List of topics and subtopics

The presentations of the second workshop have been organized in relevant topics for EAF technology. For each topic a set of sub-topics has been defined, in order to better organize the presentations and guide the discussion. A questionnaire has been distributed to stakeholders for ranking the relevance of the topics and subtopics.

list of topics and sub-topics

Advanced modelling

1

Higher integration between measurements and dynamic models

2

Development of software sensors (virtual sensors)

3

Implementation of Data Reconciliation techniques to resolve inconsistencies between plant measurements and mass and energy balances throughout the plant

4

Development and implementation of thermodynamic model of gas and slag

5

Integration of thermodynamic and fluidynamic modelling

6

Improvement and implementation of multi objective optimization techniques and intelligent manufacturing approach

7

Modelling Superstructures for conceptual design and optimization of cycles

   

Sustainability (energy recovery and environment)

1

Recovery of the maximum level of energy from hot gases (from >1500 to 250°C or less) with high dust loads

2

Efficient heat transfer solutions for high temperature solids like slags maintaining the by-products physical & chemical characteristics

3

Cross-sectorial approaches for the use of by-products and the recycling of residues

4

Certified products out of residues/wastes

5

Methodologies, tools and indicators for sustainability assessment of energy and resource efficient solutions

6

Synergetic networks of nearby plants to use recovered energy in the most effective way

7

Reduction of the ROI of technologies already available for resource and energy recovery & utilization

8

New generation of sensors and process control systems allowing synchronized regulation of global and local working conditions

9

Process integration (EAF + LF + CC)

10

Use of C based materials (i.e. biochar, plastics)

11

Use of scrap substitutes (i.e. DRI, scale)

12

Use of low quality scrap (charge optimisation)

13

Residual valorisation (i.e. slag, dust)

14

Heat recovery from off-gas and slag with low environmental impact (i.e. HE with fast cooling)

15

Reduction of emissions (i.e. dioxins, NOx)

   

Scrap control

1

Improved accuracy of chemical analysis of indivudial scrap pieces (LIBS, xrf, etc.)

2

Improved accuracy of chemical analysis and mass-flow rate of scrap flows (LIBS, gamma ray, etc.)

3

Bulk analysis for heavy scrap or baskets/trucks (gamma ray or hyperspectral analysis)

4

Validation/modification of estimated scrap properties by feedback regarding systematic deviations from expected process results (calculated by process models) in connection to use of specific grades

5

Improved density measurements of scrap (individual grades)

6

Improved density measurements of scrap mixes (loaded in baskets of furnace)

7

Objective reference measurements for filling degree in baskets and furnace needs

8

Demonstration of methods for automatic updating of estimations of scrap proerties using statistical regression

9

Feedback regarding systematic deviations from expected process results in connection to use of specific scrap grades need to be considered when updating estimations of scrap properties.

10

Development of scrap mix optimisation tools integrated with stock levels, market availability, production queue and customer order lists

11

Development or improvement of methods for Scrap pre-treatment and Pre-heating

12

Scrap mix optimisation for new EAF concepts (Quantum, COSS, Telescope EAF, etc.)

13

Research regarding optimisation of shredders and/or sorting methods combined with melting tests (lab/pilot/industrial scale)

14

Investigations about scrap quality degradation in combination with cost effective charge mix optimisation

15

Integration of scrap mix optimisation with up/downstream processes (e.g. use of clean scrap in the EAF or refining in LF, custimised DRI/HBI production, alloyed scrap in EAF or ferro alloys in LF)

   

Sensor technology

1

Implementation of promising optical measurement techniques such as LIBS or fibre-optical temperature measurement

2

In-line liquid steel temperature measurement

3

In-line liquid steel analysis (especially P content)  

4

Off-gas temperature and flow rate measurement

5

Monitoring of carbon injection systems

6

Monitoring / Imaging of closed / airtight furnace                                           

7

Accurate hot heel level measurement / slag height measurement

8

Assessment of scrap meltdown behaviour for optimal timing of second basket charging

   

Dynamic process control

1

Application of dynamic process models for end-point control regarding steel temperature and analysis

2

Utilisation of further sensor information as input for dynamic model calculations for an extended online process monitoring and control

3

Meltdown behaviour of scrap

4

Amount of hot heel   

5

Further extension of dynamic EAF process models for on-line control in the refining phase  (deP, slag reduction)

6

Closed-loop control of electrical and chemical energy input by model-based set point calculations                                                   

7

Support of dynamic model calculations by continuous measurements for liquid steel temperature as well as liquid steel and slag composition

8

Use of off-gas analysis for fully dynamic closed loop control of all sources of chemical energy input (oxygen and carbon injection)

9

Detection of inaccuracies and variations in charge material properties by statistical methods, to reduce their impact on performance of process models and operation practices

10

Dynamic control of electrical parameters depending on the charge material mix (e.g. scrap density)    

11

Through process control of the complete process chain of electric steelmaking to allow a multi-criterial optimisation of all quality relevant process parameters

12

Control of electrical energy demand due to fluctuating energy supply