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DOE OSTI2025

Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures

Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived data, extensive Monte Carlo simulation campaigns, and a wide range of end-user analysis. To manage these computational and storage demands, centralized workflow and data management systems are implemented. However, decisions regarding data placement and payload allocation are often made disjointly and via heuristic means. A significant obstacle in adopting more effective heuristic or AI-driven solutions is the absence of a quick and reliable introspective dynamic model to evaluate and refine alternative approaches. In this study, we aim to develop such an interactive system using real-world data. By examining job execution records from the PanDA workflow management system, we have pinpointed key performance indicators such as queuing time, error rate, and the extent of remote data access. The dataset includes five months of activity. Additionally, we are creating a generative AI model to simulate time series of payloads, which incorporate visible features like category, event count, and submitting group, as well as hidden features like the total computational load—derived from existing PanDA records and computing site capabilities. These hidden features, which are not visible to job allocators, whether heuristic or AI-driven, influence factors such as queuing times and data movement.

kilic, Ozgur Ozan [Brookhaven National Laboratory ↗

DOE OSTI2025

Soil Carbon Saturation: What Do We Really Know?

Managing soils to increase organic carbon storage presents a potential opportunity to mitigate and adapt to global change challenges, while providing numerous co-benefits and ecosystem services. However, soils differ widely in their potential for carbon sequestration, and knowledge of biophysical limits to carbon accumulation may aid in informing priority regions. Consequently, there is great interest in assessing whether soils exhibit a maximum capacity for storing organic carbon, particularly within organo–mineral associations given the finite nature of reactive minerals in a soil. While the concept of soil carbon saturation has existed for over 25 years, recent studies have argued for and against its importance. Here, we summarize the conceptual understanding of soil carbon saturation at both micro- and macro-scales, define key terminology, and address common concerns and misconceptions. We review methods used to quantify soil carbon saturation, highlighting the theory and potential caveats of each approach. Critically, we explore the utility of the principles of soil carbon saturation for informing carbon accumulation, vulnerability to loss, and representations in process-based models. We highlight key knowledge gaps and propose next steps for furthering our mechanistic understanding of soil carbon saturation and its implications for soil management.

Environmental sciences↗

DOE OSTI2025

Effects of Galactic Irradiation on Thermal and Electronic Transport in Tungsten

The impact of irradiation on the thermal and electronic properties of materials is a persistent puzzle, particularly defect formation at the atomic and nanoscales. This work examines the nanoscale effects of low-energy irradiation on tungsten (W), focusing on defect-induced modifications to thermal and electronic transport. Using the site-projected thermal conductivity (SPTC) method [A. Gautam et al. PSS-RRL, 2400306, 2024], bulk and twin-grain boundary W with vacancy defects based on the Norgett–Robinson–Torrens displacements per atom model is analyzed. SPTC provides a detailed prediction of postcascade spatial thermal conductivity distribution. Electronic conductivity activity is estimated using the “N 2 method” [K. Nepal et al. Carbon, 119711, 2025] to explore the consequences of vacancies and grain boundaries, highlighting the defect-dependent nature of charge transport behavior. These findings offer high-resolution insights into irradiation-driven transport phenomena, with implications for space-exposed materials and nanoscale thermal/electronic management.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Design of Hypothetical Processes for the Production of 131 I and 99 Mo from Activation Targets

For over six decades, medical isotope production has been a high-priority focus of many research reactors across the globe. The majority of these isotopes were produced using highly-enriched uranium (HEU) or low enriched uranium (LEU) – delivering millions of doses of diagnostic and therapeutic isotopes. As a consequence of this production, however, six decades of isotope production has resulted in massive quantities of spent uranium material worldwide with no known disposition pathway creating growing proliferation concerns. Supported by the National Nuclear Security Administration’s (NNSA) Material Management and Minimization (M3) program, there has been increased focus in the production of high-priority isotopes without special nuclear materials or without uranium altogether. Isotope production via activation can potentially fulfill regional isotope demands – particularly in under-developed regions without access to isotope supply chains. The benefits of this approach would be a reduction in uranium proliferation risks, less special nuclear material wastes, and reduced risk of supply disruption in the likely event that major isotope producers will again go off-line as has happened in recent years due to a number of factors.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2024

