Estimation of Metal Loss by Corrosion Process in Heat Exchangers Applied to Hydrotreating Systems

It is well known that among of all the components of hydrotreating systems used in the industrial processes, the heat exchangers that pre-heat the reactor suffer the greatest degree of degradation by pitting corrosion due to extreme temperature exposure. Typically, two different mathematical analysis were used to estimate the probability of failure by metal loss as a consequence of pitting corrosión mechanism: short-term and long-term corrosion rate (STCR and LTCR, respectively), as designated by API 510 standard method. However, the results are often misunderstood when the difference between the calculated data of STCR and LTCR is large. For this reason, in this research the STCRs and LTCRs models were fitted to a generalized extreme value distribution (GEVD) to characterize the metal loss that take place in four heat exchangers, as well as to determine what kind of corrosion rate model is better for predicting the metal loss estimation. According to the results obtained in this research, the STCR model appears to be the most appropriate analysis for estimating future metal loss by pitting corrosion for the heat exchangers reactors used in hydrotreating systems.Thanks to Secretaria de Investigación y Estudios Avanzados SIyEA/UAEM for its financial support through research projects

A Bayesian Approach for Estimating the Thinning Corrosion Rate of Steel Heat Exchanger in Hydrodesulfurization Plants

Fuel consumption has been increasing in recent years, especially that of diesel and jet fuel. For this reason, the necessity to build new plants to reduce their sulfur content has arisen. Sometimes, just revamping existing plants is feasible, but determining which pieces of equipment are in the appropriate condition to be reused is also necessary. In order to select the equipment, it is essential to have information about the wall thickness of vessels. Sometimes, the information is limited; consequently, the application of advanced statistical techniques is needed. ,e Bayesian Data Analysis (BDA) used in this study has the goal of determining a more accurate, unobserved thinning rate distribution for existing heat exchangers, taking into consideration all the information available about the thinning rate of the heat exchangers that cool down the effluent of the hydrotreating reactors in Mexican oil refineries. ,e information obtained from BDA was compared with existing shell wall thickness obtaining favorable results