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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Low cloud investigations for project FIRE: Island studies of cloud properties, surface radiation, and boundary layer dynamics. A simulation of the reflectivity over a stratocumulus cloud deck by the Monte Carlo method

The radiation field over a broken stratocumulus cloud deck is simulated by the Monte Carlo method. We conducted four experiments to investigate the main factor for the observed shortwave reflectively over the FIRE flight 2 leg 5, in which reflectivity decreases almost linearly from the cloud center to cloud edge while the cloud top height and the brightness temperature remain almost constant through out the clouds. From our results, the geometry effect, however, did not contribute significantly to what has been observed. We found that the variation of the volume extinction coefficient as a function of its relative position in the cloud affects the reflectivity efficiently. Additional check of the brightness temperature of each experiment also confirms this conclusion. The cloud microphysical data showed some interesting features. We found that the cloud droplet spectrum is nearly log-normal distributed when the clouds were solid. However, whether the shift of cloud droplet spectrum toward the larger end is not certain. The decrease of number density from cloud center to cloud edges seems to have more significant effects on the optical properties.

Ackerman, Thomas P.↗
NASA NTRS2014

James Webb Space Telescope Initial Mid-Course Correction Monte Carlo Implementation using Task Parallelism

The James Webb Space Telescope will be launched into a highly elliptical orbit that does not possess sufficient energy to achieve a proper Sun-Earth/Moon L2 libration point orbit. Three mid-course correction (MCC) maneuvers are planned to rectify the energy deficit: MCC-1a, MCC-1b, and MCC-2. To validate the propellant budget and trajectory design methods, a set of Monte Carlo analyses that incorporate MCC maneuver modeling and execution are employed. The first analysis focuses on the effects of launch vehicle injection errors on the magnitude of MCC-1a. The second on the spread of potential V based on the performance of the propulsion system as applied to all three MCC maneuvers. The final highlights the slight, but notable, contribution of the attitude thrusters during each MCC maneuver. Given the possible variations in these three scenarios, the trajectory design methods are determined to be robust to errors in the modeling of the flight system.

James Webb Space Telescope↗
NASA NTRS2014

James Webb Space Telescope Initial Mid-Course Correction Monte Carlo Implementation using Task Parallelism

The James Webb Space Telescope will be launched into a highly elliptical orbit that does not possess sufficient energy to achieve a proper Sun-Earth L2 libration point orbit. Three mid-course correction (MCC) maneuvers are planned to rectify the energy deficit: MCC-1a, MCC-1b, and MCC-2. To validate the propellant budget and trajectory design methods, a set of Monte Carlo analyses that incorporate MCC maneuver modeling and execution are employed. The first analysis focuses on the effects of launch vehicle injection errors on the magnitude of MCC-1a. The second on the spread of potential V based on the performance of the propulsion system as applied to all three MCC maneuvers. The final highlights the slight, but notable, contribution of the attitude thrusters during each MCC maneuver. Given the possible variations in these three scenarios, the trajectory design methods are determined to be robust to errors in the modeling of the flight system.

Libration Point Orbit↗
DOE OSTI2021

Learning the ground state of a non-stoquastic quantum Hamiltonian in a rugged neural network landscape

Strongly interacting quantum systems described by non-stoquastic Hamiltonians exhibit rich low-temperature physics. Yet, their study poses a formidable challenge, even for state-of-the-art numerical techniques. Here, we investigate systematically the performance of a class of universal variational wave-functions based on artificial neural networks, by considering the frustrated spin- 1/2 1 / 2 J_1-J_2 J 1 − J 2 Heisenberg model on the square lattice. Focusing on neural network architectures without physics-informed input, we argue in favor of using an ansatz consisting of two decoupled real-valued networks, one for the amplitude and the other for the phase of the variational wavefunction. By introducing concrete mitigation strategies against inherent numerical instabilities in the stochastic reconfiguration algorithm we obtain a variational energy comparable to that reported recently with neural networks that incorporate knowledge about the physical system. Through a detailed analysis of the individual components of the algorithm, we conclude that the rugged nature of the energy landscape constitutes the major obstacle in finding a satisfactory approximation to the ground state wavefunction, and prevents learning the correct sign structure. In particular, we show that in the present setup the neural network expressivity and Monte Carlo sampling are not primary limiting factors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Ca-isotopes as a robust tracer of magmatic differentiation

