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Multiscale Modeling

MW2359Applications in Computational Science and Engineering - Elective Modules5 ECTSEnglishsummer semesterProfessur für Data-driven Materials Modeling (Prof. Koutsourelakis)
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

In this module you will gain a systematic overview of models and methods of multiscale modeling from the continuum level down to the quantum- or atomistic level. You will learn fundamental principles, numerical techniques and multi-physical approaches, and you will be able to apply suitable simulation techniques for multiscale partial and ordinary differential equations as well as coarse-grained molecular dynamics models.

What you will be able to do

  • Advanced knowledge of the fundamental challenges in multiscale problems
  • Familiarity with physical models at different scales
  • Basic understanding of molecular dynamics simulation and related software
  • Basic knowledge of numerical, multi-resolution and multiscale techniques
  • Ability to recognize connections between exemplary models and research/engineering problems
  • Application of suitable simulation techniques to elliptic PDEs with multiscale coefficients
  • Application of appropriate methods to ODEs with different time scales
  • Creation of coarse-grained models for molecular dynamics simulations
  • Recognizing the limits of existing models and open research questions

What the module consists of

  • LectureConveying mathematical derivations and theoretical foundations; supplemented by animations and numerical examples
  • ExercisesDeepening the lecture content: Matlab and Python scripts, implementation of missing building blocks for coarse-graining tasks
  • Self-study / additional assignmentsFurther tasks to deepen understanding outside regular sessions; individual supervision by instructors

Teaching method

  • Lecture with derivationsExplanation of theoretical foundations and mathematical concepts
  • Animations and numerical examplesDemonstration of the capability and application of the methods to engineering problems
  • Practical exercises in Matlab and PythonIndependent implementation and application of the discussed methods (e.g. coarse-graining)
  • Consultation / office hoursClarification of individual questions and advising outside teaching sessions
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