Abstract The structural condition of the cable-stayed towers anchorage on power transmission lines requires constant monitoring. Maintenance routines must be able to identify faulty anchor rods and substitute them to avoid tower collapses and power delivery interruptions. Modern statistical diagnostic systems based on machine learning requires the generation of several distinct rod sample signals to be trained, which is a time-consuming process in typical electromagnetic solvers. Aiming to generate samples in a feasible time span, this paper presents a modeling strategy based on the cascade analysis of the transmission line composed by the anchor and the reference rods, interconnected by a dedicated high-frequency connector. Each distinct transmission line part is modeled by a quadrupole as a partial ABCD matrix. The complete response for each experimental setup is obtained from the cascaded-multiplying of the partial matrices. The proposed modeling proved to be accurate and provides a faster way to obtain the S-parameters from distinct faulty rods if compared to the traditional methodologies using electromagnetic tools.

The objective of this study was to evaluate the concentration of Cu, Zn, Cr and Pb in different species of fish collected in the estuarine and limnic regions of the São Gonçalo channel, located in the Patos-Mirim lagoon complex in the coastal plain of Rio Grande do Sul State (Southern Brazil) during 2013 (autumn, winter and spring) and 2014 (summer). Fish samples were decomposed in a digester block with a reflux system under conditions optimized using a central composite design as it follows: 250 mg of fish sample, 5 mL HNO3, 2 mL H2O2 during 2 h at 150 °C. The concentrations obtained ranged from 6.7 to 12.0 mg kg -1 for Cu; 1.8 to 23.6 mg kg -1 for Zn; 37 to 487 µg kg -1 for Pb; and 40 to 1268 µg kg -1 for Cr. The highest concentrations of Cu, Zn and Pb, were observed in fishes collected at locations in the estuarine region and Cr showed high levels, especially in the limnic region. The samples of the species Loricariichthys anus (viola) showed the highest concentrations of all analytes investigated.