Course Details in 2027/28 Session

Module Title	LI Modelling Materials Behaviour
School	Metallurgy and Materials
Department	Metallurgy & Materials
Module Code	04 31193
Module Lead	Dr Hector Basoalto
Level	Intermediate Level
Credits	20
Semester	Semester 2
Pre-requisites	LC Design for Structural Applications - (04 31174)
Co-requisites
Restrictions	None
Contact Hours	Lecture-30 hours Tutorial-12 hours Practical Classes and workshops-12 hours Guided independent study-146 hours Total: 200 hours
Exclusions
Description	In this module the dependence of microstructure in metals upon temperature and strain is explored numerically. Key techniques underpinning this are presented. Concepts from LC DSA, LC FMS, LI PMS and LI FFD are combined. This links to the following topics from the 2017 QAA Materials Subject Benchmark Statement section 3.4: iv mechanical behaviour - elastic and plastic deformation, creep and fatigue, fracture, strengthening, toughening and stiffening mechanisms vi structural characterisation - optical and electron microscopy techniques, electron and X-ray diffraction, scanning probe techniques, thermal analysis viii mechanical test methods vi computational simulation of materials across the length-scales and corresponding time-scales, from atomistic (classical and quantum) to finite elements viii bulk processing, heat and mass transfer, and fluid mechanics
Learning Outcomes	By the end of the module students should be able to: Mathematically analyse and simulate simple processes; Use and implement numerical approaches to find the minima, maxima and solution(s) of functions; Use and implement the finite difference approach to solve partial differential equations given a set of boundary conditions; Use matrix algebra to solve elasticity problems, and predict the mechanical behaviour of materials; Extend some of the numerical approaches above to 2-dimensional situations; Compare and contrast different processing methods; Discuss and analyse the phenomena occurring during different processing methods. These relate to AHEP3 learning outcomes: Develop a knowledge and understanding of mathematical and statistical methods necessary to underpin their education in their engineering discipline and to enable them to apply mathematical and statistical methods, tools and notations proficiently in the analysis and solution of engineering problems (SM2); Identify, classify and describe the performance of systems and components through the use of analytical methods and modelling techniques (EA2); Apply quantitative and computational methods in order to solve engineering problems and to implement appropriate action (EA3); Communicate their work to technical and non-technical audiences (D6); Understand the use of technical literature and other information sources (EP4); Understand appropriate codes of practice and industry standards (EP6); Work with technical uncertainty (EP8); Exercise initiative and personal responsibility, which may be as a team member or leader (AGS4); A comprehensive knowledge and understanding of mathematical and computational models relevant to the engineering discipline, and an appreciation of their limitations (SM5m); Demonstrate wide knowledge and comprehensive understanding of design processes and methodologies and the ability to apply and adapt them in unfamiliar situations (D7m).
Assessment	31193-02 : Coursework : Coursework (100%)
Assessment Methods & Exceptions	Assessments: Written examination (40%), Continuous assessment (60%) Reassessment: Exam only
Other
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