ME EN 275

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Computational Methods in Engineering

Mechanical Engineering Ira A. Fulton College of Engineering

Course Description

Numerical methods and statistics for engineers, implemented using software and computer programming

When Taught

Fall, Winter, Spring

Fixed

3

Fixed

3

Fixed

2

Other Prerequisites

Math 302 or Math 314 or concurrent

Title

Title: Fundamentals of Numerical Methods

Learning Outcome

Students will apply fundamental principles of numerical methods (including round-off error, truncation error, and convergence) and a knowledge of methodological advantages and limitations to solve engineering problems.

Title

Numerical Methods – Approximating Integrals and Derivatives

Learning Outcome

Students will apply numerical methods fundamentals to appropriately compute approximations of integrals and derivatives.

Title

Numerical Methods – Solving Equations

Learning Outcome

Students will apply numerical methods fundamentals to solve non-linear equations and systems of linear equations.

Title

Numerical Methods – Approximating Solutions of Ordinary Differential Equations

Learning Outcome

Students will apply numerical methods fundamentals to appropriately compute approximate solutions to ordinary differential equations.

Title

Fundamentals of Statistics

Learning Outcome

Students will apply fundamental concepts of statistics (including randomness and uncertainty) and a knowledge of methodological advantages and limitations to solve engineering problems.

Title

Statistics – Descriptions of Data

Learning Outcome

Students will apply statistical fundamentals to appropriately describe data distributions using measures of central tendency, spread, and data visualization techniques.

Title

Statistics – Estimating Data Patterns

Learning Outcome

Students will apply statistical fundamentals and generalized linear regression to obtain and assess least-squares approximations to data sets.

Title

Statistics – Estimating Statistical Significance

Learning Outcome

Students will apply statistical fundamentals to calculate confidence intervals, perform basic hypothesis testing (t-test, paired t-test, etc.), and correctly interpret p-values.

Title

Programming Languages

Learning Outcome

Using Excel, MATLAB, and Python, students will perform numerical/statistical analyses using their own code as well as packages/libraries while demonstrating best practices in programming techniques.

Title

Real-World Problem Solving – Explore

Learning Outcome

Students will learn the BYU ME methodology for exploring the solution space of engineering problems.

Title

Real-World Problem Solving – Communicate

Learning Outcome

Students will be introduced to the importance of clear, concise, and convincing communication and apply these principles by writing effective technical memos.