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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
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)]↗
DOE OSTI2025

Data for Bistline, et al. (2025) "Policy Implications of Net-Zero Emissions: A Multi-Model Analysis of United States Emissions and Energy System Impacts"

These files contain input assumptions, results, and figures associated with the Bistline, et al. (2025) article "Policy Implications of Net-Zero Emissions: A Multi-Model Analysis of United States Emissions and Energy System Impacts" in Energy and Climate Change as part of the Energy Modeling Forum 37 study. Please refer to the original paper for details.

climate policy↗
DOE OSTI2024

Once-Through Steam Generator Model Analysis Using Python and Advanced Optimization Tools (Summer Internship Report)

This study focuses on the parametric analysis of design parameters for a once-through steam generator (OTSG) model, using python and advanced optimization tools to facilitate applications such as the flowing autoclave steam generator (FASG) test cases. Building on previous research involving another OTSG with a different design, this project aims to enhance our understanding of how steam generators (SGs) behave and how their outputs are influenced by changes in design. The reason for this design change is to allow for more precise modeling and optimization of SG performance, to provide a comparative analysis between the two designs, and to set up the model for integration with the FASG test case. The OTSG python-model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor-type small modular reactor system. Design studies involve changing the model’s input design parameters to observe the resulting effects on the output of the system. By using advanced optimization tools, such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory, detailed design parametric studies and model optimization were performed. Six input parameters—pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid), respectively, of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (i.e., ±1%, ±5% and ±10% relative changes) for 600 samples. The analysis provides valuable insights into SG optimization and can be used for sensor placement optimization to effectively monitor and obtain experimental data in other tests.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Unpacking Modeling Analysis for the Circular Economy

This session will cover: (1) How models simulate material recovery, recycling, product life cycles and waste management. (2) Using life cycle analysis (LCA) to measure environmental impacts across product life cycles and guide decision-making. (3) Optimizing resource use, reducing energy consumption and minimizing waste in recycling systems. (4) Evaluating EPR and other interventions through scenario analysis to make informed decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Quantitative SANS and multi-model analysis of spacer-dependent micellization of urea-based gemini surfactants

The micellization behavior of urea-based cationic gemini surfactants was investigated using small-angle neutron scattering (SANS) with multi-model form factor analysis. A homologous series of surfactants with urea group included in the hydrophobic tail and polymethylene spacers consisting of two to ten methylene units was analyzed using three form factor models: a core–shell ellipsoid and two variants of homogeneous ellipsoids. The results from all models show a consistent trend of the micelle structures, confirming that the spacer length critically influences micellar geometry, aggregation number, and hydration. The surfactant with four CH 2 groups in the spacer formed the largest micelles with the highest aggregation number, while longer spacers led to progressively smaller, more compact aggregates. The shell hydration—quantified as the volume fraction of heavy water within the hydrophilic region—decreased systematically with increasing spacer length due to enhanced hydrophobicity of the headgroup-spacer region. Intermicellar interactions, modeled as screened Coulomb interaction using the rescaled mean spherical approximation (RMSA), revealed the strongest electrostatic repulsion for the case of four methylene groups in the spacer, corresponding to the highest micellar charge and largest interparticle spacing. The observed spacer-dependent trends were robust across all modeling approaches, demonstrating that the spacer length serves as a key structural determinant of self-assembly in this type of urea-based gemini systems. These findings provide insight into the design of gemini surfactants with tailored aggregation behavior for applications in drug delivery, nanostructure templating, and solubilization technologies.

Core–shell ellipsoid model↗
DOE OSTI2024

Offshore Wind to Hydrogen - Modeling, Analysis, Testing and International Collaboration Work

This project explores electrolytic hydrogen production from an offshore wind turbine by: Modeling: Simulate an offshore wind turbine and generate power output profiles; Analysis: Analyze offshore conditions and determine operational modes of the stack; Testing: Perform hardware testing to evaluate dynamic characteristics; and International Collaboration Work: Share learnings and publish. Potential Outcomes: Accelerate development of an integrated, in-turbine offshore wind hydrogen system; and Support two DOE Energy Earthshots - Hydrogen and Floating Offshore Wind.

electrolyzer↗
DOE OSTI2025

System Safety Risk Analysis Models (SSRAM)

This presentation provides a high level overview of the System Safety Risk Analysis (SSRAM) methodology and motivation.

