MABY5040 Advanced Railway Engineering Course description

Railway transportation is one of the key and fastest modes of mobility for passengers and cargo in large quantities. This course covers both basic topics such as the key components of railway systems and their characteristics, track geometric design and speed limitation, and advanced topics including coupled train-track system, track dynamics and vibration, and geotechnical aspects related to railway tracks. In this course, different types of railway tracks, the interaction between the track and the rolling stock, the static and dynamic modelling and analysis, urban railway systems, high-speed rails, as well as the safety and maintenance of railway systems will be discussed.

1) Two internal examiners.

2) Two internal examiners

 External examiners are used regularly.

Upon completing the course, the student should have the following outcomes, defined in terms of knowledge, skills, and general competence:

Knowledge

Students have in-depth knowledge of:

• various railway systems and vehicle and track structures
• track geometry, superelevation and speed limitation
• the interaction between the vehicle and the track
• dynamic behavior of railway systems
• high-speed rails, urban rails and design considerations

Skills

Students can:

• select and design an appropriate track system
• calculate the vehicle loads and speed limitation
• perform computational modelling and analysis of coupled vehicle-track system
• quantify the effect of railway imperfection and wear and tear

General competence

Students:

• can understand the principles for geometric and structural design of railway tracks
• are capable of conducting simple and complex train-track simulations with the aid of computational tools and programming languages
• are familiar with railway maintenance requirements and techniques

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge:

The student has advanced knowledge of:

• research methods, especially in engineering research
• statistical and analytical techniques, including knowledge of the most common libraries and tools used in statistical analysis and visualisation of the results
• designing experiments, preparing data and interpreting analysis results
• how relevant statistical and computational techniques relate to each other and where they are used

Skills:

The student has:

• required skills in setting up sound experiments, hypotheses and research questions, and in finding and preparing relevant data
• required skills in identifying which statistical and analytical techniques are to be used and how and where they should be used
• hands-on experience with some of the most common computational techniques and libraries as well as related tools for statistical analysis
• hands-on experience with relevant tools for use in analyses

General competence:

The student:

• has broad overview of the computational tools and techniques used in analysis and engineering research, including statistical techniques and techniques related to data science and machine learning
• has an overview of the terminology related to statistical analysis and data science.
• is able to design experiments for successful engineering research, analyses and critical interpretation of results
• can extend his/her knowledge and skills in programming/scripting, analysing, managing and visualizing data

This course features 3 optional preparatory weeks and 9 weeks of lectures that provide both theoretical and practical content and hands-on experience. The students will be given one mandatory project task to work in groups during the semester.

The preparatory weeks are optional and is for supporting the students who need to build up or renew Python/R programming skills, also using tools like Notebooks for presenting with embedded code. Notebooks will be used widely in lectures, exercises and in the mandatory project.

Students are required to complete one mandatory project assignment in allocated time and get it approved. Students who fail to meet the coursework requirements can be given up to one re-submission opportunity.

1) A final course report in predefined areas prepared in groups of 2 (or more) students, approx. 15 - 20 pages (excluding appendices, but including code and calculations), weighted 60%.

2) Oral presentation and examination of the report, 15 minutes + 5 minutes Q&A, weighted 40%.

Both assessment parts must be awarded a pass grade (E or better) to pass the course. 

Assessment parts: 1) can be appealed, 2) cannot be appealed

1) All aids are permitted, as long as the rules for source referencing are complied with.

2) None

Graded scale A-F.