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DOE OSTI2025

Governance and resilience as entry points for transforming food systems in the countdown to 2030

Due to complex interactions, changes in any one area of food systems are likely to impact—and possibly depend on—changes in other areas. Here we present the first annual monitoring update of the indicator framework proposed by the Food Systems Countdown Initiative, with new qualitative analysis elucidating interactions across indicators. Since 2000, we find that 20 of 42 indicators with time series have been trending in a desirable direction, indicating modest positive change. Qualitative expert elicitation assessed governance and resilience indicators to be most connected to other indicators across themes, highlighting entry points for action—particularly governance action. Literature review and country case studies add context to the assessed interactions across diets, environment, livelihoods, governance and resilience indicators, helping different actors understand and navigate food systems towards desirable change.

Schneider, Kate R. [Johns Hopkins Univ., Washingto↗
DOE OSTI2023

Genomes to Structure and Function Workshop Report 2022

The goal of the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Program is to achieve a predictive understanding of complex biological, earth, and environmental systems with the aim of advancing the nation’s energy and infrastructure security. (https://www.energy.gov/science/ ber/biological-and-environmental-research). To pursue this goal, collaborations among experts in diverse research areas that lead to multidisciplinary projects are indispensable. The roles of DOE’s User Facilities, which offer unique and powerful resources for such research projects, are evolving, and expectations for the facilities are increasing. To respond to Users’ needs, the Joint Genome Institute (JGI) and Environmental Molecular Sciences Laboratory (EMSL) initiated the Facilities Integrating Collaborations for User Science (FICUS) program in 2014. This collaboration has grown into a popular and successful program, advancing more than 100 multidisciplinary projects to date. Similarly, the new interFacility collaborations among the JGI, EMSL, and User resources for BER structural biology and imaging at the Basic Energy Science (BES) Program’s synchrotron and neutron facilities are becoming essential for cutting-edge transdisciplinary science. To further explore the need for the BER research community to combine genomic, functional, and structural approaches to advance their research, an organizing committee was formed to develop and jointly host a 3-part workshop. The committee’s members represented seven DOE National Laboratory User Facilities (Appendix 1 lists the members). The “Genomes to Structure and Function” virtual workshop (see Appendices 2–5) was composed of three sessions. The first session, titled “Molecular Structures” (October 27– 28, 2021), highlighted diverse integrative experimental and computational approaches correlating structural data with sequencing and functional information, as well as predicting protein structures to model complex biological systems. The second session, “Intracellular Organization, and Material Synthesis and Decomposition” (December 15–16, 2021), covered imaging methods for observing, quantifying, and manipulating biosystems. The third session, “Imaging the Rhizosphere and Cellular Organization” (January 26–27, 2022) emphasized advanced and non-invasive imaging techniques applied to plant root-microbe-soil interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

IBR Digital Supply Chain Gap Analysis and Recommendations

The adoption of clean energy technologies, including solar photovoltaics, continues to introduce non-traditional stakeholders to the operations and planning of the electric system. Stakeholders such as manufacturers, vendors, owners, aggregators, and others are enabling the adoption, integration, and optimum operations of solar technologies at accelerated rates. Inverters form the foundation of many digitally controlled energy sources for clean energy technologies, including Solar, Battery Energy Storage Systems, Hybrid Systems, and Hydrogen Fuel Cells. Their supply chain is complex, a series of microchips, electronic switches and other components making up its primary functions. The complexity of this space and the growing digitization associated with these components can create supply chain cyber risks. One measure to mitigate cybersecurity attacks is proper digital supply chain security. The U.S. Department of Energy (DOE) Solar Energy Technologies Office (SETO), in partnership with the Cybersecurity, Energy, Security, and Emergency Response (CESER) office, is hosting a workshop to bring together solar vendors and services providers to discuss digital supply chain security for solar systems and challenges and opportunities in the transitioning to a fully domestic supply chain for solar energy in the U.S. This workshop will support the Securing Solar for the Grid (S2G) and Energy Cyber Sense program activities. During the workshop, industry experts and researchers from DOE National Laboratories will discuss the current solar supply chain landscape and the transition to domestic manufacturing of solar components in the U.S. Tools and techniques to better manage and secure the digital supply chain of solar devices and systems will be discussed.

