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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Stage-local partitioned two-step runge-kutta methods for large systems of ordinary differential equations

We introduce stage-local partitioned two-step Runge-Kutta methods are an extension of standard two-step Runge-Kutta methods, which are an alternative to the standard additive two-step Runge-Kutta methods currently existing in the literature. Furthermore, these new schemes are designed with an eye towards truly N-partitioned systems and leverage local stage approximations to make several computationally interesting approximations viable. Specifically, the focus on local stage approximations makes possible the construction of truly asynchronous schemes, in the parallel sense, possible. In addition, we show that an implicit-explicit approach to these schemes can lead to methods that require the inversion of only local nonlinear systems.

Applied Dynamical Systems↗
DOE OSTI2022

Mechanistic study of chemical looping reactions between solid carbon fuels and CuO

Copper (Cu) based chemical-looping combustion (CLC) is a promising process that utilizes solid carbon fuel such as coal and biomass. Understanding the reaction kinetics in this process can facilitate the industrial design of CLC units. Here, in this work, molecular dynamics (MD) simulations were performed to investigate the reaction kinetics of n-butane and two simplified solid carbon fuels (lignite and anthracite) with/without copper oxide (CuO) nanoparticle. In addition, experiments were conducted on the thermal characteristics, flammability, and flame speeds of CuO and solid carbon mixtures. For n-butane, oxidation on the CuO surface is the primary reaction since the activation energy of the surface reaction is much lower than that of oxygen (O 2 ) combustion (9.2 vs. 53.3 kcal/mol). On the other hand, for lignite, there is a smaller difference in the activation energy of O 2 combustion and surface reaction (23.04 vs. 6.34 kcal/mol). We hypothesize that some solid carbon fuels can have different reaction kinetics dependent upon temperature. This is proven by the case of a simplified anthracite coal: an Arrhenius plot shows that this solid carbon fuel has two different reaction kinetic regimes and the critical temperature for the change in kinetics is related to the oxygen uncoupling of the CuO nanoparticle. Like the modeling simulations, a change in activation energy is observed in the experimental results, where desorption of molecular oxygen from CuO becomes important.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Temporal dynamics of large-scale structures for turbulent Rayleigh–Bénard convection in a moderate aspect-ratio cylinder

We investigate the spatial organization and temporal dynamics of large-scale, coherent structures in turbulent Rayleigh–Bénard convection via direct numerical simulation of a 6.3 aspect-ratio cylinder with Rayleigh and Prandtl numbers of 9.6×10 7 and 6.7, respectively. Fourier modal decomposition is performed to investigate the structural organization of the coherent turbulent motions by analysing the length scales, time scales and the underlying dynamical processes that are ultimately responsible for the large-scale structure formation and evolution. We observe a high level of rotational symmetry in the large-scale structure in this study and that the structure is well described by the first four azimuthal Fourier modes. Two different large-scale organizations are observed during the duration of the simulation and these patterns are dominated spatially and energetically by azimuthal Fourier modes with frequencies of 2 and 3. Studies of the transition between these two large-scale patterns, radial and vertical variations in the azimuthal energy spectra, as well as the spatial and modal variations in the system's correlation time are conducted. Rotational dynamics are observed for individual Fourier modes and the global structure with strong similarities to the dynamics that have been reported for unit aspect-ratio domains in prior works. It is shown that the large-scale structures have very long correlation time scales, on the order of hundreds to thousands of free-fall time units, and that they are the primary source for a horizontal inhomogeneity within the system that can be observed during a finite, but a very long-time simulation or experiment.

42 ENGINEERING↗
DOE OSTI2026

Comparing Synoptic Pattern Evolution for Flash‐Flood‐Producing and Non‐Flash‐Flood‐Producing Mesoscale Convective Systems in the United States

Understanding how the short-term evolution of synoptic weather patterns influence Mesoscale Convective Systems (MCSs) is essential, as these systems are responsible for over half of central U.S. flash floods, leading to substantial socioeconomic and water resource management impacts. This study analyzes long-term MCS data, flash flood reports, and atmospheric reanalyses from 2007 to 2017 using a machine learning clustering algorithm to examine how the synoptic weather patterns evolve prior to MCS initiation. While the clusters reflect seasonal and regional differences in MCS occurrence, they do not consistently distinguish between MCSs that do and do not produce flash floods. Systems in the southern Great Plains are more flood-prone when a synoptic-scale forcing, located near the system, drives strong water vapor transport from the nearby moisture source. More generally under different synoptic weather patterns, a broader precipitating area is the most dominant factor governing MCS flash flood potential.

