Pages: 46-55

Authors: Miltiadis Alamaniotis, Sean Terrill, John Perry, Rong Gao, Lefteri Tsoukalas, Tatjana Jevremovic

Abstract

The detection of hazardous materials has been identified as one of the most urgent needs of homeland security, especially in scanning cargo containers at United States ports. To date, special nuclear materials have been detected using neutron or gamma interrogation, and recently the nuclear resonance fluorescence has been suggested. We show a new paradigm in detecting the materials of interest by a method that combines four signals (radiography/computer tomography, acoustic, muon scattering, and nuclear resonance fluorescence) in cargos. The intelligent decision making software system is developed to support the following scenario: initially, radiography or the computer tomography scan is constructed to possibly mark the region(s) of interest. The acoustic interrogation is utilized in synergy to obtain information regarding the ultrasonic velocity of the cargo interior. The superposition of the computer tomography and acoustic images narrows down the region(s) of interest, and the intelligent system guides the detection to the next stage: no threat and finish, or proceed to the next interrogation. If the choice is the latter, knowing that high Z materials yield large scattering angle for muons, the muon scattering spectrum is used to detect the existence of such materials in the cargo. Additionally, the nuclear resonance fluorescence scan yields a spectrum that can be likened to the fingerprint of a material. The proposed algorithm is tested for detection of special nuclear materials in a comprehensive scenario.

Key words: nuclear material detection, cargo scanning, multiple signals, fuzzy logic, intelligent decision

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