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DOE OSTI2025

Circularity Futures Workshop Series: Summary Report

The aim of this report is to synthesize key feedback received from the three-part Circularity Futures workshop series held in Spring 2024. The workshop series was conducted by the National Renewable Energy Laboratory (NREL) on behalf of U.S. Department of Energy, Office Energy Efficiency and Renewable Energy (EERE), and was broken into three workshops: Workshop 1 - Circularity Analysis Needs and Priorities; Workshop 2 - Circularity Metrics and Indicators; and Workshop 3 - Circularity Data. Together, the workshops focused on identifying the existing priorities and gaps in the circularity modeling space, understanding different stakeholders' use and interpretation of circularity metrics and indicators, identifying common data gaps and data quality challenges, and assessing the robustness of available solutions. The workshop series brought a diverse group of stakeholders - including representatives from U.S. government offices, national labs, nonprofit organizations, industry, and academia - to collect first-hand feedback on needs, priorities, challenges and opportunities in the circularity modeling and analysis space. The workshop discussions highlighted numerous common needs, priorities and challenges among the interviewed groups. Several topics were frequently discussed, including: 1) Circularity as a pathway for sustainable economic growth: While circularity is generally defined in terms of resource conservation and reducing wasteful disposal of materials, participants agreed that circular strategies should serve broader economic, environmental, and social goals. It is therefore crucial for circularity analysis to look beyond waste reduction and instead evaluate a variety of impact metrics such as cost savings, job creation, air quality, and pollutant emissions. Mutli-criteria decision-making frameworks may be useful for making sense of disparate metrics and evaluating tradeoffs between impact categories.; 2) Economic and social factors are not well understood: Underdevelopment of existing end-of-life (EOL) management infrastructure, inconsistent standardization codes and policy space in reusing recycled content, and suboptimal collection and sorting strategies collectively contribute to uncertainty about the economic potential of circular pathways. The latter observation is consistent among all technologies but more emphasized for renewable energy systems. Social impacts of circularity practices are less understood and less researched than other sustainability aspects.; 3) Inconsistent methods for assessing emerging technologies: LCA and TEA results vary widely depending on the assumptions made with regards to market adoption of new technologies. Emerging technologies suffer limited availability of data needed to conduct a robust circularity analysis. Yet, understanding projected impacts of proposed nascent technology is a key need for different stakeholder groups.; and 4) Lack of temporally and geospatially explicit data: There is a need for open data that represents variations in circularity technologies over time and location. The lack thereof leads to aggregated and potentially misrepresented results in circularity analysis. Sensitivity analyses should be included to verify whether options perceived as more sustainable align with real-world practices.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

In-Silico Design of Next Generation Cellulose-Derived Packaging Materials (CRADA Final Report)

Developing sustainable solutions for single-use packaging is an important objective to combat the environmental crisis of plastics pollution. Most embodiments of cellulose-based packaging materials, including CellophaneTM, are completely biodegradable in both terrestrial and marine environments. However, petroleum-derived alternatives offer some performance advantages for metrics such as moisture barriers and mechanical properties. This project leverages molecular dynamics simulation to investigate how molecular modifications to cellulose-based polymer assemblies impact their material properties. An important performance criterion for the modified materials was to retain biodegradability; thus, modifications by naturally occurring, biodegradable additives were the focus of this study. Specifically, we developed models with xylan and lignin of varying monomeric compositions into the cellulose matrix. The mechanical properties were investigated by performing stress-strain simulations, and the water barrier and hydrophobicity were investigated by simulating the water contact angle. Our findings indicate that the incorporation of xylan into the cellulose matrix tends to increase the mechanical properties with an optimal loading of ~27 wt%. We also predict that orienting the nanoscale directionality of the xylan chains such that they are perpendicular to the cellulose fibrils will dramatically increase mechanical strength. In contrast, the incorporation of lignin tends to weaken the composite at all loadings investigated. Simulations of water contact angle predicted that coating polymers on the surface of the cellulose assembly creates a more hydrophobic surface than incorporating them throughout the matrix. Of the coatings investigated, lignin resulted in the most hydrophobic surface, followed by pectin and keratin, which both imparted modest increases in hydrophobicity. Future experimental work done by Futamura will focus on designing material prototypes to capitalize on the predictions of performance enhancement obtained from molecular modeling. While substantial progress was made by the simulations performed in this project, there still exists a vast parameter space that we were unable to investigate, including branching, functional group decoration, and degree of polymerization of polymer additives. However, the methods developed in this initial investigation will facilitate more rapid evaluation of the impact of molecular characteristics on the performance of biopolymer composite materials and thereby accelerate future materials discovery efforts in this area.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Coal Power Plant Reinvestment Visualization Tool

