2006
DOI: 10.2172/883456
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Milagro Version 2 An Implicit Monte Carlo Code for Thermal Radiative Transfer: Capabilities, Development, and Usage

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Cited by 23 publications
(15 citation statements)
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“…We simulated these test problems using the Milagro IMC code [20] with a time-step size of Dt = 0.01 ns and 1 million particles per time step. To represent the frequency dependence of the opacity, we employed 30 frequency groups logarithmically spaced between 0.1 eV and 100 keV and the average value of Eq.…”
Section: Numerical Resultsmentioning
confidence: 99%
“…We simulated these test problems using the Milagro IMC code [20] with a time-step size of Dt = 0.01 ns and 1 million particles per time step. To represent the frequency dependence of the opacity, we employed 30 frequency groups logarithmically spaced between 0.1 eV and 100 keV and the average value of Eq.…”
Section: Numerical Resultsmentioning
confidence: 99%
“…All of the SAAI calculations were performed using the solution technique described in the previous section. An Implicit Monte-Carlo (IMC) code was used to provide solutions for comparison with the SAAI solutions [23,24].…”
Section: Computational Resultsmentioning
confidence: 99%
“…8, where we see a 2 to 4 increase in the material temperature FOM and a 2 to 4 decrease in the radiation temperature FOM. In the IMC simulation for both methods, the particles undergo implicit absorption between effective scatters [17]. The radiation temperature derives from a path-length estimator of the radiation energy and the material temperature derives from an inverse heat capacity-weighted energy deposition, which derives from a path-length estimator of the particles undergoing implicit absorption.…”
Section: Figure Of Merit For Adaptive Methodsmentioning
confidence: 99%