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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1967

An alternative to Monte Carlo.

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

PROBABILITY THEORY↗
NASA NTRS1994

Direct simulation Monte Carlo and Navier-Stokes simulations of blunt body wake flows

Numerical results obtained with direct simulation Monte Carlo and Navier-Stokes methods are presented for a Mach-20 nitrogen flow about a 70-deg blunted cone. The flow conditions simulated are those that can be obtained in existing low-density hypersonic wind tunnels. Three sets of flow conditions are considered with freestream Knudsen numbers ranging from 0.03 to 0.001. The focus is on the wake structure: how the wake structure changes as a function of rare faction, what the afterbody levels of heating are, and to what limits the continuum models are realistic as rarefunction in the wake is progressively increased. Calculations are made with and without an afterbody sting. Results for the afterbody sting are emphasized in anticipation of an experimental study for the current flow conditions and model configuration. The Navier-Stokes calculations were made with and without slip boundary conditions. Comparisons of the results obtained with the two simulation methodologies are made for both flowfield structure and surface quantities.

WAKE STRUCTURE↗
NASA NTRS2002

Monte Carlo transport model comparison with 1A GeV accelerated iron experiment: heavy-ion shielding evaluation of NASA space flight-crew foodstuff

Deep-space manned flight as a reality depends on a viable solution to the radiation problem. Both acute and chronic radiation health threats are known to exist, with solar particle events as an example of the former and galactic cosmic rays (GCR) of the latter. In this experiment Iron ions of 1A GeV are used to simulate GCR and to determine the secondary radiation field created as the GCR-like particles interact with a thick target. A NASA prepared food pantry locker was subjected to the iron beam and the secondary fluence recorded. A modified version of the Monte Carlo heavy ion transport code developed by Zeitlin at LBNL is compared with experimental fluence. The foodstuff is modeled as mixed nuts as defined by the 71st edition of the Chemical Rubber Company (CRC) Handbook of Physics and Chemistry. The results indicate a good agreement between the experimental data and the model. The agreement between model and experiment is determined using a linear fit to ordered pairs of data. The intercept is forced to zero. The slope fit is 0.825 and the R2 value is 0.429 over the resolved fluence region. The removal of an outlier, Z=14, gives values of 0.888 and 0.705 for slope and R2 respectively. c2002 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

NASA Discipline Radiation Health↗
NASA NTRS2001

Monte Carlo predictions of DNA fragment-size distributions for large sizes after HZE particle irradiation

DSBs (double-strand breaks) produced by densely ionizing space radiation are not located randomly in the genome: recent data indicate DSB clustering along chromosomes. DSB clustering at large scales, from >100 Mbp down to approximately 2 kbp, is modeled using a Monte-Carlo algorithm. A random-walk model of chromatin is combined with a track model, that predicts the radial distribution of energy from an ion, and the RLC (randomly-located-clusters) formalism, in software called DNAbreak. This model generalizes the random-breakage model, whose broken-stick fragment-size distribution is applicable to low-LET radiation. DSB induction due to track interaction with the DNA volume depends on the radiation quality parameter Q. This dose-independent parameter depends only weakly on LET. Multi-track, high-dose effects depend on the cluster intensity parameter lambda, proportional to fluence as defined by the RLC formalism. After lambda is determined by a numerical experiment, the model reduces to one adjustable parameter Q. The best numerical fits to the experimental data, determining Q, are obtained. The knowledge of lambda and Q allows us to give biophysically based extrapolations of high-dose DNA fragment-size data to low doses or to high LETs.

NASA Center JSC↗
NASA NTRS1999

Monte Carlo mixture model of lifetime cancer incidence risk from radiation exposure on shuttle and international space station

Estimating uncertainty in lifetime cancer risk for human exposure to space radiation is a unique challenge. Conventional risk assessment with low-linear-energy-transfer (LET)-based risk from Japanese atomic bomb survivor studies may be inappropriate for relativistic protons and nuclei in space due to track structure effects. This paper develops a Monte Carlo mixture model (MCMM) for transferring additive, National Institutes of Health multiplicative, and multiplicative excess cancer incidence risks based on Japanese atomic bomb survivor data to determine excess incidence risk for various US astronaut exposure profiles. The MCMM serves as an anchor point for future risk projection methods involving biophysical models of DNA damage from space radiation. Lifetime incidence risks of radiation-induced cancer for the MCMM based on low-LET Japanese data for nonleukemia (all cancers except leukemia) were 2.77 (90% confidence limit, 0.75-11.34) for males exposed to 1 Sv at age 45 and 2.20 (90% confidence limit, 0.59-10.12) for males exposed at age 55. For females, mixture model risks for nonleukemia exposed separately to 1 Sv at ages of 45 and 55 were 2.98 (90% confidence limit, 0.90-11.70) and 2.44 (90% confidence limit, 0.70-10.30), respectively. Risks for high-LET 200 MeV protons (LET=0.45 keV/micrometer), 1 MeV alpha-particles (LET=100 keV/micrometer), and 600 MeV iron particles (LET=180 keV/micrometer) were scored on a per particle basis by determining the particle fluence required for an average of one particle per cell nucleus of area 100 micrometer(2). Lifetime risk per proton was 2.68x10(-2)% (90% confidence limit, 0.79x10(-3)%-0. 514x10(-2)%). For alpha-particles, lifetime risk was 14.2% (90% confidence limit, 2.5%-31.2%). Conversely, lifetime risk per iron particle was 23.7% (90% confidence limit, 4.5%-53.0%). Uncertainty in the DDREF for high-LET particles may be less than that for low-LET radiation because typically there is very little dose-rate dependence. Probability density functions for high-LET radiation quality and dose-rate may be preferable to conventional risk assessment approaches. Nuclear reactions and track structure effects in tissue may not be properly estimated by existing data using in vitro models for estimating RBEs. The method used here is being extended to estimate uncertainty in spacecraft shielding effectiveness in various space radiation environments.

NASA Center LaRC↗
NASA NTRS2005

Influence of a fat layer on the near infrared spectra of human muscle: quantitative analysis based on two-layered Monte Carlo simulations and phantom experiments

The influence of fat thickness on the diffuse reflectance spectra of muscle in the near infrared (NIR) region is studied by Monte Carlo simulations of a two-layer structure and with phantom experiments. A polynomial relationship was established between the fat thickness and the detected diffuse reflectance. The influence of a range of optical coefficients (absorption and reduced scattering) for fat and muscle over the known range of human physiological values was also investigated. Subject-to-subject variation in the fat optical coefficients and thickness can be ignored if the fat thickness is less than 5 mm. A method was proposed to correct the fat thickness influence. c2005 Optical Society of America.

NASA Discipline Life Sciences Technologies↗
NASA NTRS2008

Evaluation of Lightning Incidence to Elements of a Complex Structure: A Monte Carlo Approach

There are complex structures for which the installation and positioning of the lightning protection system (LPS) cannot be done using the lightning protection standard guidelines. As a result, there are some "unprotected" or "exposed" areas. In an effort to quantify the lightning threat to these areas, a Monte Carlo statistical tool has been developed. This statistical tool uses two random number generators: a uniform distribution to generate origins of downward propagating leaders and a lognormal distribution to generate returns stroke peak currents. Downward leaders propagate vertically downward and their striking distances are defined by the polarity and peak current. Following the electrogeometrical concept, we assume that the leader attaches to the closest object within its striking distance. The statistical analysis is run for 10,000 years with an assumed ground flash density and peak current distributions, and the output of the program is the probability of direct attachment to objects of interest with its corresponding peak current distribution.

Mata, Carlos T.↗