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DOE OSTI2025

Unlocking the biofuel power of cover crop in Washington State: Enhancing potential through hydrothermal liquefaction

This study evaluates cover crops in Washington State (WA) as a renewable feedstock for hydrothermal liquefaction (HTL), supported by techno-economic (TEA) and life cycle (LCA) analysis. In the Pacific Northwest, fallow land is the common winter practice, generating no income for farmers. Over three years, field trials at two representative sites—Puyallup (cool, wet) and Othello (irrigated, no-till)tested triticale, hairy vetch, crimson clover, winter pea, and fava bean preceding cash crops. Biomass yields, composition, soil impacts, and net revenue were assessed across removal treatments. HTL conversion produced 32–37 wt% biocrude, lower than 48 wt% for sewage sludge, with modeled cradle-to-grave carbon intensities of 26–31 g CO 2 e/MJ and minimum fuel selling prices (MFSP) of $\$$6.75–$\$$7.18 per gallon gasoline equivalent (GGE), comparable to other lignocellulosic feedstocks. No significant changes were observed in soil carbon, nitrogen, or subsequent cash crop yields after cover crop removal. Farmer profitability was possible, particularly for triticale and hairy vetch at $\$$60 per dry ton. To address seasonal variability, blending with wastewater sludge was evaluated. All scenarios delivered >70 % carbon intensity reductions relative to fossil fuels, and with Renewable Identification Number (RIN) credits, MFSPs below $\$$2.5 GGE were achievable. These results demonstrate that cover crops can generate new revenue streams for farmers while serving as a flexible, low-carbon feedstock. Integrating cover crops with waste biomass offers a practical pathway to expand the bioeconomy and support year-round renewable fuel production.

Biofuels↗

DOE OSTI2025

Nanodiamonds in Advancing Biomedical Sciences

Nanodiamonds (NDs), tetrahedral carbon frameworks with size ranging from 1 to 100 nanometers, have gained growing attention in recent years due to their distinct optical, thermal, and mechanical properties compared to other carbon nanomaterials (e.g., graphene, carbon nanotubes, carbon dots). Combined with a high surface-to-volume ratio and tunable and chemically versatile surfaces, these support broad applications across catalysis, electronics, and life sciences. Moreover, the biocompatible characteristics of NDs enable their controllable interfacial interactions with biological systems, positioning them as excellent candidates for advancing cutting-edge biomedical sciences, particularly through the engineering of efficient material-biointerfaces that facilitate optimal interactions with biological systems. Among various forms of NDs, fluorescent nanodiamonds (FNDs) have emerged as some of the most impactful and rapidly advancing materials, demonstrating strong potential in ultrasensitive spin-enhanced bioimaging, high-precision biosensing, traceable drug delivery, and quantum-enabled biomedical technologies. This Perspective introduces the key principles underlying NDs and FNDs, including their structural properties, synthesis methods, and surface functionalization strategies. It also highlights emerging biomedical applications of NDs and FNDs, with particular emphasis on neurological disorders. Last, the article discusses current challenges in advancing NDs as a multifunctional platform for neural therapies with translational potential toward clinical trials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Wind Turbine Design Guideline DG03: Yaw and Pitch Bearings

This design guideline describes the design criteria, calculation methods, and applicable standards recommended for use in performance and life analyses of ball and roller (rolling) bearings for yaw and pitch motion support in wind turbine applications. The formulae presented here for rolling bearing analytical methods and bearing-life ratings are consistent with methods currently used by wind turbine designers and rolling bearing manufacturers. The original yaw and pitch bearing design guideline was first drafted in 1999 by industry members and finally published in 2009 by the National Renewable Energy Laboratory. It was conceived as the third in a series of design guidelines, but it was the only one actually published by NREL and since has been known by the name "DG03." Other design guidelines were started, but instead of being published by NREL, they eventually became some of the International Electrotechnical Commission wind turbine standards in use today. This updated design guideline includes advances in research and field experiences made between 2009 and 2023. A better understanding of the operating conditions and damage mechanisms, advances in computational design, and publicly available test results facilitate more reliable yaw and pitch bearing designs.

