The Influence of the Leveling Process on the Local Material Properties of Heavy Steel Plates

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@phdthesis{bd8de52368974134aa719f2451655f0a,
title = "The Influence of the Leveling Process on the Local Material Properties of Heavy Steel Plates",
abstract = "Increasing customer specifications and decreasing tolerances for the mechanical properties of heavy steel plates necessitate sound knowledge of the influence of all consecutive process steps during the manufacturing. In order to meet the demanded specifications and to increase the share of first-time-right products computer based process chain simulation is employed. Heavy steel plates are often manufactured via thermomechanical processing, whereby the last process step is usually the leveling process. Leveling belongs to the class of rectification processes that aim at the improvement of flatness and the reduction of undesired residual stresses. Furthermore, the mechanical properties as for instance the yield strength and the ultimate tensile strength will be altered by leveling. The heavy plate passes through the rolls of the leveler and is alternatingly bent upwards and downwards thereby subjecting the material to cyclic tension and compression with decreasing strain magnitude. Even if constant mechanical properties across the plate thickness are assumed before the leveling operation starts the plastic strain gradient imposed by plastic bending may induce a gradient in the final properties after leveling. The focus of the present thesis is dedicated to the characterization and prediction of the local material strength evolution due to the leveling process. The aim is to establish a tool which is capable to predict the spatial resolved strength distribution as well as an integral value for the strength of the entire plate cross section. To this end a threefold approach is chosen: (i) the systematic experimental characterization of the material behavior, (ii) the modeling of the entire leveling process which has been split into the development of a process model and a predictor model and (iii) the definition of an efficient predictor tool emerging from model reduction of the previously mentioned predictor model. Within the relevant temperature regime, the material behavior is investigated using cyclic experiments for tensile and bending samples on the one hand, and experiments performed with the real leveling machine on the other hand. The insights gained from the experiments about the change of the mechanical properties after plastic deformation characteristic for leveling are to be implemented in a proper material model. For a particular leveler setup, a finite element based process model is employed to calculate the total strain history. These strains are used in the predictor model to forecast the resulting change of the strength distribution along the plate thickness and additionally a representative integral value for the entire plate thickness. The physically motivated material law implemented in the predictor model includes the full complexity observed from the experiments and serves as reference for a reduced predictor tool. Particularly, the predictor tool is optimized with respect to the calculation time for the relevant leveling scenarios in the actual production process.",
keywords = "Heavy Steel Plates, Modeling and Simulation, Local Material Properties, Property Prediction, Process Conrol, Grobblech, Modellierung und Simulation, Lokale Materialeigenschaften, Eigenschaftsprognose, Prozesskontrolle",
author = "Thomas Kaltenbrunner",
note = "embargoed until 14-08-2023",
year = "2018",
language = "English",
school = "Montanuniversitaet Leoben (000)",

}

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TY - BOOK

T1 - The Influence of the Leveling Process on the Local Material Properties of Heavy Steel Plates

AU - Kaltenbrunner, Thomas

N1 - embargoed until 14-08-2023

PY - 2018

Y1 - 2018

N2 - Increasing customer specifications and decreasing tolerances for the mechanical properties of heavy steel plates necessitate sound knowledge of the influence of all consecutive process steps during the manufacturing. In order to meet the demanded specifications and to increase the share of first-time-right products computer based process chain simulation is employed. Heavy steel plates are often manufactured via thermomechanical processing, whereby the last process step is usually the leveling process. Leveling belongs to the class of rectification processes that aim at the improvement of flatness and the reduction of undesired residual stresses. Furthermore, the mechanical properties as for instance the yield strength and the ultimate tensile strength will be altered by leveling. The heavy plate passes through the rolls of the leveler and is alternatingly bent upwards and downwards thereby subjecting the material to cyclic tension and compression with decreasing strain magnitude. Even if constant mechanical properties across the plate thickness are assumed before the leveling operation starts the plastic strain gradient imposed by plastic bending may induce a gradient in the final properties after leveling. The focus of the present thesis is dedicated to the characterization and prediction of the local material strength evolution due to the leveling process. The aim is to establish a tool which is capable to predict the spatial resolved strength distribution as well as an integral value for the strength of the entire plate cross section. To this end a threefold approach is chosen: (i) the systematic experimental characterization of the material behavior, (ii) the modeling of the entire leveling process which has been split into the development of a process model and a predictor model and (iii) the definition of an efficient predictor tool emerging from model reduction of the previously mentioned predictor model. Within the relevant temperature regime, the material behavior is investigated using cyclic experiments for tensile and bending samples on the one hand, and experiments performed with the real leveling machine on the other hand. The insights gained from the experiments about the change of the mechanical properties after plastic deformation characteristic for leveling are to be implemented in a proper material model. For a particular leveler setup, a finite element based process model is employed to calculate the total strain history. These strains are used in the predictor model to forecast the resulting change of the strength distribution along the plate thickness and additionally a representative integral value for the entire plate thickness. The physically motivated material law implemented in the predictor model includes the full complexity observed from the experiments and serves as reference for a reduced predictor tool. Particularly, the predictor tool is optimized with respect to the calculation time for the relevant leveling scenarios in the actual production process.

AB - Increasing customer specifications and decreasing tolerances for the mechanical properties of heavy steel plates necessitate sound knowledge of the influence of all consecutive process steps during the manufacturing. In order to meet the demanded specifications and to increase the share of first-time-right products computer based process chain simulation is employed. Heavy steel plates are often manufactured via thermomechanical processing, whereby the last process step is usually the leveling process. Leveling belongs to the class of rectification processes that aim at the improvement of flatness and the reduction of undesired residual stresses. Furthermore, the mechanical properties as for instance the yield strength and the ultimate tensile strength will be altered by leveling. The heavy plate passes through the rolls of the leveler and is alternatingly bent upwards and downwards thereby subjecting the material to cyclic tension and compression with decreasing strain magnitude. Even if constant mechanical properties across the plate thickness are assumed before the leveling operation starts the plastic strain gradient imposed by plastic bending may induce a gradient in the final properties after leveling. The focus of the present thesis is dedicated to the characterization and prediction of the local material strength evolution due to the leveling process. The aim is to establish a tool which is capable to predict the spatial resolved strength distribution as well as an integral value for the strength of the entire plate cross section. To this end a threefold approach is chosen: (i) the systematic experimental characterization of the material behavior, (ii) the modeling of the entire leveling process which has been split into the development of a process model and a predictor model and (iii) the definition of an efficient predictor tool emerging from model reduction of the previously mentioned predictor model. Within the relevant temperature regime, the material behavior is investigated using cyclic experiments for tensile and bending samples on the one hand, and experiments performed with the real leveling machine on the other hand. The insights gained from the experiments about the change of the mechanical properties after plastic deformation characteristic for leveling are to be implemented in a proper material model. For a particular leveler setup, a finite element based process model is employed to calculate the total strain history. These strains are used in the predictor model to forecast the resulting change of the strength distribution along the plate thickness and additionally a representative integral value for the entire plate thickness. The physically motivated material law implemented in the predictor model includes the full complexity observed from the experiments and serves as reference for a reduced predictor tool. Particularly, the predictor tool is optimized with respect to the calculation time for the relevant leveling scenarios in the actual production process.

KW - Heavy Steel Plates

KW - Modeling and Simulation

KW - Local Material Properties

KW - Property Prediction

KW - Process Conrol

KW - Grobblech

KW - Modellierung und Simulation

KW - Lokale Materialeigenschaften

KW - Eigenschaftsprognose

KW - Prozesskontrolle

M3 - Doctoral Thesis

ER -