New Efficient Blast Furnace Model Presented at Digital Transformation Forum
Our research on “A Multi-Input & Output Model for Blast Furnace Operational Guidance Using a Pre-generated CFD Simulation Dataset” was presented by Professor Tyamo Okosun at the 2023 AIST Digital Transformation Forum for the Steel Industry on March 8th, in Pittsburgh, Pennsylvania. This research uses machine learning and a database of CFD modeling results to develop a Reduced-Order Model (ROM) for operators and engineers to quickly perform “what-if” calculations on their blast furnaces, which provides a useful tool for physics-based and data-driven quick decision making. This is a part of a large collaborative project to develop an Integrated Virtual Blast Furnace sponsored by the Department of Energy.
The 2023 Digital Transformation Forum was organized by AIST’s Digitalization Applications Technology Committee. The forum included papers, panel discussions, workshops and demonstrations of DT topics and projects. This event involves decision-makers and those with a technical background who are interested in learning more about how to make their areas smarter by utilizing digital transformation methods. Digital transformation is a critical component for steel companies’ future success.
In addition, the Digital Transformation Forum discusses the essential roles humans play in a successful digital transformation journey. Strategies and methods to efficiently manage the cultural change and human involvement are also explored through the high-quality presentations and panel discussion sessions.