17 WIND ENERGY↗

DOE OSTI2026

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗

DOE OSTI2026

Technology Impact and Resource Assessment of Existing and Planned U.S. Biofuel Production: Life Cycle Water Consumption, Water Stress, Land Use, and Criteria Air Pollutants

Biofuels have the potential to strengthen the U.S. energy supply, enhance energy security, and promote economic development. As the United States continues to expand biofuel production, quantifying resource requirements and location-specific constraints is crucial for planning, siting, and technology development to support long-term viability. Accordingly, this work assesses the life cycle resource consumption (water consumption, and land use), water stress and criteria air pollutants associated with expanded U.S. biofuel production over the 2020–2035 period, based on producers’ plans. We perform a bottom-up technology impact assessment and resource assessment by integrating facility-level production statistics with Argonne’s Research and Development (R&D) GREET model and county-level water-stress characterization factors from Available Water Remaining for the United States (AWARE-US) model. Results suggest that by 2035, biofuels could meaningfully contribute to U.S. energy demand, driven primarily by first-generation and waste-based feedstocks with plans for substantial capacity expansion, although cellulosic and e-fuel technologies remain limited. However, growth must be managed to minimize impacts on water resources and land use. These impacts vary by fuel type and facility location, specifically, projected expansion increases water consumption and can elevate water-stress impacts in certain regions like Nebraska, Kansas, Colorado, Idaho, California and North Texas. Direct land use also increases overall, particularly for first-generation feedstocks such as corn and soybeans. These findings underscore the need for continued technological improvements and innovative strategies to manage resource demands as the industry scales and to support complementary deployment within the evolving U.S. energy system.

09 BIOMASS FUELS↗

DOE OSTI2025

Mondo: integrating disease terminology across communities

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.

biomedical informatics↗

DOE OSTI2025

Polylactic acid (PLA)-based multifunctional and biodegradable nanocomposites and their applications

Polylactic acid (PLA)-based nanocomposites are emerging as multifunctional, biodegradable materials, offering sustainable alternatives to petroleum-based plastics. This review examines recent advancements in PLA nanocomposites, focusing on enhanced mechanical strength, thermal stability, and biodegradability achieved through nanofillers like metallic particles, carbon-based materials, and ceramics. Techniques such as in situ polymerization, melt mixing, and electrospinning enable application-specific improvements. PLA's limitations, including brittleness and low barrier properties, are addressed to support diverse applications: in packaging (e.g., extended shelf life), biomedicine (e.g., degradable implants), and electronics (e.g., flexible devices). Despite challenges with filler dispersion and thermal resistance, continued innovations expand PLA's potential across multiple industries, contributing to a sustainable, circular economy.

Biodegradable polymers↗

DOE OSTI2026

Tracing U.S. fuel life-cycle greenhouse gas emissions in a multi-sector dynamics model using LC-GCAM

Model-based analysis of fuel pathways is essential for informing energy and environmental policy. Two major model types are typically used: multi-sector dynamics models, which capture the broader energy-economy, such as GCAM (Global Change Analysis Model), and life cycle assessment models, such as GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation). Each has distinct strengths and limitations, and recent studies increasingly adopt hybrid approaches to harness the advantages of both. However, such integration is often time-consuming and complicated by inconsistencies in system boundaries and technology definitions. We present LC-GCAM, a new tool that enables estimation of life-cycle greenhouse gas emissions and primary energy use for any fuel pathway represented in GCAM. We apply LC-GCAM to 300 scenarios designed to explore key uncertainties affecting the life-cycle performance of future fuel options in the U.S. freight sector. To evaluate LC-GCAM, we compare its results with those from GREET for nine fuel types in a 2030 reference scenario. When input assumptions are modestly aligned, LC-GCAM and GREET estimates typically agree within 10% (absolute sum-based mean absolute percentage error). LC-GCAM offers a flexible and efficient approach to generating life-cycle metrics within an integrated modeling framework, supporting robust policy analysis across a wide range of interacting energy system uncertainties.

Wolfram, Paul↗

DOE OSTI2024

Hydrogen Sustainable Infrastructure Guidelines (H2SIG)

