No abstract

Infrared emissions from the detonation of three bomb types and four weights in a series of 56 events were recorded by a Fourier transform spectrometer in the midwave IR (1800-6000 cm 1 ) at temporal and spectral resolutions of 0.047 s and 16 cm 1 , respectively. Fifteen time-resolved spectral datasets corresponding to two distinct chemical explosives were selected for this study. The detonation fireball intensities are well described as cooling greybodies, and a single Planckian distribution, modified by atmospheric absorption, has been fit to the spectra. Agreement between the model and data is within a few percent on average. However, the model underestimates the observed intensity by as much as 40% in the 2000-2200 cm 1 window and hot CO 2 at the surface of the fireball is a likely source of this spectral emission (spectral assignments have not yet been performed). For the statically detonated munitions, temperature curves are characterized by initial temperatures of 1685-1885 K and lifetimes of 0.91-1.24 s. Temperatures for some air delivered ordnance exhibited secondary maxima. Fireball areas are estimated without imagery. The model provides features which are reproducible within and characteristic of the munition type, providing promise for proposed event classification schemes. The timedependent Planckian fit residual near 2150 cm 1 versus time provided the best discrimination between the two munition types, indicating that better understanding the non-Planckian behavior is key to the classification problem. A novel method to estimate the atmospheric transmittance function from the time-resolved fireball spectra is also developed.

No abstract

An index is presented for quantifying the geometric complexity of a three-dimensional solid model. This provides a measure by which components may be compared one with another in relation to their relative complexity. The index is alphanumeric and readily computable. Such an index can be of use in the field of feature recognition as a means to determine how efficiently one algorithm handles components of varying complexity compared to another such algorithm.The performance of the authors' own feature recognition algorithm is tested against components of differing complexity as determined by the index.