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The capacity to promptly and efficiently detect any source of contamination of the environment (a radioactive cloud) at a local and a country scale is mandatory to a safe and secure exploitation of civil nuclear energy. It must rely upon a robust network of measurement devices, to be optimized vs. several parameters, including the overall reliability, the investment, the operation and maintenance costs. We show that a network can be arranged in different ways, but many of them are inadequate. Through simulations, we test the efficiency of several configurations of sensors, in the same domain. The denser arrangement turns out to be the more efficient, but the efficiency is increased when sensors are non-uniformly distributed over the country, with accumulation at the borders. In the case of France, as radioactive threats are most likely to come from the East, the best solution is densifying the sensors close to the eastern border. Our approach differs from previous work because it is "failure oriented": we determine the laws of probability for all types of failures and deduce in this respect the best organization of the network.

Approaches that are widely used to characterize propensity of soils to liquefaction are mainly of empirical type. The potential of liquefaction is assessed by using correlation formulas that are based on field tests such as the standard and the cone penetration tests. These correlations depend however on the site where they were derived. In order to adapt them to other sites where seismic case histories are not available, further investigation is required. In this work, a rigorous one-dimensional modelling of the soil dynamics yielding liquefaction phenomenon is considered. Field tests consisting of core sampling and cone penetration testing were performed. They provided the necessary data for numerical simulations performed by using DeepSoil software package. Using reliability analysis, the probability of liquefaction was estimated and the obtained results were used to adapt Juang method to the particular case of sandy soils located in Tangier.