some cases better) accuracy than state-of-the-art machine learning and deep learning solutions, with just one month of field data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Molecular Hypernetworks for Exploration of Multi-Dimensional Metabolomics Data (Chyper)

Orthogonal separations of data from high-resolution mass spectrometry can provide insight into sample composition and help address the challenge of complete annotation of molecules in untargeted metabolomics. “Molecular networks” (MNs), as used, for example, in the Global Natural Products Social Molecular Networking platform, are an increasingly popular computational strategy for exploring and visualizing molecular relationships and improving annotation. MNs use graph representations to show the relationships between measured multidimensional data features. MNs also show promise for using network science algorithms to automatically identify targets for annotation candidates and to dereplicate features associated to a single molecular identity. However, more advanced methods may better represent the complexity present in samples. Our work aims to increase confidence in annotation propagation by extending molecular network methods to include “molecular hypernetworks” (MHNs), able to natively represent multiway relationships among observations supporting both human and analytical processing. In this paper we first introduce MHNs illustrated with simple examples, and demonstrate how to build them from liquid chromatography- and ion mobility spectrometry- separated MS data. We then describe a method to construct MHNs directly from existing MNs as their “clique reconstructions”, demonstrating their utility by comparing examples of previously published graph-based MNs to their respective MHNs.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring the THz Frontier of Experimental Microplasma (Final Report)

This is the final report for a three-year program to explore photonic crystals as a scalable medium for creating extremely high frequency plasma. The plasmas are then experimentally characterized and modeled. The conclusion of this work is that the photonic crystal is an attractive mode for creating plasma devices that extend into the THz band.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Combining Molecular Simulations and Machine Learning to Comprehensively Explore Adsorption Space (Final Report)

This is the final report for the project "Combining Molecular Simulations and Machine Learning to Comprehensively Explore Adsorption Space". The central aim of this project was to develop modeling tools that vastly increase the diversity of molecules for which reliable adsorption isotherms in nanoporous materials are available. Within the project, molecular simulation data for a diverse set of examples was combined with machine-learning (ML) methods to rapidly predict adsorption equilibria in crystalline nanoporous materials (primarily MOFs).

36 MATERIALS SCIENCE↗

Exploring the impact of the local environment on charge transfer states at molecular donor-acceptor heterojunctions

This program explored a broad range of charge transfer (CT) states in organic solar cells with the goal of understanding how molecular energetics, structure, and morphology influence CT state energy and dynamics, and how this in turn influences solar cell performance. We identified new types of delocalized CT states at ordered molecular heterojunctions, determined the factors that dictate CT state energetic disorder in bulk heterojunctions, determined that hot CT state dissociation is negligible for most systems, that the occupation of CT states is generally non-thermal in disordered heterojunctions, and that quasi-equilibrium generally does not hold in organic solar cells. These findings allowed us to demonstrate the lowest loss in potential of any organic solar cell to date and provide valuable guidance for designing higher efficiency organic solar cells in the future.

14 SOLAR ENERGY↗

Benefits and Burdens: Exploring the Role of Community Benefits in Wind Energy Development [Slides]

In this webinar hosted by the U.S. Department of Energy's WINDExchange initiative, NREL will provide an introduction to community benefit agreements (CBAs) and related funds and investments that serve as voluntary mechanisms that developers may utilize to provide additional financial and/or non-financial benefits for communities impacted by wind energy projects. Community benefits can come in different forms, be developed through diverse processes, and have varying impacts on key outcomes in the wind industry like project success and equity. This webinar explores the nuances of community benefits from multiple angles and provides insights that are relevant to land-based wind energy, offshore wind energy, and other renewable energy technologies.

17 WIND ENERGY↗

Exploring Wholesale Energy Price Trends: The Renewables and Wholesale Electricity Prices (ReWEP) tool (Ver. 2024.1)

The Renewables and Wholesale Electricity Prices (ReWEP) visualization tool from Berkeley Lab has been updated with nodal electricity pricing and wind and solar generation data through the end of 2023. ReWEP users can explore trends in wholesale electricity prices and their relationship to wind and solar generation. ReWEP includes nodal pricing trends across locations, regions, and different timeframes. The tool consists of maps, time series, and other interactive figures that provide: (1) a general overview of how average pricing, negative price frequency, and extreme high prices vary over time, and (2) a summary of how pricing patterns are related to wind and solar generation. Interactive functionality allows investigation by year, season, time of day, and region, where region is defined as the Independent System Operators (ISO) or Regional Transmission Organizations (RTO) region. ReWEP also contains prices throughout much of the western United States from the Western Energy Imbalance Market and the Western Energy Imbalance Service Market.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Exploring Wholesale Energy Price Trends: The Renewables and Wholesale Electricity Prices (ReWEP) tool (Ver. 2024.1)