atmospheric dynamics↗
DOE OSTI2025

Multiscale drivers of extreme southern California flooding: ENSO, MJO, North Pacific jet, and atmospheric rivers

Extreme rainfall and flooding, driven by a powerful atmospheric river (AR) and a persistent Madden-Julian Oscillation (MJO), hit Southern California in February 2024 during the 2023–2024 El Niño, affecting over 10 million people. ARs are key contributors to extreme rainfall and flooding along the U.S. West Coast. Although the AR-MJO link has been documented, its spatio-temporal variability remains a major forecasting and risk-management challenge. Combining precipitation, stream gauge and demographic data, we quantify the physical drivers and population exposure to this extreme event. Leveraging a Lagrangian MJO precipitation tracking algorithm, we unravel the multiscale interactions responsible for the AR’s development. El Niño favored a large, long-lived MJO that interacted with the North Pacific Jet (NPJ) over more than three weeks. The MJO convective outflow modulated the NPJ by inducing negative potential vorticity advection along the tropopause. The ensuing NPJ extension and acceleration induced explosive cyclogenesis, whose AR-driven moisture transport resulted in extreme rainfall.

Atmospheric dynamics↗
DOE OSTI2025

High-Fidelity CFD Simulation of Mixed Convection and Forced Convection in a Pebble Bed Test Reactor Core

The Hermes low-power [35-MW(thermal)] reactor will be built and operated by Kairos Power LLC (KP) to demonstrate its fluoride salt-cooled high-temperature reactor (FHR) technology. In the KP FHR, the reactor core is composed of randomly packed pebbles with TRISO fuel particles inside with FLiBe flow upward through the core acting as a coolant. Previous numerical and experimental studies have been limited to either a small-size bed or to a lack of detailed measurements for heat transfer. Here, to address the lack of high-fidelity heat transfer data in a real-size FHR core, in this study, we simulated a pebble bed core with 34 374 pebbles randomly packed, similar to the Hermes reactor's size. The core radius was 14 times that of the pebble diameter, while the core height was 45 times. In this work, we were particularly interested in a mixed convection regime, where buoyancy is important. Therefore, we performed several large-eddy simulations at different Reynolds numbers (160 to 1000) with gravitational force included. The spectral element computational fluid dynamics code NekRS with graphics processing unit acceleration was used for this study. The low-Mach number approximation was applied to address property changes in the FLiBe and to account for buoyancy. A pure hexahedral mesh with 60 million elements was generated by the Voronoi cell method. At the polynomial order of 5, the total degrees of freedom was 7.5 billion. The developed case in this work is the first of its kind in terms of size and complexity. The local numerical data across the domain were obtained and compared with empirical correlations. After examining the data, we found the following conclusions. For pressure drop, the Reger correlation predicted less than a 5% error. On the other hand, for heat transfer, the Wakao correlation outperformed the others. Based on our findings, we recommend the use of the Wakao correlation for the Nusselt number calculation, and for pressure drop, the KTA (Kerntechnischer Ausschuss) correclation, among the available experimental correlations. In conclusion, the Reger direct numerical simulation-driven correlation for pressure drops should also be considered, given its best agreement with our calculations.

Mixed Convection↗
DOE OSTI2025

Development, Verification, and Validation of an OpenFOAM-Based Solver for Modeling Inertial Fusion Energy Chambers

Our work seeks to introduce a computational tool tailored to the physics of inertial fusion energy chambers, in particular, those concepts based on thick liquid walls. In this approach, the structural materials are protected by several neutron mean-free-paths of renewable liquid and thus will be able to survive much longer than un-shielded walls, with virtually all structures lasting for the life of the plant and enabling the use of commercially available and qualified materials. The OpenFOAM-based solver named rhoCentralFoam has been used as a starting point. rhoCentralFoam belongs to the standard OpenFOAM solver toolset. It is a high-speed, explicit compressible flow solver with shock-capturing capability. While the main features have been retained, the solver had to be restructured to make use of tabular data for equations of states, a necessary addition to model the complex thermo-physical properties of ionized gasses. This entailed the need to change the independent state variables used by the solver, resulting in a new thermodynamic library and slightly different solution algorithm. Moreover, a radiation heat transfer model based on the P-1 approximation was added to the solver. The solver is verified against an analytical solution from the Sedov-Taylor-Neumann test problem to showcase the ability of the hydrodynamic solvers to handle strong shocks, whereas the P-1 model was verified using a simple one-dimensional problem with an analytical solution. Additionally, a validation case involving shock-wave propagation through jet array is presented, and the results are compared with experimental data from the open literature. Lastly, in order to showcase the utility of the solver for practical cases, we applied the refined solver to two representative scenarios: gas venting within the HYLIFE-II chamber and the compression of the gas following the partial ablation of the liquid wall.