Clark, Andrew Jordan [Sandia National Laboratories↗
DOE OSTI2024

Geomagnetically Induced Current Field Test on Large Grid-Connected Power Transformers: Analysis, Model Development, and Simulations

Geomagnetic-induced current (GIC) flow in power grids can cause undesirable effects such as transformer overheating, harmonics, higher reactive power demand, etc. Many simulation models have been developed to study these effects, but real-world verification on modern transformer designs is rare. Here, this paper presents the first long-duration GIC field test in the U.S. performed on high-voltage, grid-connected transformers featuring winding clamps and tie rods instead of conventional tie bars. Field measurements were taken to evaluate GIC effects. These measurements also aided in developing and validating thermal and electromagnetic transient (EMT) models of the transformers. During the test, significant current and voltage distortions were observed along with considerable transformer reactive power losses. Analysis of the field measurements showed that the transformers’ hottest spot was at the inner windings, and their k-factors were close to factory test and software default values. Thermal simulations indicated that the transformers would not violate their thermal limits even for a GIC waveform that peaks at about 200 A/phase. EMT simulations revealed that increased transformer loading may reduce GIC-induced reactive power demand and harmonics in certain scenarios. The study also highlighted potential inaccuracies in using the k-factor method to calculate transformer reactive power losses.

EMTDC↗
DOE OSTI2026

Multi-model analysis of the impact of water vapor on the radiative forcing of volcanic aerosols after the 2022 Hunga Eruption

On 15 January 2022, the Hunga volcano eruption released unprecedented amounts of water vapor into the atmosphere alongside a modest amount of SO 2 . In this work we analyse results from multiple Earth system models as part of the Hunga Tonga-Hunga Ha'apai Volcano Impact Model Observation Comparison Project. Our results show a good model agreement over the climatic outcomes of the eruption, overall indicating a significant negative radiative forcing from the Hunga eruption. The multi-model mean of global instantaneous radiative forcing averaged over 2022–2023 is estimated at −0.19 ± 0.06 W m −2 at the top-of-atmosphere (TOA), and −0.16 ± 0.06 W m −2 at the surface. Simulations with free-running meteorology and climatological sea surface temperatures and sea ice yield a global mean TOA forcing of −0.14 ± 0.10 W m −2 across two models for the first 2 years, decreasing to −0.09 ± 0.10 W m −2 on average between 2022 and 2027. However, these global values may be underestimated by about 50 %, considering that recent SO 2 injection retrievals suggest nearly twice the amount than the 0.5 Tg-SO 2 used in the protocol. We also find that the contribution from added stratospheric water vapor is minimal and that the injected SO 2 and the resulting formation of stratospheric sulfate dominate the radiative forcing. However, water vapor played a key role in the initial aerosol growth, leading to a stronger negative radiative forcing during the first 6 months after the eruption compared to simulations without water vapor co-injection.

Geosciences↗
DOE OSTI2025

Policy implications of net-zero emissions: A multi-model analysis of United States emissions and energy system impacts

Many countries, subnational jurisdictions, and companies are setting net-zero emissions goals; however, questions remain about strategies to reach these targets, policy measures, technology gaps, and economic impacts. Here, we investigate the potential policy implications of reaching economy-wide net-zero CO 2 emissions across the United States by 2050 using results from a multi-model comparison with 14 energy-economic models. Model results suggest that achieving net-zero CO 2 targets depends on policies that accelerate deployment of zero- and low-emitting technologies that have seen rapid cost reductions in recent years (including wind, solar, battery storage, and electric vehicles) as well as relatively nascent options (including carbon capture and storage, advanced biofuels, low-carbon hydrogen, advanced nuclear, and long-duration energy storage). While net-zero policies are likely to lower fossil fuel consumption, including considerable coal and petroleum reductions, achieving net-zero emissions does not necessarily mean phasing out all fossil fuels. Model results indicate that the Inflation Reduction Act’s energy and climate provisions amplify near-term decarbonization but that net-zero policies have larger impacts on long-run outcomes. Stringent climate policy can have large fiscal impacts on tax revenue and government spending—revenues from carbon pricing and subsidies for carbon removal range from 0.1 % to 3.7 % of GDP in 2050 across models. Each dollar per metric ton carbon price leads to a 0.06 % to 0.31 % reduction in economy-wide CO 2 emissions relative to a reference scenario with current policies. Spending on energy across the economy decreases relative to today for many models under reference and net-zero policies, especially as a share of GDP, due primarily to end-use electrification and energy efficiency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Update on Parallel Process Execution in the Next Generation System Analysis Model

