Subject Datasheet
Completion requirements
Subject Datasheet
Download PDFI. Subject Specification
1. Basic Data
1.1 Title
Digital Twins of Structures
1.2 Code
BMEEOHSMSFST14-00
1.3 Type
Module with associated contact hours
1.4 Contact hours
| Type | Hours/week / (days) |
| Lecture | 1 |
| Seminar | 1 |
1.5 Evaluation
Midterm grade
1.6 Credits
3
1.7 Coordinator
| name | Dr. Joó Attila László |
| academic rank | Associate professor |
| joo.attila@emk.bme.hu |
1.8 Department
Department of Structural Engineering
1.9 Website
1.10 Language of instruction
hungarian
1.11 Curriculum requirements
Recommended elective in the Specialization of Structures, Strcutural Engineering (MSc) programme
1.12 Prerequisites
1.13 Effective date
1 September 2025
2. Objectives and learning outcomes
2.1 Objectives
The course aims to equip students with comprehensive knowledge of digital twins in structural engineering, covering theoretical foundations, automated monitoring systems, numerical modeling, and BIM development. It emphasizes practical skills in sensor creation, data processing, parametric design, and system integration. The course also fosters innovation, problem-solving, and independent project management, preparing students to effectively utilize digital twin technologies in real-world engineering applications.
2.2 Learning outcomes
Upon successful completion of this subject, the student:
A. Knowledge
1. Students will gain a solid theoretical knowledge of digital twins and their applications in structural engineering.
2. They will have knowledge about different types of automated monitoring systems and how to construct and implement them effectively.
3. The students will cover knowledge of real-time data extraction, storage, and processing techniques.
4. Students will acquire knowledge in parametric design and low-code solutions for automated numerical modeling.
5. They will understand and know the processes involved in modeling with programming and extracting analytical results.
6. The knowledge of BIM model development will be taught, including parametric design and advanced visualization methods.
7. Students will know digital twin processes, including connecting systems, decision support, and cloud-based data management.
8. They will also know how to independently develop a digital twin project from start to finish.
B. Skills
1. Students will develop the ability to plan and create custom sensors for structural monitoring systems.
2. They will gain skills in collecting and processing real-time sensor data.
3. The course will enhance their skills in automated numerical modeling, including parametric design and result analysis.
4. Students will become proficient in using BIM tools for model development and visualization.
5. They will have skills how to integrate digital twin systems with databases, cloud services, and decision-making tools.
6. Project management skills will be strengthened through the independent execution of digital twin projects.
7. Students will improve their programming skills for modeling and automating numerical analyses.
8. They will also acquire the ability to analyze data, visualize results, and present their findings professionally.
C. Attitudes
1. Students will develop an innovative mindset towards leveraging digital twins for structural engineering challenges.
2. Students will adopt a problem-solving approach, utilizing advanced technologies for real-world applications.
3. The course encourages a proactive attitude toward independent work and continuous learning.
4. Students will cultivate an appreciation for interdisciplinary collaboration in digital twin development.
D. Autonomy and Responsibility
1. Students will take responsibility for independently planning and executing digital twin projects.
2. They will exercise autonomy in selecting appropriate monitoring systems and modeling techniques.
3. Students will develop accountability for accurate and secure data collection, processing, and interpretation.
4. Leadership and teamwork skills will be enhanced through collaborative project development and presentation.
2.3 Methods
The Mirrored Classroom and Learning by doing methods plays an important role in education. The knowledge of the subject helps to synthesise knowledge from previous subjects, and therefore the subject also uses the Research Based Learning method.
2.4 Course outline
1.Introduction to the theory of digital twins, practical examples, course structure
2.Automated monitoring systems 1: types of measurement systems, their construction, real-time data extraction, data storage, processing
3. Digital Twin Lab: monitoring systems lab 1, plan and create sensors, independent work
4. Digital Twin Lab: monitoring systems lab 2, collect sensor data, independent work
5. Automated numerical modeling: parametric design, low code solution, modeling with programming
6. Digital Twin Lab: automated numerical analysis lab 1, modeling, independent work
7. Digital Twin Lab: automated numerical analysis lab 2, analysis levels, results extraction, independent work
8. BIM model development, parametric design, vizualisation solutions
9. Digital Twin Lab: BIM model development, parametric design, visualisation 1, independent work
10. Digital Twin Lab: BIM model development, parametric design, visualisation 1, independent work
11. Digital twin processes, connecting systems, visualisation, decision support, databases, data storage, cloud-based services
12. Digital Twin Lab: developing a digital twin project 1, independent work
13. Digital Twin Lab: developing a digital twin project 2, independent work
14. Digital Twin Lab: developing a digital twin project 3, independent work
The above programme is tentative and subject to changes due to calendar variations and other reasons specific to the actual semester. Consult the effective detailed course schedule of the course on the subject website.
The above programme is tentative and subject to changes due to calendar variations and other reasons specific to the actual semester. Consult the effective detailed course schedule of the course on the subject website.
2.5 Study materials
Digital Twin journals
Software learning materials
2.6 Other information
0
2.7 Consultation
Consultation take place during the course.
This Subject Datasheet is valid for:
2025/2026 semester II
II. Subject requirements
Assessment and evaluation of the learning outcomes
3.1 General rules
The assessment of the learning outcomes is specified in clause 2. above, and the continuous evaluation of student
performance occurs via a projectwork, class questions, consultations.
3.2 Assessment methods
| Assessment Name (Type) | Code | Assessed Learning Outcomes |
|---|---|---|
| projectwork | P | A 1-8. B1-8. C1-4. D1-4 |
The dates of deadlines of assignments/homework can be found in the detailed course schedule on the subject’s website.
3.3 Evaluation system
| Code | Weight |
|---|---|
| P | 100% |
| Total | 100% |
3.4 Requirements and validity of signature
Signature cannot be obtained
3.5 Grading system
| Grade | Score (P) |
|---|---|
| excellent (5) | 90≤P |
| good (4) | 75≤P<90% |
| satisfactory (3) | 65≤P<75% |
| pass (2) | 50≤P<65% |
| fail (1) | P<50% |
3.6 Retake and repeat
The projectwork can be re-submitted on the extra week at the end of the semester.
3.7 Estimated workload
| Activity | Hours/Semester |
|---|---|
| contact hours | 28 |
| self-learning | 20 |
| projectwork | 42 |
3.8 Effective date
1 September 2025
This Subject Datasheet is valid for:
2025/2026 semester II