The large mass difference (~10%) between the two most abundant isotopes of calcium, 40 Ca and 44 Ca, gives Ca great potential in tracking mass-dependent fractionation during magmatic processes. Resolvable Ca-isotope fractionation during fractional crystallization of magma, particularly by feldspar in evolved melts, has been theoretically inferred but not robustly tested in nature. To further explore the effects of magmatic differentiation on Ca-isotope systematics, we studied the late-Permian alkaline igneous suite of the Øyangen Caldera, Oslo Rift, Norway, consisting of volcanic and intrusive units ranging from basanitic to rhyolitic compositions. Major and trace element variations and modeling demonstrate that the main series of samples (N = 21), including basanites, ring-dyke syenites, and central-dome syenites, likely documents a co-genetic and closed-system fractional crystallization sequence. Our data show minimal δ 44/40 Ca variation (< 0.05 ‰) in the intermediate magma and a marked increase in δ 44/40 Ca in the felsic magma of the Øyangen Caldera (from 0.62 ± 0.02 ‰ to 1.15 ± 0.03 ‰ relative to Ca standard, SRM915a). The systematic increase is best explained by equilibrium isotopic fractionation dominated by alkali feldspar in the fractionating mineral assemblage. This is further supported by strong correlations between δ 44/40 Ca, CaO, and Eu/Eu* in the main-series samples. Implementing a Monte Carlo approach, isotopic modeling of the liquid line of descent using Rayleigh fractionation is highly consistent with the observed Ca-isotope evolution. For the first time, we confirm prominent Ca stable isotope fractionation in felsic-stage differentiation of alkaline magma and constrain the isotope fractionation factors of plagioclase and K-feldspar. Integrated with extant estimations on mineral fractionation factors from the literature, our results suggest increasing fractionation effects of rock-forming minerals with decreasing Ca content. Finally, the affirmation of significant Ca-isotope fractionation in alkaline magma by feldspar empowers the application of Ca as a versatile tracer of crustal evolution, allowing further tests in other magmatic conditions across various planetary objects.

58 GEOSCIENCES↗
DOE OSTI2020

Sensor Distortion Effects in Photon Monte Carlo Simulations

We present a detailed method to simulating sensor distortions using a photon and electron Monte Carlo method. We use three-dimensional electrostatic simulations to parameterize the perturbed electric field profile for nonideal sensor details. We follow the conversion of simulated photons, and the subsequent response of the converted electrons to the electric field pattern. These nonideal sensor details can be implemented efficiently in a Monte Carlo approach. We demonstrate that the nonideal sensor distortions have a variety of observable consequence including the modification of the astrometric pattern; the distortion of the electron diffusion size and shape; and the distortion of flats. We show analytic validation of the diffusion physics, reproduce two kinds of edge distortion, and show qualitative validation of field-free regions, lithography errors, and fringing. We also demonstrate that there are two related effects of doping variation having different observable consequences. We show that field distortions from accumulated electrons lead to intensity-dependent point-spread functions and the sublinear variance in flats. The method is implemented in the Photon Simulator and the code is publicly available.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2003

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been proposed by the Society of Automotive Engineers (SAE). The test cases compare different probabilistic methods within NESSUS because it is important that a user can have confidence that estimates of stochastic parameters of a response will be within an acceptable error limit. For each response, the mean, standard deviation, and 0.99 percentile, are repeatedly estimated which allows confidence statements to be made for each parameter estimated, and for each method. Thus, the ability of several stochastic methods to efficiently and accurately estimate density parameters is compared using four valid test cases. While all of the reliability methods used performed quite well, for the new LHS module within NESSUS it was found that it had a lower estimation error than MC when they were used to estimate the mean, standard deviation, and 0.99 percentile of the four different stochastic responses. Also, LHS required a smaller amount of calculations to obtain low error answers with a high amount of confidence than MC. It can therefore be stated that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ and the newest LHS module is a valuable new enhancement of the program.

Chamis, Chrisos C.↗
DOE OSTI2025

Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work, we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction, a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms two other approaches in estimation efficiency: one that utilizes periodic spline quantile regression and another that generates data from the commonly used Abe-Ley distribution for cylindrical data. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios. Our method indicates significant changes in the variation of wind speed with respect to some directions.

17 WIND ENERGY↗
NASA NTRS1993

MeV Gamma Ray Detection Algorithms for Stacked Silicon Detectors

By making use of the signature of a gamma ray event as it appears in N = 5 to 20 lithium-drifted silicon detectors and applying smart selection algorithms, gamma rays in the energy range of 1 to 8 MeV can be detected with good efficiency and selectivity. Examples of the types of algorithms used for different energy regions include the simple sum mode, the sum-coincidence mode used in segmented detectors, unique variations on sum-coincidence for an N-dimensional vector event, and a new and extremely useful mode for double escape peak spectroscopy at pair-production energies. The latter algorithm yields a spectrum similar to that of the pair spectrometer, but without the need of the dual external segments for double escape coincidence, and without the large loss in efficiency of double escape events. Background events due to Compton scattering are largely suppressed. Monte Carlo calculations were used to model the gamma ray interactions in the silicon, in order to enable testing of a wide array of different algorithms on the event N-vectors for a large-N stack.

