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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Corrosion is an unavoidable phenomenon in ship hull structures and thickness loss of the structural members due to corrosion is a great concern when the integrity of hull structures is considered. It is well known that pitting corrosion occurring on coated hold frames will surely result in a significant degradation of the ultimate strength of these members. Extensive study on the effect of pitting corrosion on structural strength under a wide variety of loading conditions is necessary to assess the relationship between pitting corrosion intensity and residual strength precisely. The aim of the present study is to investigate the ultimate strength characteristics of steel beams with pit and uniform corrosions wastage. Then pitted member will predict with a member that its thickness decreases uniformly in terms of ultimate strength. A series of ABAQUS nonlinear elastic-plastic analyses by Finite Element Method (FEM) has been carried out on I-shape section steel models, varying the degree of pit corrosion intensity. Load-carrying capacity of deteriorated steel beam models with different pit corrosion under patch loading has been estimated using Artificial Neural Network (ANN) method using FE results. The ultimate strength reduction factor due to web pitting corrosion of steel beams is empirically derived by ANNs of the computed results as a function of DOP. Hence, the results of this study can be used for better prediction of the failure of deteriorated steel beams by practice engineers.

ULTIMATE CAPACITY ASSESSMENT OF WEB PLATE BEAMS WITH PITTING CORROSION SUBJECTED TO PATCH LOADING BY ARTIFICIAL NEURAL NETWORKS