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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Statistical analysis of near-wall structures in turbulent channel flow

The two-point correlation tensor is used to analyze near-wall structures in turbulent channel flow. Simulation results have been utilized to obtain the correlation tensor with sufficient spatial resolution to permit accurate differentiation for computing the vorticity correlation, and the resolution of sharp features such as the shear layer and its corresponding region of spanwise vorticity. Proper orthogonal decomposition and stochastic estimation were observed to yield similar results when appropriate conditions were employed for the estimation. Resulting structures were such that they would be detected by standard conditional sampling methods. The results of decomposing the vorticity field and the velocity field were significantly different, indicating that if a coherent structure is found that dominates the velocity fields, the curl of that velocity structure will not dominate the vorticity field.

Moser, Robert D.↗
NASA NTRS2009

Combined Modeling of Acceleration, Transport, and Hydrodynamic Response in Solar Flares: The Numerical Model - 1

Acceleration and transport of high-energy particles and fluid dynamics of atmospheric plasma are interrelated aspects of solar flares, but for convenience and simplicity they were artificially separated in the past. We present here self consistently combined Fokker-Planck modeling of particles and hydrodynamic simulation of flare plasma. Energetic electrons are modeled with the Stanford unified code of acceleration, transport, and radiation, while plasma is modeled with the Naval Research Laboratory flux tube code. We calculated the collisional heating rate directly from the particle transport code, which is more accurate than those in previous studies based on approximate analytical solutions. We repeated the simulation of Mariska et al. with an injection of power law, downward-beamed electrons using the new heating rate. For this case, a -10% difference was found from their old result. We also used a more realistic spectrum of injected electrons provided by the stochastic acceleration model, which has a smooth transition from a quasi-thermal background at low energies to a non thermal tail at high energies. The inclusion of low-energy electrons results in relatively more heating in the corona (versus chromosphere) and thus a larger downward heat conduction flux. The interplay of electron heating, conduction, and radiative loss leads to stronger chromospheric evaporation than obtained in previous studies, which had a deficit in low-energy electrons due to an arbitrarily assumed low-energy cutoff. The energy and spatial distributions of energetic electrons and bremsstrahlung photons bear signatures of the changing density distribution caused by chromospheric evaporation. In particular, the density jump at the evaporation front gives rise to enhanced emission, which, in principle, can be imaged by X-ray telescopes. This model can be applied to investigate a variety of high-energy processes in solar, space, and astrophysical plasmas.

STOCHASTIC ACCELERATION MODEL↗
DOE OSTI2022

Protein drift-diffusion dynamics and phase separation in curved cell membranes and dendritic spines: Hybrid discrete-continuum methods

We develop methods for investigating protein drift-diffusion dynamics in heterogeneous cell membranes and the roles played by geometry, diffusion, chemical kinetics, and phase separation. Our hybrid stochastic numerical methods combine discrete particle descriptions with continuum-level models for tracking the individual protein drift-diffusion dynamics when coupled to continuum fields. We show how our approaches can be used to investigate phenomena motivated by protein kinetics within dendritic spines. The spine geometry is hypothesized to play an important biological role regulating synaptic strength, protein kinetics, and self-assembly of clusters. We perform simulation studies for model spine geometries varying the neck size to investigate how phase-separation and protein organization is influenced by different shapes. We also show how our methods can be used to study the roles of geometry in reaction-diffusion systems including Turing instabilities. Furthermore, our methods provide general approaches for investigating protein kinetics and drift-diffusion dynamics within curved membrane structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Chapter 6: Abuse Response of Batteries Subjected to Mechanical Impact

Electrochemical and thermal models to simulate nominal performance and abuse response of lithium-ion cells and batteries have been reported widely in the literature. Studies on mechanical failure of cell components and how such events interact with the electrochemical and thermal response are relatively less common. This chapter outlines a framework developed under the Computer Aided Engineering for Batteries program to couple failure modes resulting from external mechanical loading to the onset and propagation of electrochemical and thermal events that follow. Starting with a scalable approach to implement failure criteria based on thermal, mechanical, and electrochemical thresholds, we highlight the practical importance of these models using case studies at the cell and module level. The chapter also highlights a few gaps in our understanding of the comprehensive response of batteries subjected to mechanical crash events, the stochastic nature of some of these failure events, and our approach to build safety maps that help improve robustness of battery design by capturing the sensitivity of some key design parameters to heat generation rates under different mitigation strategies.

