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Third-Cycle Courses

Faculty of Engineering | Lund University

Details for the Course Syllabus for Course FMNN05F valid from Autumn 2013

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General
Aim
  • Simulation techniques is a field which demands experience in modelling, knowledge in Scientific Computing and programming skills. The aim of the course is to give the postgraduate student a chance to solve, in a working team, industrially relevant computational problems in connection with modelling of complex mechanical systems. The participants meet numerical methods on different levels in industrial simulation tools. In particular ordinary differential equations with and without algebraic constraints, methods for large systems of nonlinear equations and computations of eigenvalues.
Contents
  • Theoretical part: Numerical treatment of ordinary differential equations with discontinuities and/or algebraic constraints. Variants of different modelling techniques, variational integrators and other methods suitable for modelling. Introduction to a modelling language.

    Practical part: numerical experiments with computational tools within commercial and industrial software packages, e.g. Dymola. Similar experiments with selfproduced code in Python/SciPy.
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • understand how the mathematical modelling of mechanical systems may yield differential equations with discontinuous coefficients or algebraic constraints.
    understand how such systems are handled by modern software packages, e.g., ASSIMULO.
    be able to describe structural parallels between different engineering problems that are discussed during the course.
Competences and Skills
  • For a passing grade the doctoral student must
  • independently be able to apply and critically evaluate numerical methods which are common in industrial software packages.
    write an algorithmically well structured report in suitable terminology on mathematical methods applied in industrial simulation tools.
Judgement and Approach
  • For a passing grade the doctoral student must
Types of Instruction
  • Lectures
  • Exercises
  • Project
Examination Formats
  • Written report
  • Failed, pass
Admission Requirements
Assumed Prior Knowledge
Selection Criteria
Literature
  •  
  • Relevant material (journal articles and extracts from web based handbooks) will be provided at the start of the course.
Further Information
Course code
  • FMNN05F
Administrative Information
  •  -09-15
  • FN1/Anders Gustafsson

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