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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Novel Geochemistry Determined from High P-T Simulation Experiments of HFTS 2

A standard method in unconventional oil and gas production is the process of hydraulic fracturing followed by a shut-in period, during which the fracture fluid remains pressurized in the reservoir for up to three weeks before production begins. Despite this widely used process, very little is known about what occurs in the reservoir during this shut-in process. In order to properly delineate potential reservoir reactions that may occur during shut-in that would lead to corrosion and scaling events, experiments were conducted in high pressure, high temperature reactors to simulate conditions of the Wolfcamp Formation in the Delaware Basin. Experimental design allowed the assessment of the effect of proppant, microbiology, and time on the mineralogy and fluid chemistry in the reservoir. Results suggest the biggest impact on fluid chemistry and shale mineralogy during shut-in is time. Analyses demonstrate dissolution of the shale material, with maximum dissolved ions occurring after 7 days of the shut-in period. After 21 days, results suggest precipitation occurs. The Delaware Basin is demonstrated to be high in sulfate content, which further increases in the fluid due to dissolution reactions during shut-in. The pressure vessel experiments suggest there was no significant contribution to reactions from microbiology during the shut-in period. However, early production samples demonstrate a significant selection of the microorganism Caminicella, a genus of which has previously been correlated to corrosion and sulfide production. Results suggest shut-in conditions may provide high sulfate concentrations that could later be utilized by a shifted microbial community to drive potential well infrastructure failure. This is the first study to incorporate microbiology, mineralogy, and fluid chemistry to investigate the fundamental geochemical reactions that occur during shut-in and early phase production of the Delaware Basin. Results from this study can complement observations from the Hydraulic Fracture Test Site 2 observations.

Gulliver, Djuna↗
DOE OSTI2021

Quantitative Evaluation of Autonomous Driving in CARLA

There has been a great deal of recent advancements in end-to-end imitation and reinforcement learning for self-driving vehicles. Despite this, there is a severe lack of standardized metrics for evaluating the performance of autonomous self-driving agents. Existing metrics are generally lacking in their ability to capture a wide range of driving behaviors and compare the severity of different failure cases. In this work, we introduce the Quantitative Evaluation for Driving metric, or QED, which assigns a quantitative score from 0-100 that captures the quality of driving for any driving agent. Our QED metric assesses different aspects of driving behavior including the ability to stay in the center of the lane, avoid weaving and erratic behavior, follow the speed limit, and avoid collisions, and it can be used under a wide range of driving scenarios. To show the effectiveness of our QED metric, we compare the scores generated by QED against scores assigned by human evaluators on a total of 30 different drivers and 6 different towns in the CARLA driving simulator. In ``easy'' evaluation scenarios, where it is relatively straightforward to distinguish better drivers from worse drivers, QED attains an average Pearson correlation of 0.96 and average Spearman correlation of 0.97 when compared against human evaluators. In ``hard'' evaluation scenarios, where it is far more ambiguous how to rank/score different types of bad driving behavior, QED attains an average Pearson correlation of 0.82 and average Spearman correlation of 0.75 when compared against human evaluators, which are both slighter higher than when we compare human evaluators against each other. While QED may not capture every characteristic that defines good driving, we consider it an important foundation for reproducibility and standardization in the community.

Gao, Shang↗
DOE OSTI2021

A Time-Dependent Directional Damage Theory for Brittle Rocks Considering the Kinetics of Microcrack Growth

In this work, a novel microcrack damage theory for describing the time-dependent behavior of brittle rocks is proposed. Instead of using scalar or tensorial variables to approximate the effect of microcracks, the concept of directional damage is introduced by upscaling the directional distribution density of microcracks through the noninteracting homogenization scheme. The contribution of an individual crack on global strain is first derived from the crack-opening displacements including sliding, closure, and dilation. The model is then cast in the free energy form, and the range of parameters ensuring compliance with the second law of thermodynamics is derived rigorously. Considering that the subcritical propagation of microcracks is the dominant mechanism behind the time-dependent deformation and failure of brittle rocks, the driving force for directional damage is defined as the corresponding energy release rate, and the effect of time is introduced through a damage evolution law inspired from the kinetics of subcritical crack growth. The model is applied to simulate the behavior of basalt rock under various loading conditions. In addition to predicting the stress–strain–time response, the model offers enhanced resolution in representing the anisotropic characteristics of microcrack-induced damage in brittle rocks and their time-dependent evolutions.

