Undergraduate Course: Multi-Scale Modelling of Fluid Transport Phenomena (CHEE11037)
Course Outline
| School | School of Engineering |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Year 5 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course introduces advanced concepts and methods for multiscale modelling of fluid dynamics in chemical engineering, with a particular focus on meso- to macro-scale phenomena. Students will examine fluid problems where important physical effects occur on multiple, coupled length and time scales that cannot be fully resolved or simulated within a single model, and will learn how to construct and justify model hierarchies that combine different levels of abstraction. Using a provided multiscale simulation code, students will explore how mesoscale simulations can be used to extract effective properties and closures for use in continuum-scale models. The course emphasises physical understanding, model credibility (including verification, validation and uncertainty at different scales) and the emerging role of machine learning for building surrogate models and data-driven closures, preparing students to critically assess multiscale modelling strategies for complex fluid engineering applications. |
| Course description |
The course will cover:
- Advanced mathematical modelling of physical phenomena
- Background and relevance of multiscale modelling of fluid transport phenomena in engineering and science
- Continuum description of and closure relations for mesoscale and macroscale phenomena
- Heterogeneity, anisotropy and scale separation
- Multiscale modelling strategies (such as parameter passing, upscaling, embedded models)
- Scenario-dependent decision making in multiscale model design
- Hands-on numerical simulations of representative problems in multiscale fluid dynamics
- Verification, validation and uncertainty in multiscale modelling
- Ongoing developments and opportunities of machine learning in multiscale modelling
- Revision with integrated example and exam preparation
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Information for Visiting Students
| Pre-requisites | Programming, Fluid Mechanics and Mathematics knowledge equivalent to Y2 of the Chemical Engineering programmes. |
| High Demand Course? |
Yes |
Course Delivery Information
| Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- Identify and justify multiscale model hierarchies
- Explain and critique closure relations for continuum models
- Propose and justify multi-scale coupling strategies
- Critically evaluate multiscale model credibility and limitations
- Discuss the role of machine learning in multiscale fluid dynamics
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Reading List
- Weinan, 'Principles of Multiscale Modeling'
- Basmadjian, 'The Art of Modeling in Science and Engineering'
- Aris, 'Mathematical Modeling - A Chemical Engineer's Perspective'
- Oberkampf & Roy, 'Verification and Validation in Scientific Computing' |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Mathematical modelling,Multiscale modelling,Fluid dynamics,Numerical simulation |
Contacts
| Course organiser | Dr Timm Krueger
Tel: (0131 6)50 5679
Email: Timm.Krueger@ed.ac.uk |
Course secretary | Mr Mark Ewing
Tel:
Email: mewing2@ed.ac.uk |
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