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This paper reviews state-of-the-art in nondestructive testing (NDT) and semidestructive testing (SDT) methods applicable for imaging the condition of structural timber. Both NDT and SDT imaging reveal defects, damages, and decay, while the extent of wood decay can also be quantified. Combined with an appropriate data interpretation concerning the internal defects, the mechanical properties of the material can also be assessed. The possibilities and limitations of the most relevant individual NDT and SDT methods, also in combination with each other, are outlined and compared. To facilitate comparison, many observations are reported based on the same test specimen.
Neutron cameras allow visualizing hydrogen distributions with radiographic or tomographic imaging methods in iron and steel.
The necessary contrast between hydrogen and iron stems from the high difference in the total neutron cross section of both elements. This allows e.g. the in situ measurement of hydrogen mass flow inside cm thick steel samples with a temporal resolution of 20 s using neutron radiography as well as the quantitative measurement of hydrogen accumulations at the crack’s inner surfaces in hydrogen embrittled iron samples with neutron tomography. We could detect directly gaseous hydrogen in the crack cavities and we measured the gas pressure. This new quality of the information on a micrometer scale allows new insights for the analysis of hydrogen-induced damage mechanisms. Further, this method is non-destructive and provides local information in situ and in three dimensions with a spatial resolution of 20-30 μm.
In this contribution, we show examples that demonstrate the spatial and temporal resolution of the neutron radiography and tomography methods in order to visualize and quantify hydrogen accumulations at cracks. The measurements were performed
at the research reactor BER II of the HZB in Berlin and at the FRM II reactor of the neutron source Heinz Maier-Leibnitz in
Garching.
The inspection of complex-shaped components, such as those enabled by additive manufacturing, is a major challenge in industrial quality assurance. A frequently adopted approach to volumetric non-destructive evaluation is X-ray computed tomography, but this has major drawbacks. Two-dimensional radiography can overcome some of these problems, but does not generally provide an inspection that is as capable.
Moreover, designing a detailed inspection for a complex-shaped component is a labour-intensive task, requiring significant expert input. In response, a computational framework for optimizing the data acquisition for an image-based inspection modality has been devised. The initial objective is to advance the capabilities of radiography, but the algorithm is, in principle, also applicable to alternative types of imaging. The algorithm exploits available prior
information about the inspection and simulations of the inspection modality to allow the Determination of the optimal inspection configuration, including specifically component poses with respect to the imaging system. As an intermediate output, spatial maps of inspection performance are computed, for understanding spatially varying limits of detection. Key areas of innovation concern the defect detectability evaluation for arbitrarily complex indications and the creation of an application-specific optimization algorithm. Initial trials of the algorithm are presented, with good results.