A comprehensive academic archive for Computational Methods and Modeling for Engineering Applications (GENG 8030), documenting technical proficiency in MATLAB programming, numerical analysis, Simulink modeling, and engineering simulation standards within the Master of Engineering program.
Overview · Contents · Reference Books · Personal Preparation · Quizzes · MATLAB Project · Lecture Notes · Grades · Syllabus · Usage Guidelines · License · About · Acknowledgments
Computational Methods and Modeling for Engineering Applications (GENG 8030) is a foundational graduate course in the Master of Engineering (MEng) program at the University of Windsor. This course focuses on developing the advanced computational skills essential for professional engineers, encompassing MATLAB programming, numerical methods for calculus and differential equations, and Simulink-based system modeling.
The curriculum encompasses several key computational and modeling domains:
- MATLAB Foundations: Mastering matrix operations, numeric arrays, and function development for complex engineering tasks.
- Numerical Analysis: Applying iterative methods for solving linear algebraic equations, statistics, and interpolation.
- Calculus & Differential Equations: Implementing numerical methods for solving advanced calculus problems and differential models.
- Simulink Modeling: Developing block-diagram based simulations for dynamic systems and control engineering.
- Model Building: Leveraging regression analysis and model optimization for engineering applications.
This repository represents a curated collection of study materials, reference books, course assessments, and personal preparation notes compiled during my academic journey. The primary motivation for creating and maintaining this archive is simple yet profound: to preserve knowledge for continuous learning and future reference.
As I progress in my career, I recognize that computational foundations remain essential for solving complex engineering problems and explaining them with technical precision. This repository serves as my intellectual reference point: a resource I can return to for relearning concepts, reviewing methodologies, and strengthening understanding when needed.
Why this repository exists:
- Knowledge Preservation: To maintain organized access to comprehensive study materials beyond the classroom.
- Continuous Learning: To support lifelong learning by enabling easy revisitation of fundamental computational principles.
- Academic Documentation: To authentically document my learning journey through Computational Methods and Modeling for Engineering Applications.
- Community Contribution: To share these resources with students and learners who may benefit from them.
Note
All materials were created, compiled, and organized by me during the Summer 2023 semester as part of my MEng degree requirements.
This collection includes comprehensive reference materials covering all major topics:
| # | Resource | Focus Area |
|---|---|---|
| 1 | MATLAB for Engineering Applications - William J. Palm | Core textbook for advanced MATLAB programming and engineering modeling. |
| 2 | MATLAB Cheat Sheet | A condensed guide for syntax, functions, and plotting commands. |
| 3 | Simulink YouTube Video Resources | Curated digital library for block-diagram based simulation learning. |
| 4 | MATLAB Plotting & Visualization Script - July 4, 2023 | Practical implementation of 2D data visualization techniques including Scatter, Stem, Bar, and Stair plots. |
Academic roadmap and administrative records for the Summer 2023 session:
| # | Resource | Description |
|---|---|---|
| 1 | Course Syllabus | Official course outcomes and assessment specifications |
| 2 | MEng Class Schedule | Enrollment record and pedagogical timeline |
| 3 | Exam Schedule | Summative evaluation roadmap |
| 4 | Announcements | Archival log of instructor communications and project directives |
A granular record of analytical in-class assessments and tactical computational proofs conducted during the Summer 2023 session.
| # | Quiz | Topics | Marks |
|---|---|---|---|
| 1 | Quiz 1 | Overview of MATLAB & Arrays | 4/6 |
| 2 | Quiz 2 | Functions & Programming | 3.25/6 |
| 3 | Quiz 3 | Advanced Plotting & Visualization | 4.8/6 |
| 4 | Quiz 4 | Model Building & Regression | 6/6 |
| 5 | Quiz 5 | Statistics & Interpolation | 6/6 |
| 6 | Quiz 6 | Linear Algebra & Numerical Methods | — |
Design and implementation of an Adaptive Cruise Control (ACC) system using MATLAB and Simulink.
Important
Special thanks to Nandeshwar Royal Uppalapati and Brano Bruno Barshmen for their meaningful contributions, guidance, and support that helped shape this work.
The Adaptive Cruise Control (ACC) system serves as a cornerstone implementation of sensor-driven automation within this archive. This project transcends basic scripting by synthesizing complex control laws with real-time sensor feedback loops, specifically utilizing Arduino-integrated logic to bridge the gap between software simulation and physical actuation. The implementation focuses on longitudinal vehicle dynamics, where the MATLAB-based control algorithm dynamically modulates velocity based on proximity data, demonstrating the high-fidelity modeling required for advanced driver-assistance systems (ADAS). The inclusion of a comprehensive Simulink framework allows for deterministic modeling of vehicle response under varied operational constraints, ensuring rigorous validation of the control logic before deployment.
Tip
Live Implementation: For a granular exploration of the autonomous logic and real-world system behavior, explore the Live Demo and Technical Walkthrough available in the dedicated Adaptive Cruise Control repository. This live record provides the empirical proof of the analytical models curated in this master archive.
You can also explore the interactive browser-based simulation, no hardware or MATLAB required:
Note
The Final Project Report score of 109% (21.8/20) reflects the successful completion of an on-the-spot technical challenge, validating the real-time application of adaptive control logic beyond the standard assessment criteria.
| # | Phase | Milestone | Deliverables | Marks |
|---|---|---|---|---|
| 1 | Formative | Project Groups | Group allocation and technical title registration | — |
| 2 | Strategic | Preliminary Report | Technical framework and initial system architecture | 4.8/5 |
| 3 | Finalization | Final Project Report | Comprehensive technical analysis and system validation | 21.8/20 |
| 4 | Implementation | MATLAB Source Code | Applied logic for Arduino-integrated ACC simulation | — |
A comprehensive archival log documenting pedagogical discourse across ten chapters, including weekly slides and applied tutorials for the Summer 2023 session.
