SEARCH · Engineering Papers

Results for “kinetic”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Impact of various DIII-D diagnostics on the accuracy of neural network surrogates for kinetic EFIT reconstructions

Abstract Kinetic equilibrium reconstructions make use of profile information such as particle density and temperature measurements in addition to magnetics data to compute a self-consistent equilibrium. They are used in a multitude of physics-based modeling. This work develops a multi-layer perceptron (MLP) neural network (NN) model as a surrogate for kinetic Equilibrium Fitting (EFITs) and trains on the 2019 DIII-D discharge campaign database of kinetic equilibrium reconstructions. We investigate the impact of including various diagnostic data and machine actuator controls as input into the NN. When giving various categories of data as input into NN models that have been trained using those same categories of data, the predictions on multiple equilibrium reconstruction solutions (poloidal magnetic flux, global scalars, pressure profile, current profile) are highly accurate. When comparing different models with different diagnostics as input, the magnetics-only model outputs accurate kinetic profiles and the inclusion of additional data does not significantly impact the accuracy. When the NN is tasked with inferring only a single target such as the EFIT pressure profile or EFIT current profile, we see a large increase in the accuracy of the prediction of the kinetic profiles as more data is included. These results indicate that certain MLP NN configurations can be reasonably robust to different burning-plasma-relevant diagnostics depending on the accuracy requirements for equilibrium reconstruction tasks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy

Abstract The majority of computational catalyst design focuses on the screening of material components and alloy composition to optimize selectivity and activity for a given reaction. However, predicting the metastability of the alloy catalyst surface at realistic operating conditions requires an extensive sampling of possible surface reconstructions and their associated kinetic pathways. We present CatGym, a deep reinforcement learning (DRL) environment for predicting the thermal surface reconstruction pathways and their associated kinetic barriers in crystalline solids under reaction conditions. The DRL agent iteratively changes the positions of atoms in the near-surface region to generate kinetic pathways to accessible local minima involving changes in the surface compositions. We showcase our agent by predicting the surface reconstruction pathways of a ternary Ni 3 Pd 3 Au 2 (111) alloy catalyst. Our results show that the DRL agent can not only explore more diverse surface compositions than the conventional minima hopping method, but also generate the kinetic surface reconstruction pathways. We further demonstrate that the kinetic pathway to a global minimum energy surface composition and its associated transition state predicted by our agent is in good agreement with the minimum energy path predicted by nudged elastic band calculations.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Kinetic beaming in radiative relativistic magnetic reconnection: a mechanism for rapid gamma-ray flares in jets

ABSTRACT Rapid gamma-ray flares pose an astrophysical puzzle, requiring mechanisms both to accelerate energetic particles and to produce fast observed variability. These dual requirements may be satisfied by collisionless relativistic magnetic reconnection. On the one hand, relativistic reconnection can energize gamma-ray emitting electrons. On the other hand, as previous kinetic simulations have shown, the reconnection acceleration mechanism preferentially focuses high energy particles – and their emitted photons – into beams, which may create rapid blips in flux as they cross a telescope’s line of sight. Using a series of 2D pair-plasma particle-in-cell simulations, we explicitly demonstrate the critical role played by radiative (specifically inverse Compton) cooling in mediating the observable signatures of this ‘kinetic beaming’ effect. Only in our efficiently cooled simulations do we measure kinetic beaming beyond one light crossing time of the reconnection layer. We find a correlation between the cooling strength and the photon energy range across which persistent kinetic beaming occurs: stronger cooling coincides with a wider range of beamed photon energies. We also apply our results to rapid gamma-ray flares in flat-spectrum radio quasars, suggesting that a paradigm of radiatively efficient kinetic beaming constrains relevant emission models. In particular, beaming-produced variability may be more easily realized in two-zone (e.g. spine-sheath) set-ups, with Compton seed photons originating in the jet itself, rather than in one-zone external Compton scenarios.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Fully kinetic simulations of strong steady-state collisional planar plasma shocks