Compositional Variation Tests on DuraMelter 100 with LAW Sub-Envelope B1 Feed in Support of the LAW Pilot Melter, VSL-02R62N0-5, Rev. 0 (May 2003)

The principal objective of the DM100 tests was to demonstrate the robustness of the vitrification process with respect to feed and glass compositional changes resulting from variations in the simulant-to-additive ratio. The DM100-WV unit was selected for these tests; this melter was used for all of the Part B 1 tests on LAW Envelopes A, B, and C sulfate incorporation that were used to support the subsequent tests on the Pilot Melter as well as for the more recent LAW Sub-Envelope Al, A2, A3 and Cl tests. The same melter was selected for the present tests in order to maintain comparisons between the data sets. In addition, the somewhat smaller glass volume for the same melt surface area as compared to the DM100-BL melter means that more glass turnovers are achieved for a given test duration. The DM100 tests used nominal feed and feed with a 15% surplus in waste simulant. Previous Pilot Melter tests on Envelope A with 10% variations (but with sulfate removal) showed significant impacts on glass production rates that were ultimately corrected by adjustments in the sugar additions. Consequently, robustness with respect to throughput as well as sulfate tolerance are important motivations for these tests.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

MACCS User Guide (V.5.0)

MACCS is used by the Nuclear Regulatory Commission (NRC) and various national and international organizations for probabilistic consequence analysis of nuclear power accidents. This user guide is intended to assist analysts in understanding the MACCS/MACCS-UI User Interface (UI) model and to provide information regarding the code. This user guide version describes MACCS Version 5.0, model history, explains how to set up and execute a problem, and informs the user of the definition of various input parameters and any constraints placed on those parameters. This report is part of a series of reports documenting MACCS. Other reports include the MACCS Theory Manual, MACCS Verification Report, Technical Bases for Consequence Analyses Using MACCS, as well as documentation for preprocessor codes including SecPop, MelMACCS, and COMIDA2.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Ecological connectivity and habitat loss shape patterns of genetic diversity in a threatened salamander

Context The maintenance of genetic diversity is essential for preserving adaptive potential in populations, yet it is increasingly threatened by landscape alteration. The field of landscape genetics offers a framework for assessing how patch-level landscape conditions, modeled at multiple scales, influence genetic diversity. Objectives We sought to assess how local environmental features and connectivity influence genetic diversity across 74 four-toed salamander (Hemidactylium scutatum) breeding wetlands in the southeastern United States. Methods Using next-generation sequencing data and hierarchical Bayesian models, we examined genome-wide heterozygosity in relation to local landscape features and ecological connectivity. We also assessed the scale of effect of landscape features and tested for temporal lag effects. Results Genetic diversity was lower in wetlands with higher levels of historic deforestation and lower connectivity. An interaction between deforestation and connectivity indicated that deforestation had stronger negative effects in isolated wetlands but weaker effects in well-connected wetlands. Accounting for scale of effect and temporal lags was critical for detecting these relationships. Conclusions Our analyses highlight the importance of assessing the spatial scale (scale of effect) and temporal lag of landscape features to detect key drivers of genetic diversity. In line with population genetic theory, our results indicate that the genetic consequences of habitat loss do not affect populations uniformly and are most severe in isolated populations where gene flow cannot buffer against loss of diversity. Altogether, we highlight the importance of considering the interaction of habitat loss and connectivity in conservation genetic management.

