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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Distortions of the Rain Distribution With Warming, With and Without Self-Aggregation

We investigate how mesoscale circulations associated with convective aggregation can modulate the sensitivity of the hydrologic cycle to warming. We quantify changes in the full distribution of rain across radiative-convective equilibrium states in a cloud-resolving model. For a given Sea Surface Temperature (SST), the shift in mean rainfall between disorganized and organized states is associated with a shift in atmospheric radiative cooling, and is roughly analogous to the effect of a 4K SST increase. With rising temperatures, the increase in mean rain rate is insensitive to the presence of organization, while extremes can intensify faster in the aggregated state, leading to a faster amplification in the sporadic nature of rain. When convection aggregates, heavy rain is enhanced by 20%–30% and nonlinear behaviors are observed as a function of SST and strength of aggregation feedbacks. First, radiative- and surface-flux aggregation feedbacks have multiplicative effects on extremes, illustrating a non-trivial sensitivity to the degree of organization. Second, alternating Clausius-Clapeyron and super-Clausius-Clapeyron regimes in extreme rainfall are found as a function of SST, corresponding to varying thermodynamic and dynamic contributions, and a large sensitivity to precipitation efficiency variations in some SST ranges. The potential for mesoscale circulations in amplifying the hydrologic cycle is established. However, these nonlinear distortions question the quantitative relevance of idealized self-aggregation. This calls for a deeper investigation of relationships which capture the coupling between global energetics, aggregation feedbacks and local convection, and for systematic tests of their sensitivity to domain configurations, surface boundary conditions, microphysics, and turbulence schemes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Connecting Large‐Scale Meteorological Patterns to Extratropical Cyclones in CMIP6 Climate Models Using Self‐Organizing Maps

Abstract Extratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Mapping the global distribution of C 4 vegetation using observations and optimality theory

Plants with the C 4 photosynthesis pathway typically respond to climate change differently from more common C 3 -type plants, due to their distinct anatomical and biochemical characteristics. These different responses are expected to drive changes in global C 4 and C 3 vegetation distributions. However, current C 4 vegetation distribution models may not predict this response as they do not capture multiple interacting factors and often lack observational constraints. Here, we used global observations of plant photosynthetic pathways, satellite remote sensing, and photosynthetic optimality theory to produce an observation-constrained global map of C 4 vegetation. We find that global C 4 vegetation coverage decreased from 17.7% to 17.1% of the land surface during 2001 to 2019. This was the net result of a reduction in C 4 natural grass cover due to elevated CO 2 favoring C 3 -type photosynthesis, and an increase in C 4 crop cover, mainly from corn (maize) expansion. Using an emergent constraint approach, we estimated that C 4 vegetation contributed 19.5% of global photosynthetic carbon assimilation, a value within the range of previous estimates (18–23%) but higher than the ensemble mean of dynamic global vegetation models (14 ± 13%; mean ± one standard deviation). Our study sheds insight on the critical and underappreciated role of C 4 plants in the contemporary global carbon cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Quantifying the phase diagram and Hamiltonian of S = 1/2 kagome antiferromagnets: bridging theory and experiment

Spin-1/2 kagome antiferromagnets are leading candidates for realizing quantum spin liquid (QSL) ground states. While QSL ground states are predicted for the pure Heisenberg model, understanding the robustness of the QSL to additional interactions that may be present in real materials is a forefront question in the field. Here we employ large-scale density-matrix renormalization group simulations to investigate the effects of next-nearest neighbor exchange couplings J 2 and Dzyaloshinskii-Moriya interactions D, which are relevant to understanding the prototypical kagome materials herbertsmithite and Zn-barlowite. By utilizing clusters as large as XC12 and extrapolating the results to the thermodynamic limit, we precisely delineate the scope of the QSL phase, which remains robust across an expanded parameter range of J 2 and D. Direct comparison of the simulated static and dynamic spin structure factors with inelastic neutron scattering reveals the parameter space of the Hamiltonians for herbertsmithite and Zn-barlowite, and, importantly, provides compelling evidence that both materials exist within the QSL phase. These results establish a powerful convergence of theory and experiment in this most elusive state of matter.

