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EGN 6430 Advanced Engineering Analysis

Florida Gulf Coast University
U.A. Whitaker College of Engineering
Spring 2025
Last updated: Jan 3, 2025

Recorded Lessons: Link

Course Information

EGN 6430 Advanced Engineering Analysis
CRN: 15845
Credit hours: 3
Class: Online - Asynchronous
Exam: Wednesday Apr 30 from 6:00 pm to 8:00 pm - In-Person at Holmes Engineering 330.

Instructor

Ahmed S. Elshall, PhD
Assistant Professor
Department of Bioengineering, Civil Engineering, and Environmental Engineering
U.A. Whitaker College of Engineering Joint Appointment with The Water School
Office: Holmes Hall 423 (inside 416)
Research Website: https://aelshall.weebly.com
Office Hours : Tuesday and Thursday 2:00 pm - 4:00 pm, and by appointment

Course Catalog Description

Methods of analysis applied to engineering problems. Topics include a review of vector calculus, linear algebra, analytical solutions and numerical integration of differential equations, finite integrals, and computer simulation and modeling.

Course Learning Objectives

At the completion of the course, students will be able to:

  1. Perform differentiation and integration using analytical and numerical methods
  2. Apply optimization techniques in engineering problem solving
  3. Apply ordinary differential equations and partial differentiation in engineering problem solving
  4. Understand and apply basic concepts of computer simulation and modeling to analyze engineering systems
  5. Use linear algebra and operations involving matrices to solve simultaneous equations

Course Schedule

These topics and number of assignments are tentative and subject to change based on class progress.

Week Date (From - To) Topic Due date
1 6-Jan - 12-Jan Course introduction; Dimensional analysis: Review Homework 1
2 13-Jan - 19-Jan Dimensional analysis: Pi theorem and physical models Homework 2
3 20-Jan Martin Luther King Holiday Observed (no classes)  
3 20-Jan - 26-Jan Differential calculus: Review Homework 3
4 27-Jan - 2-Feb Differential calculus: Optimization Homework 4
5 3-Feb - 9-Feb Differential calculus: Multivariable systems Homework 5
6 10-Feb - 16-Feb Differential calculus: Vector calculus Homework 6
7 17-Feb - 23-Feb Integral calculus: Review Homework 7
8 24-Feb - 2-Mar Integral calculus: Integral function Homework 8
9 3-Mar - 9-Mar Spring break (no classes)  
10 10-Mar - 16-Mar Differential equations: Laws of conservation Homework 9
11 17-Mar - 23-Mar Differential equations: Engineering applications Homework 10
12 24-Mar - 30-Mar Computer simulation and modeling: Mathematical models Homework 11
13 31-Mar - 6-Apr Computer simulation and modeling: Numerical solutions Homework 12
14 7-Apr - 13-Apr Linear algebra: Solving systems of linear equations Homework 13
15 14-Apr - 20-Apr Elective1 - Monte Carlo Simulation: Cost Estimation  
15 14-Apr - 20-Apr Elective1 - Regression analysis : Linear regession  
16 21-Apr - 27-Apr Exam review Homework 14
17 30-Apr In-class comprehensive final exam Final exam

1 You are required to complete one of the two elective topics.

Topics

This course is designed for students in construction management, environmental engineering, and water resources engineering, with consideration that some students may not have completed a calculus course. Modules 0 to 6 are required. Module 7 and 8 are elective, and you only need to complete one of them.

Module 0 Course Introduction

Learning objectives: Understand the course structure and problem-solving approaches in engineering (1 contact hours)

Moudle 1 Dimensional Analysis – 2 Weeks

Learning objectives: Apply dimensional analysis and Pi theorem to simplify complex engineering problems (4 contact hours)

Module 2 Differential Calculus – 4 Weeks

Learning objectives: Use derivatives for optimization, system analysis, and function approximation (10 contact hours)

Module 3 Integral Calculus – 2 Weeks

Learning objectives: Apply integration techniques to solve engineering problems involving accumulated quantities and series solutions for complex integral problems (5 contact hours)

Module 4 Differential Equations – 2 Weeks

Learning objectives: Solve ordinary and partial differential equations for engineering applications (5 contact hours)