Hemidactylium scutatum↗

DOE OSTI2024

Preliminary Screening of Features, Events, and Processes for an Arctic-Focused Climate Intervention Performance Assessment

Geoengineering, the deliberate large-scale intervention in Earth's climate system, holds significant potential in the rapidly warming Arctic, where temperatures currently rise at more than twice the global average, accelerating ice sheet and permafrost melt. This contributes to global sea-level rise and releases methane, a potent greenhouse gas. Strategies like solar radiation management (SRM) and carbon dioxide removal (CDR) could mitigate these effects; for instance, SRM techniques aim to reflect a portion of the sun's energy back into space, potentially slowing ice melt and stabilizing permafrost. However, geoengineering in the Arctic faces challenges, including potential unintended consequences on the fragile ecosystem, disruption of local weather patterns, and impacts on indigenous communities. Effective governance requires robust international cooperation, environmental impact assessments, and regulatory frameworks. Despite these challenges, geoengineering's potential benefits make it a critical research area. This report explores application of the Performance Assessment (PA) methodology to Arctic Climate Intervention, providing an initial screening of relevant features, events, and processes (FEPs). At the core of the PA approach is the identification and evaluation of FEPs that could impact the performance of the intervention scheme. Here we provide an initial screening of FEPs to consider in the application of PA to Arctic Climate Intervention.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

A Framework for Building Security into the Design Process

This report presents guidance to support the implementation of security objectives during the design process for nuclear facilities using an organization’s quality management system. The guidance in this document is intended for design vendors and operators of nuclear power facilities. Additionally, this guidance document can be beneficial to regulatory bodies, industry partners, customers, and other stakeholders within the nuclear power market. This report aims to ensure security consequences are identified before designs are completed, which may lead to reduced costs and higher security effectiveness and efficiency.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

A Framework for Building Security into the Design Process

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Data for The Value of Reversible Carbon Storage in a Zero-Emissions World

Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.

Carbon↗

DOE OSTI2024

Online and Offline Identification of False Data Injection Attacks in Battery Sensors Using a Single Particle Model

The cells in battery energy storage systems are monitored, protected, and controlled by battery management systems whose sensors are susceptible to cyberattacks. False data injection attacks (FDIAs) targeting batteries’ voltage sensors affect cell protection functions and the estimation of critical battery states like the state of charge (SoC). Inaccurate SoC estimation could result in battery overcharging and over discharging, which can have disastrous consequences on grid operations. This paper proposes a three-pronged online and offline method to detect, identify, and classify FDIAs corrupting the voltage sensors of a battery stack. To accurately model the dynamics of the series-connected cells a single particle model is used and to estimate the SoC, the unscented Kalman filter is employed. FDIA detection, identification, and classification was accomplished using a tuned cumulative sum (CUSUM) algorithm, which was compared with a baseline method, the chi-squared error detector. Online simulations and offline batch simulations were performed to determine the effectiveness of the proposed approach. Throughout the batch simulations, the CUSUM algorithm detected attacks, with no false positives, in 99.83% of cases, identified the corrupted sensor in 97% of cases, and determined if the attack was positively or negatively biased in 97% of cases.

25 ENERGY STORAGE↗

DOE OSTI2025

Improved PV System Control Strategies to Reduce Power Management Costs in Nanogrids

An improved PV system control method is proposed to reduce nanogrid operation costs in this paper. A model including it various components such as photovoltaic (PV) systems, energy storage systems (ESSs), gateways, and household loads is considered with the constraints of the ESS, PV irradiance from real data, and household load. We designed an optimal economic dispatch strategy with an improved PV system control method. Combining the proposed optimal economic dispatch and PV system control strategies, it can improve the control performance for both transient and steady-state responses thereby enabling the maximum power to be extracted from the PV. Consequently, the PV power is maximized, which allows the ESS to use less power and sell the surplus to external power sources, which means the proposed method decreases the nanogrid operation costs. Furthermore, this performance is verified via nanogrid simulations and PV experimental kit.

