English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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. The 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. The information obtained from BDA was compared with existing shell wall thickness obtaining favorable results.

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