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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 289 records · Page 16

Upward Flame Spread Over Thin Solids in Partial Gravity

The effects of partial-gravity, reduced pressure, and sample width on upward flame spread over a thin cellulose fuel were studied experimentally and the results were compared to a numerical flame spread simulation. Fuel samples 1-cm, 2-cm, and 4-cm wide were burned in air at reduced pressures of 0.2 to 0.4 atmospheres in simulated gravity environments of 0.1-G, 0.16-G (Lunar), and 0.38-G (Martian) onboard the NASA KC-135 aircraft and in normal-gravity tests. Observed steady flame propagation speeds and pyrolysis lengths were approximately proportional to the gravity level. Flames spread more quickly and were longer with the wider samples and the variations with gravity and pressure increased with sample width. A numerical simulation of upward flame spread was developed including three-dimensional Navier-Stokes equations, one-step Arrhenius kinetics for the gas phase flame and for the solid surface decomposition, and a fuel-surface radiative loss. The model provides detailed structure of flame temperatures, the flow field interactions with the flame, and the solid fuel mass disappearance. The simulation agrees with experimental flame spread rates and their dependence on gravity level but predicts a wider flammable region than found by experiment. Some unique three-dimensional flame features are demonstrated in the model results.

Feier, I. I.↗

Variability in the Propagation Phase of CFD-Based Noise Prediction: Summary of Results From Category 8 of the BANC-III Workshop

The usage of Computational Fluid Dynamics (CFD) in noise prediction typically has been a two part process: accurately predicting the flow conditions in the near-field and then propagating the noise from the near-field to the observer. Due to the increase in computing power and the cost benefit when weighed against wind tunnel testing, the usage of CFD to estimate the local flow field of complex geometrical structures has become more routine. Recently, the Benchmark problems in Airframe Noise Computation (BANC) workshops have provided a community focus on accurately simulating the local flow field near the body with various CFD approaches. However, to date, little effort has been given into assessing the impact of the propagation phase of noise prediction. This paper includes results from the BANC-III workshop which explores variability in the propagation phase of CFD-based noise prediction. This includes two test cases: an analytical solution of a quadrupole source near a sphere and a computational solution around a nose landing gear. Agreement between three codes was very good for the analytic test case, but CFD-based noise predictions indicate that the propagation phase can introduce 3dB or more of variability in noise predictions.

Lopes, Leonard↗

Electron Drift Resonance in the MHD-Coupled Comprehensive Inner Magnetosphere-Ionosphere Model

Relativistic electrons in the outer radiation belt are highly dynamic and respond to interplanetary solar wind structures interacting with the Earth's magnetic field. A known mechanism dictating electron dynamics is the drift-resonant interaction with ultralow frequency (ULF) waves. The present work simulates the ring current and radiation belt electron populations in the bounce-averaged, kinetic Comprehensive Inner Magnetosphere-Ionosphere model coupled with the Block Adaptive Tree Solar Wind Roe-type Upwind Scheme global magnetospheric magnetohydrodynamic (MHD) code using an idealized ULF wave solar wind density driver. ULF waves generated with 10 min periods (at 1.67 mHz frequencies) in the MHD model are characterized and the corresponding energization of electrons and radial transport of electron phase space density is presented. The drift-resonant electron energy is determined in the simulation and is consistent with the electron resonance conditions in dipolar magnetic fields. The present results will be an important component of understanding inner magnetospheric dynamics and how these inner magnetospheric populations interact with ULF waves resulting from interplanetary solar wind structures.

Komar, C. M.↗

Accelerating SNP Development with Radiation Source Approximations for Far-Field Environment Modeling

The successful development and deployment of space nuclear power and propulsion technology requires a high-fidelity, efficient means of modeling ex-core radiation fields. Monte Carlo particle transport codes provide enable the highest level of fidelity in radiation field modeling but are inefficient for modeling ex-core radiation without modification. This paper details the development of an approach to ex-core radiation field modeling that maintains the fidelity of a Monte Carlo transport approach without sacrificing computational efficiency. This approach is based on recent improvements to an existing Monte Carlo transport acceleration technique known as surface source banking. As the transport of many particles is required to ensure adequate uncertainty in far field transport, analytical reconstruction techniques are employed to represent surface source banks as sampleable series of distributions in particle phase from which an arbitrarily large number of particles can be generated and simulated. All steps of this approach are incorporated into an AMA model to test both the underlying mathematics of the analytical source reconstruction process, as well as the relevance of the technique as a whole towards SNP applications. These tests demonstrated that this approach is capable of accelerating far-field radiation modeling in SNP-relevant scenarios by factors of at least nine over purely eigenvalue-based scenarios without significantly sacrificing simulation accuracy.

