TY - BOOK

T1 - Process Models for the Manufacturing of Railway Components

AU - Bialowas, Jakob

N1 - no embargo

PY - 2023

Y1 - 2023

N2 - The railway industry plays a pivotal role in global transportation, necessitating the development of efficient and reliable railway components. This thesis focuses on advancing the manufacturing process of these components through the development of process models. These models aim to optimize component performance, enhance safety, and promote sustainability within the railway industry. Process models including advanced material models allow for understanding and optimizing not only the manufacturing processes but also the in-service conditions that arise. Within the context of railway components, these models provide valuable insights into the material behavior and guide the optimization of these processes. By accurately predicting residual stresses, the stress redistribution, and the influencing process parameters, these process models contribute to improve and better understand the behavior of railway components. This thesis presents a novel process model specifically designed for the cold rolling of wheelset axles with the finite element method. This advanced model incorporates cyclic material behavior, various process parameters, and geometrical features to precisely predict the residual stress distribution across the entire cross section of the wheelset axle. By incorporating and combining smart periodic boundary conditions, a notable reduction in model size and computation time is achieved, while maintaining the integrity of the results. Notably, the process model developed for the cold rolling of wheelset axles enhances the accuracy of the prediction of the residual stress state compared to previous approaches. Additionally, this thesis addresses the manufacturing process of railway wheels, focusing on the influence of heterogeneously distributed solid phases of steel. An advanced material model is developed to accurately capture localized effects during the heat treatment, including phase transformations and transformation induced plasticity. To adequately represent the intricate material behavior within a finite element process model, precise coordination among experiments, mathematical and physical models for changing material properties, and the finite element model of the process itself is imperative. Such a material model provides comprehensive insights into the behavior of the railway steel ER7, while the developed process model allows to understand the stress evolution of a railway wheel in various and rapidly changing conditions. In summary, this thesis contributes to the advancement of the manufacturing of railway components. The established process models provide deep insights into the development of residual stresses and stress redistribution of railway components enabling a further process optimization.

AB - The railway industry plays a pivotal role in global transportation, necessitating the development of efficient and reliable railway components. This thesis focuses on advancing the manufacturing process of these components through the development of process models. These models aim to optimize component performance, enhance safety, and promote sustainability within the railway industry. Process models including advanced material models allow for understanding and optimizing not only the manufacturing processes but also the in-service conditions that arise. Within the context of railway components, these models provide valuable insights into the material behavior and guide the optimization of these processes. By accurately predicting residual stresses, the stress redistribution, and the influencing process parameters, these process models contribute to improve and better understand the behavior of railway components. This thesis presents a novel process model specifically designed for the cold rolling of wheelset axles with the finite element method. This advanced model incorporates cyclic material behavior, various process parameters, and geometrical features to precisely predict the residual stress distribution across the entire cross section of the wheelset axle. By incorporating and combining smart periodic boundary conditions, a notable reduction in model size and computation time is achieved, while maintaining the integrity of the results. Notably, the process model developed for the cold rolling of wheelset axles enhances the accuracy of the prediction of the residual stress state compared to previous approaches. Additionally, this thesis addresses the manufacturing process of railway wheels, focusing on the influence of heterogeneously distributed solid phases of steel. An advanced material model is developed to accurately capture localized effects during the heat treatment, including phase transformations and transformation induced plasticity. To adequately represent the intricate material behavior within a finite element process model, precise coordination among experiments, mathematical and physical models for changing material properties, and the finite element model of the process itself is imperative. Such a material model provides comprehensive insights into the behavior of the railway steel ER7, while the developed process model allows to understand the stress evolution of a railway wheel in various and rapidly changing conditions. In summary, this thesis contributes to the advancement of the manufacturing of railway components. The established process models provide deep insights into the development of residual stresses and stress redistribution of railway components enabling a further process optimization.

KW - finite element simulation

KW - heat treatment

KW - coldrolling

KW - residual stresses

KW - Finite Elemente Simulation

KW - Wärmebehandlung

KW - Festwalzen

KW - Eigenspannungen

U2 - 10.34901/mul.pub.2023.196

DO - 10.34901/mul.pub.2023.196

M3 - Doctoral Thesis

ER -