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Course Description
Contents:
  1. HPC methods for Computational Fluid Dynamics and Astrophysics
  2. NUMERICAL AND COMPUTATIONAL METHODS - 2018/9
  3. | Numerical Analysis - TOKYO TECH OCW

HPC methods for Computational Fluid Dynamics and Astrophysics

Academic year Subject Area Mathematics. Language of Instruction Portuguese.

Product Details

Other Languages of Instruction English. Mode of Delivery Face-to-face. Level 2nd Cycle Studies - Mestrado.

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Teaching Methods Classes are expository and include examples and exercises for applying the acquired knowledge. Learning Outcomes The aim of this course is to develop skills to solve numerically steady and evolution partial differential problems and to analyze and interpret the computed solutions. The assessment strategy is designed to provide students with the opportunity to demonstrate: Understanding of and ability to derive, devise and analyse numerical methods.

Subject knowledge through the recall of key definitions, theorems and their proofs.

NUMERICAL AND COMPUTATIONAL METHODS - 2018/9

Analytical ability through the solution of unseen problems in the test and exam. Practical skills of implementing numerical methods in MATLAB code, and ability to understand and interpret given code.

Students are given lab sheets and template codes in order to solve practical problems. Instructor and teaching assistant s provide real time guidance, and students can also discuss with peers. Indicated Lecture Hours which may also include seminars, tutorials, workshops and other contact time are approximate and may include in-class tests where one or more of these are an assessment on the module.

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| Numerical Analysis - TOKYO TECH OCW

This will usually be after the initial publication of the teaching timetable for the relevant semester. Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. Module Overview When an analytical approach is not known or practical for solving a mathematical problem, the numerical approach can be useful in finding approximate solutions as close as possible to the exact one.


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Module Availability Semester 2. Module content The module will consider the following: Numerical solution of systems of linear equations Numerical solution of systems of nonlinear equations Polynomial interpolation Numerical methods for differentiation and integration Numerical methods for solving ordinary differential equation. Assessment Strategy The assessment strategy is designed to provide students with the opportunity to demonstrate: Understanding of and ability to derive, devise and analyse numerical methods.


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Module aims The aim of this module is to introduce students to a selection of numerical methods in terms of their derivation, their accuracy and efficiency and their implementation. Learning outcomes Attributes Developed 1 Demonstrate knowledge and literacy of the taught numerical methods; K 2 For basic numerical methods, prove their convergence and error bounds, and demonstrate understanding of their efficiency; KC 3 Derive and devise numerical schemes with specific details for a range of mathematical problems; KCT 4 Apply the above knowledge to determine the most suitable numerical method s for a practical problem; CPT 5 Implement some numerical Linear Algebra methods in Matlab code, and gain proficiency in basic programming structures and methodology that can be used for general coding purposes.

Attributes Developed. Overall student workload.