We report on simulations of strong, steady-state collisional planar plasma shocks with fully kinetic ions and electrons, independently confirmed by two fully kinetic codes (an Eulerian continuum and a Lagrangian particle-in-cell). While kinetic electrons do not fundamentally change the shock structure as compared with fluid electrons, we find an appreciable rearrangement of the preheat layer, associated with nonlocal electron heat transport effects. The electron heat-flux profile qualitatively agrees between kinetic- and fluid-electron models, suggesting a certain level of “stiffness,” though substantial nonlocality is observed in the kinetic heat flux. We also find good agreement with nonlocal electron heat-flux closures proposed in the literature. Finally, in contrast to the classical hydrodynamic picture, we find a significant collapse in the “precursor” electric-field shock at the preheat layer leading edge, which correlates with the electron-temperature gradient relaxation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Kinetic frustration by limited bond availability controls the LAT protein condensation phase transition on membranes

LAT is a membrane-linked scaffold protein that undergoes a phase transition to form a two-dimensional protein condensate on the membrane during T cell activation. Governed by tyrosine phosphorylation, LAT recruits various proteins that ultimately enable condensation through a percolation network of discrete and selective protein-protein interactions. Here, we describe detailed kinetic measurements of the phase transition, along with coarse-grained model simulations, that reveal that LAT condensation is kinetically frustrated by the availability of bonds to form the network. Unlike typical miscibility transitions in which compact domains may coexist at equilibrium, the LAT condensates are dynamically arrested in extended states, kinetically trapped out of equilibrium. Modeling identifies the structural basis for this kinetic arrest as the formation of spindle arrangements, favored by limited multivalent binding interactions along the flexible, intrinsically disordered LAT protein. These results reveal how local factors controlling the kinetics of LAT condensation enable formation of different, stable condensates, which may ultimately coexist within the cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Revealing the Electrochemical Kinetics of Electrolytes in Nanosized LiFePO 4 Electrodes

Lithium-ion battery rate performance is ultimately limited by the electrolyte, yet the behaviors of electrolytes during high-rate (dis)charge remain elusive to electrochemical measurement. Herein, we develop and study a nanosized LiFePO 4 model system in which the electrolyte completely controls the electrochemical kinetics of the porous electrode. Impedance spectroscopy, cyclic voltammetry, and rate performance testing prove that ion transport in the electrolyte is the sole rate-limiting process, even in thin electrodes. A novel pseudo-steady-state extrapolation (S3E) method for Tafel analysis shows that LiFePO 4 obeys Butler-Volmer kinetics with a transfer coefficient of 3. The combination of these unexpectedly rapid interfacial kinetics and an activation barrier for phase transformation causes extreme reaction heterogeneity, which manifests as a moving reaction zone. Resistance versus capacity analysis enables direct measurement of electrolyte resistance growth during high-rate (dis)charge, revealing how the interaction between concentration polarization and a moving reaction zone controls electrolyte rate performance in LiFePO 4 electrodes. This work elucidates the profound impacts of the electrolyte on electrochemical measurements in porous battery electrodes: when the active material is not rate limiting, it is impossible to directly measure the intrinsic kinetics of the active material, but conversely, it becomes possible to directly measure the kinetics of the electrolyte.

