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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Understanding Dynamics and Thermodynamics of ENSO and Its Complexity Simulated by E3SM and Other Climate Models

Despite the seeming success of most state-of-the-art climate models in simulating the El Niño-Southern Oscillation (ENSO), there is strong evidence that models achieve realistic levels of ENSO activity do so often for wrong reasons. This is owing to an often occurred near cancelation of large errors in terms of contributions to ENSO growth rate from coupled dynamic and thermodynamic feedback processes. Climate models remain deficient in simulating the observed ENSO’s spatial and temporal complexity that involves interplays of coupled dynamic and thermodynamic feedbacks, interactions across multiple scales, nonlinear processes in the tropical atmosphere and ocean system, biases in mean sate and physical processes, and influences external to equatorial Pacific coupled ENSO dynamics. Our proposed research aims at advancing predictive and process-level understandings of ENSO simulated in E3SM and other climate models under current and future climate conditions with two main objectives: (i) better understanding the aforementioned broad range interactive processes and sources that control fundamental properties of ENSO in E3SM and CIMP6 outputs as well as in observational (reanalysis) data sets, using a hierarchical of coupled dynamical frameworks consisting of theoretical analysis, intermediate complexity modeling, and coupled dynamic diagnostics; (ii) to use this understanding to explore pathways towards improving E3SM’s capability of simulating ENSO and its complexity. More specifically, we will focus on four main thrusts of research: (1) ENSO’s dynamic and thermodynamic feedbacks; (2) the across-scale interactions of ENSO with annual cycle and MJO/WWB/TIW (Madden Julian Oscillation/Westerly Wind Burst/Tropical Instability Wave) activity; (3) key nonlinear processes of ENSO involving atmospheric convective thresholds, nonlinear ocean dynamic heating, and thermocline outcropping; and (4) the impacts of climate mean-state biases/changes and perturbed physical processes on simulated ENSO and its complexity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Structures of fluoride containing aluminosilicate low activity nuclear waste glasses: A molecular dynamics simulations study

Fluorine and other halides commonly exist in nuclear waste forms, and due to their volatile nature, halide retention poses an issue affecting waste loading during vitrification. The compositional effect on fluorine incorporation in aluminosilicate glasses is investigated through molecular dynamics simulations. Oxygen and fluorine coordination numbers around glass former and modifier cations, bond angle distributions, and medium range structure features such as Q n distributions, ring size distributions and neutron diffraction structure factors were calculated. It was found that fluorine has higher preference to bond to Ca 2+ than to Na + , both in the melt and the glass, and there is no Si-F bond formation in the glass but they do exist in the melt. Consequently, CaO for Na 2 O substitution can be an effective way to help fluorine retention without significantly changing the glass chemistry. Furthermore, these results thus provide insights on fluorine incorporation in the aluminosilicate nuclear waste glasses and the strategy on how to improve fluorine retention both in the glass and the melt.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Extreme Metastability of Diamond and its Transformation to the BC8 Post-Diamond Phase of Carbon

Diamond possesses exceptional physical properties due to its remarkably strong carbon–carbon bonding, leading to significant resilience to structural transformations at very high pressures and temperatures. Despite several experimental attempts, synthesis and recovery of the theoretically predicted post-diamond BC8 phase remains elusive. Through quantum-accurate multimillion atom molecular dynamics (MD) simulations, we have uncovered the extreme metastability of diamond at very high pressures, significantly exceeding its range of thermodynamic stability. We predict the post-diamond BC8 phase to be experimentally accessible only within a narrow high pressure–temperature region of the carbon phase diagram. The diamond to BC8 transformation proceeds through premelting followed by BC8 nucleation and growth in the metastable carbon liquid. Here we propose a double-shock compression pathway for BC8 synthesis, which is currently being explored in experiments at the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Antecedent Hydrologic Conditions Reflected in Stream Lithium Isotope Ratios During Storms

Antecedent hydrological conditions are recorded through the evolution of dissolved lithium isotope signatures (δ 7 Li) by juxtaposing two storm events in an upland watershed subject to a Mediterranean climate. Discharge and δ 7 Li are negatively correlated in both events,but mean δ 7 Li ratios and associated ranges of variation are distinct between them. We apply a previously developed reactive transport model (RTM) for the site to these event-scale flow perturbations, but observed shifts in stream δ 7 Li are not reproduced. To reconcile the stability of the subsurface solute weathering profile with our observations of dynamic stream δ 7 Li signatures, we couple the RTM to a distribution of fluid transit times that evolve based on storm hydrographs. The approach guides appropriate flux-weighting of fluid from the RTM over a range of flow path lengths, or equivalently fluid residence times. This flux-weighted RTM approach accurately reproduces dynamic storm δ 7 Li-discharge patterns distinguished by the antecedent conditions of the watershed.

