Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (13/13 displayed)

  • 2024Classification of pitting corrosion damage in process facilities using supervised machine learning3citations
  • 2022Experimental analysis of pitting corrosion in offshore structures5citations
  • 2020Pitting corrosion modelling of X80 steel utilized in offshore petroleum pipelines64citations
  • 2018Condition monitoring of subsea pipelines considering stress observation and structural deterioration38citations
  • 2017Modelling the impacts of fire in a typical FLNG processing facilitycitations
  • 2017Modelling the impacts of fire in a typical FLNG processing facilitycitations
  • 2017Accelerated pitting corrosion test of 304 stainless steel using ASTM G48; Experimental investigation and concomitant challenges30citations
  • 2017Integrated probabilistic modelling of pitting and corrosion fatigue damage of subsea pipelinescitations
  • 2017Pitting degradation modelling of ocean steel structures using Bayesian network26citations
  • 2016Dynamic risk-based maintenance for offshore processing facility47citations
  • 2016Reliability assessment of offshore asset under pitting corrosion using Bayesian Networkcitations
  • 2016Reliability assessment of offshore asset under pitting corrosion using Bayesian Networkcitations
  • 2015Modelling of pitting corrosion in marine and offshore steel structures - A technical review423citations

Places of action

Chart of shared publication
Patel, Parth
1 / 4 shared
Kafian, Hesam
1 / 1 shared
Aryai, Vahid
1 / 1 shared
Patel, P.
1 / 10 shared
Aryai, V.
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Abaei, Mohammad Mahdi
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Chia, Bing H.
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Abbassi, Rouzbeh
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Arzaghi, Ehsan
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Abaei, Mm
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Chen, L.
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Khan, Faisal
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Dadashzadeh, M.
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Baalisampang, T.
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Lau, S.
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Lisson, D.
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Khan, F.
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Bhandari, J.
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Rabanal, Roberto Ojeda
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Khakzad, N.
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Reniers, G.
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Binns, Jonathan
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Ojeda, Roberto
1 / 1 shared
Bhandari, Jyoti
1 / 1 shared
Chart of publication period
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2022
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Co-Authors (by relevance)

  • Patel, Parth
  • Kafian, Hesam
  • Aryai, Vahid
  • Patel, P.
  • Aryai, V.
  • Abaei, Mohammad Mahdi
  • Chia, Bing H.
  • Abbassi, Rouzbeh
  • Arzaghi, Ehsan
  • Abaei, Mm
  • Chen, L.
  • Khan, Faisal
  • Dadashzadeh, M.
  • Baalisampang, T.
  • Lau, S.
  • Lisson, D.
  • Khan, F.
  • Bhandari, J.
  • Rabanal, Roberto Ojeda
  • Khakzad, N.
  • Reniers, G.
  • Binns, Jonathan
  • Ojeda, Roberto
  • Bhandari, Jyoti
OrganizationsLocationPeople

article

Pitting corrosion modelling of X80 steel utilized in offshore petroleum pipelines

  • Abaei, Mohammad Mahdi
  • Chia, Bing H.
  • Abbassi, Rouzbeh
  • Arzaghi, Ehsan
  • Garaniya, Vikram
Abstract

<p>High strength steels such as X80 steels have recently been used more frequently in production of offshore structures. However, they may still be subject to degradation processes such as corrosion considering the conditions in marine environment. Pitting corrosion is a destructive form of corrosion which reduces the material resistance and may result in failure accidents with severe financial, human life and environmental consequences. The process of pitting corrosion is inconsistent and largely stochastic being influenced by a number of parameters with a high level of uncertainty. This makes it very difficult to predict corrosion in terms of its initiation time and spatial behavior. Therefore, it is vital to investigate pitting corrosion phenomena in offshore structures using a probabilistic approach for the assessment of structural reliability and operational safety. In this study, an in-situ experiment has been conducted on X80 steel in an NaCl solution in a laboratory environment to observe the generation and growth of corrosion pits. A probabilistic model based on Hierarchical Bayesian Approach (HBA) is developed for predicting the pitting corrosion growth rate using experimental results. In order to model the process more realistically, the proposed methodology considers the degradation process to be consisting of the time needed for pit initiation and propagation. The results indicate that the proposed methodology is capable of predicting the time required to reach a specific pit size. The methodology developed in this study can be applied to estimate the remaining useful life of subsea structures.</p>

Topics
  • impedance spectroscopy
  • experiment
  • strength
  • pitting corrosion
  • steel