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Hardcover. Zustand: Near Fine. Dust Jacket Included. 1st Edition. 256 pages, a near fine hardback in a near fine dust-jacket [0300005369].

Taschenbuch. Zustand: Neu. Modeling the Material Behavior under Metal Cutting Conditions | Marvin Hardt | Taschenbuch | Englisch | 2022 | Apprimus Verlag | EAN 9783985550456 | Verantwortliche Person für die EU: Apprimus, Steibachstr. 25, 52074 Aachen, info[at]iif[dot]rwth-aachen[dot]de | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The scientific goal of the present work was to model the workpiece material behavior of steels in the metal cutting process depending on the occurring thermo-mechanical loads. The results of this work shall make a significant contribution to the predictive process design of the cutting process by means of Finite Element (FE) simulations for the virtual representation of the reality in the sense of the digital twin.To achieve the objective, extensive empirical examinations were conducted in a first step, which included conventional material scientific and orthogonal cutting tests. This enabled the establishment of a database of the workpiece response with increasing thermo-mechanical loads. During the orthogonal cutting examinations, integral and locally resolved process results were measured, which were used as calibration and validation variables in the modeling of the workpiece material behavior.By extending an established friction test bench with a workpiece pre-heating system, the friction conditions between tool and workpiece could be investigated under conditions equivalent to the cutting process. Based on the experimental results, a friction model was derived, in which the observed effects of thermal softening and the localized adhesion-induced increase in the apparent friction coefficient were superposed. A phenomenological material model was developed to describe the workpiece material behavior in the cutting process. The formulation of the material mode was developed based on empirical examinations as well as results from the state of the art. The material model was implemented in an FE-chip formation simulation using a subroutine. A hybrid optimization algorithm was developed to inversely determine the material model parameters. By means of the optimization algorithm, the material model parameters could be systematically determined inversely, taking the experimentally determined process observables into account. An automated procedure linked to a user interface lowered the entry hurdle for industrial companies and unexperienced users of FE-simulations and reduced the computational effort for the inverse parameter determination to about 10 days of computational execution time. The quality of the developed models and the determined model parameters were further verified by a final deduction step using the industrial example of face turning. 202 pp. Englisch.…

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Within this thesis, the material and friction behavior of steels under metal cutting conditions was investigated. To model the material behavior under these conditions, a new material and friction model was developed. An inverse procedure was originated for.…

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Within this thesis, the material and friction behavior of steels under metal cutting conditions was investigated. To model the material behavior under these conditions, a new material and friction model was developed. An inverse procedure was originated for the determination of the material model parameters, utilizing a novel hybrid optimization algorithm. The results of the simulations showed a close agreement with their corresponding experimental cutting examinations.Books on Demand GmbH, Überseering 33, 22297 Hamburg 202 pp. Englisch.…

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The scientific goal of the present work was to model the workpiece material behavior of steels in the metal cutting process depending on the occurring thermo-mechanical loads. The results of this work shall make a significant contribution to the predictive process design of the cutting process by means of Finite Element (FE) simulations for the virtual representation of the reality in the sense of the digital twin.To achieve the objective, extensive empirical examinations were conducted in a first step, which included conventional material scientific and orthogonal cutting tests. This enabled the establishment of a database of the workpiece response with increasing thermo-mechanical loads. During the orthogonal cutting examinations, integral and locally resolved process results were measured, which were used as calibration and validation variables in the modeling of the workpiece material behavior.By extending an established friction test bench with a workpiece pre-heating system, the friction conditions between tool and workpiece could be investigated under conditions equivalent to the cutting process. Based on the experimental results, a friction model was derived, in which the observed effects of thermal softening and the localized adhesion-induced increase in the apparent friction coefficient were superposed. A phenomenological material model was developed to describe the workpiece material behavior in the cutting process. The formulation of the material mode was developed based on empirical examinations as well as results from the state of the art. The material model was implemented in an FE-chip formation simulation using a subroutine. A hybrid optimization algorithm was developed to inversely determine the material model parameters. By means of the optimization algorithm, the material model parameters could be systematically determined inversely, taking the experimentally determined process observables into account. An automated procedure linked to a user interface lowered the entry hurdle for industrial companies and unexperienced users of FE-simulations and reduced the computational effort for the inverse parameter determination to about 10 days of computational execution time. The quality of the developed models and the determined model parameters were further verified by a final deduction step using the industrial example of face turning.…