Search NASA⌕ Search

SEARCH · Search NASA

Results for “reverse Monte Carlo”

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.

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

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Development and application of a reverse Monte Carlo radiative transfer code for rocket plume base heating

A reverse Monte Carlo radiative transfer code to predict rocket plume base heating is presented. In this technique rays representing the radiation propagation are traced backwards in time from the receiving surface to the point of emission in the plume. This increases the computational efficiency relative to the forward Monte Carlo technique when calculating the radiation reaching a specific point, as only the rays that strike the receiving point are considered.

Everson, John↗
NASA NTRS1993

Rocket plume base heating methodology

A review of radiative transport calculation methods for base heating is presented followed by a description of the current methodology for the Space Shuttle plume radiation predictions and improvements for the Advanced Solid Rocket Booster (ASRB). The calculation methods include empirical methods, the SIRRM code and the forward and reverse Monte Carlo methods. Current plume radiation methods include those used for the Space Shuttle Main Engines and the Solid Rocket Booster (SRB). Methods being developed for the ASRB include changes in plume property prediction methodology and application of the reverse Monte Carlo method in predicting plume radiation models. Results of the prediction methods are compared with experimental measurements on the current SRB and on 1/6-scale motors using both SRB and ASRB propellants. Examples are also presented demonstrating the statistical results available with the reverse Monte Carlo method.

Reardon, John E.↗
NASA NTRS1994

Physical Retrievals of Over-Ocean Rain Rate from Multichannel Microwave Imagery: Theoretical Characteristics of Normalized Polarization and Scattering Indices - Part 1

Microwave rain rate retrieval algorithms have most often been formulated in terms of the raw brightness temperatures observed by one or more channels of a satellite radiometer. Taken individually, single-channel brightness temperatures generally represent a near-arbitrary combination of positive contributions due to liquid water emission and negative contributions due to scattering by ice and/or visibility of the radiometrically cold ocean surface. Unfortunately, for a given rain rate, emission by liquid water below the freezing level and scattering by ice particles above the freezing level are rather loosely coupled in both a physical and statistical sense. Furthermore, microwave brightness temperatures may vary significantly (approx. 30-70 K) in response to geophysical parameters other than liquid water and precipitation. Because of these complications, physical algorithms which attempt to directly invert observed brightness temperatures have typically relied on the iterative adjustment of detailed micro-physical profiles or cloud models, guided by explicit forward microwave radiative transfer calculations. In support of an effort to develop a significantly simpler and more efficient inversion-type rain rate algorithm, the physical information content of two linear transformations of single-frequency, dual-polarization brightness temperatures is studied: the normalized polarization difference P of Petty and Katsaros (1990, 1992), which is intended as a measure of footprint-averaged rain cloud transmittance for a given frequency; and a scattering index S (similar to the polarization corrected temperature of Spencer et al.,1989) which is sensitive almost exclusively to ice. A reverse Monte Carlo radiative transfer model is used to elucidate the qualitative response of these physically distinct single-frequency indices to idealized 3-dimensional rain clouds and to demonstrate their advantages over raw brightness temperatures both as stand-alone indices of precipitation activity and as primary variables in physical, multichannel rain rate retrieval schemes. As a byproduct of the present analysis, it is shown that conventional plane-parallel analyses of the well-known foot-print-filling problem for emission-based algorithms may in some cases give seriously misleading results.

Petty, G. W.↗
NASA NTRS2008

Role of Hf on Phase Formation in Ti45Zr(38-x)Hf(x)Ni17 Liquids and Solids

Hafnium and zirconium are very similar, with almost identical sizes and chemical bonding characteristics. However, they behave differently when alloyed with Ti and Ni. A sharp phase formation boundary near 18-21 at.% Hf is observed in rapidly-quenched and as-cast Ti45Zr38-xHfxNi17 alloys. Rapidly-quenched samples that contain less than 18 at.% Hf form the icosahedral quasicrystal phase, whiles samples containing more than 21 at.% form the 3/2 rational approximant phase. In cast alloys, a C14 structure is observed for alloys with Hf lower than the boundary concentration, while a large-cell (11.93 ) FCC Ti2Ni-type structure is found in alloys with Hf concentrations above the boundary. To better understand the role of Hf on phase formation, the structural evolution with supercooling and the solidification behavior of liquid Ti45Zr38-xHfxNi17 alloys (x=0, 12, 18, 21, 38) were studied using the Beamline Electrostatic Levitation (BESL) technique using 125keV x-rays on the 6ID-D beamline at the Advanced Photon Source, Argonne National Laboratory. For all liquids primary crystallization was to a BCC solid solution phase; interestly, an increase in Hf concentration leads to a decrease in the BCC lattice parameter in spite of the chemical similarity between Zr and Hf. A Reitveld analysis confirmed that as in the cast alloys, the secondary phase that formed was the C14 below the phase formation boundary and a Ti2Ni-type structure at higher Hf concentrations. Both the liquidus temperature and the reduced undercooling change sharply on traversing the phase formation boundary concentration, suggesting a change in the liquid structure. Structural information from a Honeycutt-Anderson index analysis of reverse Monte Carlo fits to the S(q) liquid data will be presented to address this issue.