This tool, available at https://energycommunities.gov/coal-power-plant-reinvestment-visualization-tool/, serves as a public database and map for the purposes of enabling state and local economic development officials, project developers, and power plant owners to identify and pursue opportunities for plant and community reinvestment. The Coal Power Plant Reinvestment Visualization Tool focuses on coal power plants that have been closed or set-to-retire, alongside key infrastructure characteristics that are relevant for potential redevelopment reinvestment opportunities, including the opportunity to query these data based off pre-defined or user-set queries to identify opportunities for coal power facility reinvestment to support solar, wind, manufacturing, and nuclear. These Data for visualization and query include, but are not limited to: • Electric Transmission Lines • EPA Brownfield Sites (assessed with Federal funding) • Petroleum Terminals • Ports • Railroads • Others The tool will be updated periodically to provide relevant information to enable state and local economic development officials, project developers, and power plant owners to identify and pursue opportunities for economic revitalization and community reinvestment. Within this application data are focused on U.S. power plants with coal generation, where at least one on-site generator utilizes or utilized coal as a fuel source, including planned retirements through 2058 (EIA, 2024). Additional information on energy communities and revitalization opportunities can be accessed on the Interagency Working Group on Coal & Power Plant Communities & Economic Revitalization Energy Communities website (https://energycommunities.gov).

Closures↗

DOE OSTI2021

First principles molecular dynamics maps out complete mineral surface acidity landscape

In “Interfacial structures and acidity constants (pKa) of goethite from first principles molecular dynamics simulations,” authors Y. Zhang, X. Lui, J. Cheng, and X. Lu apply First Principles molecular dynamics (FPMD, also called Density Functional Theory MD, DFT/MD, or ab initio MD, AIMD), to evaluable the complete set of acidity constants (pK a ) of the hydroxyl groups on the most prominent goethite crystal facets. The pK a of these OH and OH$^+_2$ groups are compared with available data from the multisite complexation (MUSIC) model traditionally used to estimate pK a on mineral surfaces. The authors have presented eloquent rationale for the importance and implications of understanding goethite acidity constants in room temperature geochemistry settings. In this paper, I focus on the computational aspects, the strengths of FPMD, and its possibilities.

58 GEOSCIENCES↗

DOE OSTI2022

Lightning Flash Detection System (LFDS) [Poster]

The Electromagnetics Group wanted another system for detecting lightning flashes near/around the Pantex Plant. The current system in use detects lightning by detecting RF signals at a particular frequency. LFDS detects lightning by detecting flashes of light in the visual and near IR spectrums. This work is primarily focused on detecting cloud-to-ground lightning.

42 ENGINEERING↗

DOE OSTI2023

Performance Assessment Maintenance Plan for the Active Low-Level Burial Ground Trenches 31, 34, and 94 at the Hanford Site

