Programplaner og emneplaner - Student
SMUA4300 Advanced Research Methods Course description
- Course name in Norwegian
- Advanced Research Methods
- Study programme
-
Master's Degree Programme in Transport and Urban Planning
- Weight
- 5.0 ECTS
- Year of study
- 2023/2024
- Curriculum
-
FALL 2023
- Schedule
- Programme description
- Course history
-
Introduction
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.
Recommended preliminary courses
None
Required preliminary courses
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
Learning outcomes
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
Teaching and learning methods
The exam consist of two parts:
1) Written project report approx 30 pages, weighted 70 %
2) Oral examination of project presentation, weighted 30 %
All assessment parts must be awarded a pass grade (E or better) in order for the student to pass the course.
Assessment part 1) can be appealed. Assessment part 2) can not be appealed.
Course requirements
All types of materials and equipment are allowed.
Assessment
Grade scale A-F
Permitted exam materials and equipment
1) One internal examiner,
2) Two internal examiners
External examiners are used regularly.
Grading scale
BYVE3610 Jernbaneteknikk
BYVE3620 Vei- og jernbaneteknikk
Examiners
1) Two internal examiners.
2) Two internal examiners
External examiners are used regularly.
Course contact person
Lena Magnusson Turner