Wessels, V.↗
NASA NTRS2011

Ares I-X Ascent Base Environments

Plume induced base heating environments were measured during the flight of the NASA Constellation Ares I-X developmental launch vehicle, successfully flown on October 28, 2009. The Ares IX first stage is a four segment Space Shuttle derived booster with base consisting of a flared aft skirt, deceleration and tumble motors, and a thermal curtain surrounding the first stage 7.2 area ratio nozzle. Developmental Flight Instrumentation (DFI) consisted of radiometers, calorimeters, pressure transducers and gas temperature probes installed on the aft skirt and nozzle to measure the base environments. In addition, thermocouples were also installed between the layers of the flexible thermal curtain to provide insight into the curtain response to the base environments and to assist in understanding curtain failure during reentry. Plume radiation environment predictions were generated by the Reverse Monte Carlo (RMC) code and the convective base heating predictions utilized heritage MSFC empirical methods. These predictions were compared to the DFI data and results from the flight videography. Radiation predictions agreed with the flight measured data early in flight but gauge failures prevented high altitude comparisons. The convective environment comparisons demonstrated the need to improve the prediction methodology; particularly for low altitude, local plume recirculation. The convective comparisons showed relatively good agreement at altitudes greater than 50,000 feet.

Mobley, B. L.↗
NASA NTRS1985

Monte Carlo study of reversible growth of clusters on a surface

The effect of binding energy on the growth of clusters on a two-dimensional square lattice was studied by a means of a Monte Carlo simulation. The results indicate that for binding energies higher than 0.5kT, clusters grow relative to the initial random distribution, while for binding energies lower than 0.5 kT, clusters decompose. It was also found that at low binding energies the equilibrium percentage of atoms that are bound in clusters is linearly dependent on the binding energy. The cluster density behaved in a similar manner. This similarity reflects the fact that at low binding energies the growth proceeds mainly by the formation of new clusters rather than by an increase in the size of existing ones.

Salik, J.↗
NASA NTRS2011

Unsupervised Detection of Planetary Craters by a Marked Point Process

With the launch of several planetary missions in the last decade, a large amount of planetary images is being acquired. Preferably, automatic and robust processing techniques need to be used for data analysis because of the huge amount of the acquired data. Here, the aim is to achieve a robust and general methodology for crater detection. A novel technique based on a marked point process is proposed. First, the contours in the image are extracted. The object boundaries are modeled as a configuration of an unknown number of random ellipses, i.e., the contour image is considered as a realization of a marked point process. Then, an energy function is defined, containing both an a priori energy and a likelihood term. The global minimum of this function is estimated by using reversible jump Monte-Carlo Markov chain dynamics and a simulated annealing scheme. The main idea behind marked point processes is to model objects within a stochastic framework: Marked point processes represent a very promising current approach in the stochastic image modeling and provide a powerful and methodologically rigorous framework to efficiently map and detect objects and structures in an image with an excellent robustness to noise. The proposed method for crater detection has several feasible applications. One such application area is image registration by matching the extracted features.

Troglio, G.↗
NASA NTRS1991

ASRM radiation and flowfield prediction status

Existing and proposed methods for the prediction of plume radiation are discussed in terms of their application to the NASA Advanced Solid Rocket Motor (ASRM) and Space Shuttle Main Engine (SSME) projects. Extrapolations of the Solid Rocket Motor (SRM) are discussed with respect to preliminary predictions of the primary and secondary radiation environments. The methodology for radiation and initial plume property predictions are set forth, including a new code for scattering media and independent secondary source models based on flight data. The Monte Carlo code employs a reverse-evaluation approach which traces rays back to their point of absorption in the plume. The SRM sea-level plume model is modified to account for the increased radiation in the ASRM plume due to the ASRM's propellant chemistry. The ASRM cycle-1 environment predictions are shown to identify a potential reason for the shutdown spike identified with pre-SRM staging.

Reardon, J. E.↗
NASA NTRS1987

Finite element methods in probabilistic mechanics

Probabilistic methods, synthesizing the power of finite element methods with second-order perturbation techniques, are formulated for linear and nonlinear problems. Random material, geometric properties and loads can be incorporated in these methods, in terms of their fundamental statistics. By construction, these methods are applicable when the scale of randomness is not too large and when the probabilistic density functions have decaying tails. By incorporating certain computational techniques, these methods are shown to be capable of handling large systems with many sources of uncertainties. Applications showing the effects of combined random fields and cyclic loading/stress reversal are studied and compared with Monte Carlo simulation results.

