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EG3001 - Finite Element Analysis

Credit points: 3
Year: 2019
Student Contribution Band: Band 2
Administered by: College of Science and Engineering

Students will learn fundamental theory of numerical methods in engineering and will learn to apply such methods in the analysis of various thermal, fluid, static and dynamic mechanical problems. The complementary numerical theory and application sections will be taught in parallel during the semester to provide context for one another and to expose graduates to the wide variety of numerical tools available to today's engineers. Within the theory section of the subject, students will learn the fundamentals and implementation of a variety of numerical methods; specifically the finite difference method (FD), discrete element method (DEM), and finite element method (FEM). Through hands-on experience, students will come to understand the difference between implicit and explicit numerical schemes and their applications and limitations, as well as the nature and application of both Eulerian and Lagrangian methods. In the application proportion of the subject, students will be trained in the use of the ANSYS commercial FEM package for static and dynamic mechanical problems, as well as in the interpretation and analysis of results. Students will learn the place of numerical software in the design workflow and will graduate with practical skills in analysis.

Learning Outcomes

  • understand the fundamental numerical mathematics behind a variety of numerical methods allowing informed use of such methods in practice (EAC1.2a);
  • develop practical experience in the application of commercial finite element packages to solve static and dynamic mechanical problems in engineeering (EAC1.3a);
  • understand which numerical method is most appropriate for a given engineering application, including selection of the most suitable sub-class (eg implicit/explicit etc) (EAC2.2b,c,d);
  • assess numerical model accuracy, determine sources of errors, and implement systematic approaches to problem decomposition that facilitate solution (EAC2.1b,c,d);
  • produce written analysis briefs that effectively and concisely report the approach and outcome of computational modelling (EAC3.2b).
Prerequisites: EG1002 AND EG1011 AND MA2000
CS4006 ME3514


Townsville, Internal, Study Period 1
Census Date 28-Mar-2019
Coordinator: Dr Mehdi Khatamifar, Dr Peter To
Lecturers: Dr Mehdi Khatamifar, Dr Peter To.
Workload expectations:

The student workload for this 3 credit point subject is approximately 130 hours.

  • 26 hours lectures
  • 52 hours practicals
  • assessment and self-directed study
Assessment: end of semester exam (30%); quizzes or tests (20%); assignments (20%); implementation workshops (15%); ansys workshops (15%).

Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.