cybersecurity↗
DOE OSTI2020

Validation of Synthetic U.S. Electric Power Distribution System Data Sets

There is a strong need for synthetic yet realistic distribution system test data sets that are as diverse, large, and complex to solve as real systems. Such data sets can facilitate the development of advanced algorithms and the assessment of emerging distributed energy resources while avoiding the need to acquire proprietary critical infrastructure or private data. Such synthetic data sets, however, are useful only if they are realistic enough to look and behave similarly to actual systems. This paper presents a comprehensive framework for validating synthetic distribution data sets using a three-pronged statistical, operational, and expert validation approach. Furthermore, it also presents a set of statistical and operational metric targets for achieving realistic data sets based on detailed characterization of more than 10,000 real U.S. utility feeders. The paper demonstrates the use of the proposed validation approach to validate three large-scale synthetic data sets developed by the authors representing Santa Fe, New Mexico; Greensboro, North Carolina; and the San Francisco Bay Area, California.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Building Capacity: Solar Photovoltaics Site Assessment and Feasibility Study

While Bhutan is abundant with clean energy hydropower, there are dry months in winter when solar energy could reduce expensive power inputs and bolster Bhutan's energy resilience and independence. As the country explores solar photovoltaic (PV) development as an option to achieve that goal, grid planners and renewable energy experts are partnering with the South Asia Group for Energy (SAGE) to determine the benefits and challenges of building solar energy systems in Bhutan.

14 SOLAR ENERGY↗
DOE OSTI2024

Demonstration and Evaluation of Explainable and Trustworthy Predictive Technology for Condition-based Maintenance

The domestic nuclear power plant (NPP) fleet has historically relied on labor-intensive and time-consuming predictive maintenance (PdM) programs, thus driving up operation and maintenance (O&M) costs to achieve high-capacity factors. Artificial intelligence (AI) and machine-learning (ML) can help simplify complex problems such as diagnosing equipment degradation to enable more effective decision-making efforts. The benefits of AI will be felt through more efficient plant O&M, improved work processes, and better integration of people and technology. Together, these benefits hold the promise to make nuclear power more sustainable by reducing O&M costs while improving employee engagement. While AI and ML technologies hold significant promise for the nuclear industry, there are challenges or barriers to their adoption. Explainability and trustworthiness of AI are two salient challenges that need to be addressed for wider deployment of these technologies in NPPs. This research focuses specifically on addressing the explainability and trustworthiness of AI technologies to advance the human, technical, and organization (HTO) readiness levels in adopting a risk-informed PdM strategy at commercial NPPs. In addition, this approach can be adapted to enhance the acceptability of AI in other nuclear applications with a few application-specific modifications. The technical approach ensuring wider adoption of AI technologies was developed by Idaho National Laboratory (INL)—in collaboration with Public Service Enterprise Group (PSEG), Nuclear, LLC—by utilizing the circulating water system (CWS) at two PSEG-owned plant sites for demonstration. Focused user studies were performed in collaboration with subject matter experts (SMEs) from PSEG and other nuclear domains to enhance human and organization readiness by building trust in AI-informed technologies. VIsualization for PrEdictive maintenance Recommendation (VIPER)—a Battelle Energy Alliance, LLC, copyrighted software—was developed and expanded to provide a user-centric visualization by incorporating inputs from the collaborating utility, human factors engineering guidelines, and data analysts. The VIPER software enables users, who may be unfamiliar with ML in general, to be interactively engaged by asking technical questions about PdM, work orders, diagnosis results and their confidence levels, the kind of data being used, and the types of ML algorithms employed. This interactive engagement enhances explainability and builds trust. One of the enabling accomplishments was the integration of large language models (LLMs), both text-based and vision-based, in the VIPER software.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Community Microgrid Assistance Partnership (C-MAP)

The Community Microgrid Assistance Partnership (C-MAP) provides funding, access to technical experts, and educational resources to energy providers in remote and electrically isolated areas to help them build, operate, and enhance microgrid systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Urban-Scale Processes in High-Spatial-Resolution Earth System Models

