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.

The fourth industrial revolution and market demands for advanced steels are driving the research towards transformation of the manufacturing processes and to ever-more sustainable steel compositions. The conventional ‘trial and error’ approach traditionally used to develop metallurgical processes still prevails in the industrial steel plants. However, it is a time-consuming, labour-intensive process entailing high material waste and associated carbon emissions. Also, it can ultimately lead down to a repetitive path that consists of creating a process design, putting it into production, and detecting possible process design flaws too late, resulting in high component rejection rates. Ascertaining the inadvertent flaws in the manufacturing approach before its implementation on industrial lines could be the key to major cost savings. With the introduction of AI- and simulation-driven design, back-and-forth interaction between part and process designs can be significantly diminished. The main objective of AID4GREENEST is to develop six new AI - based rapid characterization methods and modelling tools. AID4GREENEST tools’ scope will cover the steel design (chemistry and microstructure), process design (processing parameters), product design (processing and heat treatments) and product performance (creep) stages. Proposed tools will be complemented with a roadmap designed to enable model-based innovation processes, from materials design to product development, while considering the industry needs: enhanced material quality, reduction of carbon emission and waste generation, and reduced supply risk of critical raw materials. In order to facilitate the knowledge transfer of the characterization and modelling data generated in this project and across the wider European characterization and modelling community, the project will also develop an open online platform, based on a standardized and interoperable data management system and following the EMMC, EMCC and EMMO approach.

Growing demand for high quality iron ores and scrap as well as abandonment of carbon intensive sintering in the future require novel technological approaches for upgrading of low-grade iron ores and recycling of mill scale. TransZeroWaste will apply hydrometallurgy for mill scale de-oiling and use this iron-rich scrap equivalent to upgrade low-grade iron ores. For that, TransZeroWaste will develop low carbon technologies such as cold pelletising and briquetting, hot microwave pelletising, and magnet-supported hydrometallurgy from TRL 6 to TRL 8. The developed technologies will be transferable to further material flows such as dusts and sludges. On European level, the expected impact will be the potential upgrade of over 18 million t/a low-grade iron ore, up to 6 million t/a mill scale and 3 million t/a pellet sieving residue. Total impact of TransZeroWaste will include upgrading of 27 million t/a materials with low carbon technologies and avoiding of corresponding sinter plant carbon footprint of 4,3 – 9,9 MtCO2/a. Technological competences and know-how are owned by the participating partners from the applied research. They will be developed and transferred to the two industrial partners with 9 production sites. Thoroughly planned dissemination and exploitation activities will ensure effective implementation of technologies after project end. Life cycle assessment and economic evaluation will be performed; sustainable business models will be developed. Furthermore, a decision support platform for industrial users will be installed. In combination with workshops and trainings it will help to find and implement the best upgrading technology for various low-grade materials considering environmental and economic aspects. TransZeroWaste will serve as a vehicle for the transition of the European steel industry to the carbon free zero waste future.

The fourth industrial revolution and market demands for advanced steels are driving the research towards transformation of the manufacturing processes and to ever-more sustainable steel compositions. The conventional ‘trial and error’ approach traditionally used to develop metallurgical processes still prevails in the industrial steel plants. However, it is a time-consuming, labour-intensive process entailing high material waste and associated carbon emissions. Also, it can ultimately lead down to a repetitive path that consists of creating a process design, putting it into production, and detecting possible process design flaws too late, resulting in high component rejection rates. Ascertaining the inadvertent flaws in the manufacturing approach before its implementation on industrial lines could be the key to major costsavings. With the introduction of AI- and simulation-driven design, back-and-forth interaction between part and process designs can be significantly diminished. The main objective of AID4GREENEST is to develop six new AI - based rapid characterization methods and modelling tools. AID4GREENEST tools’ scope will cover the steel design (chemistry and microstructure), process design (processing parameters), product design (processing and heat treatments) and product performance (creep) stages. Proposed tools will be complemented with a roadmap designed to enable model-based innovation processes, from materials design to product development, while considering the industry needs: enhanced material quality, reduction of carbon emission and waste generation, and reduced supply risk of critical raw materials. This HOP-ON will elaborate on the tools and models developed in the AID4GREENEST project by incorporating surface (oxidation) considerations into the quenching model for meter-scale parts, examining creep-fatigue interactions during product service life, and including the effects of surface oxidation on the creep and creep-fatigue performance of steel.