Electrochemistry↗

DOE OSTI2025

Kinetic Model of Photochemical Nitrogen Reduction [SWR-25-97]

The code in this repository was used to model the kinetics of photochemical nitrogen reduction. Each directory represents a manuscript. The directory titled Dahl_CRPS_2025 contains the code used to fit the kinetic models presented in the manuscript titled, "Pre-steady-state kinetics of nanocrystal:molybdenum nitrogenase biohybrids reveals hole-scavenging efficiency is critical to achieving N2 reduction" by Peter J. Dahl, Lauren M. Pellows, Zhi-Yong Yang, Lance C. Seefeldt, John W. Peters, Gordana Dukovic, David W. Mulder, and Paul W. King. Molybdenum (Mo) nitrogenase is a two-component enzyme complex that catalyzes the reduction of dinitrogen to ammonia and protons to hydrogen gas. We have shown that electrons for dinitrogen reduction can be delivered photochemically to the catalytic MoFe protein component by CdS nanocrystals. In this study, we used electron paramagnetic resonance spectroscopy to measure the transient populations of catalytic intermediates. We fit the populations with a pre-steady-state kinetic model which allowed us to distinguish between productive and non-productive reaction pathways and extract the rate constants for the reaction. Our results demonstrated that the rate of catalytic electron delivery into MoFe protein increased with the concentration of sacrificial electron donor. This enabled electron delivery to exceed the rate of hydride protonation, a relaxation pathway which competes with N2 binding. Thus, managing the balance between electron transfer and hole transfer reactions is required to achieve a kinetic regime that favors N2 reduction.

Dahl, Peter [National Renewable Energy Laboratory ↗

DOE OSTI2025

Kinetic Deep Learning v0.1

Here, we present a method that uses protein levels to predict times series of metabolite concentrations. Understanding this type of pathway dynamics is important in order to predict the behavior of the pathway and, more pragmatically, to be able to design biological systems (such as strains bioengineered to produce chemical products) reliably. Typically, for this purpose, kinetic models consisting of differential equations based on the Michaelis-Menten dynamics have been used in the past. However, these methods can rarely produce good fits to measured data time series. Possibly, this happens because the kinetic constants are unknown or are different from the ones measured in vivo, or perhaps because Michaelis-Menten dynamics is not a satisfactory description. In order to improve the predictive nature of these kinetic models we have eliminated the Michaelis-Menten description of pathway dynamics and we have substituted it by algorithms that automatically learn these dynamics from previously obtained metabolomics and proteomics data using machine learning approaches. Specifically, kinetic deep learning uses deep learning to map proteomics time series to metabolite concentration time series, instead of learning the first metabolite derivative and integrating in (as in the first version of kinetic learning). This approach is shown to provide good to excellent results with a data set specifically collected for this purpose.

Garcia Martin, Hector [Joint BioEnergy Institute (↗

DOE OSTI2022

Assessment of Physics Models for Phase Transition Kinetics

The time dependence of phase diagrams and how to model rate dependent transitions remains one of the key unanswered questions in physics. When a material is loaded dynamically through equilibrium phase boundaries, it is the kinetics that determines the real time expression of a phase transition. Here we report the atomic and nanosecond-scale quantification of kinetics of shock-driven phase transition in multiple materials. We uniquely make use of a both a simple shock as well as shock-and-hold loading pathways compress different crystalline solids and induce structural phase transitions below melt. Coupling shock loading with time-resolved synchrotron x-ray diffraction (DXRD), we probe the structural transformations of these solids in the short-lived high pressure and temperature states generated. The novelty and power of using DXRD for the assessment of kinetics of phase transitions lies in the ability to discover and identify new phases and to examine kinetics without prior knowledge of a material's phase diagram. Our results provide a quantified expression and a physics model of kinetics of formation of high-pressure phases under shock loading: transition incubation time, evolution, completion time and crystallization rate.

36 MATERIALS SCIENCE↗

NASA NTRS1976

A kinetic-theory approach to turbulent chemically reacting flows

The paper examines the mathematical and physical foundations for the kinetic theory of reactive turbulent flows, discussing the differences and relation between the kinetic and averaged equations, and comparing some solutions of the kinetic equations obtained by the Green's function method with those obtained by the approximate bimodal method. The kinetic method described consists essentially in constructing the probability density functions of the chemical species on the basis of solutions of the Langevin stochastic equation for the influence of eddies on the behavior of fluid elements. When the kinetic equations are solved for the structure of the diffusion flame established in a shear layer by the bimodal method, discontinuities in gradients of the mean concentrations at the two flame edges appear. This is a consequence of the bimodal approximation of all distribution functions by two dissimilar half-Maxwellian functions, which is a very crude approximation. These discontinuities do not appear when the solutions are constructed by the Green's function method described here.