Module 5 Computer Simulation and Modeling – 2 Weeks

Learning objectives: Develop and solve mathematical models using analytical and numerical methods (5 contact hours)

Module 6 Linear Algebra – 1 Weeks

Learning Objectives: Solve systems of linear equations using matrix and vector operations to analyze engineering systems (2.5 contact hours)

Module 7 Monte Carlo Simulation – 1 Week

Learning Objectives: Use Monte Carlo methods for uncertainty analysis (2.5 contact hours)

Module 8 Linear Regression – 1 Week

Learning Objectives: Apply linear regression to analyze data and evaluate model performance (2.5 contact hours)

For more information, refer to course map

Course Materials

Slides and videos are available on Canvas. Key references used in preparing course materials include:

Assessment and Grading

Grading scale

The instructor may elect to employ a curve that favors the students.

Grade Range Grade Range Grade Range
A 94% or above B- 80% to 82.99% D+ 67% to 69.99%
A- 90% to 93.99% C+ 77% to 79.99% D 60% to 66.99%
B+ 87% to 89.99% C 73% to 76.99% F Below 60%
B 83% to 86.99% C- 70% to 72.99%    

Assessment plan (100%)

General notes

Participation

For participation assessment, students are expected to:

These form the majority of your participation grade.

Homework

A weekly homework will be posted on Canvas. Each assignment is due by Sunday at 11:59 pm, unless otherwise posted on CANVAS. Few assignments are designed to include self-directed learning opportunities. This is to give you the opportunity to explore and experiment with engineering problems of your interest.

Late Homework Policy

Exam

Execused Absence Policy

Course and Program Assessment

Program Learning Outcomes for the Master of Science in Engineering (MSE) Program are as follows:

Content/Discipline Knowledge and Skills (DK) – MSE graduates will be able to:

  1. Apply higher level math, science and engineering skills to research and/or design engineering systems, components, or processes to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability.
  2. Understand the professional and ethical responsibilities associated with engineering practice and engineering research.
  3. Use the techniques, skills, and modern engineering tools necessary for engineering practice and engineering research.

Content/discipline knowledge and skills are assessed at the program level using appropriate coursework including examinations, assignments and presentations.

Communication Skills (CS) – MSE graduates will be able to:

  1. Organize and relate ideas coherently in written, oral, and graphic form.
  2. Develop and present consistent arguments to diverse audiences. Communication skills are assessed at the University, College, and Program levels through oral and written presentations, project reports, and other assignments throughout the curriculum.

Critical Thinking Skills (CT) – MSE graduates will be able to:

  1. Identify problems and the relevant information needed to solve them.
  2. Analyze and synthesize information, and draw reasoned inferences.
  3. Formulate and evaluate appropriate problem-solving strategies. Critical thinking skills are assessed at the University, College, and Program levels through oral and written presentations, project reports, exams, and other assignments throughout the curriculum.

Policy for Academic Integrity Violations

Financial Aid Statement

As of fall 2015, all faculty members are required to use Canvas to confirm a student’s attendance for each course by the end of the first week of classes. Failure to do so will result in a delay in the disbursement of your financial aid. The confirmation of attendance is required for all students, not only those receiving financial aid.

Generative AI Use

Generative AI including large language models (LLMs) such as ChatGPT, Gimini, Claude, and DeepL should not be used in assignments and exams unless indicated by the text “Generative AI Permitted”. Students must cite the used generative AI tool, and failing to do so will be considered academic dishonesty. Check FGCU Generative AI policy for more details.

Core Syllabus Policies

FGCU has a set of central policies related to student recording class sessions, academic integrity and grievances, student accessibility services, academic disruption, generative AI, and religious observances that apply to all courses at FGCU. Be sure to review these online

FGCU Writing Lab

We’re here to help students, faculty, and staff become more confident writers. To this end, we offer a variety of free services including one-on-one sessions with expert writing consultants, on-demand presentations on a range of writing-related topics and a broad selection of handouts developed specifically for the needs of the FGCU community. https://www.fgcu.edu/academics/caa/writinglab/

High Performance Computing (HPC) Resources

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Syllabus Change Policy

Except for changes that substantially affect implementation of the evaluation (grading) statement, this syllabus is a guide for the course and is subject to change with advance notice.