Suomen Korroosioyhdistys

SKY Member evening: Data-driven design in process industry
2023-10-23 16:00 - 17:00 (Europe/Helsinki) | Teams
Two short presentations and free discussion on the subject.
The link will be sent to SKY members by e-mail.
Machine learning for predicting alkali salt-induced high-temperature corrosion of superheater materials (by Rasmus Fagerlund)

Short introduction on high-temperature corrosion in black liquor recovery boilers and Åbo Akademi corrosion test method
Data analysis
Modeling of data using machine learning methods
Model performance and conclusions

Modeling of steam usage at a power plant site (by Jere Espo)

Trials to manage different operational situations with a mathematical model based on process data
Correct timing of required operator manual work
Generation of more valid process measurement alarms

Rasmus Fagerlund

Doctoral student at Åbo Akademi University
Currently working on modeling of NOx formation for computational fluid dynamics (CFD) models of black liquor recovery boilers (supervisor Docent Markus Engblom)
Background in chemical engineering
Interested in AI applications, mathematical modeling and optimization

Jere Espo
Process Engineer

Team leader of Vantaa Energy Chemistry Team operating at three sites
Background in analytical chemistry

Roughly 25 years of experience in power plant chemistry including topics like:

Fuel analysis
Flue gas cleaning
Water chemistry
Chemical safety
Team leading tasks