58 GEOSCIENCES↗
DOE OSTI2023

Community Centered Solar Development (CCSD) Case Study Interviews [Slides]

Large-scale solar (LSS, defined here as ground-mounted photovoltaic projects ≥1 MWDC) has grown rapidly in the U.S., accounting for nearly half of new electric generating capacity added to the U.S. grid in 2022. All sources of electricity bring positive and negative impacts to hosting communities and the rapid growth of LSS has increased the urgency to understand those impacts. Yet, information about the potential positive and negative impacts of LSS on host communities, and the factors or drivers leading to support or opposition to a project, is lacking. This information gap limits how project developers, municipalities, and local siting authorities can address community concerns and appropriately align proposed projects to best suit and benefit local communities. As part of Berkeley Lab’s Community-Centered Solar Development (CCSD) project, this research set out to explore deep insights and perceptions from LSS stakeholders that only qualitative data can provide to identify key factors driving project success or threatened failure. Case studies, such as those utilized in this research, are uniquely adept at capturing the subjective experience of individuals and at identifying variables, structures, and interactions between stakeholders. Our case studies included 54 semi-structured interviews across 7 different LSS sites, representing a diversity of geographies, project sizes (MW), site types (i.e., greenfield, agrivoltaic, and brownfield / contaminated sites), zoning jurisdiction types, and more (Table 1). In addition to local residents living in close proximity to these LSS sites, we interviewed other key stakeholders involved in the projects such as developers, decision-makers, utility representatives, landowners, and individuals from community-based organizations. The overarching aim of this case study research was two-fold: (1) to inform subsequent tasks in the CCSD research project (including an upcoming national survey of LSS neighbors), and (2) to provide insights into the following set of research questions: -What are the key positive and negative drivers leading to support and opposition to LSS projects? -To what extent do LSS projects exacerbate or mitigate perceived inequities and marginalization within hosting communities and how can those inequities be mitigated going forward? -What strategies can communities employ to align LSS development with local land-use plans and community needs and values? The research findings and next steps are described in this slide deck report.

14 SOLAR ENERGY↗
DOE OSTI2024

Advanced Power Electronics and Electric Machines

The advanced power electronics and electric machines (APEEM) research group at the National Renewable Energy Laboratory (NREL) has developed world-class experimental and modeling capabilities for designing and evaluating efficient and reliable power electronics and electric machines thermal management systems. They also design, fabricate and characterize advanced power electronics packaging, and are developing state-of-health monitoring techniques. These researchers deliver safe, reliable, high performing, power-dense components that allow seamless integration between renewable energy sources, electric transportation, and the grid, helping to make widespread electric vehicle (EV) adoption and greenhouse gas emissions reduction more feasible. This document outlines the group's major capabilities in the areas of power electronics; module development and characterization; thermal modeling and management; thermomechanical reliability analysis of devices, modules, inverters/converters, and electric machines; physics-of-failure-based reliability analysis; and microelectronics. It also overviews the group's state-of-the-art equipment for fluid-based thermal management; thermal measurement & characterization; thermomechanical reliability analysis; micro- and power electronics measurement & characterization; and prototype fabrication, as well as the group's world-class modeling and simulation capabilities.

advanced gate drivers↗
DOE OSTI2026

Extension of Clad Damage Propagation Model for Fission Gas Dispersal and Two-Phase Flow Effects in MOOSE SubChannel Module

