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REUSteel

Dissemination of results of the European projects dealing with reuse and recycling of by-products in the steel sector

REUSteel project abstract

European Research dedicated a lot of time and efforts in the development of innovative sustainable solutions for the steel industry. The aim is to provide bridging solutions to lead the steel industry towards a reduction of its environmental impact with an obvious saving of natural resources, hence in being closer to a virtuous objective of “zero waste” goal. These thematic fields are perfectly framed in a concept that is strongly emphasized at a European level and that is receiving increasing attention in the scientific and technical community in the latest years, namely the so called Circular Economy. The circularity concept pushes researchers and industries to look for synergies with other industrial sectors to analyze and investigate solution for improving by-product reuse and recycling both inside and outside the steelmaking cycle, by thus developing examples of industrial symbiosis. However, the joint efforts of the EU steel industries on this theme are still not widely known.

REUSteel project aims at extensively disseminating and valorizing important research results on the reuse and recycling of byproducts, based on an integrated critical analysis of many list of EU-funded projects, in order to promote the results exploitation and increase the synergies with other sectors.

REUSteel project overview

“Dissemination of results of the European projects dealing with reuse and recycling of by-products steel sector (REUSteel)” is a project co-founded by the Research Fund for Coal and Steel (RFCS).

The project is framed in the context of more eco-friendly and sustainable solutions in the steel industry. The reuse and recycling of by-products of the steelmaking cycles as well as on the exploitation of by-products from other activities outside the steel production cycle, such as alternative carbon sources (e.g., biomasses and plastics) are the proper actions to move towards a saving of the natural resources together with a reduction of the environmental impact, hence being closer to a “zero-waste” goal.

“REUSteel” aims at an extensive action of dissemination and valorisation of the most important research results on by-products reuse and recycling, based on an integrated critical analysis of many EU-funded projects, in order to promote results exploitation and increase the synergies with other industrial sectors. This analysis will allow identifying the most urgent needs and ambitions of the European steel sector and defining a sequence of future research topics in this field.

A joint critical analysis, carried out by all the partners, belonging to different institutions, will provide new insights and guidelines for future research topics in this field, in order to promote the dissemination and, consequently, the implementation of the achieved results. The project will also organise the results, in order to present selected groups of topics at planned workshops and seminars. This will provide a clearer vision of the outcomes to stakeholders and new audiences, in order to get new and deeper indications for a new roadmap, future synergies with other sectors and industrial trends.

“REUSteel” will contribute to an update of the steel roadmap for a low carbon Europe 2050 and the current BIG-Scale initiative of EUROFER.

The involved Partners in the research project are:

Sant’Anna School of Advanced Studies (Coordinator)	www.santannapisa.it/en
VDEh-Betriebsforschungsinstitut GmbH (BFI)	www.bfi.de/en/
FEhS – Institut für Baustoff-Forschung e.V.	www.fehs.de/en/
Rina Consulting Centro Sviluppo Materiali S.P.A. (CSM)	www.rina.org/en
SWERIM	www.swerim.se/
European Steel Technology Platform (ESTEP) is also involved in the project as subcontractor of Sant’Anna School of Advanced Studies	www.estep.eu

The Project Coordinator is Dr. Eng. Valentina Colla (valentina.colla@santannapisa.it)

REUSteel dissemination action

The project was finalized in January 2022. Further information about events, videos and public deliverables as the roadmap of the REUSteel project can be found on https://www.reusteel.eu/index.html

• Events:
  https://www.reusteel.eu/events.html
• Documents and Videos
  https://www.reusteel.eu/documents.html
• Public Deliverables
  https://www.reusteel.eu/deliverables.html

This project is carried out with the financial support of the Research Fund for Coal & Steel – Grant Agreement Number: 839227 (2019)​

Minimise sinter degradation between sinter plant and blast furnace exploiting embedded real-time analytics (MinSiDeg) project abstract

Sinter with high and consistent quality, produced with low costs and emissions is very important for iron production. Transport and storage degrade sinter quality, generating fines and segregation effects.

Conventional sinter quality monitoring is insufficient: Slow and expensive. Consequently, the impact of sinter quality on daily BF operation is extremely intransparent.

In MinSiDeg, new transfer systems and procedures will minimise degradation during transfer to save return fines and stabilise particle size distribution.

New on-line measurements will be established, combined and exploited with Big Data technologies. This break-through in continuous quality monitoring will enable combined optimisation of sinter plant and blast furnace.