Cities and their associated urban areas have a much larger impact on the environment than their spatial footprint on the Earth's surface. This is undoubtedly true at local and regional scales, but also at global scales. At this time, more than half of the world's population lives in urban areas (80% in the United States), and the global proportion is projected to climb to 70% by 2050. Therefore, numerical models to study physics, chemistry, and biology affecting the Earth system at regional and global scales must represent the effects of urban areas on climate and the effects of a changing climate on urban areas. At the same time, it is essential to develop state of the art, simple and accurate urban models to better understand the relevant processes and also to address issues related to urban security against the spectra of chemical, biological and radiological (CBR) hazards. Towards bringing urban scientific communities together, a two-and-a-half-day international workshop was held at the Argonne National Laboratory (ANL) in the Chicago area on May 22-24, 2019. This workshop brought together more than 60 national and international experts to develop a roadmap for a better understanding of the issues associated with urban areas and at enhancing the capabilities of regional and global Earth System models (ESMs) in representing the atmospheric dynamics and chemistry, unique aspects of the biosphere and land use, and human dimensions of the urban environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DAWN: Dashboard for Agricultural Water Use and Nutrient Management—A Predictive Decision Support System to Improve Crop Production in a Changing Climate

Abstract Climate change presents huge challenges to the already-complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN’s framework for integrating climate–agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.

Meteorology & Atmospheric Sciences↗
DOE OSTI2022

Electric Power Industry Challenges Due to Increasing Shares of Inverter-Based Resources in Power Systems

The large-scale integration of variable renewable energy technologies around the world is forcing electric power systems into an unprecedented transition. This paper reports on power grid modernization and reliability issues related to the planning and operation of power systems with high levels of variable renewable energy. The contents of this paper stem from recent qualitative research in the form of a summary of an industry survey. The technical feedback from the interviewed 37 industry experts helped us identify 12 key areas of potential concern, which are discussed throughout this paper.

power system operation↗
DOE OSTI2020

DER Planning with Resilience Analysis Using REopt Lite: A Behind-the-Meter Techno-Economic Analysis Tool

REopt Lite is a techno-economic decision support model for behind-the-meter energy systems design and dispatch modeling. REopt Lite is used to optimize energy systems for buildings, campuses, communities, and microgrids. It is based on a Mixed Integer Linear Programming (MILP) optimization model. It is a fully automated and streamlined energy modeling tool that can be used off-the-shelf for a wide variety of distributed generation integration analyses and at the same time is architected to be extensible for user-specific customizations for advanced users and subject matter experts. It is publicly available as a webtool as well as has an Application Programming Interface (API). The API functionality enables programmatic access to the model facilitating smooth integration with other distribution systems modeling tools, and automated multiple scenarios/sensitivity studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Burning Embers: Towards more transparent and robust climate change risk assessments

The Intergovernmental Panel on Climate Change (IPCC) assessments provide policy-relevant insights about climate impacts, vulnerabilities, and adaptation through a process of peer-reviewed literature assessments underpinned by expert judgement. An iconic output from these assessments is the “burning embers” diagram. Burning embers were first used in the Third Assessment Report to visualize reasons for concern, which aggregate risks from various systems and sectors. In these diagrams, colour transitions show changes in the assessed level of risk to humans and ecosystems as a function of climate change indicated by increasing levels of global mean temperature. Here we review the approach to the construction of burning embers, its evolution across the various IPCC reports, and recent methodological advances in the elicitation process to reduce subjectivity in the expert judgement and improve the transparency of the assessment. We recommend the use of a standardized, transparent process of expert elicitation in the production of burning embers diagrams to enhance their quality, comparability, and credibility.

