Bath Applied and Interdisciplinary Mathematics Seminar - upcoming
Join us at AIMS on Tuesdays at 13.15 at 6E 2.1. All are welcome!
| Date | Speaker | Title |
| 29 Sep 2026 | Rahil Valani (University of Oxford) |
Superwalking droplets: active particles with a memory
Active particles come in many forms, from bacteria, cells and algae to synthetic colloids and microrobots, all converting energy into directed motion. Their dynamics become particularly interesting when their motion modifies the surrounding environment, which in turn acts back on them. What happens when this feedback gives an active particle a memory of its past? In this talk, I will explore this question using superwalking droplets which are millimetre-scale liquid droplets that self-propel across a vertically vibrated fluid bath through interaction with the waves they generate. The feedback between droplet and wave gives these active wave–particle entities an effective memory and produces surprisingly rich dynamics. I will discuss how this memory shapes individual locomotion, including steady walking and stop-and-go motion, before turning to wave-mediated interactions, collective behaviour, and emergent clusters formed by very large superwalkers. Finally, I will show how reduced models of memory-driven wave–particle motion lead to low-dimensional dynamical systems related to the Lorenz equations, providing a bridge between fluid mechanics, active matter and nonlinear dynamics. |
| 6 Oct 2026 | Mark Blyth (the younger) (University of Bristol) |
Why core-surface battery models fail and how to fix them
Thermal models are essential for the design, management, and control of rechargeable batteries. The simplest approach to thermal battery modelling is to assume that an entire cell is at the same temperature, leading to a so-called “lumped” model of battery temperature. In practice, the interior of a battery will heat up more than its surface because heat is generated throughout the battery but cooling can only occur at the battery surface. This led to the development of core-surface battery models where the core temperature and the surface temperature were treated as separate variables. Unfortunately, the most widely-used core-surface models lose accuracy as thermal gradients increase and they are prone to overfitting, meaning that models calibrated in one setting are hard to translate to other settings. In this talk, I will describe recent work where we explore fundamental problems with the approach used to develop core-surface models and show how an alternative approach based on a two-mode Galerkin approximation can lead to greatly-improved accuracy without increasing model complexity. |
| 13 Oct 2026 | Ed Brambley (University of Warwick) |
Mathematical Modelling of Industrial Metal Forming
Metal forming involves permanently deforming metal into a required shape. Many forms of metal forming are used in industry: rolling, stamping, pressing, drawing, etc; for example, 99% of steel produced globally is first rolled before any subsequent processing. Most theoretical studies of metal forming use Finite Elements, which is not fast enough for real-time control of metal forming processes, and gives little extra insight. As an example of how little is known, it is currently unknown whether a sheet of metal that is squashed between a large and a small roller should curve towards the larger roller, or towards the smaller roller. In this talk, I will give a brief overview of metal forming, and then some progress my group have been making on some very simplified models of cold sheet rolling in particular. The mathematics involved will include some modelling and asymptotics (including multiple scales), and should be accessible to a general applied mathematics audience. |
| 20 Oct 2026 | Marina Costa Merch Dos Santos, Amy Darroch, Shiyi Ding (University of Bath) |
PhD Student Presentations
|
| 27 Oct 2026 | Ross Woods (University of Bristol) |
A Stochastic Model for Understanding How Climate Affects Snowpacks
Melting snow is a key source of water for more than 2 billion people. Changes in climate are already causing changes in the amount and timing of snowmelt, and substantial further changes are expected in future. Communicating why these changes are happening, and why they aren’t the same everywhere, will help water managers to navigate these changes. At present, we have scientific capability to calculate the expected changes in snow, but not to explain conceptually why the effects vary from place to place. The difficulty arises because snowpack dynamics are driven by nonlinear (but elementary) interactions between weather elements such as temperature and precipitation, at multiple timescales. In this talk I will (i) show some typical snow and climate data (ii) present a deterministic snowpack model and explain its strengths and weaknesses (iii) propose a non-stationary stochastic model for the snowpack, and show some preliminary results. |
| 3 Nov 2026 | Elizabeth Lewis (University of Manchester) |
Integrated water management: where can mathematics improve operational hydrology?
Water management is a substantial practical challenge. Because rain falls everywhere, water can be managed anywhere, and both the complexity of the system and the number of possible interventions are very large. Producing evidenced management plans is therefore difficult, and we rely on models and data to lay out evidence in a structured way, explore options, and support decisions with critical scrutiny. In practice, water is managed at different scales and in separate silos: in England, surface water flooding is the responsibility of local authorities, river flooding of the Environment Agency, water supply of regional water companies, and water quality of several organisations. These elements are, however, parts of one interacting system, and implementation of interventions, and the funding of them, could be considerably more efficient if their benefits were assessed together. Managing water in an integrated way has long been an ambition, but technical and logistical barriers have so far limited progress. There is now both political momentum, through the government’s water reform programme, and technological capability for integrating evidence systems. We have been working with the Greater Manchester Integrated Water Management team, who are leading this approach, to design and develop the informatics infrastructure that supports it. This seminar presents that work: mapping the complex system of water processes, establishing a data catalogue, reviewing evidence on which important processes are missing from current modelling frameworks, and designing an integrated modelling system, including where AI can usefully be applied. The breadth of this work provides a basis for discussing where mathematics could improve operational hydrology. Topics will include formulating well-posed questions, scenario testing and optioneering, information theory and its relationship to data availability, model selection and benchmarking, sensitivity analysis, calibration and validation strategies, and the quantification and reduction of uncertainty. |
| 10 Nov 2026 | Simon Mathias (Durham University) |
|
| 17 Nov 2026 | David Sibley (Loughborough University) |
|
| 24 Nov 2026 | AIMS members (University of Bath) |
PhD project proposals
Project proposals from AIMS group members |
Subscribe to AIMS
Here are the steps to join the AIMS mailing list.
- Send a message to sympa@lists.bath.ac.uk from the address you want to subscribe to the list.
- In the subject line of your message, type in: subscribe aims_seminars YourFirstName YourLastName
- Leave the message body blank
Zoom meeting links
Join Zoom Meeting
https://bath-ac-uk.zoom.us/j/99753762534?pwd=4gMpJvORysHydzEzym33HsBuS0Vg2H.1
Meeting ID: 997 5376 2534
Passcode: 411754