Kick-off-Meeting for „Minimise sinter degradation between sinter plant and blast furnace exploiting embedded real-time analytics“ (MinSiDeg) in Linz

MinSiDeg objectives

Major objective of the project MinSiDeg is to clearly decrease costs and environmental impact of sinter plants and blast furnaces. To achieve this, the sinter quality will be optimised along the production chain improving both, sinter plant and blast furnace working.

The following general technical objectives are defined:

• quantify sinter quality fluctuations (minutes to several hours)
• intensify the exploitation of data by Big Data methods
• minimise sinter degradation by material handling
• make (physical) sinter quality transparent and more stable
• improve BF shaft permeability

MinSiDeg will realise the objectives by 3 main approaches (cf. Figure 1):

1. Online monitoring of physical sinter quality by new measurements
2. New equipment and material handling procedures along the transfer to the blast furnace
3. Real-time analytics of existing and new data streams for machine supported decisions

                                                                               Figure 1: Main approaches within the MinSiDeg concept.

MinSiDeg research approach

The project work will be organised within 5 technical work packages:

1. Improve sinter stability
2. Minimise sinter degradation along transport and storage
3. New online methods for sinter quality determination
4. Improve value of sinter for the blast furnace
5. Real-time machine supported decisions on sinter quality

The involved partners in this research project are

VDEh-Betriebsforschungsinstitut GmbH
thyssenkrupp Steel Europe AG
voestalpine Stahl GmbH
DK Recycling und Roheisen GmbH
K1-MET GmbH
Montanuniversität Leoben
The project leading to this application has received funding from the Research Fund for Coal and Steel under grant agreement No. 847334.

Project duration: 1 July 2019 – 31 December 2022 (42 months)

RealTimeCastSupport project abstract

Thermal and fluid-mechanical conditions in continuous casting moulds are only roughly known although highly relevant for the product quality. Manual process control is difficult due to the great number of influencing factors. Therefore, the aim of the research is the digitalisation and optimised control of continuous casting machines. Large data streams will considered online and assist the caster operators with a real-time support system. This system will provide suggestions for an optimised process control in real-time. It will be developed with application of new measuring techniques and representation of the casting machine by a digital twin.

The kick-off-meeting for the RFCS project “Embedded real-time analysis of continuous casting for machine-supported quality optimisation” (RealTimeCastSupport) took place on 1^st and 2^nd of October 2019 at premises of the coordinator BFI.

VDEh-Betriebsforschungsinstitut GmbH
AG der Dillinger Hüttenwerke
voestalpine Stahl GmbH
Materials Processing Institute (MPI)
Minkon SP ZOO

RealTimeCastSupport objectives

The main objective of the proposed research project is:

• Improved product quality in terms of reduction of hard spots on heavy plates and slivers on cold-rolled strips.

The main objective is accompanied by several sub-objectives which can be assigned to the already mentioned main components of the research project:

Online monitoring of tundish and mould with implementation of new measuring techniques

• Simultaneous temperature measurements at different positions in the tundish as well as in the mould and monitoring of the casting powder coverage.
• Online application of new measurement technologies FOTS and DynTemp® for temporally high resolving temperature.
• Implementation of IR-based 2D casting powder monitoring.

Exploitation of various CC data and surface inspection to predict reliability of steel production

• Offline material tracking, synchronisation of data streams and statistical analysis by application of big data technologies.
• Identification of defect promoting scenarios by correlation of casting powder monitoring, statistical results and hard spot as well as sliver detection.
• Realisation of an offline 3D digital twin of the CC tundish and mould considering transient steel melt flow including turbulence, filling level changes, heat transfer, inert gas feeding and solidification.
• Offline reproduction of the identified defect promoting scenarios with the 3D digital twin in order to find thermal and fluid mechanical reasons for the detected behaviour.

Advanced CC process control in real-time offering machine supported decisions

• Development of countermeasures against the defect promoting scenarios aiming at the adjustment of the thermal and fluid-mechanical caster status in order to strengthen the options for real-time process control. Assessment of their potential with the digital twin.
• Adjustment of operational windows for continuous caster operation aiming at an advanced process control.
• Development and testing of new mould powders and intumescent coatings aiming at modification and improved control of heat transfer in the mould.
• Modification of electromagnetic actuator’s operation mode.
• Offline identification of rules for the operation of the casting machine based on conclusions from measurements, statistical analysis and application of the 3D digital twin.
• Online application of a real-time support system with implementation of the defined rules.
• Online implementation of advanced real-time CC process considering large data streams.
• Verification of the effectivity of real-time support system during operational application.