This report documents the maintenance plan for the Hanford Site 200 West Area Active Low-Level Burial Ground Trenches 31 and 34 and 200 East Area Active Trench 94 performance assessment (PA). The PA maintenance plan is one of several supporting documents that are compendiums to the active trenches (Trenches 31, 34, and 94) PA as required in DOE O 435.1, Radioactive Waste Management . The PA is documented in DOE/RL-2021-26, Performance Assessment of Active Trenches in 200 East and West Low-Level Burial Grounds at the Hanford Site . This plan follows the requirements and outline specified in the applicable U.S. Department of Energy (DOE) standard used for developing documents supporting DOE-STD-5002-2017, Disposal Authorization Statement and Tank Closure Documentation . This maintenance plan summarizes the following major activities DOE plans to conduct to maintain the Trenches 31, 34, and 94 PA: Monitoring; Research and development; Planned reviews and analyses; Revisions of Trenches 31, 34, and 94 PA. The planned research and development activities relate to evaluating the key assumptions, including evaluating conceptual model assumptions and parameter value assumptions used in the PA. The planned research and development activities include those that are designed to track the release mechanisms for Category 1, Category 3, and uranium billet waste sources, as well as continued characterization and related modeling of the natural environment in the Central Plateau of the Hanford Site. In addition, the planned research and development activities include focused testing and evaluation of engineered and natural materials to reduce the uncertainty in the conceptual models and parameter values used in the PA. All key and secondary issues identified during the review of the PA by the Low-Level Waste Disposal Facility Federal Review Group have been resolved prior to finalization of the PA. There are no outstanding issues.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Future Electric Power Industry and Grids—Now What Again is Our Destination?

Having a vision that others agree to support and work toward is highly desirable but hard to achieve. We seem to lack a common and shared understanding of the vision—or worse, multiple visions (vivid mental images or documented statements) with varying areas of focus and details: • some appear to be similar but have differing underlying goals and characteristics, or • some reflect differing viewpoints as to effects on various stakeholders. These desirable and undesirable situations apply to realizing visions for enterprise and industry, including the electricity sector. Multiple industry stakeholder groups have developed goals, industry vision statements, and characterizations of the future. The viewpoints are promoted, discussed, refined by their stakeholder group, and often published to promote broad understanding and to inform or influence others. The GridWise Architecture Council asked itself how well-aligned these characterizations of the future are. If these publications collectively set the overall direction for the industry, it is useful to identify their answers to questions such as, where is the electric industry headed, guided by what objectives, and with what role(s) for the customers, electric utilities, and other stakeholders? Are these goals, visions, and future states moving toward a common vision, do they provide value for the stakeholders, and are they likely to meet the objective stated? This paper addresses these questions via an assessment and characterization of a sampling of stakeholder groups’ publicly available vision and future state reports for the electricity industry. Identified electric power grid architectural topic areas needing further work are described, along with GridWise Architecture Council analysis and observation, potential collaborative work efforts, and suggested next steps.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Direct Measurement of Galaxy Assembly Bias using DESI DR1 Data

We report the first direct measurement of galaxy assembly bias, a critical systematic in cosmology, from the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. We introduce a novel, cosmology-independent method to measure the halo occupation distribution (HOD) by combining a state-of-the-art group catalog with weak gravitational lensing. For groups binned by total luminosity, we determine the galaxy occupation number $N_{\rm gal}$ from group-galaxy cross-correlations, while weak lensing constrains the average halo mass $M_h$. Applying this to a volume-limited sample at $z{\in}[0.05,0.2]$, we measure the dependence of HOD, $N_{\rm gal}(M_h)$, on large-scale overdensity $δ_{g}$. Focusing on the satellite galaxies, we find an assembly bias parameter of $Q_{\rm sat}{=}0.05{\pm}0.14$, a result consistent with zero and in tension with many empirical galaxy formation models. Our method provides a robust approach for characterizing galaxy assembly bias to achieve precision cosmology with DESI and future Stage-V surveys.

