Room 4E 3.11
Tel: +44 (0) 1225 386296
Interested in supervising students studying:
- Energy use in buildings and cities
- Complex interactions and behaviours involved in energy consumption
- Distributed generation in cities
Dr Nick McCullen
Nick McCullen is a Lecturer in the Department of Architecture and Civil Engineering. He is interested in how the complex interactions between the various components, such as buildings, technology, the environment, and people, result in the energy consumption of the built environment.
Nick gained his undergraduate Master’s degree in Physics at the University of Manchester. He spent two years teaching English in rural Japan on the Japan Exchange Teaching (JET) programme before returning for his PhD in the Manchester Centre for Nonlinear Dynamics. On this he researched chaotic phenomena in coupled oscillators, with application to many complex behaviours arising from the interactions between simple systems. One application of the research was sensitive signal detection, related to the resonant coupling of oscillations found in insect hearing.
Nick's first post-doctoral research position was at the University of Bath, investigating electrical network models of composite materials in the Bath Institute for Complex Systems.This involved modelling the microstructure of these materials as many individual elements coupled via a network of interactions between them, to understand the macroscopic, system level 'emergent properties' observed in physical experiments.
This line of research led him to the University of Leeds as part of the multi-disciplinary project Future energy decision—making for cities: Can complexity science rise to the challenge. Nick's work involved mathematical and computational modelling of the influence of various factors affecting the uptake of energy efficiency innovations by individual households in a city, including the influence of peers via their personal social network.
Nick is currently involved in research proposals related to the modelling of the vastly complex city energy systems and end users to better understand energy use in cities and homes.
A part of this is working out what measures will be necessary to address the twin challenge of making cities capable of both remaining habitable by adapting to the possible effects of future climate change, and also mitigating further change by providing the energy needs of their citizens more sustainably.
- Low Carbon Design
Budd, C. J., McCullen, N. J. and Almond, D., 2011. Emergent behaviour in large electrical networks. In: Georgoulis, E. H., Iske, A. and Levesley, J., eds. Approximation Algorithms for Complex Systems. Springer, pp. 3-26. (Springer Proceedings in Mathematics 3)
Bale, C. S. E., McCullen, N. J., Foxon, T. J., Rucklidge, A. M. and Gale, W. F., 2013. Harnessing social networks for promoting adoption of energy technologies in the domestic sector. Energy Policy, 63, pp. 833-844.
McCullen, N. J., Rucklidge, A. M., Bale, C. S. E., Foxon, T. J. and Gale, W. F., 2013. Multiparameter models of innovation diffusion on complex networks. SIAM Journal on Applied Dynamical Systems, 12 (1), pp. 515-532.
Almond, D. P., Budd, C. J., Freitag, M. A., Hunt, G. W., McCullen, N. J. and Smith, N. D., 2013. The origin of power-law emergent scaling in large binary networks. Physica A: Statistical Mechanics and its Applications, 392 (4), pp. 1004-1027.
McCullen, N. J., Ivanchenko, M. V., Shalfeev, V. D. and Gale, W. F., 2011. A dynamical model of decision-making behavior in a network of consumers with applications to energy choices. International Journal of Bifurcation and Chaos in Applied Sciences and Engineering, 21 (09), pp. 2467-2480.
McCullen, N. and Moresco, P., 2011. Route to hyperchaos in a system of coupled oscillators with multistability. Physical Review E (PRE), 83 (4), 046212.
Mccullen, N. J., Almond, D. P., Budd, C. J. and Hunt, G. W., 2008. The robustness of the emergent scaling property of random RC network models of complex materials. Journal of Physics D: Applied Physics, 42 (6), 064001.
McCullen, N., Mullin, T. and Golubitsky, M., 2007. Sensitive signal detection using a feed-forward oscillator network. Physical Review Letters, 98 (25), p. 254101.
McCullen, N. and Moresco, P., 2006. Method for measuring unstable dimension variability from time series. Physical Review E (PRE), 73 (4), 046203.
Conference or Workshop Items
Bale, C., McCullen, N., Foxon, T., Rucklidge, A. and Gale, W., 2013. Modelling diffusion of energy innovations on a social network and integration of real-world data.
Bale, C., McCullen, N., Foxon, T., Rucklidge, A. and Gale, W., 2011. Local authority interventions in the domestic sector and the role of social networks : a case study from the city of Leeds. In: Energy and People: Futures, complexity and challenges, 2012-09-20 - 2012-09-21, Oxford.
McCullen, N., 2007. Transition to High Dimensional Dynamics in Systems of Coupled Oscillators. Thesis (Doctor of Philosophy (PhD)). University of Manchester.