EAF steelmaking is the key technology for decarbonised steelmaking, either in scrap-based plant by modification of existing processes for further decarbonisation, or as new EAF installations in decarbonised integrated steel works to (partly) replace the classical BF-BOF production. At same time the EAF is the most important example for modular and hybrid heating, already now combining electric arc heating with burner technologies. Consequently, it was selected as main focus of GreenHeatEAF for the Call „Modular and hybrid heating technologies in steel production“. GreenHeatEAF develops and demonstrates the most important decarbonisation approaches at EAFs including the use of hydrogen to replace natural gas combustion in existing or re-vamped burners or innovative technologies like CoJet. Furthermore, decarbonisation of EAF steelmaking by solid materials like DRI/HBI and renewable carbon sources like biochar is tackled. Technologies to re-optimise the heating management with maximum heat recovery of off-gas and slag employing new sensor and soft-sensor concepts as well as extended digital twins are developed: as result the extended CFD and flowsheeting models, and monitoring and control tools will prognose the influences of the different decarbonisation measures on EAF and process chain to support upcoming decarbonisation investments and to enable the control of decarbonised hybrid heating with maximum energy efficiency. GreenHeatEAF combines trials in demonstration scale, e.g. in combustion- and EAF-demo plants, with validations in industrial scale and digital optimisations with high synergy. Thus, it completely follows the Horizon Twin Transition and Clean Steel Partnership objectives and the target to progress decarbonisation technologies from TRL 5 to 7. This synergic concept of GreenHeatEAF supports implementation and digitisation to speed up the transition of the European steel industry to highly competitive energy-efficient decarbonised steel productio

H2-enriched direct reduction (DR) is the key decarbonisation technology for integrated steelworks mentioned in pathways of all major steel producers. Natural gas driven DR is established in industry mostly outside Europe but there are no experiences with high H2 enrichment > 80%. H2 based reduction is no principal issue but endothermic and the influences on morphology, diffusion and effective kinetics are not known. Also properties and movement of particles in the reactor are not know and issues like sticking cannot be excluded. Probably, temperature distribution and flow of solids and gas will be clearly different. No reliable prognosis is possible yet, in particular with regard to local permeability, process stability and product quality of industrial size furnaces with higher loads on the particles and larger local differences. Many activities are initiated for first industrial demonstration of H2-enriched DR but they will not close many of these knowledge gaps. MaxH2DR provides missing knowledge and data of reduction processes. A world-first test rig determines pellet properties at conditions of industrial H2 enriched DR furnaces and a physical demonstrator shows the linked solid and gas flow in shaft furnaces. This will be combined with digitals models including the key technology DEM-CFD to provide a hybrid demonstrator able to investigate scale-up and to optimise DR furnace design and operating point. This sound basis will be used to optimise the process integration into existing process chains. Simulation tools will be combined to a toolkits that covers impacts of product properties on downstream processes as well as impacts on gas and energy cycles. Thus, promising process chains, sustainable and flexible, will be achieved for different steps along the road to decarbonisation. The digital toolkits will support industrial demonstration and implementation and strengthen digitisation and competitiveness of the European steel industry.

ProcTwin aims to develop a demonstration platform to predict and visualize best use of multiple processing steps in a steel manufacturing chain. The methodology includes intelligent coupling of interconnected processing steps by numerical simulation, soft sensors, process data and distributed machine learning. Integrated numerical modelling that captures the interactions, relations, and feedback loops between various processing stations enables prediction for smart optimization of energy efficiency and product quality in the steel manufacturing. Continuous casting, reheating, hot metal working, quenching and leveling processes are examples that are controlled separately but strongly interconnected in terms of parameters. These processes serve as objective functions in two parallel use cases at Celsa (ES) and SSAB (SW). It is well known that process optimization can have a significant effect on reducing carbon footprint in steel production, and implementing new digital tools will enable a faster transition towards sustainable industry. ProcTwin is divided in clear work packages to reach the objectives: one is adaption of existing physically based numerical models of each process step to generate critical data that is impossible to measure or observe. Another is development of novel sensors and data integration for a secure and effective sharing industrial data. The innovative concept of ProcTwin is development of distributed machine learning to predict the process chains with large amounts of parameters. Lastly, these technologies will be combined through a demonstrator platform to model the manufacturing processes and enable control for increased product quality, energy efficiency and operator support.

In context of the transition to low-carbon, green and sustainable steel production in Europe, disruptive technologies to reduce the environmental footprint as close to zero as possible, seamless digitalisation of production processes, and skilled people to co-design and understand the transformation process are necessary. DiGreeS will address these needs by implementing an integrated digitalisation approach across the steel value chain, enabling better use of process data collected and ensuring the involvement of human experience for easier industrial integration. The aim of DiGreeS is to develop a user-friendly digital platform for networked production based on novel and soft sensors and related approaches and models to support efficient feedstock verification and real-time control of electric arc furnace crude steel production, increasing process yield while improving the quality of intermediate and final steel products. In this context, the potential of artificial intelligence techniques will be fully exploited to support the optimal use of industrial data, and different scenarios specific to each use case will be modelled. The digital platform will be implemented and verified in industrial process lines of the three use cases: scrap/secondary raw material verification, optimisation of the electric arc furnace processes and optimisation of the levelling of steel sheets. DiGreeS aims to improve the quality of crude steel and finished products, optimize scrap usage, and improve energy efficiency in the steel production process. DiGreeS has the potential to save up to €800 million in costs annually and reduce CO2 emissions from the steelmaking industry by up to 6 million tonnes per year.

Each year the EU steel sector generates several million tons of metal and mineral containing residues that are currently largely under-exploited and are often sent to landfills with an enormous waste of resources that could replace virgin materials. ReMFra main objective is the development and validation of highly efficient pyrometallurgic melting and reduction demonstration plant at relevant industrial scale for recovering metals and minerals contained in a wide range of steelmaking residues. The ReMFra process will allow to valorise steelmaking residues, such as filter dust, scale, sludge and slags, to obtain pig iron, iron rich oxides, a highly concentrated zinc oxide and an inert slag. ReMFra comprises two main parts to be developed, improved and tested at industrial scale: Plasma Reactor and RecoDust. The first will be dedicated to recover the coarse residues (scale, sludge, slag), while the second will focus on fine-grained dusts. The project will allow the improvement of iron yield using recovered pig iron instead of new pig iron and replacing the iron ore with the iron rich oxide. The recovery of concentrated ZnO and inert slag as by-products will provide a significant source of income and will contribute to the overall carbon neutrality. To reach the full circularity, the process foresees the use, as reducing agent, of secondary carbon sources (i.e. waste plastics). Energy recovery solutions will also be integrated in the metal recovery process starting from enabling the use of molten pig iron. ReMFra consortium comprises: 5 steelmaking companies, 4 RTOs as technology providers with large experience in steel sector, 1 university and the European Steel Technology Platform. To conclude, ReMFra is expected not only to enable technological advances in the demonstrators involved but will also contribute to the development of new standards, training programmes, adaptation and certification of industrial processes thus facilitating the replication of the project.