Forthcoming events in this series


Thu, 07 Mar 2024

12:00 - 13:00
L3

Short- and late-time behaviours of Fokker-Planck equations for heterogeneous diffusions

Ralf Blossey
(CNRS & University of Lille, France)
Abstract

The Fokker-Planck equation is one of the major tools of statistical physics in the description of stochastic processes, with numerous applications in physics, chemistry and biology. In the case of heterogeneous diffusions, the formulation of the equation depends on the choice of the discretization of the stochastic integral in the underlying Langevin-equation due to the multiplicative noise. In the Fokker-Planck equation, the choice of discretization then enters as a parameter in the definition of drift and diffusion terms. I show how both short- and long-time limits are affected by this choice. In the long-time limit, the existence of normalizable probability distribution functions is not always guaranteed which can be remedied by invoking elements of infinite ergodic theory. 

[1] S. Giordano, F. Cleri, R. Blossey, Phys Rev E 107, 044111 (2023)

[2] T. Dupont, S. Giordano, F. Cleri, R. Blossey, arXiv:2401.01765 (2024)

Thu, 22 Feb 2024

12:00 - 13:00
L3

Structural identifiability analysis: An important tool in systems modelling

Michael Chappell
(University of Warwick)
Abstract

For many systems (certainly those in biology, medicine and pharmacology) the mathematical models that are generated invariably include state variables that cannot be directly measured and associated model parameters, many of which may be unknown, and which also cannot be measured.  For such systems there is also often limited access for inputs or perturbations. These limitations can cause immense problems when investigating the existence of hidden pathways or attempting to estimate unknown parameters and this can severely hinder model validation. It is therefore highly desirable to have a formal approach to determine what additional inputs and/or measurements are necessary in order to reduce or remove these limitations and permit the derivation of models that can be used for practical purposes with greater confidence.

Structural identifiability arises in the inverse problem of inferring from the known, or assumed, properties of a biomedical or biological system a suitable model structure and estimates for the corresponding rate constants and other model parameters.  Structural identifiability analysis considers the uniqueness of the unknown model parameters from the input-output structure corresponding to proposed experiments to collect data for parameter estimation (under an assumption of the availability of continuous, noise-free observations).  This is an important, but often overlooked, theoretical prerequisite to experiment design, system identification and parameter estimation, since estimates for unidentifiable parameters are effectively meaningless.  If parameter estimates are to be used to inform about intervention or inhibition strategies, or other critical decisions, then it is essential that the parameters be uniquely identifiable. 

Numerous techniques for performing a structural identifiability analysis on linear parametric models exist and this is a well-understood topic.  In comparison, there are relatively few techniques available for nonlinear systems (the Taylor series approach, similarity transformation-based approaches, differential algebra techniques and the more recent observable normal form approach and symmetries approaches) and significant (symbolic) computational problems can arise, even for relatively simple models in applying these techniques.

In this talk an introduction to structural identifiability analysis will be provided demonstrating the application of the techniques available to both linear and nonlinear parameterised systems and to models of (nonlinear mixed effects) population nature.


 
Thu, 08 Feb 2024

12:00 - 13:00
L3

Ocean dynamics on the margin of rotational control

John R Taylor
(University of Cambridge)
Further Information

Professor Taylor's research focuses on the fluid dynamics of the ocean. He is particularly interested in ocean turbulence and mixing, ocean fronts and the surface boundary layer, and the impact of turbulence on micro-organisms. Recent work has uncovered a fascinating and poorly-understood collection of processes occurring at relatively small scales (<O(10km)) where the vertical motion is strong but stratification and the Earth's rotation are important factors. Since these motions are too small to be directly resolved by global ocean and climate models, understanding their impact on the structure and dynamics of the ocean is one of the most pressing topics in physical oceanography. Currently, he is studying the dynamics of upper ocean fronts, the turbulent boundary layer beneath melting ice shelves, stratified turbulence, and the influence of physical processes on biogeochemical dynamics. Please see his homepage here for more information. https://www.damtp.cam.ac.uk/person/jrt51 

Abstract

Global scale ocean currents are strongly constrained by the Earth’s rotation, while this effect is generally negligible at small scales. In between, motions with scales from 1-10km are marginally affected by the Earth’s rotation. These intermediate scales, collectively termed the ocean submesoscale, have been hidden from view until recent years. Evidence from field measurements, numerical models, and satellite data have shown that submesoscales play a particularly important role in the upper ocean where they help to control the transport of material between the ocean surface and interior. In this talk I will review some recent work on submesoscale dynamics and their influence on biogeochemistry and accumulation of microplastics in the surface waters.