abuse simulations↗
DOE OSTI2020

Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey

Uncertainty quantification (UQ) includes the characterization, integration, and propagation of uncertainties that result from stochastic variations and a lack of knowledge or data in the natural world. Monte Carlo (MC) method is a sampling-based approach that has widely used for quantification and propagation of uncertainties. However, the standard MC method is often time-consuming if the simulation-based model is computationally intensive. This article gives an overview of modern MC methods to address the existing challenges of the standard MC in the context of UQ. Specifically, multilevel Monte Carlo (MLMC) extending the concept of control variates achieves a significant reduction of the computational cost by performing most evaluations with low accuracy and corresponding low cost, and relatively few evaluations at high accuracy and corresponding high cost. Multifidelity Monte Carlo (MFMC) accelerates the convergence of standard Monte Carlo by generalizing the control variates with different models having varying fidelities and varying computational costs. Multimodel Monte Carlo method (MMMC), having a different setting of MLMC and MFMC, aims to address the issue of UQ and propagation when data for characterizing probability distributions are limited. Multimodel inference combined with importance sampling is proposed for quantifying and efficiently propagating the uncertainties resulting from small data sets. All of these three modern MC methods achieve a significant improvement of computational efficiency for probabilistic UQ, particularly uncertainty propagation. Finally, an algorithm summary and the corresponding code implementation are provided for each of the modern MC methods. The extension and application of these methods are discussed in detail.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Achieving a large transverse emittance ratio in the Relativistic Heavy Ion Collider: Beam experiments, analytical estimates, and implications for the Electron-Ion Collider

The Electron-Ion Collider (EIC), to be built at Brookhaven National Laboratory, will collide a polarized high-energy electron beam with polarized proton and light ion beams in the center-of-mass energy range of 20–140 GeV, achieving a maximum peak luminosity of up to 1 × 10 34 cm − 2 s − 1 for the proton and electron collisions. To achieve such a high luminosity, the EIC will employ small, flat beams at the interaction point, which requires a transverse emittance ratio of about 11:1. Since 2017, we have carried out a series of beam experiments to test the feasibility of achieving such a large emittance ratio in the Relativistic Heavy Ion Collider (RHIC). Thanks to the existing stochastic cooling and decoupling feedback system in RHIC, we successfully demonstrated a large transverse emittance ratio of 11:1 with gold ion beams in 2023. In this article, we will present more details and data analysis for these experiments, along with analytical estimates and numerical multiparticle simulations, and provide an outlook for future EIC coupling compensation. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Impact of confined geometries on hopping and trapping of motile bacteria in porous media

We use a random walk particle-tracking (RWPT) approach to elucidate the impact of porous media confinement and cell-cell interactions on bacterial transport. The model employs stochastic alternating motility states consisting of hopping movement and trapping reorientation. The stochastic motility patterns are defined based on direct visualization of individual trajectory data. We validate our model against experimental data, at single-cell resolution, of bacterial E. coli motion in three-dimensional confined porous media. Results show that the model is able to efficiently simulate the spreading dynamics of motile bacteria as it captures the impact of cell-cell interaction and pore confinement, which marks the transition to a late-time subdiffusive regime. Furthermore, the model is able to qualitatively reproduce the observed directional persistence. Lastly, our RWPT model constitutes a meshless simple method which is easy to implement and does not invoke ad hoc assumptions but represents the basis for a multiscale approach to the study of bacterial dispersal in porous systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Model Validation and Uncertainty Quantification on the KRUSTY Microreactor Design Using GRIFFIN Neutron Transport Code [Poster]

Argonne National Laboratory (ANL) and INL have developed a GRIFFIN steady state neutronics model for the multiphysics simulations of the Kilopower Reactor Using Sterling TechnologY (KRUSTY) microreactor in the Multiphysics Object Oriented Simulation Environment (MOOSE). The reliability of such deterministic neutronics models can be validated by comparing with computations from Monte Carlo codes (e.g. MCNP, SERPENT, OpenMC, Shift, etc). Furthermore, potential modeling/design improvements can be identified by incorporating uncertainty quantification (UQ), which can be performed by MOOSE’s Stochastic Tools Module (STM). KRUSTY is a prototype for a 5-kW thermal nuclear-powered space reactor. Its primary components consist of nuclear fuel, heat pipes, a control rod, a reflector, and the shielding. The fuel consists of 3 stacked U-7.65Mo cylinders with a hole in the center for the control rod. 8 liquid sodium heat pipes transfer fission energy from the solid fuel block to the Sterling power conversion system where the energy is extracted, and the cooled sodium flows back to the core via capillary action . The movable Boron Carbide control rod regulates the neutron population during startup or when a reactor temperature boost is needed . The beryllium oxide reflector is in 3 places in the reactor; it surrounds the core axially, it lies beneath the core on a platen, and it is present in the shim. The axial and lower reflectors rest on an adjustable stainless-steel platen that moves upward to cover the fuel and help the reactor reach criticality. Lastly, radial stainless steel surrounds the core offering protection from radiation exposure .

