Phenomenological fireball model for remote identification of high-explosives

Kevin C. Gross; Joseph Wayman; Glen P. Perram

doi:10.1117/12.719977

11 May 2007 Phenomenological fireball model for remote identification of high-explosives

Kevin C. Gross, Joseph Wayman, Glen P. Perram

Proceedings Volume 6566, Automatic Target Recognition XVII; 656613 (2007) https://doi.org/10.1117/12.719977
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

Many aspects of detonation phenomena have been well studied over the last century. However, the transient infrared and visible emissions from detonation fireballs have been poorly understood, and this has hampered attempts to remotely identify explosives via combustion signatures. Recently, time-resolved infrared spectra (1800-7000 cm^-1, 4cm^-1 resolution, 8 Hz) were collected from the detonation of uncased charges of TNT and several kinds of improvised explosive devices in four weight classes (10, 50, 100, and 1000 kg). A simple model for fireball emissions has been developed which accurately describes the observed spectra in terms of the fireball size, temperature, gaseous byproduct concentrations, and grey particulate absorption coefficient. The model affords high-fidelity dimensionality reduction and provides physical features which can be used to distinguish the uncased explosives.

Citation Download Citation

Kevin C. Gross, Joseph Wayman, and Glen P. Perram "Phenomenological fireball model for remote identification of high-explosives", Proc. SPIE 6566, Automatic Target Recognition XVII, 656613 (11 May 2007); https://doi.org/10.1117/12.719977

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available