58 GEOSCIENCES↗
DOE OSTI2026

Data Driven Approach to Public Opinion Mining on Autonomous Vehicles: Sentiment Analysis of Social Media Comments Using Large Language Models

In the realm of online identity, social media has emerged as a rich and dynamic source of user-generated content, making it an invaluable resource for understanding public sentiment on a wide range of topics. Individuals often share their raw emotions and candid opinions on these platforms without fear of judgment or backlash. In this study, we conduct a sentiment analysis on user comments collected from various online platforms, with a specific focus on discussions surrounding autonomous vehicles. Leveraging the capabilities of large language models (LLMs), we classify each comment into one of five sentiment categories: Very Negative, Negative, Neutral, Positive, and Very Positive. Our approach demonstrates the effectiveness of LLMs in capturing nuanced contextual sentiment, offering a scalable and state-of-the-art alternative to traditional manual annotation methods. The results reveal key trends and insights into public perception, enabling a deeper understanding of how autonomous vehicle technologies are received by the online community. Our findings underscore the dynamic nature of public sentiment, which is shaped not only by advances in autonomous vehicle technology but also by contextual events such as regulatory developments, political adjustment and safety incidents.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Global monthly sectoral water use for 2010–2100 at 0.5° resolution across alternative futures

Water usage is closely linked with societal goals that are both local and global in scale, such as sustainable development and economic growth. It is therefore of value, particularly for long-term planning, to understand how future sectoral water usage could evolve on a global scale at fine resolution. Additionally, future water usage could be strongly shaped by global forces, such as socioeconomic and climate change, and the multi-sector dynamic interactions those forces create. We generate a novel global gridded monthly sectoral water withdrawal and consumption dataset at 0.5° resolution for 2010–2100 for a diverse range of 75 scenarios. The scenarios are harmonized with the five Shared Socioeconomic Pathways (SSPs) and four Representative Concentration Pathways (RCPs) scenarios to support its usage in studies evaluating the implications of uncertain human and earth system change for future global and regional dynamics. To generate the data, we couple the Global Change Analysis Model (GCAM) with a land use spatial downscaling model (Demeter), a global hydrologic framework (Xanthos), and a water withdrawal downscaling model (Tethys).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A New Distributed Model-Free Control Strategy to Diminish Distribution System Voltage Violations

This paper proposes a new distributed model-free control (MFC) strategy for dynamic voltage control to diminish distribution systems' voltage violations. The objective is to maintain all critical load bus voltages within the acceptable ANSI Range A (+/- 5% of nominal). The distributed MFC strategy, which only requires local voltage measurements from designated load buses, controls online the reactive power generation of available synchronous generator (SG)-based and photovoltaic (PV)-based distributed generators (DGs). The distributed MFC strategy is computationally efficient and does not require modelling of the different system components and disturbances. Time-domain dynamic simulations are conducted for the 21-bus test distribution system fed by multiple DGs to verify the performance of the proposed MFC strategy, and the results are compared against the conventional model-based microgrid voltage stabilizer (MGVS) control strategy. The simulation results show that the distributed MFC strategy provides minimal voltage violations and achieves the dynamic voltage stability of the system under diverse disturbances.