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1987

Algorithmic commonalities in the parallel environment

The ultimate aim of this project was to analyze procedures from substantially different application areas to discover what is either common or peculiar in the process of conversion to the Massively Parallel Processor (MPP). Three areas were identified: molecular dynamic simulation, production systems (rule systems), and various graphics and vision algorithms. To date, only selected graphics procedures have been investigated. They are the most readily available, and produce the most visible results. These include simple polygon patch rendering, raycasting against a constructive solid geometric model, and stochastic or fractal based textured surface algorithms. Only the simplest of conversion strategies, mapping a major loop to the array, has been investigated so far. It is not entirely satisfactory.

Mcanulty, Michael A.↗
NASA NTRS2017

Evaluation of Galvanic Vestibular Stimulation System

Microgravity exposure results in an adaptive central reinterpretation of information from multiple sensory sources to produce a sensorimotor state appropriate for motor actions in this unique environment, but this new adaptive state is no longer appropriate for the 1-g gravitational environment on Earth. During these gravitational transitions, astronauts experience deficits in both perceptual and motor functions including impaired postural control, disruption in spatial orientation, impaired control of locomotion that include alterations in muscle activation variability, modified lower limb kinematics, alterations in head-trunk coordination as well as reduced dynamic visual acuity. Post-flight changes in postural and locomotor control might have adverse consequences if a rapid egress was required following a long-duration mission, where support personnel may not be available to aid crewmembers. The act of emergency egress includes, but is not limited to standing, walking, climbing a ladder, jumping down, monitoring displays, actuating discrete controls, operating auxiliary equipment, and communicating with Mission Control and recovery teams while maintaining spatial orientation, mobility and postural stability in order to escape safely. The average time to recover impaired postural control and functional mobility to preflight levels of performance has been shown to be approximately two weeks after long-duration spaceflight. The postflight alterations are due in part to central reinterpretation of vestibular information caused by exposure to microgravity. In this study we will use a commonly used technique of transcutaneous electrical stimulation applied across the vestibular end organs (galvanic vestibular stimulation, GVS) to disrupt vestibular function as a simulation of post-flight disturbances. The goal of this project is an engineering human-in-the-loop evaluation of a device that can degrade performance of functional tasks (e.g. to maintain upright balance) similar to what astronauts experience during transitions to new gravitational environments. Stochastic electrical stimulation can be applied to the vestibular system through electrodes placed over the mastoid process behind the ears in the binaural configuration resulting in stimulation in the mediolateral (side-to-side) plane. An additional electrode can be placed over the bony landmark of the tip of the c7 spinous process for the double monaural configuration, which will cause stimulation in the anteroposterior (forward-backward) plane. A portable constant current bipolar stimulator with subject isolation was designed and built to deliver the stimulus. The unit is powered using a 3.7 V battery pack and designed to produce currents up to 5 mA. The stimulator, controlled by a Raspberry Pi 3 computer, offers several stimulus signal generation options including a standalone mode, which uses onboard signal files stored on the flash memory card. Stochastic stimulation signals will be generated in 0-30 Hz frequency bandwidth. Stimulation amplitude can be increased incrementally to a maximum amplitude of 5.0 mA (e.g., 0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0 mA). In control trials, subjects will be experiencing vestibular stimulation with 0-mA current applied through the electrodes. The system will be evaluated at various levels of stimulation and in both the binaural and double monaural electrode configurations. One of the objectives is to identify stimulation levels producing effects most comparable to the post-flight disturbances. This is a pilot study that will set the stage for a larger, more comprehensive study that will investigate wider aspects of post-flight sensorimotor dysfunction and set sensorimotor standards for crew health.