This report presents an extension of the Clad Damage Propagation (CDAP) model implemented in the MOOSE SubChannel Module (SCM) to capture post-failure fission-gas dispersal and two-phase flow effects in sodium-cooled fast reactor assemblies. The extended model tracks discharged gas axially and radially, computes channel-averaged flow quality and void fraction using a Lockhart–Martinelli framework, evaluates two-phase frictional pressure-drop multipliers, determines inlet mass-flow degradation under fixed core pressures, and applies an intensified-void-based heat-transfer degradation to affected fuel pins. Radial plume expansion is parameterized using mineral-oil jet experiments mapped to sodium conditions via Reynolds–Weber similarity. Implementation details are documented, along with the new methods and user inputs needed to control plume mapping and two-phase behavior. Demonstration simulations for 19- and 37-pin bundles show that breach size and inlet velocity strongly influence propagation potential: small breaches (≤0.5 mm) produce limited degradation while larger breaches (~1 mm) can drive oscillatory temperature spikes and enhanced failure propagation, especially at higher velocities. These results demonstrate that the extended CDAP model provides a more complete framework for quantifying cladding damage propagation and evaluating propagation potential in transient scenarios. The approach remains computationally efficient, consistent with subchannel-level analysis, yet incorporates sufficient physics to bridge localized post-failure effects with bundle- and assembly-scale degradation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Optimized Dispatch of Distributed Energy Resources for Resiliency and Power Quality Improvements at the Grid-Edge

Distributed Energy Resources (DERs) installed on low-voltage distribution systems, both utility-owned and nonutility owned may be employed to make improvements to system resiliency and power quality, in addition to simply serving load demand. By selectively dispatching active and reactive power from these existing DERs, improvements in voltage profiles and service availability during adverse events may be achieved. Further benefits can be gained by optimally choosing which DERs to dispatch power from, and the distribution of power from those DERs. For a given operating condition, using Linear Programming methods, optimal power dispatch values for individual DERs can be determined, while considering variables such as voltage gains, losses in the lines and the DERs, and DER reserve capacities. One such optimization technique is developed in this paper, and results from a real-time simulation study on a modified IEEE 13-bus distribution system with three DERs, are being presented. The operation of the optimized DER selection and dispatch algorithm is shown during normal operation of the transmission system when the DERs operate in grid-connected mode. Similar analyses can drive decision making during transmission system failure when the DERs operate in grid-forming or islanded mode.

Chowdhury, Prithwiraj Roy↗
DOE OSTI2024

Simulated signatures of ignition

Ignition on the National Ignition Facility (NIF) provides a novel opportunity to evaluate past data to identify signatures of capsule failure mechanisms. We have used new simulations of high-yield implosions as well as some from past studies in order to identify unique signatures of different ignition failure mechanisms: jetting due to the presence of voids or defects, jetting due to the capsule fill tube, interfacial mixing due to instabilities or due to plasma transport, radiative cooling due to the presence of contaminant in the hot spot, long-wavelength drive asymmetry, and preheat. Many of these failure mechanisms exhibit unique trajectories that can be distinguished through variations in experimental observables such as neutron yield, down-scattered ratio (DSR), and burn width. Our simulations include capsules using both plastic and high-density carbon ablators and span all high-yield designs considered since the beginning of the National Ignition Campaign in 2011. We observe that the variability in trajectories through the space of neutron yield, DSR, and burn width varies little across capsule design yet are unique to the failure mechanism. The experimental trajectories are most consistent with simulated preheat and jetting due to voids and defects, which are the only failure mechanisms that are indistinguishable in our analysis. This suggests that improvements to capsule compression due to improved capsule quality or reduced preheat have played a primary role in enabling high yields on NIF. Furthermore, our analysis suggests that further improvements have the potential to increase yields further.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

