DNVGL.com

Smart Alloy Selection

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William Kovacs William Kovacs
Senior Engineer
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Challenge

Discovering the usage envelope for materials in oil & gas applications can be challenging and expensive, especially for valuable materials with a complicated corrosion mechanism.

Solution

DNV GL aims to establish a framework for the collection of publicly-viewable (and private) materials data and apply thermodynamic modelling and machine-learning algorithms to enhance the knowledge about the usage envelope for corrosion-resistant alloys (CRAs) such as 13 Cr, 316L, 22 Cr Duplex and Alloy 28/29.

Benefits

  • Predictive models for environmentally assisted cracking (EAC)
  • Database for data-driven decision-making
  • Identify new factors contributing to EAC
  • Focused (and therefore lower-cost) testing

Value

Industry partners will obtain value in various scenarios:
Oil companies/material producers

  • Wider envelope – eg, cost savings from lower alloys or sales revenue from increased material usability
  • Narrower envelope – eg, cost savings from reduced failures or sales revenue from higher alloys
  • Data aggregators – untapped revenue stream(s)

Joint Industry Projects - Smart Alloy Selection

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