Surface Source Banking↗

Energy and Mass Transport of Magnetospheric Plasmas during the November 2003 Magnetic Storm

Intensive energy and mass transport from the solar wind across the magnetosphere boundary is a trigger of magnetic storms. The storm on 20-21 November 2003 was elicited by a high-speed solar wind and strong southward component of interplanetary magnetic field. This storm attained a minimum Dst of -422 nT. During the storm, some of the solar wind particles enter the magnetosphere and eventually become part of the ring current. At the same time, the fierce solar wind powers strong outflow of H+ and O+ from the ionosphere, as well as from the plasmasphere. We examine the contribution of plasmas from the solar wind, ionosphere and plasmasphere to the storm-time ring current. Our simulation shows, for this particular storm, ionospheric O+ and solar wind ions are the major sources of the ring current particles. The polar wind and plasmaspheric H+ have only minor impacts. In the storm main phase, the strong penetration of solar wind electric field pushes ions from the geosynchronous orbit to L shells of 2 and below. Ring current is greatly intensified during the earthward transport and produces a large magnetic depression in the surface field. When the convection subsides, the deep penetrating ions experience strong charge exchange loss, causing rapid decay of the ring current and fast initial storm recovery. Our simulation reproduces very well the storm development indicated by the Dst index.

Fok, Mei-Chging↗

Benchmarking machine learning strategies for phase-field problems

Abstract We present a comprehensive benchmarking framework for evaluating machine-learning approaches applied to phase-field problems. This framework focuses on four key analysis areas crucial for assessing the performance of such approaches in a systematic and structured way. Firstly, interpolation tasks are examined to identify trends in prediction accuracy and accumulation of error over simulation time. Secondly, extrapolation tasks are also evaluated according to the same metrics. Thirdly, the relationship between model performance and data requirements is investigated to understand the impact on predictions and robustness of these approaches. Finally, systematic errors are analyzed to identify specific events or inadvertent rare events triggering high errors. Quantitative metrics evaluating the local and global description of the microstructure evolution, along with other scalar metrics representative of phase-field problems, are used across these four analysis areas. This benchmarking framework provides a path to evaluate the effectiveness and limitations of machine-learning strategies applied to phase-field problems, ultimately facilitating their practical application.

36 MATERIALS SCIENCE↗

Lunar gravitational field estimation and the effects of mismodeling upon lunar satellite orbit prediction

Lunar spherical harmonic gravity coefficients are estimated from simulated observations of a near-circular low altitude polar orbiter disturbed by lunar mascons. Lunar gravity sensing missions using earth-based nearside observations with and without satellite-based far-side observations are simulated and least squares maximum likelihood estimates are developed for spherical harmonic expansion fit models. Simulations and parameter estimations are performed by a modified version of the Smithsonian Astrophysical Observatory's Planetary Ephemeris Program. Two different lunar spacecraft mission phases are simulated to evaluate the estimated fit models. Results for predicting state covariances one orbit ahead are presented along with the state errors resulting from the mismodeled gravity field. The position errors from planning a lunar landing maneuver with a mismodeled gravity field are also presented. These simulations clearly demonstrate the need to include observations of satellite motion over the far side in estimating the lunar gravity field. The simulations also illustrate that the eighth degree and order expansions used in the simulated fits were unable to adequately model lunar mascons.

Davis, John H.↗

Wave-packet manipulation of He Rydberg states by a seeded free-electron laser

We report a two-dimensional pump-control-probe spectroscopic study of the dynamics of singly excited He Rydberg-state wave packets with a seeded extreme ultraviolet (XUV) free-electron laser (FEL) source. A pair of coherent XUV pulses, defined by their coarse time separation and relative phase, created and manipulated the wave packets. The He atoms were postionized by infrared (IR) pulses, and the ion yield was measured as a function of XUV phase and IR arrival time. We tagged and sorted the relative phase of the XUV pulse pair on a single-shot basis by fitting each FEL spectrum with a suitable function that accounts for nonidealities of the XUV pulse pairs, associated with the seeding process; more generally, the fit returns the time-dependent electric field of the FEL spectra. The experimental two-dimensional maps of ion yields, measured as a function of IR (probe) delay and of XUV (pump-control) phase, were compared with the solution of the first-order time-dependent Schrödinger equation for this field. Despite the fact that the experimental conditions imply strong excitation, beyond the approximations of first-order perturbation theory, the simulated map satisfactorily reproduces the experimental one for temporally well-separated pulses. We show that by selecting data at appropriate values of pump-control phase, we enhance or suppress the amplitude of chosen wave-packet components consisting of two or more Rydberg states. When the temporal overlap of the pulse pair cannot be neglected, the phase reconstruction is underdetermined, and we provide a simplified comparison between data and simulations. Published by the American Physical Society 2024

