CEG8006 : Digital Engineering and Analytics
- Offered for Year: 2023/24
- Module Leader(s): Dr Craig Robson
- Lecturer: Professor Stuart Barr
- Owning School: Engineering
- Teaching Location: Newcastle City Campus
Semesters
| Semester 1 Credit Value: | 10 |
| ECTS Credits: | 5.0 |
Aims
This module will introduce how digital technologies and methods are employed in civil-engineering, covering a wide range of digital technologies, analysis methods, and their associated risks and regulatory considerations. It equips the students with the knowledge and skills to represent the built environment, analyse large and complex datasets (big data), to automate simulation and modelling processes, interrogate real-time and sensor streams, and effectively communicate results.
The aims of the module are:
• How digital technologies can be used to represent and model urban environments
• To demonstrate analysis techniques that have broad applicability across all aspects of civil engineering, with particular emphasis on timeseries, processing raw data, and data quality and suitability assessment To provide an opportunity for students to assess real-world problems in an efficient manner by maximising the value of existing data and using automation
• Develop an awareness of how data-centric environments are continuing to change civil-engineering practice
• To raise an awareness of associated regulatory, legal and privacy aspects relating to data and infrastructure.
Outline Of Syllabus
Lectures and computer practical sessions will be structured around real-world problems and solutions, from how we can represent real-world features such as buildings, to how we can analyse real-world engineering problems relevant to all themes of civil-engineering with geospatial knowledge underpinning much of this.
The module with cover:
• Digital methods for modelling (e.g., BIM, 3D modelling, digital twins, coding)
• Digital environments (GIS, coding)
• Digital data handling
• Data modelling with code (e.g., timeseries modelling, quality assessment, artificial intelligence (AI), APIs, Internet of Things (IOT))
• Advanced modelling methods (e.g., batch processing, parameter sweeps, automation)
• Digital data visualisation (e.g., dashboards, decision support tools)
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 12 | 1:00 | 12:00 | Lectures covering theory and essential concepts |
| Guided Independent Study | Assessment preparation and completion | 1 | 45:00 | 45:00 | Report |
| Scheduled Learning And Teaching Activities | Practical | 5 | 3:00 | 15:00 | Practicals giving hand-on experience of working with digital tools for engineering and analytics |
| Scheduled Learning And Teaching Activities | Small group teaching | 3 | 1:00 | 3:00 | Seminars - speakers from industry with real-world examples of the use of digital technologies |
| Guided Independent Study | Independent study | 1 | 25:00 | 25:00 | Background reading and desk research |
| Total | 100:00 |
Jointly Taught With
| Code | Title |
|---|---|
| CEG3718 | BIM and City Modelling |
Teaching Rationale And Relationship
Theoretical and knowledge-based outcomes are primarily taught through lectures and seminars. This is especially appropriate where the material relates to forthcoming technology that students should have an awareness of but is not yet widespread in use, such as digital twins for infrastructure systems. An extensive set of notes will accompany these sessions.
Skills outcomes are achieved mainly through computer practical sessions, allowing the students to apply the methods to a hypothetical but realistic civil engineering scenario. Students will be supported through the practical sessions with instructions that cover the basics of the methods but will be expected to conduct their own research and work together in some instances to develop their problem solving skills.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Written exercise | 1 | M | 100 | Individual report (approx. 8 pages, including diagrams and tables) |
Assessment Rationale And Relationship
An individual report is the primary method of assessment. The report should evidence results achieved by application of the skills developed in the data, analysis, and automation techniques. In addition, the report will require discussion of the limitations and transferability of those results alongside recommendations for further work, through which it should adequately demonstrate the knowledge outcomes. A degree of flexibility in the brief should allow the students to demonstrate these with respect to their chosen stream on the programme and preferences towards specific software or methods.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CEG8006's Timetable