Distinguished Seminar in Computational Science and Engineering

Distinguished Seminar in Computational Science and Engineering

May 8, 2025, 12-1PM

45-432 in Building 45 and Zoom Webinar

Data Driven Modeling for Scientific Discovery and Digital Twins

Dongbin Xiu
Professor and Ohio Eminent Scholar
Department of Mathematics
The Ohio State University

Abstract: 

We present a data-driven modeling framework for scientific discovery, termed Flow Map
Learning (FML). This framework enables the construction of accurate predictive models
for complex systems that are not amenable to traditional modeling approaches. By
leveraging measurement data and the expressiveness of deep neural networks (DNNs),
FML facilitates long-term system modeling and prediction even when governing equations
are unavailable. FML is particularly powerful in the context of Digital Twins, an emerging concept in digital transformation. With sufficient offline learning, FML enables the construction of simulation models for key quantities of interest (QoIs) in complex Digital Twins, even when direct mathematical modeling of the QoI is infeasible. During the online execution of a Digital Twin, the learned FML model can simulate and control the QoI without reverting to the computationally intensive Digital Twin itself. As a result, FML serves as an enabling methodology for real-time control and optimization of the physical twin, significantly enhancing the efficiency and practicality of Digital Twin applications.

Data Driven Modeling for Scientific Discovery and Digital Twins
Dongbin Xiu
The Ohio State University