Numerics for Fluids, Structures and Electromagnetics: Projects Rules

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Related lectures (29)

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Vectorization in Python: Efficient Computation with Numpy

Covers vectorization in Python using Numpy for efficient scientific computing, emphasizing the benefits of avoiding for loops and demonstrating practical applications.

Numerics for Fluids, Structures & Electromagnetics

Covers numerics for fluids, structures, and electromagnetics, emphasizing the importance of eigenvalues and eigenfunctions.

Numerical Methods: Stopping Criteria, SciPy, and Matplotlib

Discusses numerical methods, focusing on stopping criteria, SciPy for optimization, and data visualization with Matplotlib.

Root Finding Methods: Bisection and Secant Techniques

Covers root-finding methods, focusing on the bisection and secant techniques, their implementations, and comparisons of their convergence rates.

NumPy Arrays and Graphical Representations: Introduction

Covers NumPy arrays and their graphical representations using Matplotlib, focusing on array creation, manipulation, and visualization techniques.

Numerical Methods: Bisection and Multidimensional Arrays

Discusses the bisection method for solving nonlinear equations and its implementation using Python with NumPy and Matplotlib.

Programming Concepts: Variables and Expressions

Covers fundamental programming concepts such as algorithms, variables, and expressions in C++.

Control Structures: Loops and Iteration

Explores control structures, emphasizing loops and iteration, and the importance of writing clear and readable code.

Numerical Analysis: Stability in ODEs

Covers the stability analysis of ODEs using numerical methods and discusses stability conditions.

Numerical Methods: Euler and Crank-Nicolson

Covers Euler and Crank-Nicolson methods for solving differential equations.