131 research outputs found

    Feature extraction and identification techniques for the alignment of perturbation simulations with power plant measurements

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    In this work, a methodology is proposed for the comparison of the measured and simulated neutron noise signals in nuclear power plants, with the simulation sets having been generated by the CORE SIM+ diffusion-based reactor noise simulator. More specifically, the method relies on the computation of the Cross-Power Spectral Density of the detector signals and the subsequent comparison with their simulated counterparts, which involves specific frequency values corresponding to the signals’ high energy content. The different simulated perturbations considered are (i) axially traveling perturbations, (ii) fuel assembly vibrations, (iii) core barrel vibrations, and finally (iv) generic “absorber of variable strength” types. The reactor core used for the current study is a German 4-loop pre-Konvoi Pressurized Water Reactor

    Group updates and multiscaling: An efficient neural network approach to combinatorial optimization

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    Multi-dimensional raycasting for fuzzy pattern classification

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    Group updates and multiscaling: an efficient neural network approach to combinatorial optimization

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    PICTORIAL INFORMATION-RETRIEVAL USING THE RANDOM NEURAL NETWORK

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