Shao, Zhiwei [Shanghai Jiaotong U.; Shanghai Jiao ↗

DOE OSTI2024

Broadband 920-nm mirror thin film damage competition

The 2023 Laser Damage conference thin-film damage competition was devoted to a survey on the state-of-the-art broadband near-IR multilayer dielectric (MLD) mirrors designed for ultra-short pulsed laser applications. The requirements for the coatings were a minimum reflection of 99.5% at 45-deg incidence angle for S-polarization from 830 nm to 1010 nm and group delay dispersion (GDD) < ± 50fs 2 . The participants were allowed to select the coating materials, coating design, and coating deposition method. Samples were damage tested at a single testing facility to enable direct comparison among the participants using a 25 ± 5 fs optical parametric chirped-pulse amplification (OPCPA) laser system operating at 5 Hz. The testing results from this set of 37 samples showed that dense coatings by ion-beam sputtering (IBS), magnetron sputtering (MS), and electron-beam ion assisted deposition (e-beam IAD) exhibited highest damage initiation onset (laser-induced damage threshold or LIDT) while e-beam coatings were low performers. In addition, multilayer coatings using tantala and/or hafnia as high index materials were top performers. Furthermore, this competition included for the first time the measurement of the damage growth onset (laser-induced damage growth threshold or LDGT). This latter performance metric plays an important role in establishing the safe operational conditions for larger aperture ultrashort pulsed lasers. Information pertaining to the morphology of the damage sites and their evolution under subsequent exposure to different laser fluences leading to damage growth is presented. Finally, not all coating samples in the survey met the GDD requirements stated above and associated measurements are discussed in the context of the present and past thin-film damage competitions focused on similar broadband near-IR MLD coatings.

23 broadband high reflectors↗

DOE OSTI2020

Consistency-Enhanced Evolution for Variable Selection Can Identify Key Chemical Information from Spectroscopic Data

In the last few decades, spectroscopic techniques such as near-infrared (NIR) spectroscopy have gained wide applications in several industries, such as the pharmaceutical, agricultural, oil, and gas industries. As a result, various soft sensors have been developed to predict sample properties from spectroscopic readings. Because the spectroscopic readings at different wavelengths, especially at the adjacent wavelengths, are highly correlated, it has been shown that variable selection could significantly improve a soft sensor’s prediction performance while reducing the model complexity. To improve the prediction performance, most variable selection methods focus on identifying the variables (i.e., wavelengths or wavelength segments) that are strongly correlated with the dependent variable. Although many successful applications have been reported, these variable selection methods do have their limitations. Specifically, the selected wavelengths sometimes show little connection to the chemical bounds or functional groups presenting in the sample. In addition, the selected variables can be quite sensitive to the choice of the training samples. In this work, we address these limitations from a different perspective: if a variable selection algorithm can identify the truly relevant input variables, it should consistently identify the same subset of variables regardless of the choice of the training samples. Therefore, we propose a variable selection method that aims to improve the consistency of variable selection resulting from different training samples. Furthermore, the new algorithm is termed consistency-enhanced evolution for variable selection (CEEVS). To demonstrate the performance and robustness of CEEVS, we compare the proposed method with three representative variable selection methods using five published NIR data sets. These case studies clearly demonstrate that by improving the variable selection consistency, we can not only achieve improved prediction performance, but also identify key chemical information from spectroscopic data.

42 ENGINEERING↗

DOE OSTI2026

Hyporheic‐Zone Processes and Stream Oxygen Dynamics: Insights From a Multiscale Reactive Transport Model

Aquatic ecosystem metabolism encapsulates the daily fixation (gross primary production, GPP d ) and mineralization (ecosystem respiration, ER d ) of organic carbon. In fluvial systems, these are commonly estimated by inverse solutions to field observations using a model that describes oxygen concentrations varying in the water column in response to metabolic fluxes and air‐water gas exchange controlled by a rate coefficient (K 600 ). The most common conceptual model is the single‐station metabolism (SSM) model. The simplicity and flexibility of this conceptualization make it attractive; however, it implicitly assumes that all the processes that consume oxygen in fluvial systems can be lumped into a bulk estimate of respiration with poorly understood consequences for estimates of GPP d , ER d , and K 600 . Here, we focus on the implications of using SSM conceptualization when estimating metabolic fluxes from oxygen dynamics in channels where hyporheic exchange occurs. We use a new multiscale numerical model for reactive transport in streams that represents hyporheic exchange and streambed heterotrophic respiration. Nondimensionalization of this model reveals dimensionless groups that collectively control oxygen dynamics. Numerical experiments offer a mechanistic understanding of the impacts of hyporheic exchange on diel oxygen dynamics revealing that potential biases arise from neglecting mass transfer limitations. Specifically, we found that hyporheic exchange significantly affects diel oxygen dynamics, even for nonreactive streambed sediments. Moreover, while the SSM performs well in many situations, we find conditions where significant bias is produced by hyporheic exchange, even when oxygen data are well‐fitted. These situations pose a major challenge in the interpretation of metabolism assessment estimates.

