Hydro value chain. Trond Furu, Dr.ing/Prof. Hydro Corporate Technology Office (1)

Transcription

1 Through-processmodelling along the Hydro value chain Trond Furu, Dr.ing/Prof. Hydro Corporate Technology Office (1)

2 Content Introduction Examples of modelling activities in Hydro Physical/Microstructure Based Modelling PROfit generation through PROduct and PROcess optimisation (PRO 3 ) Summary (2)

3 Introduction

4 A resource-rich, global aluminium company With robust positions across the value chain Bauxite & Alumina Energy Primary Metal Rolled Products Extrusion joint venture Global provider of alumina, aluminium and aluminium products Leading businesses along the value chain; raw materials, energy, primary metal production, aluminium products and recycling employees involved in activities in more than 50 countries Market capitalization ~NOK 75 billion Annual revenues ~NOK 65 billion Included in Dow Jones Sustainability Indices and FTSE4Good (3)

5 The Hydro value chain Technology Crude oil quality Raw materials Coke Anode quality Furnaceoperation Filtration Homogenization. TP* Forming operations Refinery technology (5) Raw materials Alumina Bauxite quality Fuel quality Oxide quality Primary Potline techn. Liquid metal Casting Casting techn. EI, SI, FA ingots Recycling Fabrication Sorting and upgrading * TP = Thermo mechanical processing (extrusion, rolling) Annealing Sheet Profiles Customer processes Surface treatment

6 Why modelling? In all R&D sectors of Hydro modelling is seen as an important R&D tool to serve the clients and Hydro customers in the most efficient way Shortening of time for development Saving of resources Enabling designs and developments Facts vs. speculations Cost-efficient designs Models are knowledge banks Unique process knowledge of rolling, extrusion, primary production, casting, alumina, is stored in the models and can be utilized by Hydro personnel

7 Why modelling? Models in Technical Support Competence building through the use of simulation tools in training of new R&D colleagues HES: Avoid hazardous situations by simulations Sensitivity analyses

8 Tough requirements from demanding customers drive innovation BMW: alloy development and modelling Audi: simulation to replace prototypes Oil &Gas, Consumer electronics: Key: combine macro and micro models for faster development and validation of solutions

9 Examples of modelling activities in Hydro

10 Simulation of flow in the slurry pipeline from Paragominas Simulation of flow pattern in the metal of an electrolysis pot Simulation of heat distribution in casthouse furnace during remelting of scrap Burner inlet Liquid metal Process simulation SolidSim for a Alumina plant Simulation of magnetic fields in an electrolysis pot Simulation to improve stirring and reduce melting duration (10)

11 Microstructure based models as a basis for process- and product-simulations Extrusion simulations Weld simulations DC-casting simulations Rolling simulations Mould casting Microstructure based models NaMo Alsoft 3IVM GIA ClaNG Alflow Alprop Alstruc Forming simulations Crash simulations Load bearing capacity Corrosion predictions

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13 Through Process Modelling in Rolled Products Simulation of microstructure and resulting properties during production of Al 6xxx sheet ClaNG model allows modelling the evolution of micro-chemistry (solutes,particles) along the process chain Simulation of age-hardening response Co-operation between RDB and RTD where the microstructure model NaMo was included in the simulation

14 Physical/microstructure- Based Modelling

15 Microstructure based models as a basis for process- and product-simulations Microstructure based models NaMo Alsoft 3IVM GIA ClaNG Alflow Alprop Alstruc

16 New experimental and modelling techniques New insight might improve properties even further Experimental techniques Atmomistic modelling Al 1 nm 1 nm Interfaces Diffusivities Precipitates Dislocations Grain boundaries Thermodynamics

17 Top-down vs. Bottom-up approach Engineering Structure System Continuum Component Joint RVE 4 Material 5 Discrete 5 Microstructure Atomic scale nm μm mm cm m Ref.: Prof. Magnus Langseth, SIMLab

18 (18) PROfit generation through PROduct and PROcess optimisation (PRO 3 )

19 Tough requirements from demanding customers A range of properties (i.e. a property profile ) must be according to customer expectations and requirements Property profile Castability Extrudability Corrosion Conductivity Customer requirements Fracture Formability Ductility Strength

20 PRO 3 -concept (20)

21 General Methodology (21)

22 Case: Extruded profiles for busbars in electrical applications Bus-bar Medium voltage power converter cabinets Objective: Find optimal solution of alloy and processing parameters on electrical conductivity and strength (>140 MPa) (22)

23 Electrical conductivity of Aluminium The maximum electrical conductivity of Al 99,99 is 37,67 MS/m Addition of alloying elements will increase the electrical resistivity. The effect from individual elements in solid solution is given by Mathiesen s rule (1) The following microstructural parameters developed during processing will influence electrical conductivity Elements in solid solution Particles Grain boundaries Dislocations Requirements on mechanical strength will have a strong impact on electrical properties, see table Alloy Conductivité MS/m Résistivité x10-8.m %IACS Rm (MPa) Al 99,99 37,67 2,655 64, (Al 99,95) 35,84 2,790 61, (Al 99) 33 3,030 56, (1) Mathiessen s rule) Electrical resistivity = 0, ,032 Fe + 0,0068 Si + 0,0051 Mg + 0,036 Mn + 0,080 Cr + 0,0078 Cu

24 Methodology applied on the extrusion value chain PRO 3TM PROCESSES DC - casting Homogenizing Extrusion Cooling Ageing Input data Customer Requirements After final simulation Optimization tool MODELS Property models Cost models Alstruc Sol. HalOpt Alstruc Hom. Cost vs time Extrusion model Cost vs speed Alsoft NaMo Cost vs time Properties Costs CO2/Env. Iterations Limitations

25 Workflow in ModeFrontier 25 Rune Østhus, SINTEF Raufoss Manufacturing Green boxes: "input" variable Light blue boxes: "output" variable Black boxes: Expert nodes Excel logo: Meta models Calculator: Value extraction

26 Optimisation of conductivity and mechanical properties for bus-bars (26)

27 A first attempt to optimise COSTS/PROCESSABILITY, CO 2 -FOOTPRINT and PROPERTIES kg CO 2 per kg Al produced considering electrolyses and remelting of scrap metal Yield stress (MPa) Hot Metal Cost (Scaled) (27)

28 Summary Simulation and modelling in Hydro has been going on for more than 25 years in various sectors Many of the models have become sufficiently accurate and user-friendly interfaces are established. Long term R&D efforts, as well as recent developments in software and hardware enable us to carry out simulation through the value chain, and predict resulting properties. The PRO 3 -methodology has the potential to find optimal property profiles and cost/environmental solutions of complicated processes and product requirements. (28)

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