Liu, Wing Kam↗
NASA NTRS2004

Coarse-Grained and Atomistic Modeling of Polyimides

A coarse-grained model for a set of three polyimide isomers is developed. Each polyimide is comprised of BPDA (3,3,4,4' - biphenyltetracarboxylic dianhydride) and one of three APB isomers: 1,3-bis(4-aminophenoxy)benzene, 1,4-bis(4-aminophenoxy)benzene or 1,3-bis(3-aminophenoxy)benzene. The coarse-grained model is constructed as a series of linked vectors following the contour of the polymer backbone. Beads located at the midpoint of each vector define centers for long range interaction energy between monomer subunits. A bulk simulation of each coarse-grained polyimide model is performed with a dynamic Monte Carlo procedure. These coarsegrained models are then reverse-mapped to fully atomistic models. The coarse-grained models show the expected trends in decreasing chain dimensions with increasing meta linkage in the APB section of the repeat unit, although these differences were minor due to the relatively short chains simulated here. Considerable differences are seen among the dynamic Monte Carlo properties of the three polyimide isomers. Decreasing relaxation times are seen with increasing meta linkage in the APB section of the repeat unit.

Clancy, Thomas C.↗
NASA NTRS1990

Electron heating in quasi-perpendicular shocks - A Monte Carlo simulation

To study the problem of electron heating in quasi-perpendicular shocks, under the combined effects of 'reversible' motion, in the shock electric potential and magnetic field, and wave-particle interactions a diffusion equation was derived, in the drift (adiabatic) approximation and it was solved by using a Monte Carlo method. The results show that most of the observations can be explained within this framework. The simulation has also definitively shown that the electron parallel temperature is determined by the dc electromagnetic field and not by any wave particle induced heating. Wave-particle interactions are effective in smoothing out the large gradients in phase space produced by the 'reversible' motion of the electrons, thus producing a 'cooling' of the electrons. Some constraints on the wave-particle interaction process may be obtained from a detailed comparison between the simulation and observations. In particular, it appears that the adiabatic approximation must be violated in order to explain the observed evolution of the perpendicular temperature.

Veltri, Pierluigi↗
NASA NTRS2013

A Green's Function Approach to Simulate DNA Damage by the Indirect Effect

The DNA damage is of fundamental importance in the understanding of the effects of ionizing radiation. DNA is damaged by the direct effect of radiation (e.g. direct ionization) and by indirect effect (e.g. damage by.OH radicals created by the radiolysis of water). Despite years of research, many questions on the DNA damage by ionizing radiation remains. In the recent years, the Green's functions of the diffusion equation (GFDE) have been used extensively in biochemistry [1], notably to simulate biochemical networks in time and space [2]. In our future work on DNA damage, we wish to use an approach based on the GFDE to refine existing models on the indirect effect of ionizing radiation on DNA. To do so, we will use the code RITRACKS [3] developed at the NASA Johnson Space Center to simulate the radiation track structure and calculate the position of radiolytic species after irradiation. We have also recently developed an efficient Monte‐Carlo sampling algorithm for the GFDE of reversible reactions with an intermediate state [4], which can be modified and adapted to simulate DNA damage by free radicals. To do so, we will use the known reaction rate constants between radicals (OH, eaq, H,...) and the DNA bases, sugars and phosphates and use the sampling algorithms to simulate the diffusion of free radicals and chemical reactions with DNA. These techniques should help the understanding of the contribution of the indirect effect in the formation of DNA damage and double‐strand breaks.

Plante, Ianik↗
NASA NTRS2000

An Analysis of Water Line Profiles in Star Formation Regions Observed by SWAS

We present spectral line profiles for the 557 GHz 1(sub 1,0) yields 1(sub 0,1) ground-state rotational transition of ortho-H2(16)O for 18 galactic star formation regions observed by SWAS. 2 Water is unambiguously detected in every source. The line profiles exhibit a wide variety of shapes, including single-peaked spectra and self-reversed profiles. We interpret these profiles using a Monte Carlo code to model the radiative transport. The observed variations in the line profiles can be explained by variations in the relative strengths of the bulk flow and small-scale turbulent motions within the clouds. Bulk flow (infall, outflow) must be present in some cloud cores, and in certain cases this bulk flow dominates the turbulent motions.

Ashby, Matthew L. N.↗
NASA NTRS2008

SEE Rate Estimation: Model Complexity and Data Requirements

Statistical Methods outlined in [Ladbury, TNS20071 can be generalized for Monte Carlo Rate Calculation Methods Two Monte Carlo Approaches: a) Rate based on vendor-supplied (or reverse-engineered) model SEE testing and statistical analysis performed to validate model; b) Rate calculated based on model fit to SEE data Statistical analysis very similar to case for CREME96. Information Theory allows simultaneous consideration of multiple models with different complexities: a) Model with lowest AIC usually has greatest predictive power; b) Model averaging using AIC weights may give better performance if several models have similar good performance; and c) Rates can be bounded for a given confidence level over multiple models, as well as over the parameter space of a model.

