Math Modeling Seminar: Mathematical Modeling of the Interactions between Biofilms and Hydrogel for Corrosion Prediction on Metallic Surfaces

Math Modeling Seminar
Mathematical Modeling of the Interactions between Biofilms and Hydrogel for Corrosion Prediction on Metallic Surfaces

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Dr. Olubenga (Olu) Oluwagbemi
Postdoctoral Associate, School of Mathematics and Statistics
Rochester Institute of Technology

Abstract:
Corrosion of metallic surfaces of key agricultural machines, transportation facilities and energy infrastructures, is a major problem that is costing government exorbitant expenses and poses risks to human and environmental safety. Microorganisms are important in the process of corrosion. Microorganisms contribute either to accelerating or decelerating/slowing down corrosion processes of metallic surfaces. Studying the interactions between hydrogels, biofilms and metallic surfaces can help strengthen understanding about rates of corrosion and this can create platforms for mitigating corrosion.
In this research, the knowledge of mathematical modelling was well explored using Ordinary Differential Equations (ODEs) and Partial Differential Equations (PDEs) to formulate useful mathematical models, coupled with the application of software engineering principles. Biological data/parameters were obtained from biological literature. We developed a mathematical modelling software. The suite was rigorously developed using Java programming language. The software was able to predict the corrosion rates and corrosion inhibition rates of metallic surfaces based on environmental, hydrogels and biofilm parameters. Furthermore, an advanced validation pipeline was developed to validate corrosion simulated data predicted by our model with real-life experimental corrosion-related data.
Results from the preliminary validation, reveal that our software was able to predict similar trends with real-life experimental datasets. A second validation phase was accomplished by obtaining experimental corrosion datasets of Pit depth, and Corrosion rates from the corrosion of metals which spanned 3 to about 160 days. A third validation phase was conducted with extra experimental datasets from real-life experiments spanning 1 month to about 24 months containing corroded metal datasets and computed corrosion penetration depth datasets of nine (9) different types of metals. We further developed more mathematical models for corrosion inhibition rate prediction. Future work will focus on expanding the scalability of these models.

Speaker Bio:
Olu is an NSF‑funded Postdoctoral Associate in the School of Mathematics and Statistics at RIT, New York. He holds BS and MS degrees in Computer Science and completed a 7‑week advanced Fulbright Summer Fellowship at RIT. He later earned a US Fulbright Research Fellowship, conducting his PhD research at the Johns Hopkins Bloomberg School of Public Health, USA, before defending his PhD in Computer Science at Covenant University. Olu has completed prestigious postdoctoral fellowships, including the NRF Innovation Fellowship and the DAAD Fellowship at Stellenbosch University, where he researched HIV and malaria modelling, and the AfOx Fellowship at the University of Oxford, focusing on spatial malaria modelling. He is a member of ACM, a Fellow of the Higher Education Academy (FHEA), and holds a PGCert in Higher Education from Middlesex University London. Before joining RIT, Olu held academic positions as Associate Professor and Senior Lecturer of Computer Science in the United Kingdom, South Africa, and Nigeria. Outside of work, he enjoys music and plays the piano, acoustic guitar, and bass guitar. He also loves table tennis, board games, and spending quality time with his family in Rochester.

Intended Audience:
Beginners, undergraduates, graduates. Those with interest in the topic.