Dumergue, Mathieu (ORCID:0000000236984406)↗

Beam Propagation Through Atmospheric Turbulence Using an Altitude-Dependent Structure Profile with Non-Uniformly Distributed Phase Screens

Modeling the effects of atmospheric turbulence on optical beam propagation is a key element in the design and analysis of free-space optical communication systems. Numerical wave optics simulations provide a particularly useful technique for understanding the degradation of the optical field in the receiver plane when the analytical theory is insufficient for characterizing the atmospheric channel. Motivated by such an application, we use a split-step method modeling the turbulence along the propagation path as a series of thin random phase screens with modified von Karman refractive index statistics using the Hufnagel-Valley turbulence profile to determine the effective structure constant for each screen. In this work, we employ a space-to-ground case study to examine the irradiance and phase statistics for both uniformly and non-uniformly spaced screens along the propagation path and compare to analytical results. We find that better agreement with the analytical theory is obtained using a non-uniform spacing with the effective structure constant for each screen chosen to minimize its contribution to the scintillation in the receiver plane. We evaluate this method as a flexible alternative to other standard layered models used in astronomical imaging applications.

Chahine, Yousef K.↗

Phase-field approach to cellular blebbing

Bulges in the plasma membrane of cells known as blebs can form spontaneously in a wide range of biological processes, but what controls their shape and stability remains incompletely understood. Here, to address this we introduce a dual phase-field model with coupled order parameters representing the cell cortex and plasma membrane that can quantitatively model blebbing in three dimensions. Simulations and sharp-interface analyses reveal that, depending on whether blebbing occurs by detachment of the plasma membrane or rupture of the actin cortex, blebs can form discontinuously through a saddle-node bifurcation or continuously with increasing cortical tension. The model predictions are in good quantitative agreement with existing experimental data for laser-induced cortex rupture.

Biological and medical sciences↗

The Parabolic Wave Equation Generalized to a Spatially Varying Plasma in a Vertical Magnetic Field

This report walks through the process of deriving the wave equation for a vertical wave being propagated through a spatially varying plasma in a vertical magnetic field. Additionally, this report shows how to derive the index of refraction of the plasma corresponding to three different modes of the vertical magnetic field. Finally, this paper briefly explores the next steps planned to successfully simulate and test the equations in a pre-existing phase screen scintillation code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Defect-phase-dynamics approach to statistical domain-growth problem of clock models

The growth of statistical domains in quenched Ising-like p-state clock models with p = 3 or more is investigated theoretically, reformulating the analysis of Ohta et al. (1982) in terms of a phase variable and studying the dynamics of defects introduced into the phase field when the phase variable becomes multivalued. The resulting defect/phase domain-growth equation is applied to the interpretation of Monte Carlo simulations in two dimensions (Kaski and Gunton, 1983; Grest and Srolovitz, 1984), and problems encountered in the analysis of related Potts models are discussed. In the two-dimensional case, the problem is essentially that of a purely dissipative Coulomb gas, with a sq rt t growth law complicated by vertex-pinning effects at small t.

Kawasaki, K.↗

Thermocapillary-Induced Phase Separation with Coalescence

Research has been undertaken on interactions of two or more deformable drops (or bubbles) in a viscous fluid and subject to a temperature, gravitational, or flow field. An asymptotic theory for nearly spherical drops shows that small deformations reduce the coalescence and phase separation rates. Boundary-integral simulations for large deformations show that bubbles experience alignment and enhanced coalescence, whereas more viscous drops may break as a result of hydrodynamic interactions. Experiments for buoyancy motion confirm these observations. Simulations of the sedimentation of many drops show clustering phenomena due to deformations, which lead to enhanced phase separation rates, and simulations of sheared emulsions show that deformations cause a reduction in the effective viscosity.

