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EG3021 - Applied Engineering Analysis

Credit points: 3
Year: 2014
Student Contribution Band: Band 2
Administered by: School of Engineering (pre 2015)

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.
Prerequisites: MA2000
CS3005 EG5020


Townsville, Internal, Study Period 2
Census Date 28-Aug-2014
Coordinator: <Person not found>
Lecturers: <Person not found>, Assoc. Professor Shaun Belward.
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.