Hatipoglu, Kenan↗
DOE OSTI2024

Replica symmetry breaking in spin glasses in the replica-free Keldysh formalism

We show that the algebra of Parisi ultrametric matrices is recovered by the real-time, replica-free, Dyson-Keldysh equations of infinite-range quantum spin glasses in the late time glassy limit. This connects to earlier results on classical and quantum systems showing how ultrametricity emerges from the persistent slow aging dynamics of the glass phase. The stationary spin glass state thereby spontaneously breaks thermal symmetry, or the Kubo-Martin-Schwinger relation of a state in global thermal equilibrium. We describe the Keldysh path integral of the infinite-range Ising model in transverse and longitudinal fields, and in the context of the Landau expansion of the action functional, show how the long-time limit connects to the full replica symmetry breaking obtained in the equilibrium formalism. We also illustrate our formalism by applying it to the spherical quantum p p -spin model, which only exhibits one-step replica symmetry breaking.

Lang, Johannes (ORCID:0000000283533392)↗
DOE OSTI2021

Atomic dynamics of metallic glass melts La 50 Ni 15 Al 35 and Ce 70 Cu 19 Al 11 studied by quasielastic neutron scattering

By employing quasielastic neutron scattering, we studied the atomic-scale relaxation dynamics and transport mechanism of La 50 Ni 15 Al 35 and Ce 70 Cu 19 Al 11 metallic glass melts in the temperature range of > 200K above their liquidus temperatures. The results show that both liquids exhibit stretched exponential relaxation and Arrhenius-type temperature dependence of the effective diffusion coefficient. The La 50 Ni 15 Al 35 melt exhibits an activation energy of 0.545 ± 0.008 eV and a stretching exponent ~0.77 to 0.86 in the studied temperature range; no change of activation energy, as suggested in previous reports, associated with liquid-liquid phase transition was observed. In contrast, the Ce 70 Cu 19 Al 11 melt exhibits larger diffusivity with a much smaller activation energy of 0.201±0.003eV and a smaller stretching exponent ~0.51 to 0.60, suggestive of more heterogeneous dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

A comparison of probabilistic generative frameworks for molecular simulations

Generative artificial intelligence is now a widely used tool in molecular science. Despite the popularity of probabilistic generative models, numerical experiments benchmarking their performance on molecular data are lacking. Here, in this work, we introduce and explain several classes of generative models, broadly sorted into two categories: flow-based models and diffusion models. We select three representative models: neural spline flows, conditional flow matching, and denoising diffusion probabilistic models, and examine their accuracy, computational cost, and generation speed across datasets with tunable dimensionality, complexity, and modal asymmetry. Our findings are varied, with no one framework being the best for all purposes. In a nutshell, (i) neural spline flows do best at capturing mode asymmetry present in low-dimensional data, (ii) conditional flow matching outperforms other models for high-dimensional data with low complexity, and (iii) denoising diffusion probabilistic models appear the best for low-dimensional data with high complexity. Our datasets include a Gaussian mixture model and the dihedral torsion angle distribution of the Aib9 peptide, generated via a molecular dynamics simulation. We hope our taxonomy of probabilistic generative frameworks and numerical results may guide model selection for a wide range of molecular tasks.

Artificial intelligence↗
DOE OSTI2024

Temperature and density dependent pair potential for deuterium under shock

Large-scale classical molecular dynamics (CMD) simulations naturally include the microscopic physics necessary for atomistic modeling of shock release at the ablator-fuel interface in an inertial confinement fusion (ICF) capsule. Here, the multi-megabar shocks utilized in ICF experiments can drive the deuterium fuel from ambient to electron volt temperatures (T) and multi-fold compression. Modeling interatomic interactions over such an extreme range of conditions is challenging for empirical bond order potentials. We generate a pair potential for deuterium with explicit temperature and mass density dependence from ab initio density functional theory molecular dynamics using the iterative Boltzmann inversion method. This potential accurately reproduces the radial distribution functions and pressures from DFT in CMD equilibrium simulations across a wide range of thermodynamic conditions, yet fails to return the expected Hugoniot relations when used in direct CMD shock simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Interaction of extended dislocations with nanovoid clusters