Tip
Computational methods and modeling is not merely the execution of code; it is the bridge between mathematical theory and engineering innovation. Every module below focuses on the critical translation from Numerical Algorithms to Functional Simulators, enabling the iterative design and verification of complex engineering systems.
| # | Week | Date | Topic | Lecture Slides | Applied Tutorials |
|---|---|---|---|---|---|
| 1 | Week 01 | May 09, 2023 | Overview of MATLAB | Chapter 1 | — |
| 2 | Week 02 | May 16, 2023 | Numeric & Cell Arrays | Chapter 2 | Tutorial 1 |
| 3 | Week 03 | May 23, 2023 | Victoria Day Holiday | — | — |
| 4 | Week 04 | May 30, 2023 | Functions | Chapter 3 | Tutorial 1B |
| 5 | Week 05 | June 06, 2023 | Programming with MATLAB | Chapter 4 | — |
| 6 | Week 06 | June 13, 2023 | Advanced Plotting | Chapter 5 | — |
| 7 | Week 07 | June 20, 2023 | Reading Week | — | — |
| 8 | Week 08 | June 27, 2023 | Model Building & Regression | Chapter 6 | Tutorial 4 |
| 9 | Week 09 | July 04, 2023 | Statistics & Interpolation | Chapter 7 | Tutorial 5 |
| 10 | Week 10 | July 11, 2023 | Linear Algebraic Equations | Chapter 8 | Tutorial 6 |
| 11 | Week 11 | July 18, 2023 | Numerical Methods | Chapter 9 | Tutorial 7 |
| 12 | Week 12 | July 25, 2023 | Simulink | Chapter 10 | Tutorial 8 & Tutorial 9 |
| — | — | August 18, 2023 | Final Examination | — | — |
A specialized archival directory of technical solutions, meticulously categorized by textbook chapter and tutorial milestone.
Note
This computational inventory serves as the methodological bridge of the archive, where abstract mathematical frameworks are synthesized into functional engineering implementations. By integrating textbook-driven logic with localized technical documentation, these solutions provide the evidential depth required to master high-fidelity numerical modeling and algorithmic design.
The graded performance record documents academic achievement across various assessment categories including the MATLAB project and final examination.
| # | Assessment Category | Archival Record |
|---|---|---|
| 1 | Final Grade Report | View Grades |
Official GENG 8030 Syllabus
Complete graduate-level syllabus document for the Summer 2023 session, including detailed course outcomes, assessment criteria, and module specifications for Computational Methods and Modeling.
Important
Always verify the latest syllabus details with the official University of Windsor academic portal, as curriculum specifications for computational modeling may undergo instructor-led adaptations across different sessions.
This repository is openly shared to support learning and knowledge exchange across the academic community.
For Students
Use these resources as templates for MATLAB scripting, reference materials for numerical analysis, and examples of Simulink modeling. All content is organized for self-paced learning.
For Educators
These materials may serve as curriculum references, sample project benchmarks, or supplementary instructional content in computational methods. Attribution is appreciated when utilizing content.
For Researchers
The simulations and numerical implementations may provide insights into scholarly modeling patterns and professional engineering documentation structuring.
This repository and all linked academic content are made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0). See the LICENSE file for complete terms.
Note
Summary: You are free to share and adapt this content for any purpose, even commercially, as long as you provide appropriate attribution to the original author.
Created & Maintained by: Amey Thakur
Academic Journey: Master of Engineering in Computer Engineering (2023-2024)
Institution: University of Windsor, Windsor, Ontario
Faculty: Faculty of Engineering
This repository represents a comprehensive collection of study materials, reference books, weekly lecture archives, and personal preparation notes curated during my academic journey. All content has been carefully organized and documented to serve as a valuable resource for students pursuing Computational Methods and Modeling for Engineering Applications.
Connect: GitHub · LinkedIn · ORCID
Grateful acknowledgment to Dr. Yasser M. Alginahi for his exceptional instruction in Computational Methods, which played a pivotal role in shaping my analytical understanding of the subject. His clear and disciplined approach, along with his thorough explanation of numerical analysis and modeling techniques, made the subject both accessible and engaging. His distinguished expertise and commitment to academic excellence in Computational Methods and Modeling are sincerely appreciated.
Grateful acknowledgment to my Major Project teammates, Nandeshwar Royal Uppalapati and Brano Bruno Barshmen, for their collaborative excellence and shared commitment throughout the semester. Our collective efforts in synthesizing complex datasets, developing rigorous technical architectures, and authoring comprehensive engineering reports were fundamental to the successful realization of our objectives. This partnership not only strengthened the analytical depth of our shared deliverables but also provided invaluable insights into the dynamics of high-performance engineering teamwork.
Grateful acknowledgment to Jason Horn, Writing Support Desk, University of Windsor, for his distinguished mentorship and scholarly guidance. His analytical feedback and methodological rigor were instrumental in refining the intellectual depth and professional caliber of my academic work. His dedication stands as a testament to the pursuit of academic excellence and professional integrity.
Special thanks to the mentors and peers whose encouragement, discussions, and support contributed meaningfully to this learning experience.
Overview · Contents · Reference Books · Personal Preparation · Quizzes · MATLAB Project · Lecture Notes · Grades · Syllabus · Usage Guidelines · License · About · Acknowledgments
Computer Engineering (M.Eng.) - University of Windsor
Semester-wise curriculum, laboratories, projects, and academic notes.
