Determination of the aggressiveness of atmospheric corrosion in steels structural, galvanized steel and stainless steel in the city of Barranquilla and its metropolitan area

Authors

Cristian Antonio Pedraza Yepes, Universidad del Atlántico; Oscar Fabián Higuera Cobos, Universidad del Atlántico; Mónica Johanna Monsalve Arias, Universidad del Atlántico; José Luis Cano Gómez, Universidad del Atlántico; Hebert Alejandro Gutiérrez Peña, Universidad del Atlántico

Keywords:

Corrosion phenomenon, Atmospheric corrosion

Synopsis

Atmospheric corrosion is a phenomenon of electrochemical origin that results from the interaction of a material with the surrounding environment, which causes its deterioration and translates into additional costs for industrial activity. However, despite its influence, no research has been conducted to predict the effects of the corrosive phenomenon at the local level. For this reason, the present work studied the aggressiveness of atmospheric corrosion in Barranquilla and its metropolitan area through a field investigation for four months with different commercial steels —ATM A36, ASTM A572, AISI A304, ASTM A36 galvanized and ASTM A572 galvanized— in four geographic zones distributed in the city. Our purpose was to calculate the loss of mass due to corrosive effects in these locations, taking into account characteristics such as proximity to the sea or pollutants present in the air. For this, an experimental measurement program was developed based on a multilevel factorial design, in which the loss of mass associated with atmospheric corrosion was evaluated as an output variable and as factors that could affect it, the exposure time, the geographical area and the the material. The results obtained were subjected to an analysis of variance with the help of the STATGRAPHICS® package to determine the factors that exert a significant influence on this phenomenon. The data obtained as a product of the experimental design indicated that atmospheric corrosion is a time and material dependent process. Consequently, they can be fitted to a statistical expression that takes into account the contribution of these factors by using regression methods.

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June 1, 2020

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ISBN-13 (15)

978-958-5131-78-1

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2020