PV system control↗

DOE OSTI2026

Poster: Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The rapid integration of artificial intelligence (AI) in the utility transmission and distribution (T&D) sector is revolutionizing traditional grid management practices. As utilities encounter complexities from evolving consumer behaviors and energy integration, AI becomes a critical solution for enhancing grid monitoring, fault detection, and operational optimization. However, increased reliance on interconnected technologies introduces significant cybersecurity risks, regulatory compliance challenges, and human factors concerns. This study proposes a strategic, responsible and consequence-driven approach to AI implementation, examining the dual nature of AI adoption by highlighting its transformative benefits for utilities and associated risks. It provides utilities with a framework for evaluating AI integration, enabling them to navigate challenges and capitalize on opportunities to achieve greater reliability, efficiency, and resilience in an increasingly complex energy landscape.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Interparticle Characterization of Mechanical Biomass Particle-Particle and Particle-Wall Interactions

The biomass materials industry faces significant challenges in managing material variability and its impact on storage and handling systems. Physical properties such as moisture content, particle size, and density fluctuate considerably, leading to operational issues like bridging and ratholing that disrupt material flow. These variations create a complex cascade effect throughout the process chain, affecting transportation, storage, and conversion processes. The economic consequences of this variability manifest in increased operational costs, maintenance requirements, and system downtime. Environmental factors further complicate the situation, as weather conditions and seasonal availability influence material properties and system performance. Engineers employ specialized equipment design, material characterization protocols, and pre-processing steps like size reduction and homogenization to address these challenges. A critical knowledge gap exists between continuous-level constitutive models and particle-scale behavior. This project developed a novel device to quantify interparticle mechanics between biomass particles, measuring friction and adhesion forces between particles and wall materials. The research focused on corn stover and southern pine forest residue, creating a comprehensive database of particle interactions. This breakthrough enables direct application in particle-based computational modeling, advancing the field's understanding of biomass handling characteristics and supporting the development of more reliable and efficient storage and handling systems. The project's outcomes contribute significantly to understanding biomass's mechanical and flow characteristics, particularly how variability at the particle level affects larger-scale handling operations. This knowledge is crucial for engineering feedstock supply systems that consistently meet quality and cost specifications for various conversion processes. The innovative experimental setup developed through this research represents a significant advancement in biomass characterization methodology. Providing precise measurements of particle-level interactions establishes a foundation for more accurate predictive modeling of bulk material behavior. This enhanced understanding of fundamental particle mechanics enables engineers to anticipate better and address handling challenges before they manifest in full-scale operations. This research opens new avenues for optimizing biomass handling systems through data-driven design approaches. The comprehensive database of particle interactions serves as a valuable resource for future research and development efforts, potentially leading to more efficient and cost-effective biomass processing solutions. This advancement in particle-level mechanics could revolutionize how biomass handling systems are designed and operated, contributing to more sustainable and reliable renewable energy production.

09 BIOMASS FUELS↗

DOE OSTI2024

Quantifying Uncertainty in HPC Job Queue Time Predictions

High Performance Computing (HPC) has developed at an unprecedented pace in recent decades. This growth has demanded corresponding development in the area of HPC Operational Data Analytics (ODA), which encompasses a wide range of data analysis techniques, ML/AI efforts, tools, and visualizations. Published studies in ODA offer a variety of practical ways to inform HPC users, administrators, procurement managers, and other stakeholders. Uncertainty analysis, however, is rare in the related published literature. For instance, we identify only 1 out of 14 existing studies focused on job queue time prediction that investigates the uncertainty aspect of their proposed predictions. We recognize the utmost importance uncertainty quantification can have in such predictive analytics solutions, with consequences in how users interpret information they receive, and attempt to bridge this gap. With the goal of improving access to such insights, we develop a process for determining upper and lower bounds of the predicted queue times of a regression model at a specified confidence level. Our current research is focused on the uncertainty in predicting job queue times, yet our approach may be employed in predicting other metrics.

HPC↗

DOE OSTI2024

Research Reactors Division Infrastructure Investment Plan for the High Flux Isotope Reactor

