Study of the response of a single-dof dynamic system under stationary non-Gaussian random loads aimed at fatigue life assessment.

Fatigue assessment of components subjected to random loads is a challenging task both due to the variability in amplitude and frequency of the loads and for the computational times required to perform classical time domain fatigue analysis. The frequency domain approach to fatigue life assessment offers a solution by utilizing the power spectral density of the random load, requiring minimal computational effort. However, frequency domain methods are limited to stationary Gaussian signals, while real-world loads often exhibit non-Gaussian characteristics.

Heavy metal background levels and pollution temporal trend assessment within the marine sediments facing a brownfield area (Gulf of Pozzuoli, Southern Italy).

In this study, site-specific natural background levels (NBLs) were determined for 18 elements (Al, As, Be, Cd, Co, Cu, Cr, Fe, Hg, K, Mn, Mo, Ni, Pb, Tl, U, V, and Zn) in two sediment cores collected offshore the Bagnoli-Coroglio brownfield site (Gulf of Pozzuoli, southern Italy) to accurately assess the degree of contamination and the historical trends in Heavy Metals (HMs) enrichment. This objective was pursued taking in account the high temporal and spatial variability of the geochemical properties of the area due to the local geothermal activity. Moreover, the temporal variation of Polycyclic Aromatic Hydrocarbons (PAHs) was investigated.

Deep learning models to predict flood events in fast-flowing watersheds.

This study aims to explore the reliability of flood warning forecasts based on deep learning models, in particular Long-Short Term Memory (LSTM) architecture. We also wish to verify the applicability of flood event predictions for a river with flood events lasting only a few hours, with the aid of hydrometric control stations. This methodology allows for the creation of a system able to identify flood events with acceptable errors within several hours' notice.

Baseline radionuclide and heavy metal concentrations in sediments of Sabaki River estuary (Kenya, Indian Ocean).

Baseline study of natural (Be, Pb, Ra, Th, Ra, K) and anthropogenic (Cs) radionuclides was carried out in two cores collected from Sabaki River estuary (Kenya, Indian Ocean). There was no exponential decrease of excess Pb down the cores, which did not allow dating and determination of heavy metal pollution history. The use of Cs as a time marker was not possible due to its low fallout rates in East Africa.

Mercury isotope signatures in sediments and marine organisms as tracers of historical industrial pollution.

Isotopic composition of mercury (Hg) in marine organisms and sediment cores was used to identify sources and reconstruct historical trends of contamination in the coastal-marine area of Rosignano Solvay (Italy), affected by Hg pollution from a chlor-alkali plant on the near land. Sediments show a wide range of Hg concentration and Hg isotope signatures. Particularly, coupled Hg concentration and δHg values trace inputs from different sources.