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Welcome to MATLS 4NN3: Computational Modeling in Materials Science and Engineering

Welcome to MATLS 4NN3: Computational Modeling in Materials Science and Engineering. Instructor. Prof. Nikolas Provatas JHE-357 ( provata@mcmaster.ca ) Office Hours Monday, 2:30-4:30pm, JHE-357. Lectures and Tutorials. All lectures in JHE-328 Mon 11:30am-12:20am Wed 11:30-12:30pm

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Welcome to MATLS 4NN3: Computational Modeling in Materials Science and Engineering

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  1. Welcome to MATLS 4NN3:Computational Modeling in Materials Science and Engineering

  2. Instructor • Prof. Nikolas Provatas • JHE-357 (provata@mcmaster.ca) • Office Hours • Monday, 2:30-4:30pm, JHE-357

  3. Lectures and Tutorials • All lectures in JHE-328 • Mon 11:30am-12:20am • Wed 11:30-12:30pm • Fri 1:30-2:20am • All lectures using PowerPoint and whiteboard – slides will be available on FTP site

  4. Complexity Everywhere! Connecting properties across scales is one of the greatest challenges on materials science and engineering • Macro-Scale: • Engine Block • ~1m • Performance criteria: • Power generated • Efficiency • Durability • Cost • Mesostructure: • grains • 1-10 mm • Properties affected: • High cycle fatigue • Ductility • Microstructure: • dendrites & phases: • 50-500 um • Properties affected: • Yield strength • Tensile strength • High/low cycle fatigue • Thermal growth • Ductility • Nano-structure: Precipitates • 3-100 nm • Properties affected: • Yield strength • Tensile strength • Low cycle fatigue • Ductility • Atomic Structure: • 1-100 A • Properties affected: • Young’s Modulus • Thermal Growth

  5. Benefits of Computational Modeling? • Material properties depend on microstructure & processing methods • E.g. Yield strength, ductility, electrical conductivity, etc. • Empirical property-microstructure relationships only possible in simple situations • Simulations can play out complex physical mechanisms in materials processes • Fundamental understanding • Predictive design • Cost-effective • Refining experimental directions

  6. What Will You Learn in this Course? • Materials Theory:How to develop basic mathematical models that: • Capture relevant physical & chemical properties • Establishing a connection between the model and materials parameters/processes • Programming: How to write basic simulation codes • Basics of Fortran 95 • Some exposure to Matlab and Maple • Numerical Methods:Skills for solving models that commonly arise in science and engineering • Heat and mass transfer in materials • Solidification microstructure formation • Electronic conduction

  7. Method of Assessment • Numerical Tally of Marks: • 3-4 Assignments 60% • Final Project 40% • Course will relay on two basics methods of instruction: • Lectures for learning theory and numerical methods • Team work and inquiry for practical knowledge

  8. Study Resources • Instructor notes computers • There is no textbook for this course • Reference texts (in library): • “Transport Phenomena in Materials Processing” D.R. Poirier and G.H Greiger, A Publication of the Minerals, Metals and Materials Society, Pennsylvania (1994) • “Numerical Recipes” • “An Introduction to Computer Simulations: Applications to Physical Systems 2nd ed”, Harvey Gould and Jan Tobochnik, Addison Wesley(1996) • “Computational Methods in Physics, Chemistry and Biology, An Introduction”, Paul Harrison, Jon Wiley and Sons (2001)

  9. You Comments and Feedback will be Greatly Appreciated in order to Continuously Improve this Course

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