Chung, P. M.↗

NASA NTRS1978

Kinetic energy budgets during the life cycle of intense convective activity

Synoptic-scale data at three- and six-hour intervals are employed to study the relationship between changing kinetic energy variables and the life cycles of two severe squall lines. The kinetic energy budgets indicate a high degree of kinetic energy generation, especially pronounced near the jet-stream level. Energy losses in the storm environment are due to the transfer of kinetic energy from grid to subgrid scales of motion; large-scale upward vertical motion carries aloft the kinetic energy generated by storm activity at lower levels. In general, the time of maximum storm intensity is also the time of maximum energy conversion and transport.

Fuelberg, H. E.↗

NASA NTRS1979

Kinetic energy budgets in areas of convection

Synoptic scale budgets of kinetic energy are computed using 3 and 6 h data from three of NASA's Atmospheric Variability Experiments (AVE's). Numerous areas of intense convection occurred during the three experiments. Large kinetic energy variability, with periods as short as 6 h, is observed in budgets computed over each entire experiment area and over limited volumes that barely enclose the convection and move with it. Kinetic energy generation and transport processes in the smaller volumes are often a maximum when the enclosed storms are near peak intensity, but the nature of the various energy processes differs between storm cases and seems closely related to the synoptic conditions. A commonly observed energy budget for peak storm intensity indicates that generation of kinetic energy by cross-contour flow is the major energy source while dissipation to subgrid scales is the major sink. Synoptic scale vertical motion transports kinetic energy from lower to upper levels of the atmosphere while low-level horizontal flux convergence and upper-level horizontal divergence also occur. Spatial fields of the energy budget terms show that the storm environment is a major center of energy activity for the entire area.

Fuelberg, H. E.↗

NASA NTRS1980

Kinetic energy budgets in areas of intense convection

A kinetic energy budget analysis of the AVE-SESAME 1 period which coincided with the deadly Red River Valley tornado outbreak is presented. Horizontal flux convergence was found to be the major kinetic energy source to the region, while cross contour destruction was the major sink. Kinetic energy transformations were dominated by processes related to strong jet intrusion into the severe storm area. A kinetic energy budget of the AVE 6 period also is presented. The effects of inherent rawinsonde data errors on widely used basic kinematic parameters, including velocity divergence, vorticity advection, and kinematic vertical motion are described. In addition, an error analysis was performed in terms of the kinetic energy budget equation. Results obtained from downward integration of the continuity equation to obtain kinematic values of vertical motion are described. This alternate procedure shows promising results in severe storm situations.

Fuelberg, H. E.↗

NASA NTRS1980

An investigation of the kinetics for hydrogen chemisorption on iron metal surfaces

A quasi-isothermal approach was used to study the kinetics of hydrogen and hydrogen sulfide chemisorption onto iron film in an effort to understand the environmental degradation of steels. The coverage of chemisorbed hydrogen or chemisorbed sulfur was observed as a function of time for fixed conditions of substrate temperature. Auger electron spectroscopy was used to observe the sulfur and chemisorption-induced resistance change was employed to monitor hydrogen coverage. To compare the results obtained from studying the kinetics by two different techniques, the kinetics of oxygen chemisorption onto iron films was also studied. A reaction model utilized to interpret the H2/Fe2 chemisorption kinetics was applied to data from an earlier study on the desorption kinetics for H2 chemisorbed onto nicket films in the vicinity of the Curie temperature of the film. This analysis permitted a separation of the gross desorption process into individual components so that the influence of the magnetic phase transition on the rate constants could be determined.