Kofman, I. S.↗
DOE OSTI2021

Comparison of Attila Transport Code with MCNP in the Analysis of Small Modular Reactor Shielding

Of great importance in the design of a nuclear power plant is the evaluation of shielding from the ionizing radiation produced in the core of the nuclear reactor. This requires simulation software to predict the dose rates in the areas of interest. These problems are referred to as deep penetration problems, as they involve the reduction of a radiation field by two or three orders of magnitude or more. This makes accurate analyses difficult for Monte Carlo based solutions that rely on enough particles being sampled in an area of interest. Comparing the simulation of the same modeled system with more than one computer application, especially one that uses a different algorithmic approach, is a way to gain confidence in the results. In this research, two models were created, one in Monte Carlo N Particle (MCNP) which uses a stochastic algorithmic approach, and the other in Attila, which uses a deterministic algorithmic approach to test the validity of the model and to estimate the dose rates in the area of interest. Successful comparison of the two models is a way we can validate the model used for that estimation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1982

A data based random number generator for a multivariate distribution (using stochastic interpolation)

Let X be a K-dimensional random variable serving as input for a system with output Y (not necessarily of dimension k). given X, an outcome Y or a distribution of outcomes G(Y/X) may be obtained either explicitly or implicity. The situation is considered in which there is a real world data set X sub j sub = 1 (n) and a means of simulating an outcome Y. A method for empirical random number generation based on the sample of observations of the random variable X without estimating the underlying density is discussed.

Thompson, J. R.↗
NASA NTRS1990

Linear and non-linear studies of Alfven waves in space. Stationary and dynamic processes in magnetospheric plasmas

The Final Technical Report on linear and non-linear studies of Alfven waves in space is presented. Areas of research included relaxation of magnetotail plasmas with field-aligned currents; the equilibrium dayside magnetosphere; macroscale particle simulation of kinetic Alfven wave physics; ballooning stability of plasmas with sheared equilibrium flows; theory of the drift-mirror instability; collisionless tearing instability in magnetotail plasmas; and nonadiabatic behavior of the magnetic moment of a charged particle in a dipole magnetic field and the development of stochastic webs.

Bhattacharjee, A.↗
NASA NTRS2001

A stochastic differential equation model of diurnal cortisol patterns

Circadian modulation of episodic bursts is recognized as the normal physiological pattern of diurnal variation in plasma cortisol levels. The primary physiological factors underlying these diurnal patterns are the ultradian timing of secretory events, circadian modulation of the amplitude of secretory events, infusion of the hormone from the adrenal gland into the plasma, and clearance of the hormone from the plasma by the liver. Each measured plasma cortisol level has an error arising from the cortisol immunoassay. We demonstrate that all of these three physiological principles can be succinctly summarized in a single stochastic differential equation plus measurement error model and show that physiologically consistent ranges of the model parameters can be determined from published reports. We summarize the model parameters in terms of the multivariate Gaussian probability density and establish the plausibility of the model with a series of simulation studies. Our framework makes possible a sensitivity analysis in which all model parameters are allowed to vary simultaneously. The model offers an approach for simultaneously representing cortisol's ultradian, circadian, and kinetic properties. Our modeling paradigm provides a framework for simulation studies and data analysis that should be readily adaptable to the analysis of other endocrine hormone systems.

NASA Discipline Space Human Factors↗
DOE OSTI2021

Discrete-Time Causal Control of a Wave Energy Converter With Finite Stroke in Stochastic Waves

We consider feedback control design for a wave energy converter (WEC) for which the power takeoff (PTO) system has a finite stroke limit. Stationary stochastic wave loading is assumed, with a known spectrum, and the plant dynamics are assumed to be linear. We develop a technique for the design of a discrete-time controller, which has three design stages. In the first stage, a linear controller is optimized while imposing a relaxation of the maximum stroke constraint on the design. In the second stage, a tandem nonlinear feedback loop is designed for the purpose of stroke protection. In the third stage, the two designs (linear and nonlinear) are fused in a manner that preserves the stability of the overall system. The technique is demonstrated in a simulation of a simple cylindrical buoy. We show that the controller may be tuned through the adjustment of scalar design parameters, which adjust the tradeoff between the mean generated power and the force levels required to protect the stroke.