Chamber dynamics↗
DOE OSTI2021

Quasi-one-dimensional uniform spin- 1 2 Heisenberg antiferromagnet KNaCuP 2 O 7 probed by P 31 and Na 23 NMR

Here we present the structural and magnetic properties of KNaCuP 2 O 7 investigated via x-ray diffraction, magnetization, specific heat, and P 31 and Na 23 NMR measurements and complementary electronic structure calculations. The temperature-dependent magnetic susceptibility and P 31 NMR shift could be modeled very well by the uniform spin- 1 2 Heisenberg antiferromagnetic chain model with a nearest-neighbor interaction J / k B ≃ 58.7 K . The corresponding mapping using first-principles electronic structure calculations leads to J DFT / k B ≃ 59 K with negligibly small interchain couplings, further confirming that the system is indeed a one-dimensional uniform spin- 1 2 Heisenberg antiferromagnet. The diverging trend of NMR spin-lattice relaxation rates ( 1 / T 1 31 and 1 / T 1 23 ) implies the onset of a magnetic long-range ordering at around T N ≃ 1 K . From the value of T N , the average interchain coupling is estimated to be J ' / k B ≃ 0.28 K . Moreover, the NMR spin-lattice relaxation rates show the dominant contributions from uniform ( q = 0 ) and staggered ( q = ± π / a ) spin fluctuations in the high- and low-temperature regimes, respectively, mimicking one-dimensionality of the spin lattice. We have also demonstrated that 1 / T 1 31 in high temperatures varies linearly with 1 / H , reflecting the effect of spin diffusion on the dynamic susceptibility. The temperature-dependent unit cell volume could be described well using the Debye approximation with a Debye temperature of Θ D ≃ 294 K , consistent with the heat capacity data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

PeleC: An adaptive mesh refinement solver for compressible reacting flows

Reacting flow simulations for combustion applications require extensive computing capabilities. Leveraging the AMReX library, the Pele suite of combustion simulation tools targets the largest supercomputers available and future exascale machines. We introduce PeleC, the compressible solver in the Pele suite, and detail its capabilities, including complex geometry representation, chemistry integration, and discretization. We present a comparison of development efforts using both OpenACC and AMReX’s C++ performance portability framework for execution on multiple GPU architectures. We discuss relevant details that have allowed PeleC to achieve high performance and scalability. PeleC’s performance characteristics are measured through relevant simulations on multiple supercomputers. The success of PeleC’s design for exascale is exhibited through demonstration of a 160 billion cell simulation and weak scaling onto 100% of Summit, an NVIDIA-based GPU supercomputer at Oak Ridge National Laboratory. Our results provide confidence that PeleC will enable future combustion science simulations with unprecedented fidelity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Data of High-Temperature Dynamic LCM Testing Setup

Data from high temperature dynamic sealing tests for various fracture widths, at various temperatures (degrees F), with 5 wt.% bentonite-based mud containing various material fiber contents, at 100 to 400 psi differential pressure. Data from pressure test and evaluation of the dynamic lost circulation materials (LCM) testing unit to reflect the condition of open and sealed fracture using fracture width of 1000 microns at 120 degrees F. Links to two papers based on the data - "Loss circulation prevention in geothermal drilling by shape memory polymer" which was published in Geothermics 89 (2021) 101943) as well as "Evaluating sealability of blended smart polymer and fiber additive for geothermal drilling with the effect of fracture opening size", published in the Journal of Petroleum Science and Engineering 206 (2021) 108998.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Towards provision of regularly updated climate data from the Coupled Model Intercomparison Project