Gomez‐Velez, Jesus D. [Oak Ridge National Laborato↗

DOE OSTI2024

Technology progress and clean vehicle policies on fleet turnover and equity: insights from household vehicle fleet micro-simulations with $\text{ATLAS}$

This paper documents the design and application of ATLAS (Automobile and Technology Lifecycle-Based ASsignment), a comprehensive household vehicle transaction and technology adoption micro-simulator in the San Francisco Bay Area. ATLAS evolves the fleet mix of individual households by simulating the vehicle transaction and choice decisions in response to co-evolving demographics, land use, and vehicle technology simulations. While most existing literature has focused on the aggregate clean vehicle uptake, this paper differentiates distributional effects and decomposes the underlying mechanisms across heterogeneous sub-populations of households. Using scenarios and sensitivity simulations that vary vehicle technology and policy assumptions, we find that Zero Emission Vehicles (ZEVs) penetrate into higher income groups at a faster rate than into lower income groups, which is intuitive and aligns with expectations. Interestingly, the relative income disparity in ZEV ownership shrinks over time across all scenarios, with a ZEV mandate coupled with declining battery cost leading to the greatest reduction in disparity of ZEV ownership by 2050. Federal, state, and local financial incentives influence the redistribution of ZEV uptake across income groups and contribute to narrowing income disparity. Vehicle transaction frequency and new versus used market dynamics are found to be important factors contributing to the income disparity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Multidimensional genome-wide screening in yeast provides mechanistic insights into europium toxicity

Abstract Europium is a lanthanide metal that is highly valued in optoelectronics. Even though europium is used in many commercial products, its toxicological profile has only been partially characterized, with most studies focusing on identifying lethal doses in different systems or bioaccumulation in vivo. This paper describes a genome-wide toxicogenomic study of europium in Saccharomyces cerevisiae, which shares many biological functions with humans. By using a multidimensional approach and functional and network analyses, we have identified a group of genes and proteins associated with the yeast responses to ameliorate metal toxicity, which include metal discharge paths through vesicle-mediated transport, paths to regulate biologically relevant cations, and processes to reduce metal-induced stress. Furthermore, the analyses indicated that europium promotes yeast toxicity by disrupting the function of chaperones and cochaperones, which have metal-binding sites. Several of the genes and proteins highlighted in our study have human orthologues, suggesting they may participate in europium-induced toxicity in humans. By identifying the endogenous targets of europium as well as the already existing paths that can decrease its toxicity, we can determine specific genes and proteins that may help to develop future therapeutic strategies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Surface Science Studies of Selective Fischer-Tropsch Chemistry on Cobalt Carbide Surfaces

Advances in catalysis science are critical to the progress of the United States. Catalysis is employed, in one way or another, in the production of almost every chemical and product manufactured. The catalysis research that we undertook here, regarding the role of specific facets of cobalt carbide in the Fischer-Tropsch production of low molecular weight olefins (FTO), is motivated by the work of many previous investigators. In particular two research groups from China had discovered FTO catalysts that work very selectively for low molecular weight olefins coupled with low production of methane. These are potentially very important findings that could find significant industrial utility if improvements can be discovered. With the research undertaken here we chose to focus on one of these studies and especially the Co 2 C surfaces that they implicate as being responsible for this exciting FTO catalysis with low production of methane. In this study, Zhong and co-workers investigated cobalt-manganese oxide catalysts for the Fischer-Tropsch to Olefins process. After reaching steady-state their catalyst showed a good selectivity to light olefins and low selectivity to methane with a carbon monoxide conversion of 31.8% at one atmosphere (with a H 2 /CO ratio of two and a temperature of 250°C). Lower H 2 /CO ratios and lower pressures increased the olefin production. Their catalyst characterization studies indicated that cobalt carbide quadrangular nanoprisms with preferentially exposed (101) and (020) facets were important in favoring lower olefin production and inhibiting methane formation. The authors stated that these cobalt carbide nanoprisms are a promising new catalyst system for directly converting synthesis gas to lower olefins. Motivated by the studies of Zhong and co-workers, our goal with the research here was to contribute to a better understanding of catalysis science through the study of surface chemical reactions related to the Fischer-Tropsch to Olefins reaction on specific facets of planar model cobalt carbide catalysts in ultrahigh vacuum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Data-Driven Smoothers for Extreme-Scale Computing

