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EG3021 - Applied Engineering Analysis

Credit points: 3
Year: 2012
Student Contribution Band: Band 2
Administered by: School of Engineering

This subject introduces concepts in the application of Engineering analysis. Reliability-based engineering designs and decision making based on statistical and probabilistic concepts are covered. It also develops a framework in numerical methods for future use in finite element, finite difference and computational modeling in engineering. This is taught as an application-based subject, featuring problems from civil, mechanical, environmental and chemical engineering. Reliability based Engineering Designs - Review of probability and statistics, discrete and continuous distributions; Quality control and quality assurance; Applications in engineering experiments and designs; Introduction to reliability theory; Deterministic and probabilistic approaches in engineering analysis; Capacity and demand models; Safety margin versus safety factors; reliability index, probability of failure and risk. Engineering data analysis - Design of experiments and error analysis. Modelling Uncertainly - Use of Monte Carlo simulation, point estimates, first order second moment methods, Limit state designs. Computational Methods - Review of numerical analysis techniques; Numerical methods for engineering applications; Computer programming to solve engineering problems.

Learning Outcomes

  • Develop a framework for learning the basics of reliability-based designs;
  • Use of statistical methods for data analysis;
  • Develop an understanding of the uncertainties associated with engineering variables and ways to manage them;
  • Develop tools to quantify variability in starting materials and incorporate them into sound engineering analysis;
  • Gain a basic understanding in the application of numerical analysis techniques in Engineering.

Graduate Qualities

  • The ability to think critically, to analyse and evaluate claims, evidence and arguments;
  • The ability to adapt knowledge to new situations;
  • The ability to define and to solve problems in at least one discipline area;
  • The ability to communicate effectively with a range of audiences;
  • The ability to speak and write logically, clearly and creatively;
  • The ability to calculate, produce, interpret and communicate numerical information.
Prerequisites: MA2000
CS3005 EG5020


Townsville, Study Period 2, Internal
Census Date 23-Aug-2012
Coord/Lect: <Person not found>.
Workload expectations:
  • 65 hours - Lectures, tutorials, demonstrations, practicals, site visits and/or seminars. Refer to Subject Outline for details.
Assessment: end of semester exam (50% - 70%); on-course, some of which may be invigilated (30% - 50%).

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.