PhD Research

Determining Cluster-cluster Aggregation Rate Kernels Using Inverse Methods

Supervisors: Dr. Colm Connaughton and Prof. R. C. Ball.

Funded by: The EPSRC

Brief Description: It would be useful to determine the extent to which the existence of noise, spatial correlations, and other phenomena in a real aggregation process can be `folded back’ into an estimation of a kernel function (obtained using inverse methods) that could then be used within a mean-field phenomenological surrogate. Such a surrogate model might then prove useful for enhancing the accuracy of some models of larger processes that include aggregation processes that are presently weakly modelled, e.g. rain formation in turbulent air within clouds. It might also allow us to deduce key properties of the real aggregation processes in question.
In an initial phase, we seek sufficiently robust, accurate inversion methods for determining kernel functions from benchmark data with known characteristics.

See also: A Brief Non-mathematical Introduction to this Research for the Uninitiated.

Peer-Reviewed Papers

Peter P. Jones, Robin C. Ball, Colm Connaughton, Nonlinear Least Squares Method for the Inverse Droplet Coagulation Problem, Phys. Rev. E, 88, 012138, (July 2013)

Robin C. Ball, Colm Connaughton, Peter P. Jones, R. Rajesh, Oleg Zaboronski, Collective Oscillations in Irreversible Coagulation Driven by Monomer Inputs and Large-Cluster Outputs, Phys. Rev. Lett. 109, 168304 (2012)

Colm Connaughton and Peter P. Jones, Some Remarks on the Inverse Smoluchowski Problem for Cluster-Cluster Aggregation
J. Phys.: Conf. Ser. 333 012005 (2011), doi:10.1088/1742-6596/333/1/012005

Posters

December 2011

Notes

Basic Linear Inverse Method Theory

Academic Qualifications

MA, Analytic Philosophy (Univ. of Nottingham, 1997)
MSc, Complexity Science (Univ. of Warwick, 2009)
PhD, Theoretical Physics and Complexity Science (Univ. of Warwick, 2013). [Thesis document.]

Other work

Produced a slideshow for the European Conference on Complex Systems 2009 public session.
(Right click on image below to download movie. Caution: ~60MB; .mov format needs Quicktime.)
Licence: For research, educational, and non-commercial use.