Welcome to the Process Design Unit of the Chemical Engineering School at the National Technical University of Athens. The Unit operates in the area of Process Systems Engineering and Complex Systems analysis.

The group expertise is strong in Advanced Process Design, Modelling and Optimization. The group is certified to undertake design engineering work by IChemE (UK) and collaborates with industry through several projects. Although rooted in conventional sectors of the Chemical Industry (Petrochemicals, Oil & Gas), the skills have extensively diversified in recent years to address applications in Bio-renewables and the Circular Economy. Current research areas involve applications that include the

• design and scale-up of several biorefineries (ligno-cellulosic, oleo-chemical, aquatic, waste-based)
• retrofitting of conventional process industries into Circular Economy plants
• development of industrial symbiosis networks and industrial ecology paradigms
• integration of large (or big-data streams) with systems assets with a view to build services and observatories
• systems applications in community clusters (cities, ports, professional clusters)

Process Design offers technology that combines mathematical and thermodynamic methods for

• Process integration of industrial flowsheets through state-of-the-art methods that target efficiencies for energy, water and material efficiency
• Process Synthesis methods to select integration schemes, chemical paths, unit operations, and solvents.
• Advanced designs for multi-phase reactors, thermal separation (simple and complex distillation design and sequencing), separation of azeotropes, non-thermal separations and reactive-separation schemes to intensify production

Modelling advocates a multi-scale approach using a variety of industrial and academic software (AspenPlus, SuperPro, gProms, Matlab, ANOVA) to develop

• First-principle models for simulation and flowsheeting using different platforms (often in need to integrate with each other)
• LCA technology exploiting data from commercial and public repositories (SimaPro, CCalC) to assess sustainability and/or to predict performance ahead of design
• Scale-up and engineering costing (including the use of custom-made models and in-house tools)
• Data integration and knowledge models that combine ontology engineering and semantics for speed, automation and high-throughput applications
• Multi-agent systems to study issues of strategy and the role of social networks

Optimization of large and complex systems involves separate work for applications and new methods. Technology includes methods for

• Site analysis and the optimization of energy networks
• Superstructure optimization and conceptual programming
• Cascade optimization paradigms to distribute computing in difficult and demanding problems
• Game theory and MAS to understand trade-offs in supply chains of the bio-economy