Wireless sensor networks (WSNs) are appealing options for the health monitoring of nuclear power plants due to their low cost and flexibility. Before they can be used in highly regulated nuclear environments, their reliability in the nuclear environment and compatibility with existing devices have to be assessed. In situ electromagnetic interference tests, wireless signal propagation tests, and nuclear radiation hardness tests conducted on candidate WSN systems at AECL Chalk River Labs are presented. The results are favourable to WSN in nuclear applications.

A boron-loaded liquid scintillator (LS) has been optimized for neutron detection application in a high gamma field environment. It is composed of the solvent linear alkylbenzene (LAB), a boroncontaining material, o-carborane (C2B10H12); a fluor, 2,5-diphenyloxazole (PPO); and a wavelength shifter, 1,4-bis[2-methylstyryl] benzene (bis-MSB). Preparation of the liquid scintillator and optimization of its chemical composition are described. The boronloaded LS has been tested with a neutron beam at the National Research Universal (NRU) reactor. A peak at an equivalent energy of 60 keV is observed in the energy spectrum and is attributed to neutrons. The results confirm the possibility of using B-10 loaded scintillator as a sensitive medium for neutron detection in a relatively large background of gamma rays.

Organizers: Mung Chiang (Princeton) and Steven Low (Caltech)Recently, there has been a surge in research activities that utilize the power of recent developments in nonlinear optimization to tackle a wide scope of work in the analysis and design of communication systems, touching every layer of the layered network architecture, and resulting in both intellectual and practical impacts significantly beyond the earlier frameworks. These research activities are driven by both new demands in the areas of communications and networking, and new tools emerging from optimization theory. Such tools include new developments of powerful theories and highly efficient computational algorithms for nonlinear convex optimization, as well as global solution methods and relaxation techniques for nonconvex optimization.