School of Mathematical Sciences

Society projects

A list of currently available society projects within the MASS doctoral training centre. For queries in relation to a particular project, please contact the supervisors associated with that project. Click on a project name to view more details below.

Engaging school teachers and learners in the mathematics of sustainability

Supervisors:  Dr Ria Symonds (Mathematical Sciences),  Dr Stephen Hibberd (Mathematical Sciences),  Professor Andrew Noyes (Education)

In partnership with a small number of school mathematics departments, the student will design, develop and assess the effectiveness of curriculum materials that engage teachers and learners in the mathematics of sustainability [1]. The materials would support specific curricular goals (e.g. learning of algebra, proportional reasoning). The project will also investigate young people's understanding of sustainability and the effectiveness of the materials in enhancing this understanding and developing critical-mathematical literacy. 

[1]  Maths Awareness Month, Sustainability Counts.  


Dynamic socio-hydrology modelling: mathematical approaches for adaptive co-evolution

Supervisors:  Dr Nick Mount (Geography), Prof Markus Owen (Mathematical Sciences)

Socio-hydrology is an emerging focus of hydrological science that views social and hydrological systems as co-evolutionary, governed by an array of complex feedbacks.  The International Association of Hydrological Sciences (IAHS) decadal Science Plan (2013-2023) asserts that the most pressing challenges associated with water resources globally (e.g. resilience to drought and flood, adequate water availability and quality) can only be properly addressed if the co-evolution of the socio-hydrologic system can be adequately represented and understood.  A key challenge facing those tasked with managing the world’s water resources is to develop a new modelling paradigm that moves away from isolated representation of the physical, hydrologic system towards a fully coupled representation of both social and hydrologic systems.

Preliminary attempts to do this have focussed on the issue of flooding and have progressed using relatively simple mathematical models built on differential equations.  These models seek to describe the co-evolution of hydrologic (flood height), technologic (flood defence infrastructure), societal (risk awareness), economic (wealth and defence funding) and political (planning policy) variables. These models have been very useful in revealing the likely influence of socio-hydrologic phenomena such as ‘collective flood memory’ on a community’s overall flood risk and in projecting the role that social behaviour might have on flood risk under a changing climate. However, the static nature of existing socio-hydrologic models limits their capacity to represent critical, dynamic co-evolutionary processes.  We know that major ‘shocks’ to the hydrologic and/or socio-economic sub-systems often change the rules by which the whole system co-evolves. Examples of such shocks include large shifts in the course of a river (e.g. the course of the Kosi River in India has shifted by 120 km in the last 250 years), and wholesale changes to the governance of flood risk management (e.g. following the UK summer floods of 2007).

The objective of this PhD is to advance the field of socio-hydrology by developing mathematical approaches to support adaptive causal pathways in socio-hydrologic modelling.  It will examine the potential of alternative approaches to delivering adaptive model structures (e.g. model switching and dynamic causal models) as well as methods for supporting dynamic parameter adjustment.  It is anticipated that, initially, the project will build upon existing examples of socio-hydrologic models of flood risk.  However, it is expected that the successful candidate will wish to expand the application domain to include alternative socio-hydrologic phenomena such as irrigated agriculture models.


Form, function and utility in small community energy networks

Supervisors: Prof Mark Gillott (Architecture & Built Environment), Dr Keith Hopcraft (Mathematical Sciences),Dr Parham Mirzaei Ahrnjani (Architecture & Built Environment)

This is a unique and exciting opportunity to undertake research that spans across the disciplines of energy engineering and mathematical sciences. Successful applicants will be joining a strong interdisciplinary team from academia and industry who are currently working on the delivery of the Energy Research Accelerator (ERA) Community Energy System (CES) demonstrator at the 15 acre Trent Basin site in Nottingham. The project will investigate the energy challenges and complexity science issues associated with heat and electrical power generation, storage and use arising from the connections between micro-generation output, grid/heat loads, weather, and energy/power demands (including occupant behavior) combined with variable load energy storage devices in order to provide energy stability, a reduction of cost and associated carbon emissions from fossil fuel use. The PhD research will develop new multi-vector CES models that utilise ‘big data’ obtained from a dedicated onsite monitoring platform at the housing development applied to a heterogeneous network of users. The work will ultimately help inform the design, implementation and operation of local community energy schemes in the UK. Applicants should have a Bachelor Science or Engineering (at least 2i) and/or a Master of Science or Engineering in Mathematical Sciences, Engineering or Energy related disciplines.


School of Mathematical Sciences

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