Zommers, Zinta↗
DOE OSTI2022

Assessing the Performance, Application, and Cost of Retrofit Wall Systems for Residential Buildings

The Oak Ridge National Laboratory, Pacific Northwest National Laboratory, and the University of Minnesota have been conducting a three-year study of residential retrofit wall systems. The researchers have identified, tested, and verified the hygrothermal performance of 16 wall assemblies in retrofit applications. The approach to this study includes a comprehensive literature review, the involvement of an advisory group of thermal enclosure experts, smallscale experimental in situ testing of the wall assemblies at the University of Minnesota’s Cloquet Residential Research Facility, and energy and hygrothermal simulation of wall assemblies using EnergyPlus, THERM, and WUFI. Simulation and experimental results are then combined with an economic analysis to produce a techno-economic study of residential wall systems for deep energy retrofits.This presentation summarizes the findings of this research project and is intended to guide architects and designers on how to retrofit existing wall assemblies without creating durability issues.

Desjarlais, Andre Omer↗
DOE OSTI2021

Superconducting Radio-frequency Cavity Fault Classification Using Machine Learning at Jefferson Laboratory

We report on the development of machine learning models for classifying C100 superconducting radiofrequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. Of the 418 SRF cavities in CEBAF, 96 are designed with a digital low-level RF system configured such that a cavity fault triggers recordings of RF signals for each of eight cavities in the cryomodule. Subject matter experts analyze the collected time-series data and identify which of the eight cavities faulted first and classify the type of fault. This information is used to find trends and strategically deploy mitigations to problematic cryomodules. However, manually labeling the data is laborious and time-consuming. By leveraging machine learning, near real-time - rather than postmortem - identification of the offending cavity and classification of the fault type has been implemented. We discuss the performance of the machine learning models during a recent physics run. We also discuss efforts for further insights into fault types through unsupervised learning techniques and present preliminary work on cavity and fault prediction using data collected prior to a failure event.

Tennant, C. D.↗
DOE OSTI2021

Bridge Seismic Screening Tool (BSST), Version 2.0

The Regional Resiliency Assessment Program (RRAP) is a cooperative assessment of specific critical infrastructure within a designated geographic area and a regional analysis of the surrounding infrastructure that addresses a range of infrastructure resilience issues that could have regionally and nationally significant consequences. In 2018, DHS’s Cybersecurity and Infrastructure Security Agency (CISA) sponsored the Oregon Transportation Systems RRAP project in coordination with the Office of the Governor (under the oversight of the state resilience officer), the Oregon Office of Emergency Management (OEM), the Oregon Department of Transportation (ODOT), and other regional stakeholders (CISA 2021). This project focuses on assessing the impacts of a Cascadia Subduction Zone (CSZ) earthquake on state transportation systems and, in particular, how those impacts may affect the ability of emergency response efforts to move supplies into the region. The intended outcome of this analysis is the prioritization of transportation routes and modes for additional planning, investment, hardening, or other activities to enhance their resilience—and therefore, to enhance their ability to support response and recovery efforts following a CSZ earthquake. An important part of this transportation system-level assessment has been to assess the seismic vulnerability of the state highway system. In doing so, the RRAP project team used the Bridge Seismic Screening Tool (BSST) to assess, at a system-level, the potential impacts that a CSZ earthquake could have on state highway bridges (Bergerson et al. 2019).1 Argonne National Laboratory (Argonne), in collaboration with the Washington State Department of Transportation (WSDOT), originally developed the BSST as part of the 2017 Washington State Transportation Systems RRAP project, a sister project to the 2018 Oregon Transportation Systems RRAP project. Argonne updated the BSST during this more recent project in Oregon based on feedback from stakeholders and subject matter experts (SMEs) on the original version of the tool. The first step in the BSST is to assess the seismic vulnerability of roadway bridges following a CSZ earthquake to determine a projected or potential damage state. Damage states then help determine approximate reopening times for bridge crossings.2 This document provides details on the BSST methodology, the implementation of that tool to analyze the projected damage incurred in a CSZ earthquake scenario, and the determination of corresponding reopening times of interstate, state highway, and local bridges following such an event.