Ladbury, Ray↗
NASA NTRS2001

Uncertainty Optimization Applied to the Monte Carlo Analysis of Planetary Entry Trajectories

Recently, strong evidence of liquid water under the surface of Mars and a meteorite that might contain ancient microbes have renewed interest in Mars exploration. With this renewed interest, NASA plans to send spacecraft to Mars approx. every 26 months. These future spacecraft will return higher-resolution images, make precision landings, engage in longer-ranging surface maneuvers, and even return Martian soil and rock samples to Earth. Future robotic missions and any human missions to Mars will require precise entries to ensure safe landings near science objective and pre-employed assets. Potential sources of water and other interesting geographic features are often located near hazards, such as within craters or along canyon walls. In order for more accurate landings to be made, spacecraft entering the Martian atmosphere need to use lift to actively control the entry. This active guidance results in much smaller landing footprints. Planning for these missions will depend heavily on Monte Carlo analysis. Monte Carlo trajectory simulations have been used with a high degree of success in recent planetary exploration missions. These analyses ascertain the impact of off-nominal conditions during a flight and account for uncertainty. Uncertainties generally stem from limitations in manufacturing tolerances, measurement capabilities, analysis accuracies, and environmental unknowns. Thousands of off-nominal trajectories are simulated by randomly dispersing uncertainty variables and collecting statistics on forecast variables. The dependability of Monte Carlo forecasts, however, is limited by the accuracy and completeness of the assumed uncertainties. This is because Monte Carlo analysis is a forward driven problem; beginning with the input uncertainties and proceeding to the forecasts outputs. It lacks a mechanism to affect or alter the uncertainties based on the forecast results. If the results are unacceptable, the current practice is to use an iterative, trial-and-error approach to reconcile discrepancies. Therefore, an improvement to the Monte Carlo analysis is needed that will allow the problem to be worked in reverse. In this way, the largest allowable dispersions that achieve the required mission objectives can be determined quantitatively.

Olds, John↗
NASA NTRS2026

Diffusion Quantum Monte Carlo Calculation of the Austenite and Martensite Phases of NiTi

NiTi is a promising material for smart and active technologies due to its exhibition of the shape memory effect, superelasticity, and biocompatibility. The shape memory effect is tied to the reversible transition between the austenite and martensite phases. A major research direction is to alloy NiTi with Zr, Hf, Pd, Pt, etc., in order to tune the martensitic transition temperature (MTT). Modeling the MTT from first principles is challenging because the lattice dynamics is complicated by anharmonicity and various low-energy structures. Using density functional theory, the energy difference between the austenite and martensite phases of NiTi varies by up to 100 meV/atom depending on the choice of density functional, which is of the same order of the energy difference itself. Consequently, free energy calculations with different functionals can result in estimates of the MTT that vary by several hundred K. Using diffusion quantum Monte Carlo, we calculated the energy difference between the B2 and B19' structures of NiTi to be 70.9 +- 2.5 meV/atom.

Kevin K Ly↗
NASA NTRS2025

Efficient GPU-Accelerated MultiSource Global Fit Pipeline for LISA Data Analysis

The large-scale analysis task of deciphering gravitational-wave signals in the LISA data stream will be difficult, requiring a large amount of computational resources and extensive development of computational methods. Its high dimensionality, multiple model types, and complicated noise profile require a global fit to all parameters and input models simultaneously. In this work, we detail our global fit algorithm, called “Erebor,” designed to accomplish this challenging task. It is capable of analyzing current state-of-the-art datasets and then growing into the future as more pieces of the pipeline are completed and added. We describe our pipeline strategy, the algorithmic setup, and the results from our analysis of the LDC2A Sangria dataset, which contains massive black hole binaries, compact galactic binaries, and a parametrized noise spectrum whose parameters are unknown to the user. The Erebor algorithm includes three unique and very useful contributions: GPU acceleration for enhanced computational efficiency; ensemble Markov Chain Monte Carlo (MCMC) sampling with multiple MCMC walkers per temperature for better mixing and parallelized sample creation; and special online updates to reversible-jump (or transdimensional) sampling distributions to ensure sampler mixing and accurate initial estimates for detectable sources in the data.We recover posterior distributions for all 15 (6) of the injected massive black hole binaries (MBHB) in the LDC2A training (hidden) dataset. We catalog ∼12000 galactic binaries (∼8000 as high confidence detections) for both the training and hidden datasets. All of the sources and their posterior distributions are provided in publicly available catalogs.

LISA↗