Infrastructure interacts with major global challenges inclusive of climate change, resilience, equity and social justice, environmental protection and biodiversity, public health, and economic recovery. This effort directly addresses how to apply sustainability assessments to the unique aspects of hydrogen (H2) infrastructure projects using the Envision® sustainability framework developed by the Institute for Sustainable Infrastructure (ISI). Envision is a flexible system of criteria and performance objectives to aid decision makers and help project teams identify sustainable approaches during planning, design and construction of infrastructure projects that will continue throughout the project’s operations, maintenance, and end-of-life phases. The goal of this work is to support those interested in conducting sustainability assessments for hydrogen infrastructure projects. Through this work the team has developed hydrogen-specific guidelines and best practices to assist project developers, investors and regulators in straightforward application of the Envision framework to systematically enhance clarity and increase objectivity across hydrogen projects. Subject matter experts from 20 different organizations (industry, non-profits, municipalities, emissions regulators, national labs) were engaged through 7 focus groups to discuss the H2-prioritized Envision requirements and elements to be included in the guidelines. In addition to these guidelines, the team conducted case studies as a way of demonstrating and informing the guidelines and providing examples or ideas for implementing sustainability in future projects. Through this study, the authors found that hydrogen infrastructure projects can incorporate many sustainable practices including reducing GHG emissions affecting climate change, reducing air pollutant emissions affecting the health of communities, synergistically handling waste byproducts, integrating into existing infrastructure, incorporating renewable energy, and addressing equity and environmental justice. Additionally, hydrogen infrastructure projects could benefit from 2-way communication engagement and collaborative planning with stakeholders, educational awareness of hydrogen technology, tracking and reporting on water use and water quality, and including monetized environmental and social benefits in life-cycle cost estimates. This document is the final technical report for the Hydrogen Sustainability Assessment Methods for Project Development project. While the main focus of the report is to provide guidelines for applying sustainability to hydrogen infrastructure, there are sections within the appendix providing completed project tasks and methodology.

08 HYDROGEN↗

DOE OSTI2025

srlife : a software tool for estimating the life of high temperature concentrating solar receivers. Part I – metallic receivers

Here, this paper introduces srlife, a tool for estimating the structural service life of concentrating solar power (CSP) receivers operating at high temperatures. Supporting both metallic and ceramic receiver designs, srlife is available as open-source software at https://github.com/applied-material-modeling/srlife and can be installed via the PyPi package manager (https://pypi.org). Given basic receiver geometry and incident heat flux, the tool performs thermohydraulic and structural analysis and estimates the life of a receiver. Designed for easy integration into a software stack, including solar field and levelized cost analysis, the tool can be utilized for optimizing receiver designs to meet service life and economic targets. This paper is Part I in a two-part series. Part I discusses the analysis process used to estimate the life of metallic receivers, along with a description of the required input data. Additionally, several heuristics applied within srlife can reduce analysis time significantly while maintaining accurate life estimations for metallic receivers when compared to full analyses. Several examples demonstrating the utility of srlife in receiver design are also discussed. Part II focuses on the life estimation of ceramic receivers, using time-dependent reliability analysis and various ceramic failure models implemented in srlife.

Creep-fatigue analysis↗

DOE OSTI2025

Validating Greater Sage-Grouse Individual-based Model (IBM) Tool (Final Report)

The project focused on validating the previously developed Greater Sage-Grouse Individual-based Model (GrSG IBM; LaGory et al. 2012, 2021). The objective was to transform this predictive, spatially and temporally explicit model into a portable resource to assist siting/resource managers in proactively assessing the cumulative impacts of wind energy development on the greater sage-grouse. Utilizing a bottom-up, individual-based approach, the GrSG IBM accounts for landscape context and species behavior, aiming to reduce uncertainty in estimating development impacts and support ecologically mindful land-based wind energy development. The validation effort covered approximately 6,540 km 2 near the Seven Mile Hill Wind Project in Wyoming. The GrSG IBM tool, built on the NetLogo platform (Tisue and Wilensky 2004), was executed over a 50-year period, with the analysis focusing on years following a 10-year initialization phase. Key results demonstrated the tool’s biological soundness across five key biological metrics: non-chick age class distribution (older than 10 weeks), adult sex ratio, life expectancy, population size, and overall population growth. For instance, the tool estimated that 58.6% of the non-chick population was reproductively immature, while the reference ranges from 51.4% to 57.8% (Patterson 1952, Rogers 1964). Experts confirmed the tool’s estimate was within a reasonable range for the species. The tool estimated average life expectancy of 1.43 years, while the reference ranges from 0.9 years to 1.1 years (Ammann 1957, Hamerstrom 1949). Experts also supported the model’s life-expectancy estimate as ecologically sound for the species in the study area. In terms of population change, the model estimated an annual shift between a 0.6% decline and a 1.0% increase over 50 years. While the reference suggests 2.9% annual decline in range-wide populations (Cortes et al. 2023), that includes many at-risk populations in South Dakota and Washington, for example. Our study area—in the northeastern part of Carbon County and western-edge of Albany County, Wyoming—is one of the remaining greater sage-grouse habitats supporting some of the most stable populations. Experts confirmed that the range of the annual population change spanning from a 0.6% decline to a 1.0% increase estimated by the tool was reasonable for our study area for this reason and confirmed that aligned with population estimates from existing studies on the greater sage-grouse and wind energy development in the study area (LeBeau et al. 2017a, Smith et al. 2024). Furthermore, the project showed that temporally explicit biological metrics generated by the GrSG IBM tool can complement the USGS’ Prioritizing Restoration of Sagebrush Ecosystems Tool (PReSET; Duchardt et al. 2021) by incorporating habitat restoration strategies into seasonal habitat suitability models to visualize population responses over time.

