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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

The Role of Aerosols on Precipitation Processes

Cloud physics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distribution below the clouds. Therefore, the size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral--bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Tao, Wei-Kuo↗
NASA NTRS2012

The Role of Aerosols on Precipitation Processes: Cloud Resolving Model Simulations

Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, the sub-tropics (Florida) and midlatitudes using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CeN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for these cases. It is shown that since the low (CN case produces fewer droplets, larger sizes develop due to greater condensational and collection growth, leading to a broader size spectrum in comparison to the high CCN case. Sensitivity tests were performed to identify the impact of ice processes, radiation and large-scale influence on cloud-aerosol interactive processes, especially regarding surface rainfall amounts and characteristics (i.e., heavy or convective versus light or stratiform types). In addition, an inert tracer was included to follow the vertical redistribution of aerosols by cloud processes. We will also give a brief review from observational evidence on the role of aerosol on precipitation processes.

Tao, Wei-Kuo↗
DOE OSTI2021

Stochasticity and positive feedback enable enzyme kinetics at the membrane to sense reaction size

Here, we present detailed kinetic analyses of a panel of soluble lipid kinases and phosphatases, as well as Ras activating proteins, acting on their respective membrane surface substrates. The results reveal that the mean catalytic rate of such interfacial enzymes can exhibit a strong dependence on the size of the reaction system—in this case membrane area. Experimental measurements and kinetic modeling reveal how stochastic effects stemming from low molecular copy numbers of the enzymes alter reaction kinetics based on mechanistic characteristics of the enzyme, such as positive feedback. For the competitive enzymatic cycles studied here, the final product—consisting of a specific lipid composition or Ras activity state—depends on the size of the reaction system. Furthermore, we demonstrate how these reaction size dependencies can be controlled by engineering feedback mechanisms into the enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Modeling stochastic fluctuations in relativistic kinetic theory

Using the information current, we develop a Lorentz-covariant framework for modeling equilibrium fluctuations in relativistic kinetic theory in the grand-canonical ensemble. The resulting stochastic theory is proven to be causal and covariantly stable, and its predictions do not depend on the choice of spacetime foliation used to define the grand-canonical probabilities. As expected, in a box containing N > 5 particles, Boltzmann’s molecular chaos postulate is broken with (almost exact) probability N -1/2 , leading to a breakdown of the Boltzmann equation in small systems. Here, we also verify that, in ultrarelativistic gases, transient hydrodynamics already accounts for at least 80% of the equilibrium fluctuations of the stress-energy tensor at a given time. Finally, we compute the correlators at nonequal times for two selected collision kernels: that of a chemically active diluted solution, and that of ultrarelativistic scalar particles self-interacting via a quartic potential. For the former, we compute the density-density correlators analytically in real space, and dehydrodynamization of the stochastic theory is proven to occur whenever the mean free path diverges at high energy.

Astronomy & Astrophysics↗
NASA NTRS1994

The kinetic response of a stochastic plasma to low frequency perturbations

Following suggestion that substorm breakup might be caused by an interchange or ballooning instability, several magnetohydrodynamic (MHD) and gyro-kinetic stability analysis have been performed for plasma sheet magnetic field geometries. However, the stochastic ion dynamics in the highly stressed, thin high-beta near earth plasma sheet violate the locality requirements of MHD and the invarience of the magnetic moment, mu, required by gyro-kinetic theories. In this paper we develop a new linear Vlasov kinetic theory (for low frequency modes omega less than omega(sub b), omega(sub b) being the bounce frequency) which includes the dynamics of stochastic ions.

Hurricane, Omar A.↗
DOE OSTI2023

Catalyst: Fast and flexible modeling of reaction networks

We introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high-performance simulation of chemical reaction networks (CRNs). Catalyst supports simulating stochastic chemical kinetics (jump process), chemical Langevin equation (stochastic differential equation), and reaction rate equation (ordinary differential equation) representations for CRNs. Through comprehensive benchmarks, we demonstrate that Catalyst simulation runtimes are often one to two orders of magnitude faster than other popular tools. More broadly, Catalyst acts as both a domain-specific language and an intermediate representation for symbolically encoding CRN models as Julia-native objects. This enables a pipeline of symbolically specifying, analyzing, and modifying CRNs; converting Catalyst models to symbolic representations of concrete mathematical models; and generating compiled code for numerical solvers. Leveraging ModelingToolkit.jl and Symbolics.jl, Catalyst models can be analyzed, simplified, and compiled into optimized representations for use in numerical solvers. Finally, we demonstrate Catalyst’s broad extensibility and composability by highlighting how it can compose with a variety of Julia libraries, and how existing open-source biological modeling projects have extended its intermediate representation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Stochastic hydrodynamics and hydro-kinetics: Similarities and differences