From Filamentary Failure to Durable Halide Perovskite Memristors

Halide perovskites have emerged as promising materials for memristive devices. While their pronounced electrochemical reactivity and fast ionic mobility enable numerous advantages including low-voltage operation and fast switching, the same features also render perovskite-based memristors vulnerable to metallic shunts and poor endurance, limiting their practical applications. Here, we elucidate both the resistive switching and failure mechanisms in perovskite memristors with a fluorine-doped tin oxide (FTO)/methylammonium lead triiodide (MAPbI3)/Ag structure and demonstrate a strategy to substantially enhance device durability. As opposed to commonly invoked filamentary mechanisms, electrical, structural, and spectroscopic analyses reveal that resistive switching arises from interfacial barrier modulation by reversible Ag redox reactions that drive electrochemical doping/dedoping within the perovskite. Device failure, however, originates from metallic Ag0 filamentation that ultimately forms permanent conductive pathways. Introducing an ultrathin Al2O3 interlayer at the inert-electrode interface improves device endurance by more than 30-fold, exceeding 15,000 switching cycles, without compromising other performance metrics. Interfacial characterization indicates that the Al2O3 layer modifies wettability of Ag deposits, promoting planar island growth rather than through-film filamentation. These findings establish a clear link between interfacial electrochemistry, metal precipitation behavior, and memristor reliability, highlighting inert-electrode interfacial engineering as an effective pathway toward durable perovskite-based memristors.

14 SOLAR ENERGY↗
DOE OSTI2024

NEAMS Burnup Extension Accomplishments and Remaining Modeling Gaps

The economic viability of light-water reactors (LWRs) in the United States is declining in heavily subsidized markets, and as a result, the nuclear industry is looking for opportunities to enhance the economic competitiveness of nuclear power. This is not a foreign concept to the nuclear industry: in the mid-2000s, the nuclear industry set out to achieve zero fuel failures by 2010. The goal in this effort was to drive down the cost of reactor shut down by replacing a pin or bundle in response to fuel rod failure. 2010 brought about the initiative to deliver the nuclear promise to reduce operating cost by 30% to improve nuclear energy’s economic competitiveness before 2020. The emergence of accident-tolerant fuel also offers the nuclear industry an opportunity to build on these past successes and deliver affordable, clean energy. Accident-tolerant fuel has been shown to provide superior performance compared to traditional Zircaloy/UO2 fuel concepts, offering the unique ability to remove operational limitations that inhibit the economic viability of nuclear power. This has led the industry to begin building a technical case to extend the peak rod average burnup beyond 62 GWd/tU to extend pressurized water reactor cycle lengths to 24 months and to develop more efficient boiling water reactor core designs. The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program mission is to develop advanced modeling and simulation tools and capabilities to accelerate the deployment of advanced nuclear energy technologies. The primary safety concern inhibiting the nuclear industry from extending burnup is related to high-burnup fuel fragmentation, relocation, and dispersal. Therefore, the NEAMS program developed a targeted 5-year plan to support the industry’s efforts to extend burnup. This milestone report summarizes the 5-year plan that was enacted in FY20, followed by a discussion of the ongoing activates required to fulfill the 5-year plan, as well as the approach to address the current modeling gaps. Additionally, an LWR stakeholder meeting was held to communicate work performed in the NEAMS program over the past three years, to assess the LWR community’s perspective on the impact of the program, and to identify remaining significant gaps in the NEAMS suite of capabilities. This engagement will be documented by the Electric Power Research Institute and used by NEAMS to redirect current LWR scope as needed and to develop the next phase for LWR research and development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Identifying Robust Decarbonization Pathways for the Western U.S. Electric Power System Under Deep Climate Uncertainty

