Modelling Approaches for Optimization of Heavy Plate Steels for Pressure Vessel Application 10.03.2017, Prof. Dr.-Ing. Andreas Kern; Dipl.-Kffr. Esther Pfeiffer ; Dipl.-Ing. Klaus Janhofer; Peter Walter thyssenkrupp Steel Europe; Heavy Plate Unit

Production and application of heavy plate 3rd Steel Plate Conference-Düsseldorf

Production of high-strength steels for pressure vessels Process 275 - 460 normalizing, normalizing rolling N temperature time A c 3 normalizing 300 - 550 350 - 690 thermomechanical rolling TM accelerated cooling AC A r 3 temperature time 550 - 1100 (direct) quenching and tempering (D)QT A c 3 temperature time hardening 1 tempering Treatment Microstructure Yield strength, MPa 3rd Steel Plate Conference-Düsseldorf

Benefits and application of modeling Fields of application Pre-calculation of mechanical properties Identification of significant influencing variables Fast optimization of chemical composition and production conditions Shorter test-phases for new steels Assessment of performance and risk Case studies Technical processing of customer inquiries Approval of heats Planning of plant trials Homogenization of analysis concepts Product optimization 3rd Steel Plate Conference-Düsseldorf

Concept of pre-calculation model Simulation Knowledge Quantitative description of metallurgical processes via physically based equations etc. Metall. mechanisms i.e. Grain coarsening Recrystallization Transformation Mathematical model Process step Heating Rolling Cooling Four-high mill Chemical composition, production conditions Properties 3rd Steel Plate Conference-Düsseldorf

Different usage of a simulation model – Top-Down or Bottom-Up Start Result Chemical composition Production conditions Top-Down principle Bottom-Up priciple Simulation (Mathematical model) Mechanical properties Result Start 3rd Steel Plate Conference-Düsseldorf

Verification of modeling – Comparison of measured and calculated values 95% Confidence interval Tensile strength measured, MPa Yield strength measured, MPa Yield strength calculated, MPa Tensile strength calculated, MPa 3rd Steel Plate Conference-Düsseldorf

Application of modeling: Optimization of alloying concepts for normalized pressure vessel steels Target: Reduction of cost-intensive alloying components Cu and Ni Keeping mechanical properties and carbon equivalent constant 3rd Steel Plate Conference-Düsseldorf

Bottom-up-application using Monte-Carlo-algorithm Random selection of the chemical composition and the production conditions Solution area schematic Chemical analysis Objective criteria Production conditions Calculating of the objective criteria (Re, Rm …) n = n +1 Restrictions are met? no yes Save the result (solution) Statistical analysis of the solutions (n=N) n≤N N: Number of attempts 3rd Steel Plate Conference-Düsseldorf

Bottom-up-application: Results of an optimization calculation after statistical analysis (schematic) min . max Carbon, wt % Manganese, wt % Niobium, wt % Chromium, wt % x̃ Cumulation rate x̃ : characteristic results of the bottom-up-application 3rd Steel Plate Conference-Düsseldorf

Results of modeling: New concepts for pressure vessel steels (exemplarily) Modeling of material properties P265 – P355/ASTM A 516 Gr. 60 -70 Chemical composition, max [%] old new * Carbon [%] Silicon [%] Manganese [%] Chromium [%] Copper [%] Nickel [%] 0,20 0,30 1,20 0,05 0,25 0,16 0,30 1,10 0,20 Targetted properties Properties Production parameters Chemical composition * Occasionally microalloying with Nb 3rd Steel Plate Conference-Düsseldorf

Estimation of property profile of newly developed pressure vessel steels Grade A 516 Gr. 60 -70 Attempts: 5000 Re min Rm min Cumulation rate Cumulation rate Cumulation rate Cumulation rate Cumulation rate Cumulation rate Cumulation rate Cumulation rate 3rd Steel Plate Conference-Düsseldorf

Comparison of mechanical properties of different alloying concepts (steel grade: A516 Gr.60) 3rd Steel Plate Conference-Düsseldorf

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