Jiang, Shengtao [SLAC National Accelerator Laborat↗
DOE OSTI2023

Calculated solvent reorganization entropies, free energies, and fluctuations of the energy gaps for intramolecular electron transfer and excitation of the solvatochromic dye B30

Intramolecular electron transfer between two biphenyl groups linked by an androstane spacer and excitation of the pyridinium-N-phenolate betaine dye B30 to the first excited singlet state are studied by quantum/classical molecular-dynamics simulations at temperatures between 150 and 300 K in solvents with a range of polarities. Temperature dependences of the solvent reorganization energies, free energies, entropies, and the inhomogeneous broadening of B30’s absorption band are examined. The variances of fluctuations of the energy gap between the reactant and product states do not have the direct proportionality to temperature that often is assumed to hold. An explanation for the observations is suggested.

Chemistry↗
DOE OSTI2021

A modified many-body dissipative particle dynamics model for mesoscopic fluid simulation: methodology, calibration, and application for hydrocarbon and water

The many-body dissipative particle dynamics (mDPD) is a prominent mesoscopic multiphase model for fluid transport in mesoconfinement. However, it has been a long-standing challenge for mDPD (and other multiphase-enabled DPD models) to accurately predict real-fluid static and dynamic properties simultaneously. We have developed a modified mDPD model to overcome the issue and a rigorous calibration approach that uses reference data, including experimental and/or molecular dynamics (MD) simulations to parameterise the modified mDPD for real fluids. We choose heptane as a representative example of hydrocarbon in source rocks to demonstrate the model's capability to accurately predict the equation of state (EOS), free surface tension, diffusivity, and viscosity. Our timing test shows that the modified mDPD is 400–500 times faster than its MD counterpart for simulating bulk heptane in equivalent volumes. To further demonstrate the robustness of the model, we revisited the benchmark problem of mesoscopic modelling of water, in which all the previous works on DPD reported only a limited portion of the water properties. Here, we show that the modified mDPD can provide accurate modelling of water static and dynamic properties and an EOS that matches the experimental data to a large range of confinement pressure.

42 ENGINEERING↗
DOE OSTI2025

Constraints on long-ranged interactions between dark matter and the Standard Model

Dark matter's existence is known thanks to its gravitational interaction with Standard Model particles, but it remains unknown whether this is the only force present between them. While many searches for such new interactions with dark matter focus on short-range, contact-like interactions, it is also possible that there exist weak, long-ranged forces between dark matter and the Standard Model. In this work, we present two types of constraints on such new interactions. First, we consider constraints arising from the fact that such a force would also induce long range interactions between Standard Model particles themselves, as well as between dark matter particles themselves. Combining the constraints on these individual forces generally sets the strongest constraints available on new Standard Model-dark matter interactions. Second, we consider the possibility of constraining new long-ranged interactions between dark matter and the Standard Model using the effects of dynamical friction in ultrafaint dwarf galaxies, especially Segue I. Such new interactions would accelerate the transfer of kinetic energy from stars to their surrounding dark matter, slowly reducing their orbits; the present-day stellar half-light radius of Segue I therefore allows us to exclude new forces which would have reduced stars' orbital radii below this scale by now.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Primary defect production from molecular dynamics simulations of high-energy displacement cascades in NbMoTaW alloys

In this work, we report on large-scale molecular-dynamics (MD) simulations of displacement cascades in equiatomic NbMoTaW alloys at PKA energies ranging from 0.15 to 150 keV. We find defect production to be strongly dependent on recoil energy, scaling sublinearly up to 10 keV, and linearly thereafter. We find the sublinear regime to be defined by low values of surviving Frenkel pairs, typically found as isolated point defects or small defect clusters, while at higher recoil energies dense cascades become more frequent, leading to splitting into subcascades and the production of relatively large prismatic-dislocation loops with ⟨111⟩ and ⟨001⟩ Burgers vectors. These loops immobilize large fractions of defects, leading to a rapid growth of the number of surviving defects in the linear regime. We also anneal post-cascade defect configurations using object-kinetic Monte Carlo (OKMC) simulations to account for intracascade recombination on time scales not accessible to MD simulations. Cascade annealing is strongly temperature dependent, with the OKMC simulations only showing significant recovery at 1000 K but not below. Our results are in general agreement with existing published data for refractory concentrated alloys.