 

 

Thu, 01 Feb 2024

12:00 - 13:00
L3

Stop-and-go, hovercrafts and helicopters: the complex motility of droplet microswimmers driven by interfacial instabilities

Dr. Corinna Maaß
(University of Twente & Max Planck Institute for Dynamics and Self-Organization, Dynamics of Complex Fluids, Göttingen)
Abstract
In both experiment and numerics, active droplets are a simple but versatile toy model to study active processes from single agents to collective scales.
One hallmark of active or living matter lies in the conversion of microscopic free fuel energy to mesoscopic directed motion. Bio-microswimmers have evolved complex and sophisticated motility, like helical swimming or run-and-tumble dynamics, with similarly complex  mechanical or biochemical actuation.
However, similar periodic or chaotic motion may also arise simply from the nonlinear dynamics of fuel conversion that set autophoretic droplet swimmers in motion, leading to a wealth of biomimetic phenomena. In this talk, I will demonstrate how the interaction of a self-propelling droplet with its self-generated chemical and hydrodynamic environment generates swimming and pumping states, unsteady reorientation, helical dynamics and complex collective states.
Thu, 25 Jan 2024

12:00 - 13:00
L3

Collective motion and environmental path entropy

Matthew Turner
(University of Warwick)
Further Information

Matthew Turner is a Professor in the Physics department, attached to the Complexity center, at Warwick University. He works on Biological and Soft Matter Physics, amongst other things.

Abstract

 

We study “bottom-up” models for the collective motion of large groups of animals. Similar models can be encoded into (micro)robotic matter, capable of sensing light and processing information. Agents are endowed only with visual sensing and information processing. We study a model in which moving agents reorientate to maximise the path-entropy of their visual environment over paths into the future. There are general arguments that principles like this that are based on retaining freedom in the future may confer fitness in an uncertain world. Alternative “top-down” models are more common in the literature. These typically encode coalignment and/or cohesion directly and are often motivated by models drawn from physics, e.g. describing spin systems. However, such models can usually give little insight into how co-alignment and cohesion emerge because these properties are encoded in the model at the outset, in a top-down manner. We discuss how our model leads to dynamics with striking similarities with animal systems, including the emergence of coalignment, cohesion, a characteristic density scaling anddifferent behavioural phenotypes. The dynamics also supports a very unusual order-disorder transition in which the order (coalignment) initially increases upon the addition of sensory or behavioural noise, before decreasing as the noise becomes larger.

 

 

Thu, 18 Jan 2024

12:00 - 13:00
L3

Coupling rheology and segregation in granular flows

Nico Gray
(University of Manchester)
Further Information

Professor Nico Gray is based in the Department of Mathematics at the University of Manchester. 

This is from his personal website:

My research interests lie in understanding and modelling the flow of granular materials, in small scale experiments, industrial processes and geophysical flows.

[Mixing in a rotating drum][Flow past a rearward facing pyramid]

Current research is aimed at understanding fundamental processes such as the flow past obstacles, shock waves, dead-zones, fluid-solid phase transitions, particle size segregation and pattern formation. A novel and important feature of all my work is the close interplay of theory, numerical computation and experiment to investigate these nonlinear systems. I currently have three active experiments which are housed in two laboratories at the Manchester Centre for Nonlinear Dynamics. You can click on the videos and pictures as well as the adjacent toolbar to find out more about specific problems that I am interested in.