As of the end of 2021, 88,880 metric tons of heavy metal (MTHM) (44,741 MTHM in dry storage; 44,139 MTHM in wet storage) of spent nuclear fuel (SNF) were stored at various reactor sites across the United States [1]. The Office of Storage and Transportation in the Department of Energy is planning for the transportation, storage, and eventual disposal of SNF and high-level radioactive waste (HLW). To aid in this effort and inform decision-makers about the backend of the spent fuel cycle, systems analysis tools capable of analyzing the various options with respect to SNF and HLW management are being used as well as continuously improved to meet the evolving needs of the program. System analysts typically use these tools to vary underlying assumptions (shipping rates, allocation priority, available facilities, start dates, etc.) and study the implications of these changes on site clearance schedules, campaign costs, transportation infrastructure acquisition, etc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Update on Parallel Process Execution in the Next Generation System Analysis Model (NGSAM)

As of the end of 2022, it is estimated that over 90,000 metric tons of heavy metal (MTHM) of spent nuclear fuel (SNF) were stored at various commercial nuclear power reactor sites (both operating and shutdown) across the United States [1]. The Office of Storage and Transportation within the U.S. Department of Energy’s Office of Nuclear Energy is planning for the transportation, storage, and eventual disposal of SNF and high-level radioactive waste (HLW). To aid in this effort and inform decision-makers about the backend of the spent fuel cycle, systems analysis tools capable of analyzing the various options with respect to SNF and HLW management are being used as well as continuously improved to meet the evolving needs of the program. System analysts typically use these tools to vary underlying assumptions (shipping rates, available facilities, start dates, interim storage capacity, etc.) and study the associated system implications such as timing for clearing sites of SNF, various cost elements, transportation infrastructure acquisition needs, etc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Primary System Thermal Fluids Analysis Model Development for the Compact High Temperature Gas Reactor (HC-HTGR) (Final Report)

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is collaborating on the thermal hydraulic design and analysis of HC-HTGR reactor pressure vessel internals to ensure the reactor maintains sufficient safety margins during normal operation, shutdown, and accident conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Intensified biogas to liquid (IBGTL) Process: Experimental validation and modeling analysis

The Intensified Biogas to Liquid (IBGTL) process aims to overcome traditional economy-of-scale barriers in biogas-to-liquid fuel production by integrating bi-reforming and Fischer-Tropsch synthesis (FTS) in a single IBGTL reactor. This reactor operates at uniform pressure with different optimized temperatures across two zones for efficient conversion, utilizing multifunctional bi-reforming catalysts and high-temperature FTS catalysts. Bench scale experiments were carried out using landfill gas (LFG) in a single pass process, and the yield data from these experiments were fed into process scale-up design and techno-economic analysis (TEA) across four scenarios: (1) a single pass process, (2) a process with material recycling, (3) a process with liquefied petroleum gas (LPG) co-product recovery, and (4) a process with electricity generation from the fuel gas produced. TEA identified Scenario 2 as the most cost-effective, achieving a Minimum Fuel Selling Price (MFSP) of $\$4.59$ per gallon, competitive with the current national diesel price of $\$4.7$ per gallon. However, comparison with the conventional two-reactor system highlights the need for catalyst performance improvements. Sensitivity analysis emphasized the importance of manufacturing cost, liquid fuel yield, and biogas flow rate. Further analysis determined that the IBGTL process must achieve a diesel mass yield beyond 11.7% to surpass the economic viability of the conventional TriFTS (Tri-reforming followed by Fischer-Tropsch Synthesis) process. If the IBGTL process attains the TriFTS yield of up to 17%, the resulting MFSP could be approximately 31% lower than the current TriFTS MFSP. Furthermore, renewable energy credits and carbon credits can further enhance the economic viability of BGTL processes.

09 BIOMASS FUELS↗
DOE OSTI2024

STREAM: Strategic Technology Roadmapping and Energy, Environmental, and Economic Analysis Model

This is the implementation of the framework for the planning of the technological makeup of the industrial sector. Motivated by the efforts to achieve carbon neutrality, the model of this framework modifies the portfolio of technologies over time for the sector of interest such that, - Net Present Value (NPV) is minimized - Constraint on Greenhouse Emissions (GHG), e.g. carbon dioxide, is satisfied - Demand of the underlying commodity is satisfied - The current implementation reflects a case study for the electric power sector. The for a given initial set of capacities of different vintages, the space of decisions include, - Retirement of the existing capacities. - Retrofitting the existing capacities to alternative characteristics. - Creation of new capacities from a technology portfolio. All the associated quantities with the deployments, e.g. CO2, heat requirement, etc.

Thiery, David↗
DOE OSTI2025

Reliable Integration of AI Data Centers at Scale – Analysis, Modeling and Synthetic Data Generation

This report analyzes the power consumption of large dynamic digital loads using the open-source MIT supercloud and SURF datasets. With an emphasis on the MIT data, we calculate important power consumption characteristics to help system operators improve generation planning and resource allocation. We also introduce a rudimentary model for generating synthetic load profiles.

97 MATHEMATICS AND COMPUTING↗