The Renewables and Wholesale Electricity Prices (ReWEP) visualization tool from Berkeley Lab has been updated with nodal electricity pricing and wind and solar generation data through the end of 2023. ReWEP users can explore trends in wholesale electricity prices and their relationship to wind and solar generation. ReWEP includes nodal pricing trends across locations, regions, and different timeframes. The tool consists of maps, time series, and other interactive figures that provide: (1) a general overview of how average pricing, negative price frequency, and extreme high prices vary over time, and (2) a summary of how pricing patterns are related to wind and solar generation. Interactive functionality allows investigation by year, season, time of day, and region, where region is defined as the Independent System Operators (ISO) or Regional Transmission Organizations (RTO) region. ReWEP also contains prices throughout much of the western United States from the Western Energy Imbalance Market and the Western Energy Imbalance Service Market.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Exploring Grid-Interactive Efficient Building Strategies for Laboratories Through Energy Modeling

Laboratories are often overlooked in demand flexibility research due to constraints on their operations as mission critical facilities, despite the major role they play in an organization's emissions. Laboratories consume 3-4 times more energy than a typical office building and are commonly the largest energy users on any campus. Consequently, most laboratories in the United States are significant contributors to their organization's carbon footprint if their energy needs are met through the combustion of fossil fuels. As part of the initiative to decarbonize laboratories, this report documents an analysis on specifically grid-interactive efficient building (GEB) opportunities for reducing energy costs and emissions associated with laboratory operations. The goal of this initiative was to provide a case study and guidance on how to use OpenStudio and REopt as modeling tools for GEB technologies and strategies in laboratory environments across different climate zones in the United States. The analysis found that efficiency-based GEB strategies had the most significant impact on laboratory operations, while load-shedding and load-shifting GEB strategies produced smaller results. The culmination of these approaches applied across all five climate zones generated on average: 1) 28% energy cost savings and 30% greenhouse gas (GHG) emissions reductions, and 2) 4% enhanced energy cost savings under a time-of-use (TOU) pricing schedule compared to traditional pricing schemes. Grid-interactive efficiency building measures were found to produce the greatest energy savings in both electricity and natural gas, particularly in regions with high electrical loads, such as warm climates for cooling. Laboratories that had high levels of natural gas consumption, meanwhile, experienced the greatest emission reductions. The report concludes with an analysis on the opportunities for flexible loads in lab spaces and how small-scale measures in addition to opaque pricing structures for peak demand could become barriers to demand flexibility planning. The report also explores how electrifying laboratory buildings with heat pumps could reduce energy costs and GHG emissions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Technical Report on the Belle II Summer Workshop and Explorer Workshop 2023

The 2023 Belle II Summer workshop took place July 24-28, 2023 at Duke University in Durham. The meeting webpage can be found at https://indico.belle2.org/event/8841/. The meeting had 58 registered participants with the overwhelming majority attending in person. The event at giving beginning graduate students and postdocs an overview over the Belle II physics program and detector as well as an in-depth exploration of the Belle II software. For the latter, several hands-on sessions were organized to introduce participants to the Belle II software as well as more specialized topics in statistics and Machine Learning. The workshop also featured an ML/AI competition. In addition to the DOE support, the workshop was also supported by the Duke Physics department. We were able to host almost all students that so wished in the Duke Dorms and provide a meal plan. The support enabled us to waive the registration fee for all participants and cover also part of the dorm costs. Furthermore, we covered travel costs for external speakers on ML/AI topics. Figures 1 and 2 show the group picture and a scene from the hands-on sessions, respectively.

99 GENERAL AND MISCELLANEOUS↗

Safely Exploring Solar: A Guide for Austin Energy Customers

It's easy to get overwhelmed as you start to explore your solar options. There is a wealth of information available out there, particularly online, and it can be hard to know who to trust. This informational guide has been adapted from Austin Energy's Solar Education Course and other national best practice resources, as of May 1, 2023. It will help you understand some of the key concepts and resources available to help you on your solar journey if you have a home in Austin Energy's service territory and are considering installing solar. This document includes: (1) Austin Energy Programs and Services Related to Solar; (2) Tips for Spotting a Solar Scam; (3) Things to Know When Designing Your System; (4) Key Considerations When Shopping for a Solar Contractor; and (5) Final Takeaways.

14 SOLAR ENERGY↗