Abstract
The contribution reports to the state of the art in materials characterization obtained by the authors through the use of micromagnetic nondestructive testing (NDT) techniques in order to predict mechanical properties of steel samples (surveillance program) after neutron irradiation in irradiation chambers of nuclear pressure vessels. The investigations have been performed within the framework of the EURATOM project CRETE [1]. The irradiated steel samples were delivered by different European countries: two sets of specimen came from France, two came from Germany, two from the Czech Republic and one from Spain. The specimens were stored in the hot cell of the research reactor in Petten, Netherlands, where they could be handled by robots in order to perform the measurements by different inspection teams. Besides electromagnetic (one team) and micromagnetic (two teams) techniques, thermoelectric (2 teams) techniques have been applied and the results are discussed. In order to characterize microstructure states in ferromagnetic steels micromagnetic, NDT techniques were based on the interaction of Bloch walls with lattice defects such as vacancies, dissolved atoms, precipitates, dislocations, and grain-and phase-boundaries. The way the lattice defects are the pinning points of the dislocation movement under mechanical loads, i.e., how they contribute to a strengthening effect, is similar to the way the Bloch walls interact with the lattice defects under magnetic loads. In addition, magnetic strengthening is observed that can be detected, for instance, in an increase of the coercivity. The institution of the authors has developed the so-called 3MA-approach (micromagnetic, multiple-parameter, microstructure, and stress analysis) in the last decade. This approach combines the information resulting from the performance of different micromagnetic techniques (magnetic Barkhausen noise, incremental permeability, harmonic analysis of the magnetic tangential field and eddy current testing used at 3 different frequencies). The data fusion is obtained through the use of neural networks, multiple regression algorithms, or pattern recognition procedures such as the nearest neighbor approach. Various information in a calibration process is selected such that disturbing influences, for instance, heating and cooling effects, are suppressed and the signal-to-noise ratio for the target function prediction (hardness, yield strength, Charpy energy, fracture appearance transition temperature, etc.) is optimized. 3MA is performed by an intelligent transducer and a data evaluation system with which, in a time multiplexing mode, one measuring quantity after the other is selected. The results obtained at the broken halves of ISO-V-notched Charpy specimens show a good performance of the multiple regression approach, with high regression coefficients near 1 and a small residual standard deviation between modeled and destructively determined mechanical properties. However, stochastically independently selected specimens show a larger deviation than the standard error of the calibration. The reason for this phenomenon is that the plastic deformation and the residual stress are in the broken Charpy specimen. Therefore, further investigations will be concentrated on calibration on irradiated, but unbroken, Charpy specimens.

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