The Coupled Model Intercomparison Project (CMIP) is a flagship of the World Climate Research Programme (WCRP). CMIP has become a recognised ‘brand’ in climate circles evolving over the last thirty years from a targeted research activity by a small number of climate modelling centres intercomparing their Earth System Model (ESM) simulations to a broad international coordinated research effort (Durack et al, 2025). CMIP is organized as a research activity leveraging funded and in-kind contributions from experts within modelling centres and the broader scientific community supported more recently by a fully-funded International Project Office. Within CMIP, Model Intercomparison Projects (MIPs) are community-designed to understand past, present and future climate. CMIP data provides a valuable resource for climate research and is routinely used to assess model representation of climate processes and test scientific hypotheses in the context of model uncertainty and (forced and internal) variability as evident from its prolific use in scientific publications1 . The impact relies on enabling infrastructure (most prominently via the Earth System Grid Federation (ESGF)), which allows sharing of simulation output, provision of the boundary conditions used in each simulation, and definition of the data standards that are essential to facilitating wide use of the data. The impact is supplemented by the wide-ranging scrutiny to which model simulations are subjected. Beyond its use in research, CMIP data is a key resource for communities producing derived climate information from downscaling and impact studies, such as the Coordinated Regional Downscaling Experiment (CORDEX; Gutowski et al., 2016) and the Intersectoral Impacts MIP (ISIMIP; Frieler et al., 2024). Government, academic and commercial entities also increasingly rely on CMIP and its downstream data for climate risk assessments and climate services (for example, Copernicus Climate Change Service and World Bank portal). This means that, although CMIP is a research activity, it increasingly serves a secondary and very relevant role as a provider of climate data – a long-recognised dichotomy (Stevens, 2024). Research and applications have distinct needs, with the former requiring flexibility and generality and the latter consistency. Here we explain how the design of the research activity has been adapted to reduce the burdens imposed by applications and how the research infrastructure might evolve to further enable scientific inquiry. We propose one possible approach to consistently providing model information and projections for applications in the future.

Environmental sciences↗
DOE OSTI2026

Large Eddy Simulations of the Atmospheric Boundary Layer Over Satellite‐Sensed Sea Ice Maps

Surface heterogeneity in the marginal ice zone (MIZ) causes multiscale secondary atmospheric circulations that are challenging to model or observe. The absence or inadequate representation of these circulations in ocean‐atmosphere exchange schemes in climate models is partially responsible for the underestimation of Arctic sea ice loss. Observationally, such circulations obfuscate the interpretation of polar atmospheric chemistry measurements, among others. To address this open challenge, large‐eddy simulations are conducted over real‐world satellite‐sensed sea ice maps with an ice‐sea temperature contrast, as well as over idealizations of these maps that alter the ice pattern but conserve its fraction, showing that the ice fraction of a surface is not sufficient to predict the surface heat flux. In a second suite of simulations, three other heterogeneity metrics (representing the surface fragmentation, patch edge tortuosity, and patch size variability) are introduced to complement the ice fraction in describing the surface. Simulations varying these parameters suggest that they also significantly impact surface‐air interactions. A roughness contrast is then added to the surface temperature contrast, indicating that the contribution of roughness changes to the resulting atmospheric circulations is less pronounced than that of thermal heterogeneity. Based on these results, we illustrate, using a multi‐linear regression on these map features, that MIZ surface parameterizations in Earth Systems Models can be improved if they account for these various characteristics of the sea‐ice patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Dust Direct Radiative Effect Including Large Particles and Component Minerals

The direct radiative effect (DRE) of dust aerosols in Earth system models (ESMs) remains highly uncertain, largely due to inadequate representations of particle size distribution (PSD) and mineral composition. Using NASA's Earth Surface Mineral Dust Source Investigation (EMIT) soil mineralogy data and observed PSD in an ESM that resolves dust mineral composition and emitted diameters from 0.1 to 70 μm, we find a near-neutral global dust net DRE (−0.057 W m −2 ), weaker than most previous estimates. Large dust (diameter >10 μm) contributes 30% of the global longwave dust optical depth, providing observational constraints on large-particle abundance, and offsets 20% of the dust shortwave cooling over major source regions. Incorporation of EMIT mineralogy reduces shortwave uncertainty by more than 50%. The remaining uncertainty mainly exists in processes controlling dust abundance, particularly the poorly understood transport of large dust, and longwave optical properties, which require additional observational constraints to more accurately quantify the dust DRE.

Li, Longlei [Cornell Univ., Ithaca, NY (United Sta↗
DOE OSTI2026

Modeling Large Dust Aerosols in the Community Earth System Model Version 2 (CESM2)

