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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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This core model proposal updates modeling structures, key technology assumptions, and data sources for a detailed representation of hydrogen in GCAM’s energy system, including production, transmission and distribution, and consumption in hydrogen end-use sectors (buildings, transportation, industry).
The goal of this core model proposal (CMP) is to break out Ukraine from the Europe_Eastern region. This work aims to establish Ukraine as an independent region in the GCAM core (region 14) while moving Belarus and Moldova to region 15 (Europe_Non_EU). We have: 1) Updated several mappings to recode region 14 (formerly Europe_Eastern) as Ukraine and moved Belarus and Moldova to region 15 (Europe_Non_EU); 2) Updated several assumptions in the raw data files which provide information by region to reframe Ukraine as the 14th region, including coefficients, base year values, share weight interpolation values and rules, pipeline networks for gas trade, elasticities, shares, etc. 3) Changed documentation and in-code comments at several places referring to fixed 32 regions in GCAM to indicate that GCAM can have any number of regions; 4) Updated code base in gcamdata to dynamically process data for Ukraine given special cases.
This Core Model Proposal (CMP) comprehensively restructures and updates the macroeconomic and socioeconomic modules in gcamdata. It includes visualizations of key data inputs, accounting identities, and data flows in the context of GCAM-Macro-KLEM. Major improvements include: (1) updating the Penn World Table (PWT) to version 10 and incorporating a new source, the Global Macro Database (GMD); (2) updating the SSP socioeconomics database from version 3.0.1 to 3.2; (3) introducing SSP-specific differentiation of employment and labor force data; (4) improving data integration between national accounts (from PWT, GMD, and GTAP) and GDP/population data from external sources; and (5) general data cleaning and structural refinements. We document the data sources and key assumptions used throughout the processing. These updates establish the foundation for the forthcoming KLEAM version of GCAM-macro.
This Core Model Proposal (CMP) updates the Shared Socioeconomic Pathway (SSP) database to a recent version (v3.0.1; released in 2024) within GCAM. Currently, GCAM relies on socioeconomic drivers, including population, GDP, and labor force projections, from the original SSP database version released in 2013. These projections, provided by independent socioeconomic dynamic models (e.g., multi-dimensional demographic models and macroeconomic models of convergence growth), may need regular updates when (1) near-term observations become available and (2) there are updates and advancements in the socioeconomic modeling. Timely updates of socioeconomic drivers in global economic equilibrium and multisector dynamic modeling will ensure (1) alignment of historical years and near-term projections with observations, enhancing base year calibrations, including calibration parameters and labor productivity, and (2) improvement of long-term projections with updated socioeconomic drivers, which set the scale of the economy. This CMP updates the SSP data (from v2013 to v2024) and also fixes/reconciles historical GDP data sources in GCAM. We investigate the impact of these updates on GCAM projections.
Under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, an integrated multiphysics approach is being developed to model the core bowing phenomena important to liquid metal-cooled fast reactors. Core bowing is an important passive safety mechanism in liquid metal-cooled fast reactors and involves multiphysics effects including radiation transport, fluid flow, heat transfer, and mechanical response to temperature and flux gradients. This report summarizes recent progress on developing a multiphysics, MOOSE-based workflow to predict core bowing and associated reactivity feedback. Significant new capabilities in the reactor physics code Griffin - sodium backfill and pin power reconstruction for deformed geometries - were applied in this effort. This year’s work included verification, code comparisons, sensitivity studies, and coupled demonstrations that advance the state of MOOSE-based core bowing workflow. Griffin’s sodium backfill capability was verified by demonstrating that its automated treatment of geometry expansion and material-density updates reproduces manual calculations exactly, confirming solid mass conservation and proper coolant backfilling in expanded geometries. Reconstructed pin powers were compared for Griffin’s ductheterogeneous and ring-heterogeneous treatments in single-, seven-, and nineteen-assembly cases, with best agreement observed in lower-leakage configurations and the duct-heterogeneous approach offering substantially lower computational cost. Thermal-hydraulic sensitivity sensitivities showed that MOOSE SCM, SAM, and CFD are expected to produce similar deformation predictions despite variances in their temperature predictions, and that explicit treatment of inter-assembly flow becomes increasingly important as gap flow rate increases. Finally, coupled demonstrations on small multi-assembly configurations using Griffin, MOOSE Solid Mechanics, MOOSE SCM, and Heat Conduction produced physically consistent reactivity feedback from thermal expansion and bowing. The coupled demonstrations simulated grid plate expansion as well as resultant core bowing at full power conditions. Simplifications were made in current workflow, namely the assumption of instantaneous full power conditions following hot zero power, and pre-expanding the Griffin geometry axially due to lack of an axial fuel pin expansion model and temperature feedback to Griffin.
GCAM's current base year – the last historical year used for calibration – 2015, is considerably lagged compared to the present year, indicating out-of-date assumptions about near-past state of the resources, commodities, and technologies represented in GCAM. This proposal makes data and code changes to enable updating the GCAM base year easier by making the processing code more flexible and robust.
