(6hg) Dynamic Structures in Multiphase Systems: A Pathway Towards Responsive Processes

Profile: Experimental and numerical research in powder technology, heat transfer, fluid mechanics & multiphase flow i.e. spray drying, agglomeration, fluidization, vortex flows. 8 years of experience as engineer, researcher and consultant for global manufacturers of consumer goods, water and energy sectors i.e. P&G, Acciona, ExxonMobil.

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Research Interests:

My work looks into complex dynamics in granular media and multiphase flows. I am intrigued by a transition regime between continuum fluid dynamics and solid mechanics where the attractive forces bringing particles/droplets/colloids together and the disruptive stresses pulling them apart are of the same order, resulting in dynamic structures that constantly form and break and change drastically the collective macroscopic behaviour e.g. clustering, dense granular flow, structured fluids. I want to understand how mesoscopic structures appear and react to external stimuli e.g. drag, electric, magnetic. Dynamic structures area common feature of natural processes e.g. nucleation / growth / breakage of particles, drops, snow in a storm, a riverbed, a desert or an avalanche, and industry e.g. clustering / agglomeration / flocculation / deposition / breakage. We can describe some of these phenomena independently, but we do not understand how they interact to form a dynamic system, let along how structure evolves according to various ageing phenomena e.g. drying, sintering, coking. As opposed to scales nano and molecular scales where self-organisation is well-established, in the larger inertial scales typical of the process industry, we simply avoid dynamic effects with a rigid design paradigm that tries to isolate a given process e.g. granulator, grinder. Indeed, neglecting dynamics, we often fail and suffer well-known issues e.g. riser - clustering, heat exchanger - fouling, 3D printer nozzle - clogging. I want to explore a more organic approach to process engineering where we exploit the dynamic features of particulate and colloidal systems to design more efficient and self-regulated processes, materials and devices.

Teaching Interests:

I have experience in various industrial sectors as experimentalist and modeller. I can deliver courses in transport phenomena, powder technology and other core process engineering subjects. Relating back my experience working at multinationals, universities and start-ups to teaching will help me prepare students for the working environment. In addition to invited lectures in the UK and Spain, in 2017/18 I started working as Teaching Fellow at UCL lecturing on fluidization at Masters-level and running the Process Plant Design module for undergraduates i.e. ~150 students. In the future, I would like to build into two areas: a) deliver a comprehensive view of multiphase science from its specific maths to the effects that multiple phases have in transport phenomena (momentum e.g. rheology, mass e.g. emulsions, heat e.g. drying) and the introduction of new rate processes (e.g. agglomeration, breakage) through examples taken from nature and industry, and b) New methods to improve critical thinking. Data interpretation and troubleshooting are essential skills for an engineer. Higher education makes sure that graduates can solve problems and yet, they often struggle to be critical thinkers because they have seldom had the initiative to frame problems themselves. I want to address that by establishing a platform of industrial case studies where they will troubleshoot a real-life challenge in a role-playing exercise. Each group will have a semester to look into a challenge, and unlike a classic “design” exercise, students will face initially incomplete data sets. They will have to think on the given context and ask the relevant staff (me) the right questions to obtain more data, analyse it and interpret their results in a critical manner.

Research Experience:

I have worked in multiphase flow, fluid dynamics, membrane technology and powder processes e.g. agglomeration, fluidization, spray drying. My doctorate dealt with droplet/particle agglomeration during spray drying. I developed new methods base in sonic anemometry to study turbulent air flows [1] and characterised the flow employed in P&G drying towers [2]. I identified distinct recirculation regimes associated to the flow over rough walls and drew new scale up rules accordingly [3]. My research led to fundamental changes in the traditional view of particle formation in spray drying. I proved that most of the product in swirl dryers forms through deposition and breakage of material in a dynamic structure of deposits [4], and based on this insight, redefined the study of agglomeration sources [5], proposed new methods to quantify how sprays interact [6] and optimized the operation of P&G dryers [7]. On these grounds, I won funds to move to Imperial College London and work in a numerical frame that I now follow up in collaboration with University of Salamanca. In my postdocs, I expanded my numerical skills first working in the optimization of another fouling phenomenon in the oil industry and later joining University College London where I work in granular physics. Here, we are using oscillating flows to create new designs for gas-solid processes e.g. foods, household, pharma, energy. By using a periodic perturbation to the inlet gas flow of a fluidised bed, we can suppress the flow instability that leads to chaotic bubbling and create very stable and reproducible bubble patterns in reactors or dryers. In the last two years, I have conducted/supervised experiments in pilot scale units using ultrahigh speed cameras, developed image analysis and pattern recognition codes and numerical models e.g. CFD-DEM, TFM. Several publications are being prepared: 1) identification of the regime where one can “dynamically structure” a bubbling fluidised bed, 2) methods to quantify the level or order in a bubbling system, 3) analysis of the role of friction in the self-organisation of gas bubbles in granular media and 4) quantification of mixing and heat transfer efficiency in dynamically structured beds.

Research Plans:

The mesoscale is one crucial challenge in multiphase science. It is responsible of the limits between dilute, dense and quasi-static regimes in granular flow, the rheology of structured fluids or the transport in gas-solid fluidized beds to mention a few critical questions. When a set of particles consolidates, multi-particle sustained contacts become frequent and shape, long-range effects and anisotropy more important. It is hard to replicate these effects in non-fully resolved models and it is very complex to include any structure in kinetic frames because classic formulations do not deal with correlated velocities or inhomogeneous contact distributions. This is complicated further in practical scenarios as particles evolve e.g. sinter, dry, cure, cake. We use detailed numerical tools e.g. Direct Numerical Simulation DNS, Lattice- Boltzmann LB, Large Eddy Simulations LES, Discrete Element Method DEM, to look into these phenomena at a microscale and then make a rather uncontrolled leap onto multi-scale approaches and coarse grain models in which we rarely extract constitutive equations or rate kernels for application in macroscopic models e.g. Population Balance Equation, let alone 1D formulations for optimization engines e.g. GPROMS. I want to focus on this gap: design experiments and use microscale models to derive new closures, constitutive equations and kernels that will connect physics naturally occurring at a mesoscale with multi-scale models acrtoss different disciplines. My programme will cut across the following themes:

1. Dynamic Processes: Intermittent structures at the bulk of multiphase flows, how they affect transport and how external fields may be used to control them.
2. Dynamic Fouling: Dynamic structures at the boundaries of a multiphase flow; deposition, consolidation and resuspension of multilayers for application at consumer goods, energy, medicine.
3. Smart Media: Transition of clustered structures into flow e.g. multifunctional inks, self-healing materials.
4. Industry 4.0: Hybrid optimization approaches where classic multi-scale modelling frameworks are used in combination with a machine learning frame for the estimation of complex physical magnitudes.

Theme I will initially follow up my current collaborations in the energy sector. My first initial bid as PI will focus in Theme II, launching studying particulate multilayers as combination of deposition, consolidation/sintering and removal/disengagement mechanisms. I will do so with support from previous partners in consumer goods and energy, and expand it to foods, pharma and healthcare e.g. biomass, heat exchangers, caking, gas-solid reactors, biological fluids. My goals include transferable outputs to stochastic e.g. collision rates, aggregation probability, or rate-based models e.g. diffusion coefficients, agglomeration/breakage kernels. My connexion with industry and SMEs will develop Theme IV and after having acquired expertise in the domain of processes, Theme III will pose exciting questions on how we can develop new products.