Abstract

During the last fifteen years, there has been a paradigm shift in the continuum modelling of granular materials; most notably with the development of rheological models, such as the μ(I)-rheology (where μ is the friction and I is the inertial number), but also with significant advances in theories for particle segregation. This talk details theoretical and numerical frameworks (based on OpenFOAM®) which unify these disconnected endeavours. Coupling the segregation with the flow, and vice versa, is not only vital for a complete theory of granular materials, but is also beneficial for developing numerical methods to handle evolving free surfaces. This general approach is based on the partially regularized incompressible μ(I)-rheology, which is coupled to a theory for gravity/shear-driven segregation (Gray & Ancey, J. Fluid Mech., vol. 678, 2011, pp. 353–588). These advection–diffusion–segregation equations describe the evolving concentrations of the constituents, which then couple back to the variable viscosity in the incompressible Navier–Stokes equations. A novel feature of this approach is that any number of differently sized phases may be included, which may have disparate frictional properties. The model is used to simulate the complex particle-size segregation patterns that form in a partially filled triangular rotating drum. There are many other applications of the theory to industrial granular flows, which are the second most common material used after fluids. The same processes also occur in geophysical flows, such as snow avalanches, debris flows and dense pyroclastic flows. Depth-averaged models, that go beyond the μ(I)-rheology, will also be derived to capture spontaneous self-channelization and levee formation, as well as complex segregation-induced flow fingering effects, which enhance the run-out distance of these hazardous flows.

 

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Thu, 30 Nov 2023

12:00 - 13:00
L1

Droplet dynamics in the presence of gas nanofilms: merging, wetting, bouncing & levitation

James Sprittles
(University of Warwick)
Abstract

Recent advances in experimental techniques have enabled remarkable discoveries and insight into how the dynamics of thin gas/vapour films can profoundly influence the behaviour of liquid droplets: drops impacting solids can “skate on a film of air” [1], so that they can “bounce off walls” [2,3]; reductions in ambient gas pressure can suppress splashing [4] and initiate the merging of colliding droplets [5]; and evaporating droplets can levitate on their own vapour film [7] (the Leidenfrost effect). Despite these advances, the precise physical mechanisms governing these phenomena remains a topic of debate.  A theoretical approach would shed light on these issues, but due to the strongly multiscale nature of these processes brute force computation is infeasible.  Furthermore, when films reach the scale of the mean free path in the gas (i.e. ~100nm) and below, new nanoscale physics appears that renders the classical Navier-Stokes paradigm inaccurate.

In this talk, I will overview our development of efficient computational models for the aforementioned droplet dynamics in the presence of gas nanofilms into which gas-kinetic, van der Waals and/or evaporative effects can be easily incorporated [8,9].  It will be shown that these models can reproduce experimental observations – for example, the threshold between bouncing and wetting for drop impact on a solid is reproduced to within 5%, whilst a model excluding either gas-kinetic or van der Waals effects is ~170% off!  These models will then be exploited to make new experimentally-verifiable predictions, such as how we expect drops to behave in reduced pressure environments.  Finally, I will conclude with some exciting directions for future wor


[1] JM Kolinski et al, Phys. Rev. Lett.  108 (2012), 074503. [2] JM Kolinski et al, EPL.  108 (2014), 24001. [3] J de Ruiter et al, Nature Phys.  11 (2014), 48. [4] L Xu et al, Phys. Rev. Lett. 94 (2005), 184505. [5] J Qian & CK Law, J. Fluid. Mech. 331 (1997), 59.  [6] KL Pan J. Appl. Phys. 103 (2008), 064901. [7] D Quéré, Ann. Rev. Fluid Mech. 45 (2013), 197. [8] JE Sprittles, Phys. Rev. Lett.  118 (2017), 114502.  [9] MV Chubynsky et al, Phys. Rev. Lett.. 124 (2020), 084501.
Thu, 23 Nov 2023

12:00 - 13:00
L1

Financial Health in Banking - combining automation and optimisation techniques in a multi-problem setup

Kal BUKOVSKI
(Sopra Steria)
Abstract

Predictive scoring modelling is a common approach to measure financial health and credit worthiness in banking. Whilst the latter is a key factor in making decisions for lending, evaluating financial health helps to identify vulnerable customers trending towards financial hardship, who need support. The current macroeconomic uncertainties amplify the importance of extensive flexibility in modelling data solutions so that they can remain effective and adaptive to a volatile economic environment. This workshop is focused on discussing relevant techniques and mathematical methodologies which can help modernise traditional scoring models and accelerate innovation. In summary, the problem definition in the banking context is how automation and optimality can be achieved in a multiobjective problem where a subset of existing data features should be selected by relevance and uniqueness, assigned scoring weights by importance and how a pool of customers can be categorised accordingly using their individual scores and auto-adjusting thresholds of risk classification scales. The key challenge is imposed by the mutual dependency of the three sub-problems and their objectives. Introducing or removing constraints in any of them can change the feasibility and optimality of the others and the overall solution. It is common for traditional scoring models to be mainly focused on the predictive accuracy and their setup is often defined and revised manually, following ad-hoc exploratory data analysis and business-led decision making. An automated optimisation of the data features’ selection, scoring weights and classification thresholds definition can achieve respectively: ▪ Precise financial health evaluation and book classification under changing economic climate; ▪ Development of innovative data-driven solutions to enhance prevention from financial hardship and bankruptcies.

