SPECIAL TOPICS IN DEFENSE PLATFORMS II

SAP588

Course Code: SAP588
Semester: -
Theory+Practice: 3 + 0
ECTS: 10

Course Type

Elective Course

Course Level

Master's Degree With Thesis

Year of Study

Semester

ECTS

Name of Lecturer(s)

Learning Outcomes

At the end of this course, the students;

Understand the fundamental principles of digital twins,
Develop proficiency in using 1D system simulation and MBSE tools/software,
Apply simulation, reduced order modelling and data assimilation techniques to digital twin problems in various domains,
Communicate effectively about data- and physics-driven approaches in digital twins.

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

None.

Course Description

This course provides a systematic introduction to digital twin technology, beginning with foundational concepts in digital twins and systems engineering before progressing through model-based system and software architectures using Capella. Students will gain knowledge in physics-based modeling techniques including computer-aided engineering (CAE) fundamentals and finite element methods (FEM), along with optimization approaches. Proper orthogonal decomposition (POD) as a model reduction strategy for translating complex 3D models into efficient 1D representations suitable for digital twin applications will be detailed, along with basics of other methods. Practical implementation through system modeling and simulation is covered, along with data assimilation methods for integrating real-world measurements with computational models, detailed through Kalman filters and their variations. Hardware integration concepts are covered through sensors and actuators, while the course concludes by exploring emerging trends, infrastructure requirements, and future developments in digital twin technology, culminating in a comprehensive review and project presentations that allow students to apply their knowledge to real- world digital twin scenarios.

Course Contents

WEEK	TOPICS
1^st Week	Introduction to course and digital twins
2^nd Week	Introduction to systems engineering
3^rd Week	Model-based system and software architectures with Capella I
4^th Week	Model-based system and software architectures with Capella II
5^th Week	Physics-based modelling - CAE basics and finite element methods
6^th Week	Physics-based modelling - optimization
7^th Week	Model reduction: from 3D to 1D for digital twins
8^th Week	System modelling and simulations I
9^th Week	System modelling and simulations II
10^th Week	MIDTERM
11^th Week	Data assimilation methods
12^th Week	Sensors and actuators
13^th Week	New and emerging areas, future trends, DT infrastructures
14^th Week	Review, project recitation

Recommended or Required Reading

-R.L. Woods, K.L. Lawrence. Modeling and Simulation of Dynamic Systems
-P. Roques. Systems Architecture Modeling with the Arcadia Method
-R.D. Cook, D.S. Malkus, M.E. Plesha. Concepts and Applications of Finite Element Analysis
-Steven L. Brunton, J. Nathan Kutz. Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
-P. Zarchan, H. Musoff. Fundamentals of Kalman Filtering: A Practical Approach
-S. Chapra, R. Canale. Numerical Methods for Engineers

Planned Learning Activities and Teaching Methods

Lecture
Questions/Answers
Problem Solving

Assessment Methods and Criteria

	Quantity	Percentage (%)
Mid-term	1	25
Project	1	35
Total(%)		60
Contribution of In-term Studies to Overall Grade(%)		60
Contribution of Final Examination to Overall Grade(%)		40
Total(%)		100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Midterm exam	1	2	2
Preparation for Quiz
Individual or group work	14	6	84
Preparation for Final exam	1	84	84
Course hours	14	3	42
Preparation for Midterm exam	1	36	36
Laboratory (including preparation)
Final exam	1	2	2
Homework
Project	1	56	56
Total Work Load			306
Total Work Load / 30 (h)			10.2
ECTS Credit of the Course			10

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4
K1	X	X	X
K2	X	X	X
K3	X	X	X
K4	X	X	X
K5
K6
K7
K8
K9
K10	X	X	X
K11