McMurray, Robert E. Jr.↗
DOE OSTI2026

Studies of Localization Effects on Transverse Kinematic Imbalance in the GENIE Generator

The forthcoming Deep Underground Neutrino Experiment (DUNE) requires precise modeling of neutrino--nucleus interactions to achieve its neutrino-oscillation measurement goals. GENIE, the Monte Carlo event generator used by DUNE and other Fermilab-based experiments as a central value model for neutrino-nucleus cross sections, exhibits known discrepancies in comparison to MicroBooNE cross section data, especially when considering neutrino scattering events' transverse kinematic imbalance (TKI). For quasielastic-like measurements, the data show a larger transverse missing momentum tail while maintaining a peak similar to that predicted by the baseline GENIE model. Previous attempts at a solution include variations of final-state interaction (FSI) strengths, incorrectly decreasing both the peak and tail, thus leaving the discrepancy unresolved. This work investigates whether inconsistencies between local and global treatments of intranuclear physics contribute to the observed mismodeling. In this work, GENIE FSI routines have been modified to directly utilize intranuclear particle positions, thereby introducing a newly localized momentum treatment in correlation with the nominal density in both the hA and hN intranuclear cascade models for their 2018 and 2025 variants. Meson-exchange-current (MEC) localization was also tested for the hN 2018 model. Comparisons of the intranuclear nucleons' ("scattering center") momentum and its radial dependence validate the localization implementation. However, while such consistent localization produces modest changes in the proton momentum spectrum at low-to-medium momenta, only small changes are observed in the TKI distributions. These changes are insufficient to account for the discrepancy with MicroBooNE data. Although a localized treatment improves the internal consistency of the GENIE model, the origin of the TKI discrepancy remains unresolved by such a solution.

Bulla, Braden [Ctr. Coll., Danville; Fermilab]↗
NASA NTRS1972

Degree and direction of polarization of multiple scattered light. II - Earth's atmosphere with aerosols.

The radiance, polarization, and direction of polarization of the radiation reflected and transmitted through the atmosphere are calculated by a Monte Carlo method on the basis of a realistic model of the atmosphere. The calculated polarization is shown to depend on the aerosol amount and to have normally a value intermediate between that for pure Rayleigh and pure aerosol scattering. The polarization for multiple scattered photons is usually less than the value calculated for single scattering, but may be larger in low-polarization regions near other regions of high polarization. The direction of polarization shows little variation with either the aerosol amount or the value of the surface albedo.

Plass, G. N.↗
NASA NTRS1989

Scales of North Atlantic wind stress curl determined from the comprehensive ocean-atmosphere data set

Nineteen years of wind data over the North Atlantic are used to calculate a field of wind stress curl. An empirical orthogonal function (EOF) analysis is performed on this field, resulting in spatial patterns of wind stress curl and associated time series. A Monte Carlo technique is used to establish the statistical significance of each spatial pattern, and the associated time series are spectrally analyzed. The first four statistically significant EOF modes represent more than 50 percent of the curl variance, and the spatial patterns of curl associated with these modes exhibit the major elements of North Atlantic climatology. Most of the time series spectral variance is contained in annual and semiannual frequencies. The features observed include the individual annual variation of the subtropical high and the subpolar low, the annual oscillation of intensity between pressure centers, the influence of localized strong SST gradients and associated cyclogenesis regions, and the constant nature of the trades.

Ehret, Laura L.↗
NASA NTRS1974

Reflection of a thick planar shock wave from a coplanar surface

The reflection of a thick shock wave from an adsorbing surface has been studied for argon and neon test gases using the direct simulation Monte Carlo method and laboratory shock-tube experiments. In the simulation, collisions between gas atoms were calculated with a point-center repulsive intermolecular potential, and collisions between gas atoms and the surface were described by a simple two-parameter model which includes the effects of adsorption and thermal accommodation. Experimental data included normal stress and temperature time histories on the surface of a shock-tube and wall. These data and published data of density variations near the end wall were compared with simulation results to assess the influence of adsorption and accommodation on the flowfield and the surface and also to infer optimum values for the surface-interaction model parameters. Good quantitative agreement between simulation and laboratory data was found with this simple surface-interaction model.

Deiwert, G. S.↗
NASA NTRS1984

Regularized Monte-Carlo calculations of the optical polarization induced by scattering in X-ray binaries

The results of regularized Monte Carlo calculations of the optical polarization Stokes parameters expected as a result of scattering from gas streams or accretion wakes in close binary systems whose properties resemble those of X-ray binaries are presented. The physical processes occurring in the system are represented by a model which follows a selected sample of individual photon paths from each emitting element on the surface of the primary to the photon's detection at earth. The result represents the variations in the intensity from each individual emitting element caused by the effects of limb darkening, gravity darkening, and variation in the projected area of the emitting element as seen from the scattering element.