Patch-based relaxation refers to a family of methods for solving linear systems which partitions the matrix into smaller pieces often corresponding to groups of adjacent degrees of freedom residing within patches of the computational domain. The two most common families of patch-based methods are block-Jacobi and Schwarz methods, where the former typically corresponds to non-overlapping domains and the later implies some overlap. We focus on cases where each patch consists of the degrees of freedom on a finite element method mesh cell. Patch methods often capture complex local physics much more effectively than simpler point-smoothers such as Jacobi; however, forming, inverting, and applying each patch can be prohibitively expensive in terms of both storage and computation time. To this end, we propose several approaches for performing analysis on these patches and constructing a reduced representation. The compression techniques rely on either matrix norm comparisons or unsupervised learning via a clustering approach. We illustrate how it is frequently possible to retain/factor less than 5% of all patches and still develop a method that converges only a little slower than when all patches are stored/factored.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Geothermal Play Fairway Analysis of Low-Temperature Resources for Sedimentary Basin Geothermal Play Types: An Example in the Denver Basin

This project is part of a nationwide effort to highlight the advantages of incorporating low-temperature geothermal resource evaluation into the implementation of combined heat and power (CHP), and geothermal direct use (GDU) technologies (e.g., space heating and/or cooling). The initiative aims to hasten the nation's decarbonization process by exploring the potential for using low-temperature geothermal resources (< 150 Degrees Celsius) in selected sedimentary basins that have several population centers. The Play Fairway Analysis (PFA) techniques were modified from earlier studies of sedimentary basin geothermal play types (SBGPTs) that assessed the viability of low-temperature resources. The decision-making process for leveraging low-temperature geothermal resources for GDU and CHP applications is complex and considers a variety of factors, including geological, economic, and risk criteria. This study covers workflows, relevant datasets, python code, and both common and composite maps used to create low-temperature geothermal resource favorability maps for the Denver Basin, which extends across Colorado, Nebraska, and Wyoming. The replication of these methodologies in other SBGPTs can evaluate potential for low-temperature resources. The proposed geothermal PFA approach for low-temperature geothermal resources includes: (1) identifying available relevant data and grouping data sets into PFA criteria (e.g., geological, economic, and risk criteria); (2) analyzing data gaps enable future focalized exploration; (3) performing uncertainty quantification; (4) weighting relevant data; (5) developing favorability and common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection. This project will facilitate future deployment of CHP and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources in sedimentary basins.

15 GEOTHERMAL ENERGY↗

DOE OSTI2026

Data for Resilience and Reliability [Slides]

The Energy to Communities (E2C) peer-learning cohort program provides technical assistance to groups of 15 community entities around a common energy topic over the course of 6 months. Every month, participants join a virtual meeting where they hear from experts and exchange strategies and best practices with their peers. This cohort, "Planning for Major Energy Disruptions in the Southeast" focuses on strategies for entities in the Southeast to quickly recover from impacts to energy infrastructure caused by extreme events, such as severe weather and natural disasters. This presentation focuses on the data available related to energy disruptions. The workshop is on April 23, 2026.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

E2C Cohort on Major Energy Disruptions in the Southeast: Trade-Offs and Feasibility of Energy Sector Investment for Community Resilience [Slides]

The Energy to Communities (E2C) peer-learning cohort program provides technical assistance to groups of 15 community entities around a common energy topic over the course of 6 months. Every month, participants join a virtual meeting where they hear from experts and exchange strategies and best practices with their peers. This cohort, "Planning for Major Energy Disruptions in the Southeast" focuses on strategies for entities in the Southeast to quickly recover from impacts to energy infrastructure caused by extreme events, such as severe weather and natural disasters. This presentation focuses on the tradeoffs and relative costs of different strategies to improve outcomes from these extreme events. The workshop is on May 21, 2026.

24 POWER TRANSMISSION AND DISTRIBUTION↗