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This project is part of the program area to develop and improve core capabilities for the Energy-Efficient Mobility Systems (EEMS) program that enable research, development and deployment of advanced mobility solutions and enhance the EEMS Program's ability to address system-level transportation challenges. Advancements to the Future Automotive Systems Technology Simulator (FASTSim), Route Energy Prediction Model (RouteE), Transportation Technology Total Cost of Ownership (T3CO) and Open Platform for Agile Trip Heuristics (OpenPATH) core capabilities under this project supports the overall EEMS Program goals to effectively evaluate energy and mobility impacts of future transportation technologies and services, and to identify the most promising pathways to reduce transportation costs and environmental harms, and to improve mobility access. This presentation was prepared for the 2026 Annual Merit Review of this project.
Estimating the equilibrium state for pebble bed reactors (PBRs) presents complex challenges as it requires simultaneous consideration of changes in the pebbles’ movement as well as their fuel compositions. Whereas traditional approaches use multigroup diffusion codes for neutronics calculations of PBRs’ equilibrium state, the double-heterogeneity of PBRs complicates neutron cross-section generation. Continuous-energy Monte Carlo (MC) methods are better suited for detailed PBR analysis because of their natural handling of double-heterogeneity, but they demand substantially more computational resources. Here, this study introduces a novel method for efficiently estimating the equilibrium state in small and micro PBRs with reduced computational cost. The method is anticipated to accelerate the processes of core design and performing parametric studies for utilizing advanced fuel and structural materials. The HTR-10 reactor design was used for validating the method’s predictions and evaluating its computational efficiency. When compared to reference calculation values from the literature, criticality (k-effective) was predicted to be approximately within the margin of error of the MC transport calculation, average core power density (in megawatts per cubic meter) was predicted within 2.5% relative error, and maximum thermal flux (10 13 n/cm 2 .s −1 ) was predicted within 1.8% relative error. The calculated inventory of fission products and fuel composition in the equilibrium core were within 15% and 16.6%, respectively, when compared to reported values from the literature. The difference is attributed to variance in the considered values of the core temperature, which was found to significantly affect the depletion analyses.
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Hector V3.2.0 is the version documented in Dorheim et. al (accepted in GMD), the changes between the previous version coupled with GCAM were in response to the reviewer feedback. We corrected aerosol forcing coefficients based on Zelinka et al. (2023), enabled the permafrost module to be on by default, and recalibrated the model. These changes mean that we had to update the hector-gcam.ini file, it also causes some changes in Hector output behavior (described below) which may have implications on GCAM runs. Ultimately Hector is cooler by about 0.15 degrees, although this is scenario dependent.
Using the ab initio symmetry-adapted no-core–shell model, we compute sum rules and response functions for light to medium-mass nuclei, starting from interactions that are derived in the chiral effective field theory. Specifically, we investigate electromagnetic transitions of monopole, dipole and quadrupole nature for 4 He, and explore dominant features of giant monopole resonances in symmetric nuclei such as the closed-shell 4 He and 16 O light nuclei, the intermediate-mass open-shell 20 Ne and the medium-mass closed-shell 40 Ca. Furthermore, for the NNLO opt chiral potential, we determine parameter-free monopole sum rules, which can provide information on the incompressibility of symmetric nuclear matter. Here, we report 213(10) MeV as an estimate for the compression modulus for infinite nuclear matter, which overlaps with the lower range of values often used in current astrophysical applications.
The discrepancy between models and data regarding the muon content in air showers generated by ultra-high energy cosmic rays still needs to be solved. The CONEX simulation framework provides a flexible tool to assess the impact of different interaction properties and thus address the muon puzzle. In this work, we present the multidimensional extension of CONEX and show its performance compared to CORSIKA by discussing muon-related air-shower features for three experiments: KASCADE, IceTop, and the Pierre Auger Observatory. We also implement an effective version of the core-corona model to demonstrate the impact of the core effect, as observed at the LHC, on the muon content in air showers produced by ultra-high energy cosmic rays. At a primary energy of E$_{0}$ = 10$^{19}$ eV, we obtain an increase of 15% to 20% in the muon content.
In recent years, an intense modeling activity has been focused on preparing and analyzing the second JET Deuterium–Tritium (D–T) experimental campaign DTE2. Among the numerous scientific outcomes of this campaign was the unique opportunity to test and validate the state of the art of modeling tools with fusion-relevant DT plasmas using the full metallic ITER-like wall in different scenarios. This work reports on the core predictive modeling of plasma density, electron and ion temperatures (n e , T e , T i ) performed using TRANSP (Pankin et al 2025 Comput. Phys. Commun. 312 109611) coupled with Trapped Gyro-Landau Fluid (TGLF)-SAT2 (Kinsey et al 2008 Phys. Plasmas 15 055908), (Staebler et al 2021 Nucl. Fusion 61 116007) for the JET D–T baseline scenario (I p = 3.5 MA, q 95 = 3, β N < 2, with pellet pacing) (Garzotti et al 2025 Plasma Phys. Control. Fusion 67 075011). The sensitivity to different input parameters, as the $\vec{E}$ x $\vec{B}$ shear parameterization and the values of the kinetic quantities at the boundary of the prediction domain (ρ = 0.85) has been assessed, identifying the confidence interval of the prediction results. In particular, the dependence of the electron density profile on the particle source parameters has been studied, identifying the ionization source as the main cause for the density gradient under-prediction obtained by TRANSP-TGLF, reported in (Hyun-Tae et al 2023 Nucl. Fusion 63 112004).