Thu, 16 Nov 2023

12:00 - 13:00
L1

Elastocapillary windlass in one and two dimensions

Sébastien Neukirch
(Sorbonne Jean Le Rond d’Alembert Lab)
Abstract

Capillary forces acting at the surface of a liquid drop can be strong enough to deform small objects and recent studies have provided several examples of elastic instabilities induced by surface tension. Inspired by the windlass mechanism in spider webs, we present a system where a liquid drop sits on a straight fiber and attracts the fiber which thereby coils inside the drop. We then introduce a 2D extension of the mechanism and build a membrane that can extend/contract by a factor of 20.

Thu, 09 Nov 2023

12:00 - 13:00
L1

Reframing biological function as a learning problem

Andrea Liu
(University of Pennsylvania)
Further Information

Andrea Jo-Wei Liu is the Hepburn Professor of Physics at the University of Pennsylvania, where she holds a joint appointment in the Department of Chemistry. She is a theoretical physicist studying condensed matter physics and biophysics.

Abstract

In order for artificial neural networks to learn a task, one must solve an inverse design problem. What network will produce the desired output? We have harnessed AI approaches to design physical systems to perform functions inspired by biology, such as protein allostery. But artificial neural networks require a computer in order to learn in top-down fashion by the global process of gradient descent on a cost function. By contrast, the brain learns by local rules on its own, with each neuron adjusting itself and its synapses without knowing what all the other neurons are doing, and without the aid of an external computer. But the brain is not the only biological system that learns by local rules; I will argue that the actin cortex and the amnioserosa during the dorsal closure stage of Drosophila development can also be viewed this way.

 

Thu, 02 Nov 2023

12:00 - 13:00
L1

Model and data fusion: physics-driven learning in cancer research

Pasquale Ciarletta
(MOX Laboratory, Politecnico di Milano, Italy)
Abstract

The key role of physical and mechanical interactions in cancer emerges from a very large variety of data sources and methods - from genomics to bioimaging, from proteomics to clinical records. Thus, learning physics-driven relational information is crucial to characterize its progression at different scales.

In this talk I will discuss how mathematical and computational tools allow for learning  and better understanding of  the mechano-biology of cancer thanks to the integration of  patient-specific data and physics-based models. I will present a few applications developed in the last decade in which the development of  digital twins,  empowered by ad-hoc learning tools,  allows us to test new hypotheses,  to assess the model predictions against biological and clinical data, and to aid decision-making in a clinical setting.

Funding from MUR - PRIN 2020, Progetto di Eccellenza 2023-2027 and Regione Lombardia (NEWMED Grant, ID: 117599, POR FESR 2014-2020) is gratefully acknowledged.
Thu, 26 Oct 2023

12:00 - 13:00
L1

Adjoint-accelerated Bayesian Inference for joint reconstruction and segmentation of Flow-MRI images

Matthew Juniper
(University of Cambridge)
Abstract

We formulate and solve a generalized inverse Navier–Stokes boundary value problem for velocity field reconstruction and simultaneous boundary segmentation of noisy Flow-MRI velocity images. We use a Bayesian framework that combines CFD, Gaussian processes, adjoint methods, and shape optimization in a unified and rigorous manner.
With this framework, we find the velocity field and flow boundaries (i.e. the digital twin) that are most likely to have produced a given noisy image. We also calculate the posterior covariances of the unknown parameters and thereby deduce the uncertainty in the reconstructed flow. First, we verify this method on synthetic noisy images of flows. Then we apply it to experimental phase contrast magnetic resonance (PC-MRI) images of an axisymmetric flow at low and high SNRs. We show that this method successfully reconstructs and segments the low SNR images, producing noiseless velocity fields that match the high SNR images, using 30 times less data.
This framework also provides additional flow information, such as the pressure field and wall shear stress, accurately and with known error bounds. We demonstrate this further on a 3-D in-vitro flow through a 3D-printed aorta and 3-D in-vivo flow through a carotid artery.