Climate change threatens the resource adequacy of future power systems. Existing research and practice lack frameworks for identifying decarbonization pathways that are robust to climate-related uncertainty. We create such an analytical framework, then use it to assess the robustness of alternative pathways to achieving 60% emissions reductions from 2022 levels by 2040 for the Western U.S. power system. Our framework integrates power system planning and resource adequacy models with 100 climate realizations from a large climate ensemble. Climate realizations drive electricity demand; thermal plant availability; and wind, solar, and hydropower generation. Among five initial decarbonization pathways, all exhibit modest to significant resource adequacy failures under climate realizations in 2040, but certain pathways experience significantly less resource adequacy failures at little additional cost relative to other pathways. By identifying and planning for an extreme climate realization that drives the largest resource adequacy failures across our pathways, we produce a new decarbonization pathway that has no resource adequacy failures under any climate realizations. This new pathway is roughly 5% more expensive than other pathways due to greater capacity investment, and shifts investment from wind to solar and natural gas generators. Our analysis suggests modest increases in investment costs can add significant robustness against climate change in decarbonizing power systems. Our framework can help power system planners adapt to climate change by stress testing future plans to potential climate realizations, and offers a unique bridge between energy system and climate modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Emergence of Diverse Failure Patterns in Weathering‐Induced Landslides: Insights From Particle Finite Element Simulations

Weathering is a fundamental driver of landslide evolution over geological timescales. Despite its ubiquity and importance, quantifying how weathering drives the progressive destabilization of rock slopes remains challenging. In this work, we develop a unified computational framework based on the particle finite element method to investigate the evolution of weathering‐induced landslides, from long‐term weathering to short‐term slope failure and runout dynamics. The framework integrates key processes, including weathering front propagation, time‐dependent strength degradation, rupture surface development, and post‐failure runout dynamics. Through numerical simulation experiments, we elucidate how interactions among weathering characteristics (type, intensity, and rate law), bedrock strength, fracture distribution, and slope geometry govern the failure modes and kinematics of weathering‐induced landslides. Simulations show that matrix‐dominated weathering leads to shallow translational failures, whereas fracture‐dominated weathering produces deep‐seated rotational and compound landslides. Pre‐existing fractures and slope morphology also strongly influence the movement of destabilized landmasses, affecting the failure pattern (e.g., kinematic mode and rupture surface geometry) and post‐failure behavior (e.g., runout velocity). We further demonstrate that the failure time and volume of weathered slopes are governed by the competition between gravitational driving forces and cohesive resisting forces during progressive destabilization. These findings provide new insights into the fundamental mechanisms that drive the emergence of diverse failure patterns of weathering‐induced landslides with important implications for landslide hazard assessment.

Wang, Liang [Eidgenoessische Technische Hochschule↗
DOE OSTI2026

Adaptive Cybersecurity for Distributed Energy Resources (AdCyDER): Online Reinforcement Learning with Stackelberg-Optimized Defenses — Pipeline Architecture, Evaluation Methodology, and Findings from a Synthetic-Data Evaluation

This report documents the design and evaluation of an integrated online-learning pipeline developed within the AdCyDER project for Distributed Energy Resource (DER) cybersecurity. The pipeline couples a Reinforcement Learning (RL) attack classifier — which produces an attack-type probability distribution — with a Stackelberg game-theoretic (GT) defense selector that consumes those distributions alongside SME-encoded priors over (defense, attack) effectiveness pairings and perdefense costs to choose grid-health-preserving defenses. The objective is not attack classification per se but production of distributions that drive effective defense selection through the Stackelberg layer, learned from delayed grid-health feedback rather than labeled attack data. AdCyDER as a whole is broader than the work presented here; this report covers the specific RL/GT loop integration and its evaluation. We present the integrated pipeline (SCADA telemetry with Fronius inverter physics, Suricata IDS, time-windowed aggregation, per-facility LSTM classifier, Stackelberg optimizer, OpenC2 actuators), an experimental campaign of 28 eight-hour iterations across three baseline modes, and a pipeline-ordered diagnostic protocol. The protocol identifies two distinct failure modes within the loop: paired supervised ceilings on the same features establish that the deployed online RL classifier (macro F1 ≈ 0.07) sits at least 4.7× below a same-architecture supervised LSTM (≈ 0.34) and 10–11× below a linear feature-signal ceiling (≈ 0.70–0.79 depending on per-facility isolation), localizing the dominant failure to the training procedure; and the reward signal driving online updates carries weak directional coupling with classifier correctness in the methodology-expected direction (multi-lens convergent: top-decile P(true) records produce more frequent state changes and slightly larger improvements, top-vs-bot Cohen’s 𝑑 ≈ −0.19), but at effect magnitudes too small to drive gradient-based learning at the campaign sample size. The original learning hypothesis is not supported by the data. The primary contributions are the diagnostic methodology — proposed as a transferable falsification protocol for online RL/GT defense pipelines learning from delayed environmental reward — and the open, reproducible experimental infrastructure. We outline reward reformulation as the highest-priority aspirational next step given the underpowered-but-aligned Q6 reading, with hardware-in-the-loop evaluation as the broadest scope-expansion option.

