Mathematical Modeling (MATH486) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Mathematical Modeling MATH486 Area Elective 3 0 0 3 6
Pre-requisite Course(s)
N/A
Course Language English
Course Type Technical Elective Courses
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Question and Answer, Team/Group.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives Differential equations constitute main tools that scientists and engineers use to make mathematical models of important practical problems. This course discusses three major issues: 1) Formulating a model, using differential equations; 2) Analyzing the model, both by solving the differential equation and by extracting qualitative information about the solution from the equation; 3) Interpreting the analysis in light of the physical (practical) setting modeled in step 1).
Course Learning Outcomes The students who succeeded in this course;
  • make mathematical models of practical problems by mens of differential equations
  • gain skill with solution techniques in order to understand complex physical phenomena
Course Content Differetial equations and solutions, models of vertical motion, single-species population models, multiple-species population models, mechanical oscillators, modeling electric circuits, diffusion models.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Some terminology, Examples, Separation of variables. pp. 1-8
2 The Euler method, Linear differential equations with constant coefficients. p. 23, Exercise 8
3 Vertical motion without air resistence. pp. 29-37, 41-46
4 Vertical motion with air resistence. pp. 47-51
5 Simple population model, Population with emigration. pp. 65-71
6 Population with competition (The logistic equation). pp. 72-75
7 Midterm
8 Predator-prey (Fox-rabbit) population model, Epidemics (SIR). pp. 203-215
9 Two-species competition. pp. 219-222
10 Spring-mass without damping or forcing, Spring-mass with damping and forcing. p. 77, Exercises 3 and 4, pp. 223-227
11 Pendulum without damping, Approximate pendulum without damping. pp. 227-230
12 Series RC charge, Series RLC charge and current (First-order system). pp. 428-435
13 Parallel RLC voltage (Second-order scalar equation). pp. 465-468
14 Diffusion without convection or source, Diffusion with convection and source. pp. 1-6
15 Heat flow without heat source, Time-dependent diffusion. p. 23, Exercise 8
16 Final Exam

Sources

Course Book 1. P. W. Davis, Differential Equations: Modeling with matlab, Prentice Hall, Upper Saddle River, New Jersey, 1999.
3. S. L. Ross, Differential Equations, 3rd ed.,Wiley, New York, 1984.
Other Sources 2. E. Kreyszig, Advanced Engineering Mathematics, 8th ed., Wiley, New York, 1999.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 5 10
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 50
Final Exam/Final Jury 1 40
Toplam 8 100
Percentage of Semester Work 60
Percentage of Final Work 40
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Adequate knowledge in mathematics, science and subjects specific to the software engineering discipline; the ability to apply theoretical and practical knowledge of these areas to complex engineering problems. X
2 The ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose.
3 The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose.
4 The ability to develop, select and utilize modern techniques and tools essential for the analysis and determination of complex problems in software engineering applications; the ability to utilize information technologies effectively.
5 The ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the software engineering discipline.
6 The ability to work effectively in inter/inner disciplinary teams; ability to work individually.
7 Effective oral and written communication skills in Turkish; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8 The knowledge of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
9 Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development
10 The ability to behave according to ethical principles, awareness of professional and ethical responsibility.
11 Knowledge of the standards utilized in software engineering applications.
12 Knowledge on business practices such as project management, risk management and change management.
13 Awareness about entrepreneurship, and innovation.
14 Knowledge on sustainable development.
15 Knowledge of the effects of software engineering applications on the universal and social dimensions of health, environment, and safety.
16 Awareness of the legal consequences of engineering solutions.
17 An ability to apply algorithmic principles, mathematical foundations, and computer science theory in the modeling and design of computer-based systems with the trade-offs involved in design choices.
18 The ability to apply engineering approach to the development of software systems by analyzing, designing, implementing, verifying, validating and maintaining software systems.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 14 3 42
Presentation/Seminar Prepration
Project
Report
Homework Assignments 5 4 20
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 10 20
Prepration of Final Exams/Final Jury 1 20 20
Total Workload 150