Thu, 19 Oct 2023

12:00 - 13:00
L1

Does Maxwell’s hypothesis of air saturation near the surface of evaporating liquid hold at all spatial scales?

Eugene Benilov
(University of Limerick)
Abstract

The classical model of evaporation of liquids hinges on Maxwell’s assumption that the air near the liquid’s surface is saturated. It allows one to find the evaporative flux without considering the interface separating liquid and air. Maxwell’s hypothesis is based on an implicit assumption that the vapour-emission capacity of the interface exceeds the throughput of air (i.e., its ability to pass the vapour on to infinity). If indeed so, the air adjacent to the liquid would get quickly saturated, justifying Maxwell’s hypothesis.

 

In the present paper, the so-called diffuse-interface model is used to account for the interfacial physics and, thus, derive a generalised version of Maxwell’s boundary condition for the near-interface vapour density. It is then applied to a spherical drop floating in air. It turns out that the vapour-emission capacity of the interface exceeds the throughput of air only if the drop’s radius is rd 10μm, but for rd ≈ 2μm, the two are comparable. For rd 1μm, evaporation is interface-driven, and the resulting evaporation rate is noticeably smaller than that predicted by the classical model.

Thu, 12 Oct 2023

13:00 - 14:00
L1

Surprises in a classic boundary-layer problem

Steven Strogatz
(Cornell University)
Abstract

Over the years, I've often taught a first course in asymptotics and perturbation methods, even though I don't know much about the subject. In this talk, I'll discuss a textbook example of a singularly perturbed nonlinear boundary-value problem that has revealed delightful new surprises, every time I teach it. These include a pitchfork bifurcation in the number of solutions as one varies the small parameter, and transcendentally small terms in the solutions' initial conditions that can be calculated by elementary means.

Thu, 15 Jun 2023
12:00
L1

Reconciling ecology and evolutionary game theory: or ‘when not to think cooperation’

Corina Tarnita
(Princeton University)
Abstract

I’m excited to share with everyone some new, unpublished work that we are just in the process of wrapping up and could use everyone’s reactions. It is a reconciliation of evolutionary game theory and ecological dynamics that I have wrestled with since I moved from an evolution program into an ecology-heavy department. It always seemed like, depending on the problem I was thinking about, I had to change my perspective and approach it as either an evolutionary game theorist, or an ecologist; and yet I had this nagging feeling that, at its core, the problem was often one and the same, and therefore one theoretical framework should suffice. So when should one write down an n-type replicator equation and when should one write down an n-species Lotka-Volterra system; and what does it mean mathematically and biologically when one has made such a choice? In the process of reconciling, I also got a deeper appreciation of what is and is not a proper game, such as a Prisoner’s Dilemma. These findings can help shed light on previously puzzling empirical findings.

Thu, 08 Jun 2023

12:00 - 13:00
Lecture room 5

Mathematical Modelling of Metal Forming

Ed Brambley
(University of Warwick)
Abstract

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, multiple scales, and possibly a matrix Wiener-Hopf problem if time permits.

Thu, 01 Jun 2023
12:00
L1

Plant Tropisms as a Window on Plant Computational Processes

Yasmine Meroz
(Tel Aviv University)

Note: we would recommend to join the meeting using the Zoom client for best user experience.

Abstract

A growing plant is a fascinating system involving multiple fields. Biologically, it is a multi-cellular system controlled by bio-chemical networks. Physically, it is an example of an "active solid" whose element (cells) are active, performing mechanical work to drive the evolving geometry. Computationally, it is a distributed system, processing a multitude of local inputs into a coordinated developmental response. In this talk I will discuss how plants, a living information-processing organism, uses physical laws and biological mechanisms to alter its own shape, and negotiate its environment. Here I will focus on two examples reflecting the computational and mechanical aspects: (i) probing temporal integration in gravitropic responses reveals plants sum and subtract signals, (ii) the interplay between active growth-driven processes and passive mechanics.

Thu, 25 May 2023
12:00
L1

The Thermodynamics of Mind

Gustavo Deco
(Universitat Pompeu Fabra)
Abstract

We propose a unified theory of brain function called ‘Thermodynamics of Mind’ which provides a natural, parsimonious way to explain the underlying computational mechanisms. The theory uses tools from non-equilibrium thermodynamics to describe the hierarchical dynamics of brain states over time. Crucially, the theory combines correlative (model-free) measures with causal generative models to provide solid causal inference for the underlying brain mechanisms. The model-based framework is a powerful way to use regional neural dynamics within the hierarchical anatomical brain connectivity to understand the underlying mechanisms for shaping the temporal unfolding of whole-brain dynamics in brain states. As such this model-based framework fitted to empirical data can be exhaustively investigated to provide objectively strong causal evidence of the underlying brain mechanisms orchestrating brain states. 