The hydro-kinetic formalism has been used as a complementary approach to solving the Stochastic Differential Equations (SDE) corresponding to noisy hydrodynamics. The hydro-kinetic formalism consists of a deterministic set of relaxation type equations that tracks the evolution of 2-point correlation functions of stochastic hydrodynamic quantities. Hence they are comparatively easier to solve than the SDEs, which are computationally intensive and need to deal with arbitrarily large gradients. This work compares the two approaches for the propagation and diffusion of conserved charge fluctuations in the Bjorken hydrodynamic model. For white noise, the two approaches agree. For colored Catteneo noise, which is causal, the two approaches diverge. This is because white noise only induces two-point correlations, while Catteneo noise also induces higher-order correlations. Furthermore, this difference is quantified from the effects of causal evolution and influence from higher-order correlations induced by the Catteneo noise.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

On analysis and stochastic modeling of the particle kinetic energy equation in particle-laden isotropic turbulent flows

In this study, we analyze three-dimensional particle-laden, isotropic turbulence to develop an understanding of inertial particle dynamics from a kinetic energy perspective. Data trends implying inhomogeneous sampling of the flow by particles are identified and used to support a proposed particle behavior: particles appear to accumulate in regions of low flow kinetic energy over time because they lose kinetic energy and slow down in such regions, ultimately causing them to spend more time there. To elucidate this behavior, we derive a particle kinetic energy equation from the particle momentum equation, which incorporates inertial effects through the Schiller–Naumann drag correlation. Upon extracting fundamental physics from this equation, hypotheses regarding the role of the Stokes number in the temporal change of particle kinetic energy and the previously proposed particle behavior are evaluated using simulation data considering three Stokes numbers. Finally, a Fokker–Planck equation is used to derive the steady-state probability density function of the particle kinetic energy. The model fits the simulation data well and provides a tool for further investigation into understanding preferential concentration, as well as a reduced order model for predicting particle kinetic energy in turbulent flows.

42 ENGINEERING↗
DOE OSTI2020

Runaway electron seed formation at reactor-relevant temperature

Systematic variation of the pre-disruption core electron temperature (T e ) from 1 to 12 keV using an internal transport barrier scenario reveals a dramatic increase in the production of ‘seed’ runaway electrons (REs), ultimately accessing near-complete conversion of the pre-disruption current into sub-MeV RE current. Injected Ar pellets are observed to ablate more intensely and promptly as T e rises. At high T e , the observed ablation exceeds predictions from published thermal ablation models. Simultaneously, the thermal quench (TQ) is observed to significantly shorten with increasing T e —a surprising result. While the reason for the shorter TQ is not yet understood, candidate mechanisms include: insufficiently accurate thermal ablation models, enhanced ablation driven by the seed RE population, or significant parallel heat transport along stochastic fields. Kinetic modeling that self-consistently treats the plasma cooling via radiation, the induced electric field, and the formation of the seed RE is performed. Including the combined effect of the inherent dependence of hot-tail RE seeding on T e together with the shortened TQ, modeling recovers the progression towards near-complete conversion of the pre-disruption current to RE current as T e rises. Measurement of the HXR spectrum during the early current quench (CQ) reveals a trend of decreasing energy with pre-disruption T e . At the very highest T e (≈ 12 keV), ≈ 100% conversion of the thermal current to runaway current is found. The energy of this peculiar RE beam is inferred to be sub-MeV as it emits vanishingly few MeV hard x-rays (HXRs). These measurements demonstrate novel TQ dynamics as Te is varied and illustrate the limitations of treating the RE seed formation problem without considering the inter-related dependencies of the pellet ablation, radiative energy loss, and resultant variations of the TQ duration. Finally, if the observed shortening of the TQ with increasing T e extends to fusion-grade plasmas, than their propensity to form large quantities of RE seeds at high T e may be far worse than previously thought. Positively, the high T e scenario in DIII-D produces REs so prodigiously that it can serve as a meaningful new platform for demonstrating RE avoidance techniques.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Hole in one: Pathways to deterministic single-acceptor incorporation in Si(100)-2 x 1

We report that stochastic incorporation kinetics can be a limiting factor in the scalability of semiconductor fabrication technologies using atomic-precision techniques. While these technologies have recently been extended from donors to acceptors, the extent to which kinetics will impact single-acceptor incorporation has yet to be assessed. To identify the precursor molecule and dosing conditions that are promising for deterministic incorporation, we develop and apply an atomistic model for the single-acceptor incorporation rates of several recently demonstrated molecules: diborane (B 2 H 6 ), boron trichloride (BCl 3 ), and aluminum trichloride in both monomer (AlCl 3 ) and dimer forms (Al 2 Cl 6 ). While all three precursors can realize single-acceptor incorporation, we predict that diborane is unlikely to realize deterministic incorporation, boron trichloride can realize deterministic incorporation with modest heating (50 °C), and aluminum trichloride can realize deterministic incorporation at room temperature. We conclude that both boron and aluminum trichloride are promising precursors for atomic-precision single-acceptor applications, with the potential to enable the reliable production of large arrays of single-atom quantum devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2009