Shanabarger, M. R.↗

NASA NTRS1982

A note on the maintenance of the atmospheric kinetic energy

The winter simulations of the GLAS climate model and the NCAR community climate model are used to examine the maintenance of the atmospheric kinetic energy. It is found that the kinetic energy is generated in the lower latitudes south of the maximum westerlies, transported northward and then, destroyed in the midlatitudes north of the maximum westerlies. Therefore, the atmospheric kinetic energy is maintained by the counterbalance between the divergence (convergence) of kinetic energy flux and generation (destruction) of kinetic energy in lower (middle) latitudes.

Chen, T.-C.↗

NASA NTRS1985

Chemical kinetic performance losses for a hydrogen laser thermal thruster

Projected requirements for efficient, economical, orbit-raising propulsion systems have generated investigations into several potentially high specific impulse, moderate thrust, advanced systems. One of these systems, laser thermal propulsion, utilizes a high temperature plasma as the enthalpy source. The plasma is sustained by a focused laser beam which maintains the plasma temperature at levels near 20,000 K. Since such temperature levels lead to total dissociation and high ionization, the plasma thruster system potentially has a high specific impulse decrement due to recombination losses. The nozzle flow is expected to be sufficiently nonequilibrium to warrant concern over the achievable specific impluse. This investigation was an attempt at evaluation of those losses. The One-Dimensional Kinetics (ODK) option of the Two-Dimensional Kinetics (TDK) Computer Program was used with a chemical kinetics rate set obtained from available literature to determine the chemical kinetic energy losses for typical plasma thruster conditions. The rates were varied about the nominal accepted values to band the possible losses. Kinetic losses were shown to be highly significant for a laser thermal thruster using hydrogen. A 30 percent reduction in specific impulse is possible simply due to the inability to completely extract the molecular recombination energy.

Mccay, T. D.↗

NASA NTRS1987

Kinetic aspects of tail dynamics - Theory and simulation

Kinetic theories relevant to the geomagnetic tail are reviewed. The topics discussed include kinetic instabilities, simulations, and current-sheet particle acceleration. Tearing mode and reconnection theories are emphasized. Kinetic treatment is appropriate for these topics since the tail plasma is collisionless. Fluid calculations are appropriate when stochastic processes dominate and for studies where long wavelengths are important. However, fluid treatments of tearing modes and reconnection require a finite resistivity in the diffusion region. Thus, although 'anomalous resistivity' can be guessed or in some cases calculated, ideally the kinetic treatment is often to be preferred. Particle motion and acceleration in the current sheet can give rise to beam-like distributions in the plasma-sheet boundary layer. Studies of current-sheet particle motion have also been used as the basis for 'kinetic' tail equilibrium models. Furthermore, quite recently current-sheet particle motion is used directly in Coroniti's explosive tail reconnection model. The 'inertial conductivity' from the equilibrium models provides the 'dissipation' necessary for reconnection.

Speiser, T. W.↗

NASA NTRS1988

The kinetic approach in magnetospheric plasma transport modeling

The need for a kinetic approach in magnetospheric plasma transport problems is reviewed, as are the trends in its recent applications. The need for kinetic modeling is particularly obvious when confronted with the astonishing variety of magnetospheric particle measurements that display compelling energy and pitch angle-related spatial and/or temporal dispersion, and various types of highly non-Maxwellian features in the distribution functions. Global problems in which the kinetic approach has recently been applied include solar wind plasma injection and dispersion over the cusp, substorm particle injection near synchronous orbit, synergistic energization of ionospheric ions into ring current populations by waves and induced electric field-driven convection, and ionospheric outflow from restricted source regions into the magnetosphere. Kinetic modeling can include efforts ranging from test-particle techniques to particle-in-cell studies, and this range is considered here. There are some areas where fluid and kinetic approaches have been combined or patched together, and these will be briefly discussed.

Horwitz, J. L.↗