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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Oversight and Development of a Community Monte Carlo Radiative Transfer Model

Under this grant we have developed a Monte Carlo radiative transfer code that will act as the nucleus for the 13RC Community Monte Carlo Model. All code is written in ANSI-compliant Fortran-95. Many modules define public type and procedures to manipulate them, but do not allow access to the type's internal components. This allows each module to do its own exhaustive error checking up-front, then proceed in a streamlined way. Many modules can read and write the state of their objects to persistent files. The code has been tested on a Macintosh running OS 10.2.4 and the Absoft Fortran compiler, and on Sun UltraSparcs running Solaris 5.8 and Forte V8 compilers. The code exposed bugs in the Intel Fortran Compiler (ifc) on the 13RC Linux host, and we are waiting for a resolution of these bugs before finished the port. the code base is under CVS versions control. The code base consists of the core code (nine modules providing the infrastructure), example integrators, and a suite of utilities and examples.

Source record↗
NASA NTRS2013

Monte Carlo Bayesian Inference on a Statistical Model of Sub-gridcolumn Moisture Variability Using High-resolution Cloud Observations : Sensitivity Tests and Results - Part II

Part I presented a Monte Carlo Bayesian method for constraining a complex statistical model of GCM sub-gridcolumn moisture variability using high-resolution MODIS cloud data, thereby permitting large-scale model parameter estimation and cloud data assimilation. This part performs some basic testing of this new approach, verifying that it does indeed significantly reduce mean and standard deviation biases with respect to the assimilated MODIS cloud optical depth, brightness temperature and cloud top pressure, and that it also improves the simulated rotational-Ramman scattering cloud optical centroid pressure (OCP) against independent (non-assimilated) retrievals from the OMI instrument. Of particular interest, the Monte Carlo method does show skill in the especially difficult case where the background state is clear but cloudy observations exist. In traditional linearized data assimilation methods, a subsaturated background cannot produce clouds via any infinitesimal equilibrium perturbation, but the Monte Carlo approach allows finite jumps into regions of non-zero cloud probability. In the example provided, the method is able to restore marine stratocumulus near the Californian coast where the background state has a clear swath. This paper also examines a number of algorithmic and physical sensitivities of the new method and provides guidance for its cost-effective implementation. One obvious difficulty for the method, and other cloud data assimilation methods as well, is the lack of information content in the cloud observables on cloud vertical structure, beyond cloud top pressure and optical thickness, thus necessitating strong dependence on the background vertical moisture structure. It is found that a simple flow-dependent correlation modification due to Riishojgaard (1998) provides some help in this respect, by better honoring inversion structures in the background state.

Monte Carlo Bayesian inference↗
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 NTRS2015

Instantons in Quantum Annealing: Thermally Assisted Tunneling Vs Quantum Monte Carlo Simulations

Recent numerical result (arXiv:1512.02206) from Google suggested that the D-Wave quantum annealer may have an asymptotic speed-up than simulated annealing, however, the asymptotic advantage disappears when it is compared to quantum Monte Carlo (a classical algorithm despite its name). We show analytically that the asymptotic scaling of quantum tunneling is exactly the same as the escape rate in quantum Monte Carlo for a class of problems. Thus, the Google result might be explained in our framework. We also found that the transition state in quantum Monte Carlo corresponds to the instanton solution in quantum tunneling problems, which is observed in numerical simulations.

Quantum Monte Carlo↗
NASA NTRS1986

Monte Carlo study of a model of diffusion-controlled reactions

The Monte Carlo method is used to perform averages over sink configurations in the present study of diffusion-controlled reactions occurring between solute particles and immobile spherical sinks. In order to determine the average steady state solute concentration profile in a locally perturbed solution for sink volume fractions phi of less than 0.3, the diffusion equation in the monopolar plus dipolar approximation of diffusive couplings between the sinks is solved numerically. The Monte Carlo method is shown to be the most accurate and efficient in the phi = 0.001-0.1 region, where a system of only 25 sinks suffices and the monopolar approximation alone is sufficiently accurate.

Beenakker, C. W. J.↗
NASA NTRS1961

Application of Monte Carlo Technique for Determining Maneuvering Loads from Statistical Information on Airplane Motions

Results of a statistical analysis of horizontal-tail loads on a fighter airplane are presented. The data were obtained from a number of operational training missions with flight at altitudes up to about 50,000 feet and at Mach numbers up to 1.22. The analysis was performed to determine the feasibility of calculating horizontal-tail load from data on the flight conditions and airplane motions. In the analysis the calculated loads are compared with the measured loads for the different types of missions performed. The loads were calculated by two methods: a direct approach and a Monte Carlo technique. The procedures used and some of the problems associated with the data analysis are discussed. frequencies of occurrence of tail loads of given magnitudes are derived from statistical information on the flight quantities. In the direct method, a time history of tail load is calculated from time-history measurements of the flight quantities. The Monte Carlo method could be useful for extending loads information for design of prospective airplanes . For the Monte Carlo method, the The results indicate that the accuracy of loads, regardless of the method used for calculation, is largely dependent on the knowledge of the pertinent airplane aerodynamic characteristics and center-of-gravity location. In addition, reliable Monte Carlo results require an adequate sample of statistical data and a knowledge of the more important statistical dependencies between the various flight conditions and airplane motions.

Hamer, Harold A.↗
NASA NTRS1968

A modified Monte Carlo procedure.