Biophysics Representation of the Two-Hit Model of Alzheimer's Disease for the Exploration of Late CNS Risks from Space Radiation

A concern for long-term space travel outside the Earth s magnetic field is the late effects to the central nervous system (CNS) from galactic cosmic ray (GCR) or solar particle events (SPE). Human epidemiology data is severely limited for making CNS risk estimates and it is not clear such effects occur following low LET exposures. We are developing systems biology models based on biological information on specific diseases, and experimental data for proton and heavy ion radiation. A two-hit model of Alzheimer s disease (AD) has been proposed by Zhu et al.(1), which is the framework of our model. Of importance is that over 50% of the US population over the age of 75-y have mild to severe forms of AD. Therefore we recommend that risk assessment for a potential AD risk from space radiation should focus on the projection of an earlier age of onset of AD and the prevention of this possible acceleration through countermeasures. In the two-hit model, oxidative stress and aberrant cell cycle-related abnormalities leading to amyloid-beta plaques and neurofibrillary tangles are necessary and invariant steps in AD. We have formulated a stochastic cell kinetics model of the two-hit AD model. In our model a population of neuronal cells is allowed to undergo renewal through neurogenesis and is susceptible to oxidative stress or cell cycle abnormalities with age-specific accumulation of damage. Baseline rates are fitted to AD population data for specific ages, gender, and for persons with an apolipoprotein 4 allele. We then explore how low LET or heavy ions may increase either of the two-hits or neurogenesis either through persistent oxidative stress, direct mutation, or through changes to the micro-environment, and suggest possible ways to develop accurate quantitative estimates of these processes for predicting AD risks following long-term space travel.

Cucinotta, Francis A.↗
DOE OSTI2021

On Stochastic Heating and Its Phase-space Signatures in Low-beta Kinetic Turbulence

We revisit the theory of stochastic heating of ions and investigate its phase-space signatures in kinetic turbulence of relevance to low- β portions of the solar wind. In particular, we retain a full scale-dependent approach in our treatment, and we explicitly consider the case in which electric-field fluctuations can be described by a generalized Ohm's law that includes Hall and thermoelectric effects. These two electric-field terms provide the dominant contributions to stochastic ion heating when the ion-Larmor scale is much smaller than the ion skin depth, ρ i << d i , which is the case at β << 1. Employing well-known spectral scaling laws for Alfvén-wave and kinetic-Alfvén-wave turbulent fluctuations, we obtain scaling relations characterizing the field-perpendicular particle-energization rate and energy diffusion coefficient associated with stochastic heating in these two regimes. Phase-space signatures of ion heating are then investigated using three-dimensional hybrid-kinetic simulations of continuously driven Alfvénic turbulence at low β (namely, β i = β e = 0.3 and β i = β e = 1/9). In these simulations, energization of ions parallel to the magnetic field is subdominant compared to its perpendicular counterpart ( Q ∥,i << Q ⊥,i ), and the fraction of turbulent energy that goes into ion heating is ≈75% at β i = 0.3 and ≈40% at β i ≃ 0.1. The phase-space signatures of ion energization are consistent with Landau-resonant collisionless damping and a ( β -dependent) combination of ion-cyclotron and stochastic heating. We demonstrate good agreement between our scale-dependent theory and various signatures associated with the stochastic portion of the heating. We discuss briefly the effect of intermittency on stochastic heating and the implications of our work for the interpretation of stochastic heating in solar-wind spacecraft data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

On-lattice kinetic Monte Carlo approaches for modeling molecular anisotropy in resveratrol crystallization

Stilbenes are a class of organic compounds with broad-ranging pharmaceutical and agricultural applications, which are typically isolated and purified through recrystallization. We are motivated by reducing experimental waste and optimizing yield via developing predictive simulations for processing-dependent crystal morphologies. Using resveratrol as a model stilbene system, we have developed an approach for simulating crystallization with molecular resolution using on-lattice kinetic Monte Carlo. In this work, we highlight modifications to the Stochastic Parallel PARticle Kinetic Simulator (SPPARKS) software package, which were essential to this application. Key enhancements include the incorporation of non-orthogonal cell shapes and monomer anisotropy approximations using bound hard spheres. This new SPPARKS application has been applied to resveratrol with attachment energy libraries obtained from density functional theory, resulting in excellent agreement with experimental morphology prediction.

