Peter Gorm Larsen’s work centers on the development of digital technologies that support the understanding and optimization of complex systems. By combining software engineering with modeling and data integration, he enables closer interaction between physical processes and their digital representations.
A central part of his research is the use of digital twin technology, where real-world systems are continuously mirrored by dynamic computational models. These models use real-time data from sensors and production systems to simulate behavior, test scenarios, and support decision-making in complex environments.
Within CORC, Larsen leads the project Digital Twins for CO2-to-Protein Production, which is part of the Modeling & Digitalization program. The project focuses on developing a digital twin of a pilot-scale production facility at Aarhus University, integrating data from a large number of sensors and an open data infrastructure to support process optimization and scale-up.
The aim is to create a framework that can guide improvements in production efficiency, energy use, and system design, while also supporting the transition from pilot-scale to industrial-scale solutions. By providing continuous feedback between models and experiments, the digital twin helps identify optimal operating conditions and future development pathways.
