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In many direct simulation Monte Carlo (DSMC) simulations, the majority of computation time is consumed after the flowfield reaches a steady state. This situation occurs when the desired output quantities are small compared to the background fluctuations. For example, gas flows in many microelectromechanical systems (MEMS) have mean speeds more than two orders of magnitude smaller than the thermal speeds of the molecules themselves. The current solution to this problem is to collect sufficient samples to achieve the desired resolution. This can be an arduous process because the error is inversely proportional to the square root of the number of samples so we must, for example, quadruple the samples to cut the error in half. This work is intended to improve this situation by employing more advanced techniques, from fields other than solely statistics, for determining the output quantities. Our strategy centers on exploiting information neglected by current techniques, which collect moments in each cell without regard to one another, values in neighboring cells, nor their evolution in time. Unlike many previous acceleration techniques that modify the method itself, the techniques examined in this work strictly post-process so they may be applied to any DSMC code without affecting its fidelity or generality. Many potential methods are drawn from successful applications in a diverse range of areas, from ultrasound imaging to financial market analysis. The most promising methods exploit relationships between variables in space, which always exist in DSMC due to the absence of shocks. Disparate techniques were shown to produce similar error reductions, suggesting that the results shown in this report may be typical of what is possible using these methods. Sample count reduction factors of approximately three to five were found to be typical, although factors exceeding ten were shown on some variables under some techniques.

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TYPE SAND Report YEAR 2006

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Studies of the laser-induced fluorescence of explosives and explosive compositions

Schmitt, Randal L.; Thorne, Lawrence R.; Hargis, Philip J.; Parmeter, John E.

Continuing use of explosives by terrorists throughout the world has led to great interest in explosives detection technology, especially in technologies that have potential for standoff detection. This LDRD was undertaken in order to investigate the possible detection of explosive particulates at safe standoff distances in an attempt to identify vehicles that might contain large vehicle bombs (LVBs). The explosives investigated have included the common homogeneous or molecular explosives, 2,4,6-trinitrotoluene (TNT), pentaerythritol tetranitrate (PETN), cyclonite or hexogen (RDX), octogen (HMX), and the heterogeneous explosive, ammonium nitrate/fuel oil (ANFO), and its components. We have investigated standard excited/dispersed fluorescence, laser-excited prompt and delayed dispersed fluorescence using excitation wavelengths of 266 and 355 nm, the effects of polarization of the laser excitation light, and fluorescence imaging microscopy using 365- and 470-nm excitation. The four nitro-based, homogeneous explosives (TNT, PETN, RDX, and HMX) exhibit virtually no native fluorescence, but do exhibit quenching effects of varying magnitude when adsorbed on fluorescing surfaces. Ammonium nitrate and fuel oil mixtures fluoresce primarily due to the fuel oil, and, in some cases, due to the presence of hydrophobic coatings on ammonium nitrate prill or impurities in the ammonium nitrate itself. Pure ammonium nitrate shows no detectable fluorescence. These results are of scientific interest, but they provide little hope for the use of UV-excited fluorescence as a technique to perform safe standoff detection of adsorbed explosive particulates under real-world conditions with a useful degree of reliability.

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TYPE SAND Report YEAR 2006

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