R
Roberto Ojeda
Researcher at Australian Maritime College
Publications - 41
Citations - 580
Roberto Ojeda is an academic researcher from Australian Maritime College. The author has contributed to research in topics: Slamming & Tension-leg platform. The author has an hindex of 10, co-authored 40 publications receiving 427 citations. Previous affiliations of Roberto Ojeda include University of Tasmania.
Papers
More filters
Journal ArticleDOI
Modelling of pitting corrosion in marine and offshore steel structures – A technical review
TL;DR: In this paper, the authors reviewed and analyzed the current understanding of the pitting corrosion mechanism and investigated all possible factors that can cause pitting, including accurate pit depth measurements, precise strength assessment techniques, risk analysis due to pitting and the mathematical relationship of the environmental factors that causes pitting failure.
Journal ArticleDOI
Finite element investigation on the static response of a composite catamaran under slamming loads
TL;DR: In this paper, the structural response of a fast and relatively small composite materials catamaran to slamming loads is analyzed using the ANSYS 6.0 finite element software, and suitable recommendations are made.
Journal ArticleDOI
A new approach for the large deflection finite element analysis of isotropic and composite plates with arbitrary orientated stiffeners
TL;DR: In this paper, a new approach for the large deflection analysis of isotropic and composite arbitrary orientated stiffened plates is presented, which uses the principle of virtual work applied to a continuum with a total Lagrangian description of motion.
Journal ArticleDOI
Accelerated pitting corrosion test of 304 stainless steel using ASTM G48; Experimental investigation and concomitant challenges
Jyoti Bhandari,Samantha Lau,Rouzbeh Abbassi,Vikram Garaniya,Roberto Ojeda,Denis Lisson,Faisal Khan +6 more
TL;DR: In this article, the effect of surface finish and aeration of the test solution on the corrosion behavior of 304 stainless steel specimens in 6% ferric chloride were examined and compared.
Journal ArticleDOI
Pitting Degradation Modeling of Ocean Steel Structures Using Bayesian Network
TL;DR: In this paper, a probabilistic model is developed for predicting the long-term pitting corrosion depth of steel structures in marine environment using Bayesian network, which combines an understanding of corrosion phenomenological model and empirical model calibrated using real-world data.