Course Details

Course Information

Semester	Course Unit Code	Course Unit Title	T+P+L	Credit	Number of ECTS Credits	Last Updated Date
2	CE610	İNŞAAT MÜHENDİSLİĞİ ARAŞTIRMALARINDA DENEYSEL VE HESAPLAMALI YÖNTEMLER	3+0+0	3	7,5	14.05.2025

Course Details

Language of Instruction	English
Level of Course Unit	Doctorate's Degree
Department / Program	CIVIL ENGINEERING
Type of Program	Formal Education
Type of Course Unit	Compulsory
Course Delivery Method	Face To Face
Objectives of the Course	Description This course aims to bridge the gap between traditional civil engineering research and the evolving landscape of technological advancements. The course integrates programming skills with experimental methodologies to equip doctoral candidates with a diverse set of tools for cutting-edge research. Participants will delve into the world of programming languages, simulation techniques, and data analysis to enhance their ability to model and analyze complex civil engineering problems. Practical applications of computational tools in experimental settings will be explored, fostering a hands-on approach to problem-solving. The course aligns with doctorate level studies by integrating programming, simulation, and experimental methodologies, enabling candidates to tackle complex civil engineering problems through advanced computational tools and innovative research approaches.
Course Content	Description This course aims to bridge the gap between traditional civil engineering research and the evolving landscape of technological advancements. The course integrates programming skills with experimental methodologies to equip doctoral candidates with a diverse set of tools for cutting-edge research. Participants will delve into the world of programming languages, simulation techniques, and data analysis to enhance their ability to model and analyze complex civil engineering problems. Practical applications of computational tools in experimental settings will be explored, fostering a hands-on approach to problem-solving. The course aligns with doctorate level studies by integrating programming, simulation, and experimental methodologies, enabling candidates to tackle complex civil engineering problems through advanced computational tools and innovative research approaches.
Course Methods and Techniques
Prerequisites and co-requisities	None
Course Coordinator	Prof.Dr. burak UZAL burak.uzal@agu.edu.tr
Name of Lecturers	Prof.Dr. BURAK UZAL
Assistants	None
Work Placement(s)	No

Recommended or Required Reading

Resources

Course Category

Mathematics and Basic Sciences	%30
Engineering	%25
Engineering Design	%25
Science	%20

Planned Learning Activities and Teaching Methods

Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria

In-Term Studies	Quantity	Percentage
Ödev	3	% 30
Proje/Çizim	3	% 30
Sunum/Seminer	3	% 40
Total	9	% 100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration	Total Work Load
Belirsiz	5	5	25
Tartışma	5	5	25
Sunum için Hazırlık	3	5	15
Sunum	3	3	9
Rapor	3	5	15
Araştırma	3	5	15
İnceleme	3	5	15
Yüz Yüze Ders	14	3	42
Derse Devam	14	3	42
Final Sınavı	1	15	15
Total Work Load			Number of ECTS Credits 7,5 218

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:

No	Learning Outcomes
1	Determine key programming concepts and syntax used in civil engineering research
2	Construct experimental and computational models for simulating complex civil engineering scenarios
3	Evaluate experimental data using computational tools.
4	Design an interdisciplinary research project that integrates computational methods with experimental works.

Weekly Detailed Course Contents

Week	Topics	Study Materials	Materials
1	Introduction to Experimental and Computational Methods course
2	Fundamentals of Machine learning for Cİivl Engineering Materials
3	Data Processing and Feature Engineering
4	Machine Learning Model Development for Material Property Prediction
5	Case Studies & Integration of Machine Learning with Experimental Research
6	Introduction to computational modeling, fundamentals of continuum mechanics
7	Finite-Element Method (FEM) basics
8	Advanced numerical methods
9	Hybrid testing & simulation, digital twins
10	Structural case studies
11	Geotechnical & materials case studies
12	Construction Materials Case Studies
13	Artificial Intelligence and Experimental Methodologies
14	AI & ML for experimental data analytics

Contribution of Learning Outcomes to Programme Outcomes

	P1	P2	P3	P4	P5	P6	P7	P8	P9	P10	P11	P12
C1	5	4	4	5	3	5	5	5	3	3	4	4
C2	5	5	4	4	3	5	5	5	4		4	3
C3	3	4	5			4	3				3	5
C4	3	4	4	4	3	4	4	3			3	5

Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

https://sis.agu.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=77629&lang=en

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