RealTimeCastSupport research approach

Online monitoring of tundish and mould with implementation of new measuring techniques

Available measurement techniques

An important research approach of this project is the simultaneous temperature measurements at different positions in tundish as well as in the mould and the monitoring of the casting powder coverage. This will provide a deeper insight of the conditions in the casting machine depending on time, i.e. transient conditions like ladle or tundish changes can be analysed in detail. The results can then be connected to quality information, i.e. hard spots appearance on heavy plates as well as sliver appearance on cold-rolled strips. The online application of the new measurement technologies FOTS and DynTemp® for temporally high resolving temperature is scheduled as well as the implementation of IR-based 2D casting powder monitoring system. The figure below illustrates the availability and position of the utilised measuring techniques.

Additionally, already available measurements, analysis and online modelling results systems will be utilised for the real-time machine support system:

• Melt temperature in the ladle.
• Temperature in the copper mould plates measured with thermocouples.
• Sliver detection on the cold-rolled strips.

Exploitation of various CC data and surface inspection to predict reliability of steel production

A self-evident element of this project component is the material tracking and the synchronisation of the available data streams. It has to be ensured that the quality information, i.e. hard spots and sliver occurrence, can be assigned to the corresponding casting conditions. But the casting conditions are not only valid for a certain time. They were taken at different positions, i.e. measurements with regard to the determined product quality have to be taken at different times, e.g. melt temperature in the tundish and in the mould, casting powder cover and copper plate temperatures. They have to be synchronised knowing well that different techniques show different idleness, e.g. temperature measurements in the copper plates react slower on melt temperature changes than the DynTemp® measurements. Material tracking algorithms are already available at the steel plants of the industrial partners. They will be used in the frame of the research project. Synchronisation of the measured data will be worked out in the frame of the comprehensive statistical analysis.

For the analysis and assessment of the mentioned data different methods from Data Mining and Big Data analytics will be used. For the computations with the 3D digital twin the analysis of influencing factors of casting is necessary in order to find the target parameter, e.g. the occurrence of hard spots. Therefore, a common analysis of the casting parameters, i.e. the various temperature measurements in tundish and mould and the results of image processing, will be executed by means of Data Mining methods in a first step. Several methods like Decision Tree analysis, artificial neural networks, e.g. Self Organising Map or Deep Learning methods, and others will be applied to detect relationships between the input parameters and the target one. The aim is to identify those inputs – or derived features- which are influencing mainly the target parameter. By the derived subset of input values a digital twin of the casting machine, i.e. a transient CFD model of the considered casting machine, will be developed in order to estimate the impact of altered parameters on product quality features. The findings will be integrated in the real-time support system by the definition of a set of rules describing possible countermeasures. The real-time support system will provide information about possible critical process conditions causing defects and will support operators to find appropriate countermeasures, i.e. it supports the decision making.

Based on these findings measures for an improved thermal and fluid-mechanical process control will be worked out and their potential for thermal and fluid-mechanical process control will be checked with the digital twin. These developed countermeasures will be tools which strengthen the options for real-time process control in the machine support system.

Advanced CC process control in real-time offering machine supported decisions

The chart below shows the organisation of the scheduled real-time support system with the different modules contributing to this system. Comprehensive temperature measurements in tundish and mould as well as the monitoring of the casting powder cover provide the basis for this approach. On the one hand, these data will be utilised for the offline statistical data analysis aiming at an assessment of the casting process and correlations with the corresponding product quality. On the other hand, measurements and monitoring will provide an online basis for the real-time support system. Here the defined rules for an advanced process control will be evaluated in real-time and the status of the casting machine will be judged, e.g. realised as a traffic light.

                                                    Organisation of the real-time support system

The project leading to this application has received funding from the Research Fund for Coal and Steel under grant agreement No. 847334. On 1./2. October 2019 was the kick-off meeting in the BFI. http://www.bfi.de/en/2019/10/16/kick-off-meeting-realtimecastsupport-october-1st-2nd-in-dusseldorf/

A workshop was held on Sep 08^th, 2023 via Teams. The webinar presented key findings and discussed possible perspectives.

Please watch the video.

The 6 presentations of the RealTimeCastSupport workshop can be downloaded here.

1_RTCS_Webinar_Introduction

2_RTCS_Webinar_Measurement techniques BFI

3_RTCS_Webinar_Exploitation of various CC data

4_RTCS_Webinar_Digital Twin

5_RTCS_Webinar_Conclusions

6_RTCS_Webinar_Outlook

This project has received funding from the Research Fund for Coal and Steel under grant agreement No 847334.