17 WIND ENERGY↗

DOE OSTI2024

Catalytic Deconstruction of Ethylene Vinyl Acetate Copolymer and Polyethylene Mixtures via Hydroconversion: Challenges and Solutions

We explore hydrogenolysis over ruthenium supported on zirconia (Ru/ZrO 2 ) and hydrocracking over platinum (Pt) supported on zeolites as an effective end-of-life strategy for ethylene vinyl acetate (EVA)–a widely used performance heat sealant in hard-to-recycle multilayer packaging. For Ru/ZrO 2 hydrogenolysis, EVA reacts slower than low-density polyethylene (LDPE) and the catalyst deactivates due to carbonaceous deposits originating from polyenes generated in situ during EVA thermal degradation. High H 2 pressures and temperatures can overcome catalyst deactivation; however, CH 4 yields are excessive due to cascade hydrogenolysis stemming from strong C=C/metal interactions. Polyene hydrogenation allows chains anchored by C=C to desorb from Ru, shifting product selectivity from CH 4 to higher-value liquids. Hydrogenolysis of mixed EVA and linear low-density polyethylene (LLDPE), mirroring typical frozen food packaging formulations, results in comparable catalyst activity and CH 4 yield as the pure EVA resin. For Pt/zeolite hydrocracking, pure EVA and EVA:LLDPE mixtures are deconstructed to propane or light naphtha with minimal CH 4 production. Among catalysts tested, Pt/HY gives the highest liquid productivity (g C5+products /g cat ·h). Furthermore, these findings showcase the recalcitrant nature of EVA and its associated mixtures for Ru/ZrO 2 hydrogenolysis, highlighting that hydrocracking catalysts may be superior for complex packaging waste.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Myriad World Baseline: Global Geodemographic Estimates

The LandScan Myriad World Baseline (MWB) method produces global, residential (nighttime/home-location) gridded geodemographic estimates based on 5-year age/gender cohorts—at 30-arcsecond (≈1 km) resolution. MWB is designed to fill gaps where detailed, georeferenced survey data (e.g., Demographic and Health Surveys (DHS)) are missing or outdated, and to provide a baseline that can support human security analysis, including consequence assessment, “patterns of life” modeling, and scenario-based population futures. MWB’s workflow spatializes household-level age/gender characteristics from the GLOPOP-S dataset by conflating household and gridded expected relative wealth adapted from Global Gridded Relative Deprivation Index (GRDI), then adjusts them to a target year of interest. Age/gender estimates are then applied to harmonize lowest-administrative-level statistics with LandScan residential counts, yielding final geodemographic estimates. Two validation case studies are presented: Ghana (2021) and Tokyo/Kanagawa, Japan (2020), illustrating spatial variability in demographic cohorts and comparing MWB outputs to official gridded statistics. Results show close overall alignment relative to validation criteria including population pyramids and age-dependency ratios.

Tuccillo, Joe [ORNL] (ORCID:0000000259300943)↗

DOE OSTI2026

Ambient-Pressure Chemical Recycling of Thermoset Carbon Fiber-Reinforced Polymers via Low-Temperature Solvolysis: Techno-Economic and Life-Cycle Assessment

Carbon fiber-reinforced polymer (CFRP) waste is rapidly accumulating, with global volumes projected to exceed 500,000 tons annually by 2050. Virgin carbon fiber production is extremely energy- and cost-intensive, and growing demand has intensified supply-chain vulnerabilities associated with precursor availability and reliance on critical materials. Scalable recycling technologies therefore offer not only environmental benefits but also opportunities to reduce material costs and strengthen domestic composite supply chains. This study introduces an efficient, mild chemical recycling method for epoxy-amine CFRPs, utilizing acetic acid (80 wt%) and zinc acetate (1 wt%) at atmospheric pressure and low temperature (~110 °C). The solvolysis process preserves residual resin (~40%) on recycled carbon fibers (rCF), enhancing interfacial bonding in remanufactured composite materials. Recycled fibers retain ~90% of their mechanical properties, and recovered oligomers show potential for reuse in epoxy formulations, supporting material circularity. Techno-economic analysis (TEA) and life-cycle assessment (LCA) confirm the scalability and sustainability of this process.