crystallization↗
DOE OSTI2025

Bottom-Up Simulation, Reconstruction, and Quantification of Macromolecule Sequences from Experimental Polymerizations

Motivated by the canonical sequence–structure–function paradigm, tools to characterize chemical patterning in natural biomacromolecules, from proteins to nucleic acids, have grown exponentially in recent years. However, analogous strategies for synthetic macromolecules remain in nascent stages, complicated by sequence polydispersity and analytical limitations. To address this, we have developed a comprehensive and open-source Python package, PRISM (polymer rate insights and sequence modeling), an end-to-end workflow that provides a path from experimental kinetics measurements to quantitative and qualitative metrics for describing chemical patterning in stochastic polymers. First, a numerical integration strategy was constructed to simulate and fit experimental data from reversible addition–fragmentation chain transfer (RAFT) polymerization kinetics, enabling the facile estimation of relevant reactivity ratios. These ratios were then used in a mechanism-specific stochastic kinetic simulation strategy to simulate sequence ensembles corresponding to model systems spanning experimental copolymers, classes of statistical polymers (e.g., alternating, block, and gradient), and multiblock copolymers. Lastly, inspired by sequence homology metrics from bioinformatics, we introduce visualization strategies and quantitative metrics to facilitate comparisons of different sequence ensembles. As the sequence–structure–function paradigm becomes increasingly central in de novo design of synthetic macromolecules, this toolkit provides a first step toward accurate and representative sequence description and featurization.

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

Runaway electron transport in stochastic toroidal magnetic fields

Here, we study the transport and confinement properties of runaway electrons (RE) in the presence of magnetic fields with perturbations producing different levels of stochasticity. We use Kinetic Orbit Runaway Electron Code (KORC) [Carbajal et al. , Phys. Plasmas 24, 042512 (2017) and del-Castillo-Negrete et al. , Phys. Plasmas 25, 056104 (2018)] for simulating the full-orbit (FO) and guiding-center (GC) dynamics of RE in perturbed magnetic fields that exhibit magnetic islands. We extend previous works on this problem [Wingen et al. , Nucl. Fusion 46, 941 (2006); Izzo et al. , Nucl. Fusion 51, 063032 (2011); Papp et al. , Nucl. Fusion 51, 043004 (2011); V. Izzo and P. Parks, Phys. Plasmas 24, 060705 (2017); and Sommariva et al. , Nucl. Fusion 58, 016043 (2018)] by studying in detail full-orbit effects on the RE dynamics. We quantify FO effects on RE transport by performing one-to-one comparisons between FO and GC simulations. It is found that, for the magnetic field configurations considered, GC simulations predict twice the RE losses of FO simulations for 1 MeV and four times the RE losses of FO simulations for 25 MeV. Similarly, we show how different GC and FO dynamics of RE moving around magnetic islands can be, especially in the scenario where the RE Larmor radius is on the order of the size of the magnetic island. We also study the role of rotation of the magnetic islands on RE confinement, and we find that low-frequency toroidal rotation has no observable effect on RE transport in the cases considered. These results shed some light into the potential of avoidance or mitigation mechanisms based on magnetic perturbations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Computational Aspects of Single-Molecule Kinetics for Coupled Catalytic Cycles: A Spectral Analysis

Catalysis from single active sites is analyzed using methods developed from single molecule kinetics. Using a stochastic Markov state description, the observable properties of general catalytic networks of reactions are expressed using an eigenvalue decomposition of the transition matrix for the Markov process. By the use of a sensitivity analysis, the necessary eigenvalues and eigenvectors are related to the energies of controlling barriers and wells located along the reaction routes. A generalization of the energetic span theory allows the eigenvalues to be computed from several activation energies corresponding to distinct barrier-well pairings. The formalism is demonstrated accurately for model problems for a physically realistic mechanism for an alkene hydrogenation reaction on a single atom catalyst.

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

Hydroxyl radical yields in the heavy ion radiolysis of water

The yields of hydroxyl radicals in the radiolysis of water with protons and carbon ions have been examined using experimental scavenging techniques coupled with Monte Carlo track simulations. Combined with previous results using helium ions, this set of data gives valuable information on the potential for radiation induced damage to biological systems for light ions with very different track structures. Carbon dioxide production from aerated formic acid solutions in concentrations ranging from 10 -3 to 1 M was used as a probe of hydroxyl radical yields from about 8 ns to 8 µs. Numerical interpolation of the results at slightly different ion energies in combination with data from gamma radiolysis allows for a systematic analysis of both track average and track segment yields. As expected, considerable track chemistry is found to occur on the nanosecond to microsecond time scales. Monte Carlo track simulations employing stochastic diffusion-kinetic calculations of product yields are found to reproduce experimental observations satisfactorily. The track simulations are used to extract hydroxyl radical kinetics in pure water at neutral conditions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