Hazardous materials such us drugs, biological weapons and explosives posses a very distinctive chemical composition. They consist mainly from carbon, nitrogen, oxygen and hydrogen elements. This unique characteristics makes them an ideal target for the novel detection method called atometry, which allows non-invasive, real-time, chemical analysis of any kind of substance. The basis of this technology is stoichiometry analysis of a given object conducted with the neutron beams. The Stoichiometry Analysis by Activation Techniques (SABAT) Collaboration is a team of experienced scientists and students from the Jagiellonian University, working on these novel, atometry-based, systems for chemical threat detection. To support this research, a sophisticated Monte Carlo simulation package was developed to model in detail the neutron emissions. Due to the computational complexity of this simulation, plenty of optimization techniques needs to be used. One of them is an application of the technologies borrowed from the field of computer graphics and video games, such as the ray tracing or the specialized acceleration data structures such as the k-d trees. This thesis will describe the motivation behind the selection of this particular algorithms and data structures, and also the direct application of them in the simulation package
Design of the SABAT System for Underwater Detection of Dangerous Substances
M. Silarski, D. Hunik, M. Smolis, S. Tadeja, P. Moskal
We present status of simulations used to design a novel device for the detection of hazardous substances in the aquatic environment using neutron activation. Unlike the other considered methods based on this technique, we propose to use guides for neutron and gamma quanta which speeds up and simplifies identification. First preliminary results show that both the neutron guide and the ?-ray guide increase the performance of underwater threats detection.
Monte Carlo simulations of the radiation environment for the CMS Experiment