Zhou, Xinran [Lawrence Berkeley National Laborator↗
DOE OSTI2024

Hall coefficient and resistivity in the doped bilayer Hubbard model

Finding and understanding non-Fermi-liquid transport behaviors are at the core of condensed matter physics. Most of the existing studies in this field were devoted to the monolayer Hubbard model, which is the minimal model that captures the essential features of high-temperature superconductivity. Here, we discover another type of non-Fermi-liquid behavior emergent in the hole-doped bilayer Hubbard model, using dynamical mean-field theory with a full consideration of the short-range interlayer electron correlation. We find that at low temperatures, the Hall coefficient has a strong nonmonotonic dependence on temperature, leading to a double or quadruple reversal of its sign depending on the doping level. At the same time, the resistivity exhibits two plateaus rather than linearity in its temperature dependence. Finally, we show that these intriguing transport behaviors stem from the formation of coherent interlayer singlets, which scatter off gapped collective modes arising from short-range interlayer antiferromagnetic fluctuations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Comparing event generator predictions and ab initio calculations of ν- 12 C neutral-current quasielastic scattering at 1 GeV

The measurement of neutrino oscillations and exotic physics searches are important parts of the physics program in the near future, with new state-of-the-art experiments planned within the next decade. Future and modern experiments in these fields will make use of nuclear targets. Event generators (EGs) are software used in the analysis of neutrino oscillation experiments. EGs are used to predict kinematic observables for a range of neutrino energies. These simulations make use of simple models of nucleon dynamics. As such, they may fail to capture features of more rigorous theoretical calculations. This work compares EG performance to nuclear theory calculations by comparing observables generated in the two frameworks. We provide a common set of definitions between theory and experiment and assess the adequacy of the implementation of two nuclear physics models in EG simulations. Neutral-current quasielastic (NCQE) scattering events for neutrinos and antineutrinos on a 12 C target are simulated with a specific EG, NEUT, used by the T2K experiment for its analysis. The simulated cross sections are compared to analytic calculations from nuclear theory within the factorization scheme. We compare the NEUT implementation of two different models on nuclear spectral functions: the relativistic Fermi gas (RFG) and the correlated basis spectral function (CBF) to analytic calculations of the same models in the factorization scheme. For both nuclear physics models, we compare the appearance of features in the distributions relevant to experimental analyses. The peak of the cross section dσ/(dΩ dω) is consistent in energy transfer, ω, for RFG and CBF simulations. Qualitatively, the shape of the simulated distribution is similar to the one obtained through theory calculations; however, there are some discrepancies between the theory calculations and the NEUT simulation. While the EG simulations and analytic calculations with the same model of nuclear dynamics show similar overall features, there are still differences between the two. These results demonstrate the importance of benchmarking EGs so their nuclear physics implementations can be improved for the analysis of future experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Potential quantum advantage for simulation of fluid dynamics

Numerical simulation of turbulent fluid dynamics needs to either parametrize turbulence—which introduces large uncertainties—or explicitly resolve the smallest scales—which is prohibitively expensive. Here, we provide evidence through analytic bounds and numerical studies that a potential quantum speedup can be achieved to simulate fluid dynamics using quantum computing. Specifically, we provide a lattice Boltzmann formulation of fluid dynamics for which we give evidence that low-order Carleman linearization is much more accurate than previously believed for these systems. This is achieved via a combination of reformulating the Navier-Stokes nonlinearity (u·$\triangledown$u) to lattice-Boltzmann nonlinearity (u 2 ) and accurately linearizing the dynamical equations, which effectively trades nonlinearity for additional degrees of freedom that add negligible expense in the quantum solver. Based on this, we apply a quantum algorithm for simulating the Carleman-linearized lattice Boltzmann equation and provide evidence that its cost scales logarithmically with system size compared with polynomial scaling in the best known classical algorithms. In this paper, we suggest that a quantum advantage may exist for simulating fluid dynamics, paving the way for simulating nonlinear multiscale transport phenomena in a wide range of disciplines using quantum computing.

42 ENGINEERING↗
DOE OSTI2026

LibraryX: A Framework for Cross-Library-Call Optimization

Scientific applications utilize performance libraries as a software engineering concept: these libraries encapsulate important and well-understood (mathematical) operations, allow for reuse, and are implemented and tuned by experts. Domain scientists then implement complex algorithms based on these domainspecific libraries. While individual library calls are optimized, larger performance gains across sequences of calls—sometimes spanning multiple libraries—are often unrealized, forcing a trade-off between performance and implementation complexity.To overcome this issue, we propose LibraryX, an approach and a system that allows for cross-library-call optimization even when library calls stem from multiple performance libraries. LibraryX annotates library calls with semantic information and optimizes entire directed acyclic graphs (DAGs) of calls dynamically using the SPIRAL code generation system. We demonstrate its effectiveness across a range of memory bound workloads, achieving significant speedups on Nvidia, AMD, and Intel accelerators compared to code using native libraries without cross-call optimization.

