A steel mill is about to test a new computer model that predicts exactly how hot metal will behave as it is rolled, cooled, and shaped into a finished product. The problem is that current models cannot fully account for the complex, unpredictable changes that occur inside metal during processing—tiny variations in microstructure, uneven heating, or unexpected stresses. This leaves manufacturers relying on costly trial-and-error to get the properties right. The Sheffield team is building a hybrid model that merges physical laws with data-driven methods, covering the gaps where fundamental science is incomplete. If successful, the framework will allow metals producers to achieve “right first time” production, slashing waste and energy use. The impact would ripple through industries that depend on high-performance metals: lighter, stronger car bodies, more durable railway tracks, and safer gas pipelines. This is applied engineering, not fundamental science—the goal is a practical tool for industry, validated through real mill trials and ready for commercial use.
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IMMPETUS (Institute for Microstructural and Mechanical Process Engineering: The University of Sheffield) was founded in 1997 to undertake truly integrated interdisciplinary research across the disciplines of systems, mechanical and metallurgical engineering, addressing key issues in the metals processing industry. Over the last ten years the unique inter-disciplinary research produced by IMMPETUS has secured national and international acclaim for its systems driven approach to process and property optimisation of a wide range of metals process routes. Using systems engineering we target and optimise experiments to develop basic physical metallurgy in specific areas where knowledge is incomplete, to inform model elicitation, testing and validation. For the complex industrial processes we investigate, there is insufficient basic knowledge to construct true through-process physically based models. In order to cover the intractable factors not adequately described by the existing physically based models, we use hybrid models that merge discrete data, knowledge-based and physically-based models in a unique manner to give unprecedented precision in predictive model capability. All the modelling is verified through the use of a world class array of experimental techniques. The proposal comprises 12 projects which have been constructed in conjunction with our industrial collaborators in order to answer the following questions: 1. How do we formulate a 'generic' framework for 'through-process' modelling to achieve 'right first-time' production of metals?2. Which of the metallurgical and thermomechanical variables affect the microstructure and therefore the final properties of metals, but are not yet fully described by existing models?3. How do causalities (deterministic behaviours) as well as uncertainties (heterogeneities, random behaviours) influence the processing and affect the final properties of metals?4. What are the specific modelling strategies 'best' suited for answering 1, 2, and 3 above?5. Using the elicited models in 4, can we identify the achievable properties for a given process route, and what to do if a particular property is not achievable?6. Using 5, how do we optimise the process route?The programme of work is presented as four themes, all of which are inter-dependent and interwoven. PHYSICAL SYSTEMS will be aimed at developing basic physical metallurgical understanding where knowledge is inadequate, in areas including microstructural heterogeneities, and process conditions that are dynamic and non-linear. In MODELLING SYSTEMS, the physical metallurgy, mechanical engineering and systems engineering will be fully integrated, both through the development of new modelling approaches, and the coupling of existing state-of-the-art modelling that in itself produces new methodologies. PROCESS SIMULATION will involve the upscaling of focused laboratory experiments to accurately and completely simulate the relevant industrial process routes and validate them through appropriate mill trials. SYSTEMS OPTIMISATION will act as a powerful vehicle for integrating these themes and via a careful tuning of model structures/parameters will be core to our technology transfer to our will target specific industrial sponsors and to the wider academic community.
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