Blakely, Benjamin [Argonne National Laboratory (AN↗
DOE OSTI2025

Macro-micro multiscale modeling to assist the design of HPDC Al castings microstructure and alloys for EV super-large body structures (Phase 1)

Implementation of High Pressure Die Casting (HPDC) Aluminum (Al) body structures for high volume electrified vehicles (EV) to improve electric efficiency remains a key strategy within many original equipment manufacturer (OEM)s. In addition to high strength for safety requirements, superior Self-Piercing Riveting (SPR) performance is demanded for HPDC Al alloys to be compatible with high volume SPR joining. In this work, it is proposed to extend and validate an existing Contractor finite element multiscale macro-micro modeling approach to quantify the influence of the microstructure of HPDC alloys on the fracture strain/displacement under 3-point bend and clinch testing. The success of this work will allow to replace solution treatment stage with low energy consumption heat treatment (HT) processes, or to design new non heat treatable (NHT) HPDC Al alloys to eliminate HT requirements. Ultimately, this project will facilitate the application of HPDC Al alloys for super-large vehicle structures to significantly reduce vehicle weight, and thus improving energy efficiency. The purpose of this project is to extend and validate an existing finite element code, which is based on the Contractor developed macro-micro multi-scale modeling approach, to numerically simulate the three-point bending and clinch test and study the influences of material microstructural characteristics and phase properties on the rivetability. The macro-micro modeling approach begins with a sample scale model and identify the location, which is mostly prone to failure, the deformation history of the boundaries of that location calculated will be used to drive a microstructure-based sub-models where the material microstructure and microscale properties are considered. Using this approach, the wrap-bending failure for two Al alloys are correctly predicted for the first time. This will start with phase I effort of building a framework of macro-micro three point bending test and clinch test of Al10SiMgMn HPDC alloy in the as-cast and T7 heat treated conditions. Those results will then be validated with experimental test results. The phase II effort will involve the utilization of the knowledge learned in phase I to establish the quantitative correlation between the microstructure characteristics and the riveting performance, which will be further used to guide the optimization of HPDC Al alloy microstructure using heat treatment process to achieve sufficient rivetability to join large thin-wall HPDC alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2020

In Situ Investigation of Chemomechanical Effects in Thiophosphate Solid Electrolytes

Solid-state batteries can suffer from catastrophic failure at high current densities due to solid electrolyte fracture, interface decomposition, or lithium filament growth. Failure is linked to chemomechanical material transformations that can manifest during electrochemical cycling. We systematically investigate how solid electrolyte microstructure and interfacial decomposition (e.g., interphase) affect failure mechanisms in lithium thiophosphates (Li3PS4, LPS) electrolytes. Kinetically metastable interphases are engineered with iodine doping, and microstructural control is achieved using milling and annealing processing techniques. In situ transmission electron microscopy reveals iodine diffusion to the interphase, and upon electrochemical cycling, pores are formed in the interphase region. In situ synchrotron tomography reveals that interphase pore formation drives edge fracture events, which are the origin of through-plane fracture failure. Fractures in thiophosphate electrolytes actively grow toward regions of higher porosity and are affected by heterogeneity in microstructure (e.g., porosity factor). This report provides fundamental design guidelines for high-performance solid-state batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Redefining Resource Adequacy for Modern Power Systems: A Report of the Redefining Resource Adequacy Task Force

