March 2026

Conference Paper

The Integrated Virtual Blast Furnace: Enabling Physics-Based Operational Guidance

By:
Okosun, Tyamo; Calix, Ricardo; Ugarte, Orlando; Wang, Hong ; Leontaras, Kosta; Morey, Joseph; Entwistle, Jason; Rogers, Brian; Zhou, Chenn
Page Number:
168-176
Book Title:
AISTech 2024 — Proceedings of the Iron & Steel Technology Conference
Publication Date:
March 12, 2026
Publisher Location:
AIST, Ohio, United States of America
Conference Name:
AISTech Technology Conference 2024
Conference Location:
Columbus, Ohio, United States of America
Conference Sponsor:
AIST
View DOI Listing:
https://doi.org/10.33313/388/021

Abstract

As part of a DOE-supported research effort, Purdue University Northwest researchers are collaborating with Oak Ridge National Laboratory and United States Steel Corporation to develop a tool to provide blast furnace operators and engineers with process performance insight comparable to high-fidelity computational fluid dynamics modeling, accelerated to provide “what-if” scenarios at near-real-time speed. This is accomplished by pre-simulating a baseline case and a range of potential operating scenarios to establish how the furnace responds to changing inputs, then training a neural network-based Reduced Order Model to accelerate the speed at which predictions of key parameters can be generated.


Related Researchers