Voids of nanoscale dimensions in irradiated metals can act as obstacles to dislocation motion and cause strengthening. In this work, nanovoid strengthening and the influences of void size, void spacing and material properties, such as stacking fault energies, on dislocation bypass mechanisms are investigated using Phase Field Dislocation Dynamics, a three-dimensional mesoscale model that predicts the minimum energy pathway taken by discrete dislocations. A broad range of face centered cubic metals (copper, nickel, silver, rhodium, and platinum) and nanovoid sizes and spacings are treated, altogether spanning void size–to–dislocation stacking fault width ratios from less than unity to ten. Material γ-surfaces, calculated from ab initio methods, are input directly into the formulation. The analysis reveals that the critical bypass stress scales linearly with the linear void fraction, effective isotropic shear modulus, and ratio of the intrinsic to unstable stacking fault energies. With only a few exceptions, the critical stress is controlled by the stress required for the leading partial to impinge the voids (to move within range of the attractive image stress field of the void). When the void diameter is nearly an order of magnitude greater than the stacking fault width, the mechanism determining critical strength shifts to the stress for the dislocation to breakaway after partially cutting the void. Furthermore, this situation corresponds to that treated by line tension models and is realized here for Pt, with a sub-nanometer stacking fault width.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electric-Field-Induced Spatially Dynamic Heterogeneity of Solvent Motion and Cation Transference in Electrolytes

While electric fields primarily result in migration of charged species in electrolytic solutions, the solutions are dynamically heterogeneous. Solvent molecules within the solvation shells of the cation will be dragged by the field while free solvent molecules will not. Here we combine electrophoretic NMR measurements of ion and solvent velocities under applied electric fields with molecular dynamics simulations to interrogate different solvation motifs in a model liquid electrolyte. Measured values of the cation transference number $(t^0_+)$ agree quantitatively with simulation-based predictions over a range of electrolyte concentrations. Solvent-cation interactions strongly influence the concentration-dependent behavior of $t^0_+$. We identify a critical concentration at which most of the solvent molecules lie within solvation shells of the cations. The dynamic heterogeneity of solvent molecules is minimized at this concentration where $t^0_+$ is approximately equal to zero.

42 ENGINEERING↗
DOE OSTI2021

Insights into scale translation of methane transport in nanopores

Accurate prediction of flow behavior in shale matrix is critical for efficient development of shale gas reservoirs. In these systems, the majority of pores are in the nano-size range. As a result, continuum-based approaches may not be appropriate to simulate flow in such systems. Molecular dynamics (MD) simulations are capable of capturing the relevant microscale physics. Their relatively high computational expense, however, restricts MD simulations to rather small systems and domains. This limitation creates a gap between computational need of macroscale systems and capabilities of MD simulations. The lattice Boltzmann method (LBM) is a suitable candidate to bridge this gap. In this work, the multiple-relaxation-time (MRT)-LBM is used to study methane transport in nano-size pores. Adsorption effects near solid boundaries, as well as non-ideal behavior of fluids, are accounted for via incorporating appropriate force terms in LBM. In this work, parameters associated with the force terms in the equation of state are studied in detail, and a workflow is proposed to determine optimal values of these parameters for gas flow in slit pores. Specifically, we establish these parameters such that the range of density values that the model is able to simulate is maximized. We demonstrate this workflow by simulating gas flow where velocity and density profiles from MD simulations are used as reference data. Results from LBM simulations are in good agreement with MD reference data for pores that are 4 nm in width or larger. Moreover, we propose a preconditioning scheme to improve the stability of LBM in dealing with complex geometries. The robustness of this scheme is demonstrated by simulating several roughness geometries. This work motivates the use of LBM in scale translation of the physics of mass transport in more complex permeable media.

03 NATURAL GAS↗
DOE OSTI2023

Simulations with machine learning potentials identify the ion conduction mechanism mediating non-Arrhenius behavior in LGPS