Thu, 18 May 2023
12:00
L1

Two Stories of Light and Life

Maziyar Jalaal
(University of Amsterdam)
Abstract

My talk will have two parts. First, I will tell you how a single cell produces light to survive; then, I will explain how a huddle of chloroplasts in cells form glasses to optimize plant life. Part I: Bioluminescence (light generation in living organisms) has mesmerized humans since thousands of years ago. I will first go over the recent progress in experimental and mathematical biophysics of single-cell bioluminescence (PRL 125 (2), 028102, 2020) and then will go beyond and present a lab-scale experiment and a continuum model of bioluminescent breaking waves. Part II: To remain efficient during photosynthesis, plants can re-arrange the internal structure of cells by the active motion of chloroplasts. I will show that the chloroplasts can behave like a densely packed light-sensitive active matter, whose non-gaussian athermal fluctuations can lead to various self-organization scenarios, including glassy dynamics under dim lights (PNAS 120 (3), 2216497120, 2023). To this end, I will also present a simple model that captures the dynamic of these biological glasses.

Thu, 11 May 2023

12:00 - 13:00
L1

Bifurcations leading to oscillation in small chemical reaction networks

Murad Banaji
(OCIAM)
Abstract
Which systems of chemical reactions permit oscillation? The study of chemical oscillations has a long history, but we are still far from any structural characterisation of oscillatory reaction networks. I'll summarise recent work on identifying Andronov-Hopf and Bautin bifurcations, leading to oscillation and even multiple nondegenerate periodic orbits, in bimolecular mass action networks. In fact, a mixture of theory and computational algebra allows us to fully enumerate networks of minimal size admitting these bifurcations, including checking nondegeneracy and transversality conditions across the whole parameter space. We find that bifurcations leading to (stable) oscillation in small networks are not quite as rare as often believed. The results can be used alongside previous theory on "inheritance" to identify larger oscillatory networks via examination of their subnetworks. This is joint work with Balázs Boros.
Thu, 04 May 2023

12:00 - 13:00
L1

Can we tailor the behavior of flexible sheets in flows by adding cuts or folds?

Sophie Ramananarivo
(Ecole Polytechnique)
Abstract

Lightweight compliant surfaces are commonly used as roofs (awnings), filtration systems or propulsive appendages, that operate in a fluid environment. Their flexibility allows for shape to change in fluid flows, to better endure harsh or fluctuating conditions, or enhance flight performance of insect wings for example. The way the structure deforms is however key to fulfill its function, prompting the need for control levers. In this talk, we will consider two ways to tailor the deformation of surfaces in a flow, making use of the properties of origami (folded sheet) and kirigami (sheet with a network of cuts). Previous literature showed that the substructure of folds or cuts allows for sophisticated shape morphing, and produces tunable mechanical properties. We will discuss how those original features impact the way the structure interacts with a flow, through combined experiments and theory. We will notably show that a sheet with a symmetric cutting pattern can produce an asymmetric deformation, and study the underlying fluid-structure couplings to further program shape morphing through the cuts arrangement. We will also show that extreme shape reconfiguration through origami folding can cap fluid drag.

Thu, 27 Apr 2023

12:00 - 13:00
L1

Coiled Muscles: Snapping Beams: From Nonlinear Mechanics to Miniature Robotic Design

Sameh Tawfick
(University of Illinois)
Abstract

My group is developing a roadmap to replace bulky electric motors in miniature robots requiring large mechanical work output.

First, I will describe the mechanics of coiled muscles made by twisting nylon fishing lines, and how these actuators use internal strain energy to achieve a “record breaking” performance. Then I will describe intriguing hierarchical super-, and hyper-coiled artificial muscles which exploit the interplay between nonlinear mechanics and material microstructure. Next, I will describe their use to actuate the dynamic snapping of insect-scale jumping robots. The combination of strong but slow muscles with a fast-snapping beam gives rise to dynamic buckling cascade phenomena leading to effective robotic jumping mechanisms.