16 TIDAL AND WAVE POWER↗
NASA NTRS2018

An Interplay between Photons, Canopy Structure, and Recollision Probability: A Review of the Spectral Invariants Theory of 3D Canopy Radiative Transfer Processes

Earth observations collected by remote sensors provide unique information to our ever-growing knowledge of the terrestrial biosphere. Yet, retrieving information from remote sensing data requires sophisticated processing and demands a better understanding of the underlying physics. This paper reviews research efforts that lead to the developments of the stochastic radiative transfer equation (RTE) and the spectral invariants theory. The former simplifies the characteristics of canopy structures with a pair-correlation function so that the 3D information can be succinctly packed into a 1D equation. The latter indicates that the interactions between photons and canopy elements converge to certain invariant patterns quantifiable by a few wavelength independent parameters, which satisfy the law of energy conservation. By revealing the connections between plant structural characteristics and photon recollision probability, these developments significantly advance our understanding of the transportation of radiation within vegetation canopies. They enable a novel physically-based algorithm to simulate the “hot-spot” phenomenon of canopy bidirectional reflectance while conserving energy, a challenge known to the classic radiative transfer models. Therefore, these theoretical developments have a far-reaching influence in optical remote sensing of the biosphere.

vegetation remote sensing; stochastic radiative tr↗
DOE OSTI2022

A Machine‐Learning‐Assisted Stochastic Cloud Population Model as a Parameterization of Cumulus Convection

Abstract A machine‐learning‐assisted stochastic cloud population model is coupled with the Advanced Research Weather Research and Forecasting (WRF) model to represent fluctuations in the cloud‐base mass flux associated with the life cycles and interactions among cumulus convection cells. In this cloud population model, the size distribution and the associated cloud‐base mass flux of the convective cells are related to their previous state and to the change in the total convective area via a transition function. The convective area tendency in turn is assumed to depend on the cloud‐base mass flux that is resolved by the host WRF model. The transition function is represented by a single hidden‐layer neural network trained by the evolution of convective cell size distributions in a 1‐km grid‐spacing WRF simulation run over the Australian Monsoon region. At every grid point of the host model, the cloud population model predicts the cell size and cloud‐base mass flux distributions from which a random sample of cells is fed to an entraining parcel model that calculates precipitation as well as the associated liquid water potential temperature and total moisture tendencies. These tendencies are averaged over the cells and provided to the host model. Several regional simulations are performed over tropical and midlatitude domains to test this as a potential approach to scale‐aware parameterization. It is shown that such an approach could be a new promising path to simulating realistic precipitation statistics and propagation of precipitation associated with the Madden‐Julian Oscillation while maintaining realistic depictions of the diurnal cycle over both land and ocean.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Coherent-phase or random-phase acceleration of electron beams in solar flares

Time structures of electron beam signatures at radio wavelengths are investigated to probe correlated versus random behavior in solar flares. In particular we address the issue whether acceleration and injection of electron beams is coherently modulated by a single source, or whether the injection is driven by a stochastic (possibly spatially fragmented) process. We analyze a total of approximately = 6000 type III bursts observed by Ikarus (Zurich) in the frequency range of 100-500 MHz, during 359 solar flares with simultaneous greater than or = 25 keV hard X-ray emission, in the years 1890-1983. In 155 flares we find a total of 260 continuous type III groups, with an average number of 13 +/- 9 bursts per group, a mean duration of D = 12 +/- 14 s, a mean period of P = 2.0 +/- 1.2 s, with the highest burst rate at a frequency of nu = 310 +/- 120 MHz. Pulse periods have been measured between 0.5 and 10 s, and can be described by an exponential distribution, i.e., N(P) varies as e (exp -P/1.0s). The period shows a frequency dependence of P(nu)=46(exp-0.6)(sub MHz)s for different flares, but is invariant during a particular flare. We measure the mean period P and its standard deviation sigma (sub p) in each type III group, and quantify the degree of periodicity (or phase-coherence) by the dimensionless parameter sigma (sub p)P. The representative sample of 260 type III burst groups shows a mean periodicity of sigma (sub p/P) = 0.37 +/- 0.12, while Monte Carlo simulations of an equivalent set of truly random time series show a distinctly different value of sigma (sub p)P = 0.93 +/- 0.26. This result indicates that the injection of electron beams is coherently modulated by a particle acceleration source which is either compact or has a global organization on a timescale of seconds, in contrast to an incoherent acceleration source, which is stochastic either in time or space. We discuss the constraints on the size of the acceleration region resulting from electron beam propagation delays and from Alfvenic synchronization during a pulse period. We discuss two periodic preocesses in flares, which potentially control quasi-periodic particle acceleration: (1) MHD oscillations, and (2) current sheets with oscillatory dynamics.

Aschwanden, Markus J.↗