Recycling CFRP↗

DOE OSTI2026

Agent-based Modeling for the Multi-objective Optimization of Energy Production Pathways: Integrated Techno-Economics and Life Cycle Assessment

This project developed an integrated modeling framework to evaluate how purpose-grown bioenergy feedstocks could support large-scale sustainable aviation fuel production in the United States. Led by Colorado State University with project partners, the work combined geographically resolved analysis, techno-economic assessment, life cycle assessment, multi-objective optimization, and agent-based modeling to examine feedstock performance, deployment potential, land-use implications, and adoption dynamics. The overall goal was to identify practical and sustainable pathways for producing aviation fuel from feedstocks such as energy crops, woody crops, oilseeds, and algae while helping inform policy, investment, and research needs tied to national SAF goals. In essence, the project provides a systems-level assessment of the opportunities and constraints associated with scaling bioenergy-based aviation fuels in the U.S.

09 BIOMASS FUELS↗

DOE OSTI2025

Introduction to NETL Natural Gas LCA

This work presents an overview of NETL natural gas (NG) life cycle modeling. The content covers: introduction, model structure and unit processes, co-product management, and highlights from the recently published NETL NG baseline report.

life cycle analysis (LCA)↗

DOE OSTI2025

Screening analysis of enhanced weathering of igneous rocks and industrial waste materials

Enhanced weathering (EW) is a promising emerging carbon dioxide removal approach that involves harnessing and accelerating the natural weathering process by which atmospheric CO2 passively reacts with exposed alkaline minerals and is removed from the atmosphere. This manuscript reports on a screening level techno-economic analysis of EW. Two primary cases utilizing different sources of alkaline material are considered: (1) utilizing naturally occurring mined igneous rocks, and (2) utilizing industrial waste materials. The modeled EW process encompasses material purchase, comminution, transport, distribution of material on farmland, and measurement, reporting and verification of CO2 removal. Detailed sensitivities are performed to highlight promising scenarios for application. The analysis highlights that utilizing materials with high weathering potential in suitable locations may result in relatively low levelized cost of captured (less than $100 per total tonnes of CO2 captured from the atmosphere). NETL is publishing a detailed and transparent report titled “Enhanced Weathering: Techno-Economic and Life Cycle Screening Analysis” that includes more detail on the screening level techno-economic analysis and includes a life cycle analysis.

Leptinsky, Sarah [NETL Site Support Contractor, Na↗

DOE OSTI2026

Used Nuclear Fuel Management Using the Next Generation System Analysis Model

The U.S. Department of Energy (DOE) is leading the National effort to manage the back end of the nuclear fuel cycle, encompassing the safe transportation, storage/staging, and/or eventual disposal of used nuclear fuel (UNF) and high-level radioactive waste. The Next Generation System Analysis Model (NGSAM) is DOE’s discrete-event, agent-based simulation tool designed to model the full life cycle of UNF from reactor discharge to final disposal. NGSAM supports the DOE Office of Spent Fuel and High-Level Waste Disposition by enabling a detailed, scenario-based analysis of logistics, infrastructure, and shipping strategies. NGSAM replaces legacy models with a modern, flexible platform built on Repast Simphony and enhanced by the Process Analysis Tool. NGSAM simulates the movement and interaction of individual fuel assemblies with system components such as canisters, casks, railcars, and facilities. The model integrates with the Java Transportation Operations Model to plan and execute transportation scenarios, supporting both constrained and unconstrained resource allocation. Key features include customizable allocation and acceptance algorithms, detailed facility-level operations, and a Quick Edit tool for rapid scenario adjustments. NGSAM supports multimodal transportation modeling (e.g. rail, road, barge) and provides comprehensive cost, schedule, and infrastructure data. NGSAM utilizes data from sources such as DOE’s STANDARDS UNF database and DOE’s Stakeholder Tool for Assessing Radioactive Transportation, while also allowing user-defined inputs for scenario customization. NGSAM enables stakeholders to evaluate complex UNF management strategies, assess system performance under varying assumptions, and inform decision making for future infrastructure investments. Its modular architecture and integration with other Integrated Waste Management System tools make it a critical asset for planning the safe and efficient disposition of the Nation’s growing UNF inventory.

Craig, Brian [Argonne National Laboratory (ANL)]↗