The first 96 and 192 beam vacuum Hohlraum target experiments have been fielded at the National Ignition Facility demonstrating radiation temperatures up to 340 eV and fluxes of 20 TW/sr as viewed by DANTE representing an ∼20 times flux increase over NOVA/Omega scale Hohlraums. The vacuum Hohlraums were irradiated with 2 ns square laser pulses with energies between 150 and 635 kJ. They produced nearly Planckian spectra with about 30±10% more flux than predicted by the preshot radiation hydrodynamic simulations. To validate these results, careful verification of all component calibrations, cable deconvolution, and software analysis routines has been conducted. In addition, a half Hohlraum experiment was conducted using a single 2 ns long axial quad with an irradiance of ∼2×10(15) W/cm(2) for comparison with NIF Early Light experiments completed in 2004. We have also completed a conversion efficiency test using a 128-beam nearly uniformly illuminated gold sphere with intensities kept low (at 1×10(14) W/cm(2) over 5 ns) to avoid sensitivity to modeling uncertainties for nonlocal heat conduction and nonlinear absorption mechanisms, to compare with similar intensity, 3 ns OMEGA sphere results. The 2004 and 2009 NIF half-Hohlraums agreed to 10% in flux, but more importantly, the 2006 OMEGA Au Sphere, the 2009 NIF Au sphere, and the calculated Au conversion efficiency agree to ±5% in flux, which is estimated to be the absolute calibration accuracy of the DANTEs. Hence we conclude that the 30±10% higher than expected radiation fluxes from the 96 and 192 beam vacuum Hohlraums are attributable to differences in physics of the larger Hohlraums.
Many automated image-based applications have need of finding small spots in a variably noisy image. For humans, it is relatively easy to distinguish objects from local surroundings no matter what else may be in the image. We attempt to capture this distinguishing capability computationally by calculating a measurement that estimates the strength of signal within an object versus the noise in its local neighborhood. First, we hypothesize various sizes for the object and corresponding background areas. Then, we compute the Local Area Signal to Noise Ratio (LASNR) at every pixel in the image, resulting in a new image with LASNR values for each pixel. All pixels exceeding a pre-selected LASNR value become seed pixels, or initiation points, and are grown to include the full area extent of the object. Since growing the seed is a separate operation from finding the seed, each object can be any size and shape. Thus, the overall process is a 2-stage segmentation method that first finds object seeds and then grows them to find the full extent of the object.This algorithm was designed, optimized and is in daily use for the accurate and rapid inspection of optics from a large laser system (National Ignition Facility (NIF), Lawrence Livermore National Laboratory, Livermore, CA), which includes images with background noise, ghost reflections, different illumination and other sources of variation.
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