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Logo: Institut für Kontinuumsmechanik/Leibniz Universität Hannover
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Logo: Institut für Kontinuumsmechanik/Leibniz Universität Hannover
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Improving Accuracy and Performance of Meshfree Methods

Project coordinators: Christian Weißenfels, Peter Wriggers

Simulation driven engineering is nowadays an essential part in the development process. Especially in the field of subtractive or additive manufacturing their is an increasing interest on high fidelity modeling. Due to their flexibility meshfree solution schemes are very attractive for the simulation of such processes which involve intrinsic and varying discontinuities.

Many meshfree methods were developed over the years. However all of these schemes to model continua need either special stabilization algorithm, regularization techniques or correction schemes to reproduce the behavior of academic test examples. However, even an approximate prediction of real dynamic systems can not be guaranteed with these methods. Additionally, unphysical parameters have to be determined, if such stabilization, regularization or correction schemes are used.

Nevertheless, in order to be able to make reliable statements in the high fidelity modeling of engineering applications the need on more flexible solution schemes which ensures robustness, efficiency and accuracy is still present.

The shortcomings of truly meshfree methods result mostly from a violation of mathematical requirements on computational solution schemes, like the consistency conditions or the integration constraint. Additionally, phenomena like under-integration can likely occur.

A meshfree solution scheme which exhibits the same accuracy as the meshbased Finite Element Method, which can be applied for all engineering application cases and which is robust and efficient is still not found.

Projekte: Netzfreie Methoden

Using Machine Learning to Improve the Modelling of Machining and Cutting Processes

Bild zum Projekt Using Machine Learning to Improve the Modelling of Machining and Cutting Processes

Leitung:

C. Weißenfels, P. Wriggers

Bearbeitung:

M.Sc. Dengpeng Huang

Förderung durch:

China Scholarship Council (CSC)

Kurzbeschreibung:

Metal cutting is a fundamental process in industrial production. The fast and accurate on-line prediction of metal cutting processes is crucial for the Intelligent Manufacturing (IM). With the advent of high-speed computing, robust numerical algorithms and machine learning technology, computational modelling serves as a tool for not only accurate but also fast predicting the complex machining processes and understanding the complex physics. In this work, the machine learning based numerical model is developed for simulation of metal cutting processes.

 

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ISPH-based Simulation of the Selective Laser Melting Process

Bild zum Projekt ISPH-based Simulation of the Selective Laser Melting Process

Leitung:

Christian Weißenfels, Peter Wriggers

Bearbeitung:

M.Sc. Jan-Philipp Fürstenau

Kurzbeschreibung:

Development of a thermo-mechanical model for the simulation of the SLM process.

 

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Process Simulation for Selective Laser Melting

Bild zum Projekt Process Simulation for Selective Laser Melting

Leitung:

Christian Weißenfels, Peter Wriggers

Bearbeitung:

M.Sc. Henning Wessels

Kurzbeschreibung:

A phase change model for solution with the meshfree Galerkin OTM method is developed.

 

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3D-Printing of Curing Polymers

Bild zum Projekt 3D-Printing of Curing Polymers

Leitung:

Christian Weißenfels, Peter Wriggers

Bearbeitung:

M.Sc. Philipp Hartmann

Förderung durch:

DFG (Graduiertenkolleg 1627)

Kurzbeschreibung:

3D-Printing simulations of curing polymers within the concept of Peridynamics are developed.

 

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