Histogram construction via algebraic Monte Carlo method, determining simultaneous effect of several input statistical variables on output variable

Africano, R. C.↗
NASA NTRS1978

X-ray transfer in binary systems - A Monte Carlo study

Results are presented for Monte Carlo calculations of X-ray light curves for binary systems surrounded by clouds with simple density distributions, chemical compositions, and ionization structures. Occultation of the X radiation by the companion star is taken into account along with Compton scattering and photoionization within the clouds. The models are used to examine the effect of various cloud geometries and ionization structures on the emergent X-ray flux as a function of orbital phase and X-ray energy. The results demonstrate the sensitivity of observed light curves and phase-dependent spectra with respect to the optical depth, geometry, and ionization structure of a surrounding cloud for the cases of a uniform-density cloud with a radius four times the binary orbital separation, a steady-state constant-velocity stellar wind emanating from the companion star, and a spherically symmetric shell or 'cocoon' of the type proposed for Cyg X-3. It is concluded that X-ray binary systems are unlikely to be surrounded by obscuring clouds.

Hertz, P.↗
NASA NTRS1983

Monte Carlo Modeling in Elliptic Flows

A Monte Carlo method capable of predicting scalar (e.g., concentration) probability density functions (pdf's) in nonreacting and reacting elliptic flows was developed. A research combustor specifically designed to provide measurements of concentration and temperature pdf's in nonreacting and reacting flows is emphasized.

Radhakrishnan, K.↗
NASA NTRS1985

Recent advances in Monte Carlo turbulence simulation

The purpose of Monte Carlo turbulence simulation is to add statistically accurate 'bumps' to aerospace vehicle flight simulation. Several recent improvements in the state of the art are reviewed and classified according to various characteristics affecting the realism of the simulation. Areas for future research are made clear by the classification scheme.

Campbell, C. W.↗
NASA NTRS2012

Parametric 3D Atmospheric Reconstruction in Highly Variable Terrain with Recycled Monte Carlo Paths and an Adapted Bayesian Inference Engine

We describe a method for accelerating a 3D Monte Carlo forward radiative transfer model to the point where it can be used in a new kind of Bayesian retrieval framework. The remote sensing challenge is to detect and quantify a chemical effluent of a known absorbing gas produced by an industrial facility in a deep valley. The available data is a single low resolution noisy image of the scene in the near IR at an absorbing wavelength for the gas of interest. The detected sunlight has been multiply reflected by the variable terrain and/or scattered by an aerosol that is assumed partially known and partially unknown. We thus introduce a new class of remote sensing algorithms best described as "multi-pixel" techniques that call necessarily for a 3D radaitive transfer model (but demonstrated here in 2D); they can be added to conventional ones that exploit typically multi- or hyper-spectral data, sometimes with multi-angle capability, with or without information about polarization. The novel Bayesian inference methodology uses adaptively, with efficiency in mind, the fact that a Monte Carlo forward model has a known and controllable uncertainty depending on the number of sun-to-detector paths used.

Monte Carlo↗
NASA NTRS2003

Monte Carlo Methodology Serves Up a Software Success

Widely used for the modeling of gas flows through the computation of the motion and collisions of representative molecules, the Direct Simulation Monte Carlo method has become the gold standard for producing research and engineering predictions in the field of rarefied gas dynamics. Direct Simulation Monte Carlo was first introduced in the early 1960s by Dr. Graeme Bird, a professor at the University of Sydney, Australia. It has since proved to be a valuable tool to the aerospace and defense industries in providing design and operational support data, as well as flight data analysis. In 2002, NASA brought to the forefront a software product that maintains the same basic physics formulation of Dr. Bird's method, but provides effective modeling of complex, three-dimensional, real vehicle simulations and parallel processing capabilities to handle additional computational requirements, especially in areas where computational fluid dynamics (CFD) is not applicable. NASA's Direct Simulation Monte Carlo Analysis Code (DAC) software package is now considered the Agency s premier high-fidelity simulation tool for predicting vehicle aerodynamics and aerothermodynamic environments in rarified, or low-density, gas flows.

Source record↗
NASA NTRS1985

A Monte Carlo reflectance model for soil surfaces with three-dimensional structure

A Monte Carlo soil reflectance model has been developed to study the effect of macroscopic surface irregularities larger than the wavelength of incident flux. The model treats incoherent multiple scattering from Lambertian facets distributed on a periodic surface. Resulting bidirectional reflectance distribution functions are non-Lambertian and compare well with experimental trends reported in the literature. Examples showing the coupling of the Monte Carlo soil model to an adding bidirectional canopy of reflectance model are also given.

Cooper, K. D.↗
NASA NTRS1975

Monte Carlo simulation of astronaut light flash observations on Apollo and Skylab missions

Monte Carlo calculations are performed to study the relation between cosmic ray nuclei and visual flashes observed by astronauts, in space. A satisfactory overall fit to all available data excluding the Skylab observations in the South Atlantic Anomaly (SAA) has been achieved by varying three visual system parameters: effective retinal thickness, minimum projected track length inside retina and minimum energy loss rate. All light flash data from space excluding the SAA observations can be understood fully upon the basis of the primary cosmic ray charge and energy spectra together with the fitted values of the three visual system parameters. Monte Carlo simulations of the SAA observations suggest the existence of a previously unobserved multiply-charged component of the inner radiation belt.

Osborne, W. Z.↗