Patricia Cotič

In-plane shear tests on masonry panels with plaster: correlation of structural damage and damage on artistic assets

In the paper, possibilities of correlation of structural damage and damage of attached artistic assets on multi-leaf stone masonry walls by means of destructive and non-destructive testing (NDT) methods are investigated. Results from two testing campaigns carried out at the University of Genoa and University of Ljubljana are briefly presented. In particular, diagonal tests with different levels of pre-compression and shear tests under different boundary conditions were carried out in Genoa and Ljubljana, respectively. During the tests, different damage limit states (DL) of both masonry walls (SE) and attached plasters (AA) were investigated by means of NDT’s. Two different types of rubble stone masonry were considered (uncoursed random rubble vs. coursed squared rubble). For AA the results are presented in relative form in dependence from the DL of SE. Obtained results are influenced both by the type of test and tested masonry. Results of NDT revealed strong potential and a need for data fusing of both investigated methods for the evaluation of the state of the degradation behind the plaster.

NDT Data Fusion for the Enhancement of Defect Visualization in Concrete

Ground penetrating radar (GPR) and active thermography are well known non-destructive testing (NDT) methods for structural visualization and defect detection in concrete. However, for both methods, the probability of detection is strongly depth-dependent and each method suffers from an almost blind region at a specific depth. In this study we propose the use of unsupervised clustering techniques for the fusion of GPR and thermographic phase contrast data to enhance defect visualization in concrete. The evaluation was carried out on the basis of experimental data acquired on laboratory concrete test specimens, which contain inbuilt anomalies varying in shape, material and position. To achieve an optimal fusion of radar depth slices and thermographic phase contrast images along the depth axis, we derive sensitivity curves for both NDT methods and use the probability mass information to further improve the fusion results. Results show that the fuzzy c-means algorithm may contribute to an enhanced detection probability of defects below high density reinforcement. For defects with a concrete cover from 1.5 to 2 cm, the use of weighted clustering is particularly suggested. In general, complex defect types and shapes could be better resolved by using the Gustafson-Kessel algorithm or noise clustering. In addition, we demonstrate the application of the Dempster-Shafer theory to quantitatively evaluate the effectiveness of fused data on the basis of joint mass probability.