These examples shed light on the future of automation propelled by new bioinspired materials, nonlinear mechanics, and unusual manufacturing processes.

Thu, 09 Mar 2023

12:00 - 13:00
L1

TDA for the organization of regions in segmented images and more

Maria Jose Jimenez
(University of Seville)
Further Information

 

 

Abstract

Topological data analysis (TDA) comprises a set of techniques of computational topology that has had enormous growth in the last decade, with applications to a wide variety of fields, such as images,  biological data, meteorology, materials science, time-dependent data, economics, etc. In this talk, we will first have a walk through a typical pipeline in TDA, to move later to its adaptation to a specific context: the topological characterization of the spatial distribution of regions in a segmented image

Thu, 02 Mar 2023

12:00 - 13:00
L1

The Plankton Hydrodynamic Playbook

Christophe Eloy
(IRPHE Marseille)
Further Information

 

Christophe is Professor of Fluid Mechanics at Centrale Marseille. His research activity is carried out at the IRPHE institute in Marseille.

'His research addresses various fundamental problems of fluid and solid mechanics, including fluid-structure interactions, hydrodynamic instabilities, animal locomotion, aeroelasticity, rotating flows, and plant biomechanics. It generally involves a combination of analytical modeling, experiments, and numerical work.' (Taken from his website here: https://www.irphe.fr/~eloy/).'

 

 

Abstract

By definition, planktonic organisms drift with the water flows. But these millimetric organisms are not necessarily passive; many can swim and can sense the surrounding flow through mechanosensory hairs. But how useful can be flow sensing in a turbulent environment? To address this question, we show two examples of smart planktonic behavior: (1) we develop a model where plantkters choose a swimming direction as a function of the velocity gradient to "surf on turbulence" and move efficiently upwards; (2) we show how a plankter measuring the velocity gradient may track the position of a swimming target from its hydrodynamic signature. 

Ernst Haeckel, Kunstformen der Natur (1904), Copepoda 

 

Thu, 23 Feb 2023

14:00 - 15:00
L1

Flows around some soft corals

Laura Miller
(University of Arizona)
Further Information

 

Please note the change of time for this seminar at 2pm GMT.

Laura Miller is Professor of Mathematics. Her research group, 'investigate[s] changes in the fluid dynamic environment of organisms as they grow or shrink in size over evolutionary or developmental time.' (Taken from her group website here: https://sites.google.com/site/swimflypump/home?authuser=0)&nbsp;

Abstract

In this presentation, I will discuss the construction and results of numerical simulations quantifying flows around several species of soft corals. In the first project, the flows near the tentacles of xeniid soft corals are quantified for the first time. Their active pulsations are thought to enhance their symbionts' photosynthetic rates by up to an order of magnitude. These polyps are approximately 1 cm in diameter and pulse at frequencies between approximately 0.5 and 1 Hz. As a result, the frequency-based Reynolds number calculated using the tentacle length and pulse frequency is on the order of 10 and rapidly decays as with distance from the polyp. This introduces the question of how these corals minimize the reversibility of the flow and bring in new volumes of fluid during each pulse. We estimate the Péclet number of the bulk flow generated by the coral as being on the order of 100–1000 whereas the flow between the bristles of the tentacles is on the order of 10. This illustrates the importance of advective transport in removing oxygen waste. In the second project, the flows through the elaborate branching structures of gorgonian colonies are considered.  As water moves through the elaborate branches, it is slowed, and recirculation zones can form downstream of the colony. At the smaller scale, individual polyps that emerge from the branches expand their tentacles, further slowing the flow. At the smallest scale, the tentacles are covered in tiny pinnules where exchange occurs. We quantified the gap to diameter ratios for various gorgonians at the scale of the branches, the polyp tentacles and the pinnules. We then used computational fluid dynamics to determine the flow patterns at all three levels of branching. We quantified the leakiness between the branches, tentacles and pinnules over the biologically relevant range of Reynolds numbers and gap-to-diameter ratios, and found that the branches and tentacles can act as either leaky rakes or solid plates depending upon these dimensionless parameters. The pinnules, in contrast, mostly impede the flow. Using an agent-based modeling framework, we quantified plankton capture as a function of the gap-to diameter ratio of the branches and the Reynolds number. We found that the capture rate depends critically on both morphology and Reynolds number.