We present the results of modeling intended to evaluate the feasibility of using neutrons from induced fission in highly enriched uranium (HEU) as a means of detecting clandestine HEU, even when it is embedded in absorbing surroundings, such as commercial cargo. We characterized radiation from induced fission in HEU, which consisted of delayed neutrons at all energies and prompt neutrons at energies above a threshold. We found that for the candidate detector and for the conditions we considered, a distinctive HEU signature should be detectable, given sufficient detector size, and should be robust over a range of cargo content. In the modeled scenario, an intense neutron source was used to induce fissions in a spherical shell of HEU. To absorb, scatter, and moderate the neutrons, we place one layer of simulated cargo between the source and target and an identical layer between the target and detector. The resulting neutrons and gamma rays are resolved in both time and energy to reveal the portion arising from fission. We predicted the dominant reaction rates within calcium fluoride and liquid organic scintillators. Finally, we assessed the relative effectiveness of two common neutron source energies.
The US and the Russian Federation are currently engaged in negotiating or implementing several nuclear arms and nuclear material control agreements. These involve placing nuclear material in specially designed containers within controlled facilities. Some of the agreements require the removal of nuclear components from stockpile weapons. These components are placed in steel containers that are then sealed and tagged. Current strategies for monitoring the agreements involve taking neutron and gamma radiation measurements of components in their containers to monitor the presence, mass, and composition of plutonium or highly enriched uranium, as well as other attributes that indicate the use of the material in a weapon. If accurate enough to be useful, these measurements will yield data containing information about the design of the weapon being monitored. In each case, the design data are considered sensitive by one or both parties to the agreement. To prevent the disclosure of this information in a bilateral or trilateral inspection scenario, so-called information barriers have evolved. These barriers combine hardware, software, and procedural safeguards to contain the sensitive data within a protected volume, presenting to the inspector only the processed results needed for verification. Interlocks and volatile memory guard against disclosure in case of failure. Implementing these safeguards requires innovation in radiation measurement instruments and data security. Demonstrating their reliability requires independent testing to uncover any flaws in design. This study discusses the general problem and gives a proposed solution for a high resolution gamma ray detection system. It uses historical examples to illustrate the evolution of other successful systems.
The event identification problem plays a large role in the application of unattended ground sensors to the monitoring of borders and checkpoints. The choice of features and methods for classifying features affects how accurately these classifications are made. Finding features which reliably distinguish events of interest may require measurements based on separate physical phenomena. Classification methods include neural net versus fuzzy logic approaches, and within the neural category, different architectures and transfer functions for reaching decisions. This study examines ways of optimizing feature sets and surveys common techniques for classifying feature vectors corresponding to physical events. We apply each technique to samples of existing data, and compare discrimination attributes. Specifically, we calculate the confusion matrices for each technique applied to each sample dataset, and reduce them statistically to scalar scores. In addition, we gauge how the accuracy of each method is degraded by reducing the feature vector length by one element. Finally, we gather rough estimates of the relative cpu performance of the forward prediction algorithms.
KEYWORDS: Unattended ground sensors, Sensors, Signal attenuation, Receivers, Signal processing, Physical phenomena, Wave propagation, Magnetic sensors, Particles, Signal to noise ratio
In the fall of 1995, a unique unattended ground sensor experiment was conducted at the Nevada Test Site. In the experiment, a variety of electro-mechanical equipment was operated, while data were gathered using a number of different types of unattended sensors at different locations. The sensors in this study included seismometers, accelerometers, electric dipole sensors, magnetometers and microphones. The purpose of this experiment was to gather data to explore and understand the performance of unattended ground sensor systems and the physical phenomena that can affect them. In this paper, we explore a few physical phenomena which can affect unattended ground sensor system performance.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
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.