MIC and Materials Selection

Eckert, Richard B.; Amend, Bill

doi:10.1201/9781315157818-2

Cited by 3 publications

(3 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Alloys with a PREN of 32 or greater are generally considered to be resistant to pitting corrosion in ambient-temperature seawater. A material’s PREN value may also provide some level of insight in determining its relative resistance to MIC (Eckert and Amend 2017 et al 2017 ); however, care needs to be taken not to over-interpret this value (Craig 2020 ). A general review of the literature in which MIC is cited as the cause of corrosion will show that as PREN increases, the frequency of MIC case studies decreases.…”

Section: Siloed Scientific Fields and The Need For Interdisciplinary ...mentioning

confidence: 99%

Microbiologically influenced corrosion—more than just microorganisms

Knisz

Eckert²,

Gieg

et al. 2023

FEMS Microbiology Reviews

View full text Add to dashboard Cite

Microbiologically influenced corrosion (MIC) is a phenomenon of increasing concern which affects various materials and sectors of society. MIC describes the effects, often negative, that a material can experience due to the presence of microorganisms. Unfortunately, although several research groups and industrial actors worldwide have already addressed MIC, discussions are fragmented, while information sharing and willingness to reach out to other disciplines is limited. A truly interdisciplinary approach, that would be logical for this material/biology/chemistry-related challenge, is rarely taken. In this review we highlight critical non-biological aspects of MIC that can sometimes be overlooked by microbiologists working on MIC but are highly relevant for an overall understanding of this phenomenon. Here, we identify gaps, methods and approaches to help solve MIC related challenges, with an emphasis on the MIC of metals. We also discuss the application of existing tools and approaches for managing MIC and propose ideas to promote an improved understanding of MIC. Furthermore, we highlight areas where the insights and expertise of microbiologists are needed to help progress this field.

show abstract

Section: Siloed Scientific Fields and The Need For Interdisciplinary ...mentioning

confidence: 99%

Microbiologically influenced corrosion—more than just microorganisms

Knisz

Eckert²,

Gieg

et al. 2023

FEMS Microbiology Reviews

View full text Add to dashboard Cite

show abstract

“…A general review of literature in which MIC is cited as the cause of corrosion shows that as the PREN value increases, the frequency of MIC decreases [37].…”

Section: Materials Parameter Sub-networkmentioning

confidence: 99%

“…Figure 4 presents the OOBN sub-network of the metallurgy and surface factors that influence the MIC potential and their interactions, and Table 6 summarises the variance and relevance of each factor. The Pitting resistance equivalent number (PREN) value is given by the formula as follows: A general review of literature in which MIC is cited as the cause of corrosion shows that as the PREN value increases, the frequency of MIC decreases [37].…”

Section: The Proposed Probabilistic Modelling Approach To Mic Potentialmentioning

confidence: 99%

Model for microbiologically influenced corrosion potential assessment for the oil and gas industry

Taleb‐Berrouane

Khan

Hawboldt

et al. 2018

Corrosion Engineering, Science and Technology

View full text Add to dashboard Cite

Corrosion is one of the major causes of failure in onshore and offshore oil and gas operations. Microbiologically influenced corrosion (MIC) is inherently more complex to predict, detect and measure because, for instance, the presence of biofilm and/or bacterial products is not sufficient to indicate active microbiological corrosion. The major challenge for current MIC models is to correlate factors that influence corrosion (i.e. chemical, physical, biological and molecular variables) with the potential of having MIC. Previous work has proposed the potential for MIC as a simple product of multiple factors, without fully considering the synergy or the interference among the factors. The present work proposes a network-based approach to analyse and predict MIC potential considering the complex interactions among a total of 60 influencing factors and 20 screening parameters. The proposed model has the ability to capture the complex interdependences and the synergic interactions of the factors used to assess MIC potential and uses an object-oriented approach based on a Bayesian Network. The model has been tested and verified using real data from a pipeline leakage incident that was a result of MIC. The proposed model constitutes a significant step in deepening the understanding of when MIC occurs and its predictability.

show abstract

Biological Corrosion Failures

Jack

2021

Failure Analysis and Prevention

View full text Add to dashboard Cite

MIC and Materials Selection

Cited by 3 publications

References 1 publication

Microbiologically influenced corrosion—more than just microorganisms

Microbiologically influenced corrosion—more than just microorganisms

Model for microbiologically influenced corrosion potential assessment for the oil and gas industry

Biological Corrosion Failures

Contact Info

Product

Resources

About