Module Description

Module: Multiphase Materials

Courses:

TitleTypeHrs/WeekPeriod
Applied Computational Methods for Material ScienceProject-/problem-based Learning3Winter Semester
Polymer CompositesLecture2Winter Semester

Module Responsibility:

Prof. Robert Meißner

Admission Requirements:

None

Recommended Previous Knowledge:

Knowledge in basics of polymers, physics and mechanics/micromechanics

Educational Objectives:

Professional Competence

Theoretical Knowledge

Students can

- explain the complex relationships of the mechanics of composite materials, the failure mechanisms and physical properties.

- assess the interactions of microstructure and properties of the matrix and reinforcing materials.

- explain e.g. different fiber types, including relative contexts (e.g. sustainability, environmental protection).

They know different methods of modeling multiphase materials and can apply them.

Capabilities

Students are capable of

- using standardized methods of calculation and modeling using the finite element method in a specified context to use discretization, solver, Programming with Python, Automated control and evaluation of parameter studies and examples to calculate of elastic mechanics like tensile, bending, four point bend, crack propagation, J -Integral, Cohesive zone models, Contact.

- determining the material properties (elasticity, plasticity, small and large deformations, modeling of multiphase materials).

- to calculate and evaluate the  mechanical properties (modulus, strength) of different materials.

- Approximate sizing using the network theory of the structural elements implement and evaluate.

- selecting appropriate solutions for mechanical material problems: Solution of inverse problems (neural networks, optimization methods).

Personal Competence

Social Competence

Students can

- arrive at funded work results in heterogenius groups and document them.

- provide appropriate feedback and handle feedback on their own performance constructively.

Autonomy

Students are able to,

- assess their own strengths and weaknesses

- assess their own state of learning in specific terms and to define further work steps on this basis

They are able to fill gaps in as well as extent their knowledge using the literature and other sources provided by the supervisor. Furthermore, they can meaningfully extend given problems and pragmatically solve them by means of corresponding solutions and concepts.

ECTS-Credit Points Module:

6 ECTS

Examination:

Written exam

Workload in Hours:

Independent Study Time: 110, Study Time in Lecture: 70


Course: Applied Computational Methods for Material Science (Project-/problem-based Learning)

Lecturer:

Norbert Huber

Language:

German & English

Period:

Winter Semester

Content:

Finite Element Method (discretisation, solver, programming with Python, automatized control and analysis of parametric studies)

Examples of elastomechanics (tension, bending, four-point-bending, contact)

Material behaviour (elasticity, plasticity, small and finite deformations, nonlinearities)

Solution of inverse problems (machining of data, artificial neural networks, direct and inverse solutions, existence and uniqueness)

Literature:

Alle Vorlesungsmaterialien und Beispiellösungen (Input-Dateien, Python Scirpte) werden auf Stud.IP zur Verfügung gestellt.

All lecture material and example solutions (input files, python scripts) will be made available in Stud.IP.


Course: Polymer Composites (Lecture)

Lecturer:

Robert Meißner

Language:

German

Period:

Winter Semester

Content:

Manufacturing and Properties of CNTs and Graphen

Manufacturing and Properties of 3-dimensional Graphenstruktures

Polymer Composites with carbon nanoparticles

Literature:

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