Dust aerosols have a wide size distribution from less than 0.1 to over 100 μm and dominate Earth's atmospheric aerosol mass. However, most Earth system models (ESMs) inadequately represent dust aerosols larger than 10 μm in diameter, limiting the accuracy of the simulated dust cycle and climate impacts. Here, we introduce a new modeling framework that captures the full observed size distribution of dust aerosols, incorporating recent advances into a mineral-resolved version of the Community ESM, while addressing known issues in previous versions. Comprehensive evaluation against diverse observations of bulk dust and component minerals demonstrates that the model reproduces the observed dust cycle across particle sizes. Incorporating the previously unrepresented large-dust fractions substantially alters dust budget estimates, highlighting potential changes in simulated climate impacts and underscoring the importance of comprehensive size-resolved dust modeling. Despite these advancements, uncertainties persist. Our results indicate that a size-dependent reduction in settling velocity is required to reproduce the observed dust size distribution downwind of source regions. Specifically, in the new model, the gravitational settling velocity of dust particles larger than 10 μm in diameter must be reduced by as much as 85% to achieve agreement with observations. This empirical reduction serves as a constraint on physics-based models of dust settling. Future developments should address misrepresented physical processes that hinder accurate modeling of the large dust aerosol transport. Expanding observational data sets covering the full-size distribution is also essential to better constrain the dust cycle and improve the representation of dust optical properties and climate effects.

Li, Longlei [Cornell Univ., Ithaca, NY (United Sta↗
DOE OSTI2026

Gaps and ways forward in atmospheric blocking and extreme weather research

Atmospheric blocking often results in significant weather extremes, such as heatwaves, droughts, cold spells, and floods in mid-latitude regions. However, the physical processes behind blocking and its response to climate change are not well understood, which undermines predictions and decision-making for climate mitigation and adaptation. As a phenomenon with a timescale at the interface of weather and climate, blocking interacts with various elements of the climate system and connects short-term weather events to long-term climate extremes. Understanding atmospheric blocking is crucial, given that climate change may impact its frequency, duration, and geographic distribution. This perspective discusses new experimental approaches to improve our understanding of this important subject.

Wang, Lei [Purdue University, West Lafayette, IN (↗
DOE OSTI2025

Molecular Dynamics Simulation and Theoretical Analysis of Structural Relaxation, Bond Exchange Dynamics, and Glass Transition in Vitrimers

Vitrimers are a class of polymer networks featuring dynamic covalent cross-links that can undergo associative bond exchange. There has been recent interest in these materials due to their promise as recyclable thermosets or self-healing polymers because of the ability of vitrimer networks to rearrange at the molecular level and undergo macroscopic flow. However, the practical use of these materials often occurs in the supercooled regime or glassy state, where the implications of dynamic bonds are complicated by the interplay between slow activated segmental dynamics, cross-link (i.e., bond-exchange) kinetics, and ultimately material properties. Here, in this paper, we combine coarse-grained molecular dynamics simulation and microscopic statistical mechanical theory to understand how cross-linking kinetics affect material dynamics and how this couples to segmental relaxation of the polymeric network strands across a spectrum of length and time scales, especially in the supercooled regime. We characterize the Kuhn segmental alpha relaxation time and bond exchange time for vitrimer systems across various cross-link densities, temperatures, and bond exchange rates. Simulation and theory both exhibit a bending-up behavior for bond exchange time upon cooling, suggesting a coupling between bond exchange dynamics and segmental relaxation that intensifies with faster bond exchange kinetics. We also found bond exchange dynamics have an impact on Kuhn segment alpha relaxation time, which is most significant at higher cross-link densities. Both these effects are most prominent when the bond exchange time is similar to the Kuhn segment alpha relaxation time, and the resulting coupling of these two relaxation processes is tied to both the probability of a free end to find a bonded pair and the time scale of the constraints imposed by the dynamic cross-links. This relationship is reflected by a cross-link dependence of a theoretical parameter which represents the quantitative degree of coupling between bond exchange and segmental dynamics. Overall, the combination of simulation and theory clarifies the intricate interaction between bond kinetics and segmental relaxation and demonstrates the ability to provide molecular-level insights into vitrimer dynamics over a wide temperature range.

dynamic relaxation↗
DOE OSTI2025

A GPU‐Based Ocean Dynamical Core for Routine Mesoscale‐Resolving Climate Simulations

Abstract We describe an ocean hydrostatic dynamical core implemented in Oceananigans optimized for Graphical Processing Unit (GPU) architectures. On 64 A100 GPUs, equivalent to 16 computational nodes in current state‐of‐the‐art supercomputers, our dynamical core can simulate a decade of near‐global ocean dynamics per wall‐clock day at an 8‐km horizontal resolution; a resolution adequate to resolve the ocean's mesoscale eddy field. Such efficiency, achieved with relatively modest hardware resources, suggests that climate simulations on GPUs can incorporate fully eddy‐resolving ocean models. This removes a major source of systematic bias in current IPCC coupled model projections, the parameterization of ocean eddies, and represents a major advance in climate modeling. We discuss the computational strategies, focusing on GPU‐specific optimization and numerical implementation details that enable such high performance.

Silvestri, Simone [Massachusetts Institute of Tech↗