Davis, Robert H.↗

Thermodynamic Cloud Phase Classifications Using Machine Learning at NSA and ANX

Vertically resolved thermodynamic cloud phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) THERMOCLDPHASE Value-Added Product (VAP) uses a multi-sensor approach to classify thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave radiometer-derived liquid water path, and radiosonde temperature measurements. The measured voxels are classified as ice, snow, mixed-phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multilayer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with one year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1-score, and mean Intersection over Union (IOU). Analysis of ML confidence scores shows ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential datastreams for ML thermodynamic cloud phase predictions. The ML models’ generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. Finally, we evaluate the ML models’ response to simulated instrument outages and signal degradation.

54 ENVIRONMENTAL SCIENCES↗

Mars mesosphere and thermosphere coupling - Semidiurnal tides

The Mars thermospheric general circulation model (MTGCM) is modified to examine the impact of a prescribed semidiurnal tidal wave upon Martian thermospheric fields corresponding to near solar minimum (Mariner 9) and solar maximum (Mariner 6-7) observational periods. The effects of upward propagating tides are introduced into the Mars Thermospheric General circulation Model (MTGCM) by appropriately specifying its lower boundary condition according to classical tidal theory. Estimates of the amplitude and phase of the likely dominant semidiurnal (2,2) mode at the mesopause (about 100 km) are specified for a range of possible lower atmosphere dust conditions. MTGCM simulations contrasting tidally driven fields with solar-only forced ones exhibit a dramatic change in the horizontal and vertical wind patterns, whereby the global temperature and oxygen distributions are also modified significantly.

Bougher, S. W.↗

Computational simulation of liquid fuel rocket injectors

A major component of any liquid propellant rocket is the propellant injection system. Issues of interest include the degree of liquid vaporization and its impact on the combustion process, the pressure and temperature fields in the combustion chamber, and the cooling of the injector face and chamber walls. The Finite Difference Navier-Stokes (FDNS) code is a primary computational tool used in the MSFC Computational Fluid Dynamics Branch. The branch has dedicated a significant amount of resources to development of this code for prediction of both liquid and solid fuel rocket performance. The FDNS code is currently being upgraded to include the capability to model liquid/gas multi-phase flows for fuel injection simulation. An important aspect of this effort is benchmarking the code capabilities to predict existing experimental injection data. The objective of this MSFC/ASEE Summer Faculty Fellowship term was to evaluate the capabilities of the modified FDNS code to predict flow fields with liquid injection. Comparisons were made between code predictions and existing experimental data. A significant portion of the effort included a search for appropriate validation data. Also, code simulation deficiencies were identified.

Landrum, D. Brian↗

Evolution of magnetic flux ropes associated with flux transfer events and interplanetary magnetic clouds

Spacecraft observations suggest that flux transfer events and interplanetary magnetic clouds may be associated with magnetic flux ropes which are magnetic flux tubes containing helical magnetic field lines. In the magnetic flux ropes, the azimuthal magnetic field is superposed on the axial field. The time evolution of a localized magnetic flux rope is studied. A two-dimensional compressible MHD simulation code with a cylindrical symmetry is developed to study the wave modes associated with the evolution of flux ropes. It is found that in the initial phase both the fast magnetosonic wave and the Alfven wave are developed in the flux rope. After this initial phase, the Alfven wave becomes the dominant wave mode for the evolution of the magnetic flux rope and the radial expansion velocity of the flux rope is found to be negligible. Numerical results further show that even for a large initial azimuthal component of the magnetic field, the propagation velocity along the axial direction of the flux rope remains the Alfven velocity. It is also found that the localized magnetic flux rope tends to evolve into two separate magnetic ropes propagating in opposite directions. The simulation results are used to study the evolution of magnetic flux ropes associated with flux transfer events observed at the earth's dayside magnetopause and magnetic clouds in the interplanetary space.

Wei, C. Q.↗

Numerical simulation of cloud and precipitation structure during GALE IOP-2

A regional scale model, LAMPS (Limited Area Mesoscale Prediction System), is used to investigate cloud and precipitation structure that accompanied a short wave system during a portion of GALE IOP-2. A comparison of satellite imagery and model fields indicates that much of the large mesoscale organization of condensation has been captured by the simulation. In addition to reproducing a realistic phasing of two baroclinic zones associated with a split cold front, a reasonable simulation of the gross mesoscale cloud distribution has been achieved.

Robertson, F. R.↗