Rao, Sanil [Carnegie Mellon University,Department ↗
DOE OSTI2024

In-cylinder spray evolution in a motored central-injection gasoline engine: Imaging and simulating the effects of flash-boiling and intake crossflow

Accurate predictions of fuel spray behavior and mixture formation in simulations of direct-injection spark-ignition (DISI) engines are fundamental to ensure proper description of all subsequent processes including ignition, combustion, and emissions. In this work, the spray evolution in a single-cylinder optical DISI engine was studied experimentally and numerically with the goal of enabling predictive computational fluid dynamics (CFD) modeling of in-cylinder sprays. The authors explored a wide range of operating conditions characterized by several fuel injection temperatures and engine speeds, using a well-characterized nine-component gasoline surrogate known as PACE-20. The effect of flash boiling and intake crossflow on the spray is discussed, with a focus on evaluating the ability of the spray models to capture highly transient spray behavior. In the experiments, the fuel temperature was varied between 20°C and 80°C, allowing for non-flash- to flash-boiling transition to emerge with enhanced flashing intensity at the highest temperatures. Spray collapse resulted in vapor-rich regions, owing to the locally lower inertia of the fluid. Varying the engine speed from 650 to 1950 rpm promoted increasingly more turbulent in-cylinder crossflow which interacted with the spray during the injection event and resulted in enhanced spray dispersion. The CFD model was able to capture the spray morphology transition at different fuel temperatures and engine speeds adequately. Further, it is shown that the spray breakup model could capture the transitional spray behavior induced by flash boiling atomization and intake flow via proper initialization of the spray cone angle and calibration of the spray models’ constants.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Study of the Atmospheric Boundary Layer Structure during AWAKEN (Final Report)

The American Wake Experiment (AWAKEN, https://openei.org/wiki/AWAKEN) is a collaborative, international field campaign funded by the Department of Energy (DOE) to study the dynamic and turbulent properties of wind farm wakes. The scope of the project ranges from studying individual turbine wakes, wake interactions within wind farms, to downstream wake effects of wind farms on the atmospheric boundary layer (ABL) and mesoscale environment. The latter effects influence the performance of wind farms deployed downwind and modify the weather and climate in the region. The focus of our project is on studying the mesoscale and boundary-layer effects of wind farms in more detail using advanced boundary-layer profiling facilities.

17 WIND ENERGY↗
DOE OSTI2023

Simulating and Optimizing Quantum State Transport

The goal of this project was to produce an accurate simulator of the “pitch and catch” process of sending quantum states between SRF cavities, and to find a method for optimizing the control pumps. We developed a program in C++ to integrate the equations of motion with high speed and precision, and used this as a basis for finding an optimal control function to maximize the state transfer efficiency. To demonstrate this we have shown an example of an optimal drive function and the resulting system dynamics, as well as a heat map of the cost function for a range of drive amplitudes.

Weston, Jacob↗
DOE OSTI2024

Characterize and control the multi-range structure of solution-phase systems with resonant x-ray scattering

This work aims at demonstrating the feasibility and impact of Anomalous X-ray Scattering (AXS) in characterizing the multi-range structures of solution-state systems. We will show preliminary investigation of long-range correlations in concentrated aqueous electrolytes with a combination of AXS and molecular dynamics (MD) simulations. We will also start exploring the capability of AXS to capture intra- and inter-molecular structure of dilute molecular systems, and specifically its sensitivity to the chemical environment surrounding active metal sites. We anticipate that the development of this method will help us to understand ion solvation and transport, which affect the performances of, for instance, electrocatalytic cells, as well as to identify/control the intrinsic structural factors that lead to selectivity, efficiency, and stability control during catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Mechanisms of regulation of the rhizosphere, roots and shoots of naive poplars

Trees are associated with a broad range of microorganisms colonising the diverse tissues of their host. However, the early dynamics of the microbiota assembly microbiota from the root to shoot axis and how it is linked to root exudates and metabolite contents of tissues remain unclear. Here, we characterised how fungal and bacterial communities are altering root exudates as well as root and shoot metabolomes in parallel with their establishment in poplar cuttings (Populus tremula x tremuloides clone T89) over 30 days of growth. Sterile poplar cuttings were planted in natural or gamma irradiated soils. Bulk and rhizospheric soils, root and shoot tissues were collected from day 1 to day 30 to track the dynamic changes of fungal and bacterial communities in the different habitats by DNA metabarcoding. Root exudates and root and shoot metabolites were analysed in parallel by gas chromatography-mass spectrometry.

09 BIOMASS FUELS↗