In recent history, extreme heat has been the cause of most deaths from a natural disaster. Exposure to extreme heat can aggravate preexisting conditions, increase hospitalization, and even cause death. Thus, modeling the thermal resilience of households across the United States will allow for a quantitative assessment of the health and safety risks posed by extreme heat. For the first time, we simulate occupant comfort in representative households across Boston by combining the granular results of the ResStock(TM) model with a two-node heat strain model. This model calculates occupants' core body temperature in each simulated household over a year. We compare the simulated core temperatures to two public health metrics: hyperthermia and heat stroke. Our results show for households in Boston that do not have or use aid conditioning, thousands potentially experience many dangerous heat events each summer and these events can last for more than a day at a time. These heat events peak during the late afternoon and evening, just as residents are coming home, cooking meals, and trying to go to sleep. We have found that multi-family buildings, renters, and low-income homes in more airtight and insulated homes are the most at risk for these events. These results demonstrate the scale and urgency of exposure to extreme heat.
Here, the goal of the present work was to provide the necessary reaction emulation information to enable detailed process simulation of a chemical looping H 2 production system from fossil fuels using CaFe 2 O 4 . This specifically pertained to the necessary kinetic data, reaction model development, and model rate parameters required for reaction emulation in both reducing and oxidizing environments. A logical methodology was defined, which included discretization of the reaction network, establishing a core model for reaction emulation that could be adapted based on the system phenomena, and development of a rate parameter regression tool designed around the core model. An extensive array of data sets was acquired by which parametric regressions were performed. The work presented and tabulated a comprehensive set of rate parameters for the reduction and oxidation reactions of CaFe 2 O 4 and descendent phases of Ca 2 Fe 2 O 5 , FeO, Fe 3 O 4 , Fe, and CaO to emulate reaction behavior in a looping-based process environment. This included direct reduction using CH 4 , H 2 , and CO, and direct oxidation reactions with steam, CO 2 and O 2 . Dynamic equilibrium was quantified for reactions that could utilize H 2 O and CO 2 as soft oxidants to re-saturate lattice oxygen in the depleted structure/phases. The kinetics associated with the oxidative mechanisms with the soft oxidants were quantified and compared to those of the reducing counterparts. The analysis provided critical insight to emulate reactions for a process that seeks to use natural gas (NG) or other fossil fuels as a direct reductant for the end goal of H 2 production.
Pebble-Bed High-Temperature Gas-cooled Reactors (PB-HTGR) are moderated by the graphite in the fuel pebbles and the graphite reflector surrounding the pebble-bed. Because graphite is by far the most abundant material in PB-HTGRs and the primary moderator, accurate modeling of the graphite material, including density, impurities, and temperatures, is crucial for accurate computational modeling and simulation of these reactors. While main characteristics of the graphite components are often known, the local temperature is less well known and often averaged over all components. Here, this work studies the impact of considering accurate temperature profiles in the graphite material on the generation of a small PB-HTGR model at the state of equilibrium operation and on short-term accident progression. The fuel compositions for the PB-HTGR were determined using a jump-in equilibrium modeling method, the Axial Radial Zone Equilibrium Modeling (AR-ZEM) method. In contrast to previous work, the AR-ZEM method was used considering thermal-hydraulic feedback from the MELCOR code to determine temperatures of the fuel pebbles and the surrounding graphite reflector. The consideration of an axial and radial temperature profile in the core and reflector, as opposed to uniform material temperatures, had an impact of almost 1,300 pcm on the equilibrium core eigenvalue and caused significant differences in the discharged plutonium fuel inventory with up to 4.9% and 11.0% for Pu-239 and Pu-242, respectively. To assess the impact on short-term accident progression, two Anticipated Transient Without SCRAM (ATWS) events, a Pressurized Loss of Forced Coolant (PLOFC) and a Control Rod Withdrawal (CRW) with loss of flow, were simulated with MELCOR. The use of temperature profiles in the equilibrium core models did not reveal a significant impact on the temperature, power, or reactivity responses during the transients. In conclusion, a need for consideration of accurate temperature profiles, in particular for the graphite reflector, was found for the generation of equilibrium PB-HTGRs core models using jump-in methods, but detailed temperature profiles may not be necessary when performing conservative transient analysis.