Nondestructive evaluation of concrete compression strength by means of Artificial Neural Network (ANN)

The evaluation of structural performance of existing concrete buildings, built according to standards and materials quite different to those available today, requires procedures and methods able to cover lack of data about mechanical material properties and reinforcement detailing. To this end detailed inspections and test on materials are required. As a consequence tests on drilled cores are required; on the other end, it is stated that non-destructive testing (NDT) cannot be used as the only mean to get structural information, but can be used in conjunction with destructive testing (DT) by a representative correlation between DT and NDT. The aim of this study is to verify the accuracy of some formulas of correlation available in literature between measured parameters, i.e. rebound index, ultrasonic pulse velocity and compressive strength (SonReb Method). To this end a relevant number of DT and NDT tests has been performed on many school buildings located in Cesena (Italy). The above relationships have been assessed on site correlating NDT results to strength of core drilled in adjacent locations. Nevertheless, concrete compressive strength assessed by means of NDT methods and evaluated with correlation formulas has the advantage of being able to be implemented and used for future applications in a much more simple way than other methods, even if its accuracy is strictly limited to the analysis of concretes having the same characteristics as those used for their calibration. This limitation warranted a search for a different evaluation method for the non-destructive parameters obtained on site. To this aim, the methodology of neural identification of compressive strength is presented. Artificial Neural Network (ANN) suitable for the specific analysis were chosen taking into account the development presented in the literature in this field. The networks were trained and tested in order to detect a more reliable strength identification methodology.

Study of the inter-annual variability of particle vertical fluxes in two moorings in the Ross Sea (Antarctica)

The most ocean - atmosphere exchanges take place in polar environments due to the low temperatures which favor the absorption processes of atmospheric gases, in particular CO2. For this reason, the alterations of biogeochemical cycles in these areas can have a strong impact on the global climate. With the aim of contributing to the definition of the mechanisms regulating the biogeochemical fluxes we have analyzed the particles collected in the Ross Sea in different years (ROSSMIZE, BIOSESO 1 and 2, ROAVERRS and ABIOCLEAR projects) in two sites (mooring A and B). So it has been developed a more efficient method to prepare sediment trap samples for the analyses. We have also processed satellite data of sea ice, chlorophyll a and diatoms concentration. At both sites, in each year considered, there was a high seasonal and inter-annual variability of biogeochemical fluxes closely correlated with sea ice cover and primary productivity. The comparison between the samples collected at mooring A and B in 2008 highlighted the main differences between these two sites. Particle fluxes at Mooring A, located in a polynia area, are higher than mooring B ones and they happen about a month before. In the mooring B area it has been possible to correlate the particles fluxes to the ice concentration anomalies and with the atmospheric changes in response to El Niño Southern Oscillations. In 1996 and 1999, years subjected to La Niña, the concentrations of sea ice in this area have been less than in 1998, year subjected to El Niño. Inverse correlation was found for 2005 and 2008. In the mooring A area significant differences in mass and biogenic fluxes during 2005 and 2008 has been recorded. This allowed to underline the high variability of lateral advection processes and to connect them to the physical forcing.