The High Flux Isotope Reactor (HFIR) is a unique national asset. Operational for nearly 60 years, continued investment into the aging infrastructure is necessary to ensure operation for another 6 decades. Additionally, growing missions require HFIR as well as important upgrades. Consequently, carefully integrated planning is required to ensure that infrastructure investments are timely executed to ensure long-term, reliable operation of HFIR. Concerns about challenges to the operational reliability of HFIR resulted in a recommendation from the 2023 Operations Review by the US Department of Energy (DOE) Office of Basic Energy Sciences that a HFIR management strategy be developed to address the infrastructure needs. This report defines the investment needs, which are evolving as new upgrade efforts are better defined. HFIR is part of the three-source strategy within the Neutron Sciences Directorate (NScD) and contributes to the five strategic science areas outlined in the NScD 10 Year Strategic Science Plan: quantum materials, soft matter, materials and engineering, chemistry, and biosciences. Fundamental to this strategy are three core values: operational excellence, responsible stewardship, and servant leadership. These values guide our mission of safe and reliable operation of the reactor and require a strong and just nuclear safety culture, a solemn respect for responsible care of the facility, good workforce development, robust procedures and processes, an effective communication strategy, world-class asset management, a determined customer focus, and a commitment to protecting the environment, the safety and health of the public and our people, and the quality of work performed within our facility. These principles are all essential to operate HFIR at a world-class level. The Research Reactors Division (RRD) will lead a new era of neutron science and isotope production at HFIR through responsible and purposeful leadership and unwavering support of the science community. The approach outlined in this plan highlights the direction leadership is taking to ensure that HFIR is ready to support the science challenges and national needs of the future and that the United States maintains world leadership in neutron sciences. The plan is in alignment with the DOE’s desire to continue operating HFIR and with the NScD strategic science goals for the future. HFIR is an aging facility with numerous infrastructure challenges and needs. It has an aging workforce in relation to the general population of Oak Ridge National Laboratory (ORNL), with many expected retirements over the next 5–10 years. With an increase in work scope caused by changing national priorities and science goals, several critical hires have been identified. To manage HFIR’s infrastructure needs, a prioritized list of equipment upgrades has been identified along with an analysis of future staffing requirements. A desire to operate HFIR at eight cycles per year will necessarily require some significant changes to procedures and processes currently in place as well as targeted staffing additions. Many of the equipment upgrades identified in this plan will significantly increase the reliability of the plant, thus contributing to the effort to reach the goal of safely operating eight cycles per year. A plan to attain eight-cycle operation is being prepared in parallel with the activities identified in this plan, although the actions identified to satisfy both plans will overlap. This plan identifies new infrastructure needs—for both plant equipment and staffing—thus necessitating formulation of future budget requests to fund the increased work scope and improvement activities. Some activities are currently being scheduled with the expectation that funding will be received. Any delays to funding or reductions of funding from the identified cost estimations will directly and negatively affect the plan’s implementation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Data Centers and Digital Assurance Workshop 3 – Mitigations for Digital Assurance Risks

The third session of the TADA (Technical Assistance for Digital Assurance) Data Centers Cohort, held on November 18, 2025, focused on developing mitigation strategies for digital assurance risks identified in previous workshops. Hosted by Idaho National Laboratory (INL) and ScottMadden, the session emphasized the application of Cyber-Informed Engineering (CIE) to data center infrastructure, particularly at the utility–data center interface. Participants revisited and ranked key digital assurance risks, including architecture and interface weaknesses, governance gaps, and AI-enabled threats. The workshop introduced the 12 principles of CIE, advocating for consequence-focused design, engineered controls, and secure information architecture to proactively reduce cyber-physical vulnerabilities. These principles were applied to critical data center systems such as power distribution, UPS, cooling, SCADA/BMS, and grid-forming batteries. The session also addressed governance challenges at the interconnection boundary, highlighting the need for clear roles in telemetry sharing, firmware management, and trip settings. Special attention was given to emerging risks from behind-the-meter (BTM) generation, including reverse-power flow and the integration of small modular reactors (SMRs), which shift data centers from large loads to complex generation nodes. Participants explored how interconnection agreements can serve as enforceable instruments for digital assurance, and reviewed gaps in current standards such as NERC CIP, IEC 62443, and IEEE 1547. The workshop concluded with pathways to standardization, including model agreement language, state-level programs, and expanded NERC guidance. INL also presented tools and frameworks for secure procurement and supplier risk management, reinforcing the need for integrated engineering and policy solutions to secure the evolving data center–grid ecosystem. Session 3 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