Chaotic mixing
Project Description
Mixing occurs in many diverse situations, ranging from large-scale systems such as planets and stars (e.g. the dynamo problem) to small-scale systems such as in the food industry (e.g. optimum ways of mixing as applied to bread making). Mixing is not only particularly rich in terms of applications but also benefits from having an active link with mathematics, largely via the theory of dynamical systems as well as some recent work on topology and functional analysis. Set against this background, the research project/area (depending on the applicant's wish for something shorter and concrete or longer and more open-ended) is motivated by a wish to better understand bio-physical interactions and consequences for ecological behaviour in the ocean.
Motivated by the research in the "fast dynamo" problem in astrophysics (e.g. Soward, 1987, J. Fluid Mech.; Gilbert, 1991, Nature; Galloway & Proctor, 1992, Nature) the proposed project wishes to consider the chaotic mixing of "active" tracer(s), in the sense that the "active" tracer(s) follows it's own governing equation (in this case some ecological model) and the advective flow is prescribed. The initial research will start with a numerical investigation, and has the flexibility to go more into modelling and/or analysis of mixing using more technical mathematical tools depending on the student's interest/training. While the problem is ocean ecology inspired, it is fundamentally a fluid dynamics / applied mathematics problem, so would particularly suit someone with training in a numerate subject (e.g. mathematics, physics, engineering). Willingness to do some scientific programming is essential; knowledge or willingness to learn Julia and/or Python would be desirable.
Motivated by the research in the "fast dynamo" problem in astrophysics (e.g. Soward, 1987, J. Fluid Mech.; Gilbert, 1991, Nature; Galloway & Proctor, 1992, Nature) the proposed project wishes to consider the chaotic mixing of "active" tracer(s), in the sense that the "active" tracer(s) follows it's own governing equation (in this case some ecological model) and the advective flow is prescribed. The initial research will start with a numerical investigation, and has the flexibility to go more into modelling and/or analysis of mixing using more technical mathematical tools depending on the student's interest/training. While the problem is ocean ecology inspired, it is fundamentally a fluid dynamics / applied mathematics problem, so would particularly suit someone with training in a numerate subject (e.g. mathematics, physics, engineering). Willingness to do some scientific programming is essential; knowledge or willingness to learn Julia and/or Python would be desirable.
Supervisor
MAK Julian
Quota
2
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles
* Create a numerical program (ideally in Julia or Python) to carry out the numerical experiments
* Carry out numerical experiments with the program created
* Create diagnostics for computing quantities quantifying e.g. mixing rates, degree of chaos etc.
* Investigate consequences arising from changing the advecting flow field and/or the equation governing tracer advection on mixing
* Update themselves with the advances in related research fields
* Document code and research progress where appropriate
* Carry out numerical experiments with the program created
* Create diagnostics for computing quantities quantifying e.g. mixing rates, degree of chaos etc.
* Investigate consequences arising from changing the advecting flow field and/or the equation governing tracer advection on mixing
* Update themselves with the advances in related research fields
* Document code and research progress where appropriate
Applicant's Learning Objectives
* gain experience in applying knowledge from courses to a concrete problem
* gain experience in combining tools from different fields to tackle an inter-disciplinary problem
* gain insight into the process of knowledge creation
* obtain transferable skills (e.g. scientific programming, communication, time-management)
* gain experience in combining tools from different fields to tackle an inter-disciplinary problem
* gain insight into the process of knowledge creation
* obtain transferable skills (e.g. scientific programming, communication, time-management)
Complexity of the project
Moderate