Today's rapidly increasing levels of wind, solar, storage, and load flexibility require the industry to rethink reliability planning and resource adequacy methods for modern power systems. Periods with a risk of shortfall often no longer coincide with peak demand - reliability risks are less about peak load and more about the daily setting of the sun, extended cloud cover, wind speeds, cold snaps, and heat waves. In addition, demand is increasingly flexible. Key resources are time-sensitive, as batteries need time to recharge and electricity customers can only be asked to provide demand response for just so long. And reliability failures are often correlated - with one another and with the weather. Two driving factors require the industry to reconsider its analytical approach for resource adequacy: (1) Chronological grid operations: The increasing importance of variable renewable resources (such as wind and solar) and of energy-limited resources (storage and demand response) make it essential to understand the full year of chronological operation of the grid. Specific attention must be paid to hourly, seasonal, and inter-annual resource variability. The sequence of the variability is key, as energy-limited resources such as batteries or demand response require either a preceding period or subsequent period of high production to be useful for grid reliability. (2) Correlated events: Historically, resource adequacy analysis focused on shortfalls caused by random, discrete mechanical failures of large generating units. In contrast, shortfalls today are often caused by multiple, correlated events caused by common weather patterns. Resource adequacy analysis must increasingly shift its focus to these correlated events. The redesign of resource adequacy methods will benefit from a set of guiding principles to better allow for sharing of insights and best practices, interregional resource coordination, and a smoother regulatory process for resource procurement. The objective of this report is to move this redesign forward. It provides an overview of key drivers changing the way resource adequacy needs to be evaluated, identifies shortcomings of conventional approaches, and outlines first principles for practitioners to consider as they adapt their approaches. The central message is: what got us here won't get us there.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing

Neuromorphic computing inspired by mammalian intelligence aims to emulate the nonlinear dynamics of biological neurons and synapses to achieve fast, low-energy, and highly efficient information processing. Brain-inspired computing relies on the design and discovery of materials exhibiting nonlinear current–voltage profiles, frequently underpinned by electronic state transitions, to achieve spiking neurons and dynamically tunable synapses. A signature challenge in the design of artificial neurons is controlling the steepness of first-order transitions in active elements, as abrupt transitions are at risk of driving unstable voltage and temperature oscillations, which result in catastrophic device failure. A critical knowledge gap is the lack of structure–function correlations mapping the composition and atomistic structure of crystalline solids to nonlinear dynamical response characteristics. Here, we address the key question of how modification of atomistic structure correlates with alteration of neuron-like functionality. Constructing oscillator circuits from millimeter-scale single crystals enables high-resolution atomic structure solutions, which we use to demonstrate that the selective positioning of Pb cations modifies charge ordering along a one-dimensional CuxV2O5 framework even at low insertion stoichiometries, thereby providing an atom-precise design parameter for damping first-order transitions. We use temperature-variant X-ray diffraction and X-ray spectroscopy to elucidate the suppression of Cu-ion shuttling based on the precise positioning of Pb ions in seven-coordinated tunnel interstitial sites as the mechanistic basis for transition broadening, thus bridging a critical gap between statistical mechanics and quantum chemical descriptions of phase transitions. Such mechanistic understanding thus paves the way to site-selective modification strategies for modulating the sharpness of first-order transitions, with an exemplary demonstration here in tuning neuronal signal processing.

Crystal structure↗
DOE OSTI2024

Collection of Disk Failure Events from Alpine, the Parallel File System for Summit Supercomputer

This dataset contains disk (HDD) failure events collected from the Alpine storage system of the Summit supercomputer, hosted at OLCF, spanning from January 4, 2019, to December 21, 2023 (a total of 4 years, 11 months, and 18 days), covering 89% of its operational lifetime. It includes 3,766 disk failure events, each recorded with its detection timestamp (in ISO 8601 format) and detailed by its location within the storage system - rack, enclosure, and drive slot number.

97 MATHEMATICS AND COMPUTING↗