58 GEOSCIENCES↗
DOE OSTI2023

Turboexpander for Direct Cooling in Hydrogen Vehicle Fueling Infrastructure

Hydrogen fuel cell electric vehicles (FCEVs) have been identified as one of a few options for zero carbon emissions transportation. A major advantage of FCEVs is that they can fuel quickly and follow a familiar fueling behavior to hydrocarbon-fueled vehicles. Whether light duty or heavy duty, the goal for a hydrogen dispenser is to fuel a vehicle in the same amount of time as the fossil fuel equivalent. When hydrogen is dispensed into the vehicle storage system, however, the temperature rises due to the Joule-Thomson effect and the heat of compression. Typically, vehicles store the compressed hydrogen in composite overwrapped pressure vessels that have a polymer liner with an operational temperature limit of 85°C. This temperature limit can be exceeded during fast fueling if hydrogen is not precooled. Precooling allows for a dispenser to fuel a vehicle at a faster flow rate by preventing the storage tank on the vehicle from overheating. Fueling protocols and requirements are presented in SAE J2601 Fueling Protocols for Light Duty Gaseous Hydrogen Surface Vehicles [1]. A heavy-duty equivalent is under development with similar requirements for precooling. Currently, conventional precooling for light-duty vehicle refueling uses a heat exchanger and chiller to cool the hydrogen gas to -40°C before entering the vehicle. The precooling system represents a significant part of the station capital and operating costs, so if the cost of the precooling system can be reduced by improving its efficiency, the overall station capital and operating cost can be reduced. In this project, National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (SNL) researchers teamed up to investigate the turboexpander precooling application. A turboexpander is a device that places a turbine in a flow path where a pressure differential can be attained. This expansion device will extract work and lower the temperature of the fluid as the pressure reduces. While initial calculations based on established principles showed potential for a turboexpander to generate cooled gas, much work needs to be done to prove the concept. Turboexpanders typically work best under steady state conditions, while the dispenser is a very dynamic flow system. Dynamic turboexpander systems have been proven, such as a turbocharger on a gasoline vehicle. The inlet pressure at a dispenser is also much higher than any other known turboexpander system but should behave similarly to higher density fluids at lower pressures. Having both performed initial calculations, NREL and SNL researchers teamed up to investigate the turboexpander precooling application further. A project was soon built around the idea with SNL performing system modeling using previously proven capabilities and NREL performing hardware characterization with established station capabilities. Creare LLC was contracted as the turbomachinery expert to design and build the concept device. Part way through the project, however, contracting issues with the funding partner caused the project to terminate early before building and characterizing the concept device. While the project could not continue, many key findings were already learned. This paper is a summary of those findings.

08 HYDROGEN↗
DOE OSTI2023

"Safety First: Though on the Other Hand, Time is Critical”

This talk describes the deployment of research-quality software and hardware for open-road driving experiments by fleets of vehicles. Technological advancements in single-vehicle autonomy have expanded beyond the academic community, and are driven largely by industry stakeholders and manufacturers. However, as the penetration rate of cars with advanced driver assistance features increases, the impact on emergent behavior in traffic is still unknown. Compelling reasons to experiment within open-road conditions must be considered alongside the technical and human factor safety issues in deploying experimental controllers. This is even more challenging when it is necessary to deploy experimental fleets at scale. The talk will describe approaches for co-design of a research testbed for societal-scale systems. Discussion is devoted to the research-quality data gathering and control layers and their technical implementation, the different interfaces for experts in other fields to use these testbeds for research without violating safety requirements, and process and management considerations when deploying the platforms at scale when considering training time and operation complexity of human operators.

Sprinkle, Jonathan↗
DOE OSTI2025

U.S. Efforts in Support of Examinations at Fukushima Daiichi - September 2024 Meeting Notes

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. Commercial nuclear power plants. A collaborative U.S. and Japanese effort was initiated in 2014 by the Department of Energy Office of Nuclear Energy to identify Daiichi examination needs and evaluate recent Daiichi examination data to address these needs. This document summarizes information presented at and findings, action items, and recommendations by U.S. and Japanese experts in reactor safety and plant operations during the September 2024 Forensics Effort meeting. Significant safety insights were obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties and knowledge gaps in severe accident modeling progression, these insights continue to be used to assess whether additional updates are needed in guidance for severe accident prevention, mitigation, and emergency planning. Furthermore, Daiichi-related activities, such as code modeling improvements and analysis, testing, and new technology deployment efforts, have the potential to offer additional safety and economic benefits to the operating fleet and new light water reactor (LWR) and non-LWR designs.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