Abstract Li 10 Ge(PS 6 ) 2 (LGPS) is a highly concentrated solid electrolyte, in which Coulombic repulsion between neighboring cations is hypothesized as the underlying reason for concerted ion hopping, a mechanism common among superionic conductors such as Li 7 La 3 Zr 2 O 12 (LLZO) and Li 1.3 Al 0.3 Ti 1.7 (PO 4 ) 3 (LATP). While first principles simulations using molecular dynamics (MD) provide insight into the Li + transport mechanism, historically, there has been a gap in the temperature ranges studied in simulations and experiments. Here, we used a neural network potential trained on density functional theory (DFT) simulations, to run up to 40-nanosecond long MD simulations at DFT-like accuracy to characterize the ion conduction mechanisms across a range of temperatures that includes previous simulations and experimental studies. We have confirmed a Li + sublattice phase transition in LGPS around 400 K, below which the ab -plane diffusivity D a b ∗ is drastically reduced. Concomitant with the sublattice phase transition near 400 K, there is less cation-cation (cross) correlation, as characterized by Haven ratios closer to 1, and the vibrations in the system are more harmonic at lower temperature. Intuitively, at high temperature, the collection of vibrational modes may be sufficient to drive concerted ion hops. However, near room temperature, the vibrational modes available may be insufficient to overcome electrostatic repulsion, thus resulting in less correlated ion motion and comparatively slower ion conduction. Such phenomena of a sublattice phase transition, below which concerted hopping plays a less significant role, may be extended to other highly concentrated solid electrolytes such as LLZO and LATP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A probabilistic graphical model foundation for enabling predictive digital twins at scale

A unifying mathematical formulation is needed to move from one-off digital twins built through custom implementations to robust digital twin implementations at scale. This work proposes a probabilistic graphical model as a formal mathematical representation of a digital twin and its associated physical asset. We create an abstraction of the asset–twin system as a set of coupled dynamical systems, evolving over time through their respective state spaces and interacting via observed data and control inputs. The formal definition of this coupled system as a probabilistic graphical model enables us to draw upon well-established theory and methods from Bayesian statistics, dynamical systems and control theory. The declarative and general nature of the proposed digital twin model make it rigorous yet flexible, enabling its application at scale in a diverse range of application areas. Here, we demonstrate how the model is instantiated to enable a structural digital twin of an unmanned aerial vehicle (UAV). The digital twin is calibrated using experimental data from a physical UAV asset. Its use in dynamic decision-making is then illustrated in a synthetic example where the UAV undergoes an in-flight damage event and the digital twin is dynamically updated using sensor data. The graphical model foundation ensures that the digital twin calibration and updating process is principled, unified and able to scale to an entire fleet of digital twins.

42 ENGINEERING↗
DOE OSTI2022

Simulations of graphite boronization: A molecular dynamics study of amorphization resulting from bombardment

The molecular dynamics code LAMMPS was used to simulate the bombardment of a graphite structure by atomic boron with impact energies ranging from 50–250 eV. The transient structural evolution, penetration depth, and amorphous layer thickness were analyzed. Simulations show that larger impact energies lead to a greater volume of amorphization and penetration of boron, but that the growth rate of the amorphous layer decreases with increasing fluence. Furthermore, the change in surface chemistry of the amorphized structures was studied using the ReaxFF formalism, which found that the amorphization process introduces dangling bonds thus increasing reactivity in the amorphous region.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Spatiotemporal spread of perturbations in power-law models at low temperatures: Exact results for classical out-of-time-order correlators

Here, we present exact results for the classical version of the out-of-time-order commutator (OTOC) for a family of power-law models consisting of N particles in one dimension and confined by an external harmonic potential. These particles are interacting via power-law interaction of the form ∝ $Σ_{i,j=(i≠j)}^{N}$ |x i -x j | -k for every k>1 where x i is the position of the i th particle. We present numerical results for the OTOC for finite N at low temperatures and short enough times so that the system is well approximated by the linearized dynamics around the many-body ground state. In the large-N limit, we compute the ground-state dispersion relation in the absence of external harmonic potential exactly and use it to arrive at analytical results for OTOC. We find excellent agreement between our analytical results and the numerics. We further obtain analytical results in the limit where only linear and leading nonlinear (in momentum) terms in the dispersion relation are included. The resulting OTOC is in agreement with numerics in the vicinity of the edge of the “light cone.” We find remarkably distinct features in OTOC below and above k=3 in terms of going from non-Airy behavior (1 < k < 3) to an Airy universality class (k>3). We present certain additional rich features for the case k=2 that stem from the underlying integrability of the Calogero-Moser model. We present a field theory approach that also assists in understanding certain aspects of OTOC such as the sound speed. Our findings are a step forward towards a more general understanding of the spatiotemporal spread of perturbations in long-range interacting systems.

1-dimensional systems↗