Dolan, J. F.↗
NASA NTRS1991

Three-dimensional rarefied flow simulations for the Aeroassist Flight Experiment vehicle

Hypersonic rarefied flow about the Aeroassist Flight Experiment vehicle has been investigated using a three-dimensional direct simulation Monte Carlo method. Calculations are performed for the transitional flows encountered during the vehicle's atmospheric entry for altitudes of 110 and 100 km with an entry velocity of 9.9 km/s. The simulations are performed using a five-species reacting gas model that account for rotational and vibrational internal energies. The solutions indicate that dissociation is important at altitudes of 110 km and below. Results are presented for surface pressures, convective heating, flowfield structure, and aerodynamic coefficient variations with altitude.

Celenligil, M. Cevdet↗
NASA NTRS2008

Uncertainty and Sensitivity Analyses of a Two-Parameter Impedance Prediction Model

This paper presents comparisons of predicted impedance uncertainty limits derived from Monte-Carlo-type simulations with a Two-Parameter (TP) impedance prediction model and measured impedance uncertainty limits based on multiple tests acquired in NASA Langley test rigs. These predicted and measured impedance uncertainty limits are used to evaluate the effects of simultaneous randomization of each input parameter for the impedance prediction and measurement processes. A sensitivity analysis is then used to further evaluate the TP prediction model by varying its input parameters on an individual basis. The variation imposed on the input parameters is based on measurements conducted with multiple tests in the NASA Langley normal incidence and grazing incidence impedance tubes; thus, the input parameters are assigned uncertainties commensurate with those of the measured data. These same measured data are used with the NASA Langley impedance measurement (eduction) processes to determine the corresponding measured impedance uncertainty limits, such that the predicted and measured impedance uncertainty limits (95% confidence intervals) can be compared. The measured reactance 95% confidence intervals encompass the corresponding predicted reactance confidence intervals over the frequency range of interest. The same is true for the confidence intervals of the measured and predicted resistance at near-resonance frequencies, but the predicted resistance confidence intervals are lower than the measured resistance confidence intervals (no overlap) at frequencies away from resonance. A sensitivity analysis indicates the discharge coefficient uncertainty is the major contributor to uncertainty in the predicted impedances for the perforate-over-honeycomb liner used in this study. This insight regarding the relative importance of each input parameter will be used to guide the design of experiments with test rigs currently being brought on-line at NASA Langley.

Jones, M. G.↗
DOE OSTI2025

Observation of Cosmic-Ray Anisotropy in the Southern Hemisphere with 12 yr of Data Collected by the IceCube Neutrino Observatory

We analyzed the 7.92 × 10 11 cosmic-ray-induced muon events collected by the IceCube Neutrino Observatory from 2011 May 13, when the fully constructed experiment started to take data, to 2023 May 12. This data set provides an up-to-date cosmic-ray arrival direction distribution in the Southern Hemisphere with unprecedented statistical accuracy covering more than a full period length of a solar cycle. Improvements in Monte Carlo event simulation and better handling of year-to-year differences in data processing significantly reduce systematic uncertainties below the level of statistical fluctuations compared to the previously published results. We confirm the observation of a change in the angular structure of the cosmic-ray anisotropy between 10 TeV and 1 PeV, more specifically in the 100–300 TeV energy range. For the first time, we analyzed the angular power spectrum at different energies. The observed variations of the power spectra with energy suggest relatively reduced large-scale features at high energy compared to those of medium and small scales. The large volume of data enhances the statistical significance at higher energies, up to the PeV scale, and smaller angular scales, down to approximately 6° compared to previous findings.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Low-Density Nozzle Flow by the Direct Simulation Monte Carlo and Continuum Methods

Two different approaches, the direct simulation Monte Carlo (DSMC) method based on molecular gasdynamics, and a finite-volume approximation of the Navier-Stokes equations, which are based on continuum gasdynamics, are employed in the analysis of a low-density gas flow in a small converging-diverging nozzle. The fluid experiences various kinds of flow regimes including continuum, slip, transition, and free-molecular. Results from the two numerical methods are compared with Rothe's experimental data, in which density and rotational temperature variations along the centerline and at various locations inside a low-density nozzle were measured by the electron-beam fluorescence technique. The continuum approach showed good agreement with the experimental data as far as density is concerned. The results from the DSMC method showed good agreement with the experimental data, both in the density and the rotational temperature. It is also shown that the simulation parameters, such as the gas/surface interaction model, the energy exchange model between rotational and translational modes, and the viscosity-temperature exponent, have substantial effects on the results of the DSMC method.

Chung, Chang-Hong↗