Turbulent emulsification is of considerable industrial interest. Nevertheless, numerical experiments (direct nu-merical simulations, DNS, with highly resolved interface tracking) have been mainly used to study drop breakup in idealized flows. This study, therefore, compares drop breakup in two different settings (homogenous and isotropic flow, and a simplified high-pressure homogenizer) with the intention of better understanding how insight gained from the idealized systems can be applied to industrially relevant devices. The flow differs be-tween the two cases, with highly anisotropic and inhomogeneous turbulence in the latter. Results show simi-larities between the two cases regarding morphology of breakup, suggesting that the underlying mechanism, as a function of Weber number, is similar. However, differences are also observed, e.g., in terms of breakup time and deformed morphology, which are associated with the locality of the turbulence in the homogenizer. Implications for an improved understanding of turbulent breakup in industrially relevant devices are discussed.

We present the Fluid Transport Accelerated Solver, FluTAS, a scalable GPU code for multiphase flows with thermal effects. The code solves the incompressible Navier-Stokes equation for two-fluid systems, with a direct FFT-based Poisson solver for the pressure equation. The interface between the two fluids is represented with the Volume of Fluid (VoF) method, which is mass conserving and well suited for complex flows thanks to its capacity of handling topological changes. The energy equation is explicitly solved and coupled with the momentum equation through the Boussinesq approximation. The code is conceived in a modular fashion so that different numerical methods can be used independently, the existing routines can be modified, and new ones can be included in a straightforward and sustainable manner. FluTAS is written in modern Fortran and parallelized using hybrid MPI/OpenMP in the CPU-only version and accelerated with OpenACC directives in the GPU implementation. We present different benchmarks to validate the code, and two large-scale simulations of fundamental interest in turbulent multiphase flows: isothermal emulsions in HIT and two-layer Rayleigh-Bénard convection. FluTAS is distributed through a MIT license and arises from a collaborative effort of several scientists, aiming to become a flexible tool to study complex multiphase flows. Program summary: Program Title: : Fluid Transport Accelerated Solver, FluTAS. CPC Library link to program files: https://doi.org/10.17632/tp6k8wky8m.1 Developer's repository link: https://github.com/Multiphysics-Flow-Solvers/FluTAS.git. Licensing provisions: MIT License. Programming language: Fortran 90, parallelized using MPI and slab/pencil decomposition, GPU accelerated using OpenACC directives. External libraries/routines: FFTW, cuFFT. Nature of problem: FluTAS is a GPU-accelerated numerical code tailored to perform interface resolved simulations of incompressible multiphase flows, optionally with heat transfer. The code combines a standard pressure correction algorithm with an algebraic volume of fluid method, MTHINC [1]. Solution method: the code employs a second-order-finite difference discretization and solves the two-fluid Navier-Stokes equation using a projection method. It can be run both on CPU-architectures and GPU-architectures.

The dynamics of droplet fragmentation in turbulence is described by the Kolmogorov-Hinze framework. Yet, a quantitative theory is lacking at higher concentrations when strong interactions between the phases and coalescence become relevant, which is common in most flows. Here, we address this issue through a fully-coupled numerical study of the droplet dynamics in a turbulent flow at R-lambda & AP; 140, the highest attained up to now. By means of time-space spectral statistics, not currently accessible to experiments, we demonstrate that the characteristic scale of the process, the Hinze scale, can be precisely identified as the scale at which the net energy exchange due to capillarity is zero. Droplets larger than this scale preferentially break up absorbing energy from the flow; smaller droplets, instead, undergo rapid oscillations and tend to coalesce releasing energy to the flow. Further, we link the droplet-size distribution with the probability distribution of the turbulent dissipation. This shows that key in the fragmentation process is the local flux of energy which dominates the process at large scales, vindicating its locality.

Turbulent breakup in emulsification devices is a dynamic process. Small viscous drops undergo a sequence of oscillations before entering the monotonic deformation phase leading to breakup. The turbulence-interface interactions prior to reaching critical deformation are therefore essential for understanding and modeling breakup. This contribution uses numerical experiments to characterize the critically deformed state (defined as a state from which breakup will follow deterministically, even if no further external stresses would act on the drop). Critical deformation does not coincide with a threshold maximum surface area, as previously suggested. A drop is critically deformed when a neck has formed locally with a curvature such that the Laplace pressure exceeds that of the smallest of the bulbs connected by the neck. This corresponds to a destabilizing internal flow, further thinning the neck. Assuming that the deformation leads to two spherical bulbs linked by a cylindrical neck, the critical deformation is achieved when the neck diameter becomes smaller than the radius of the smallest bulb. The role of emulsifiers is also discussed.

More detailed investigation of the flow inside emulsification devices, e.g., High-pressure homogenizers (HPHs) helps the industry to broaden the fundamental understanding of the working principle of these machines which in turn will pave the road to increase the breakup efficiency of emulsification processes. Direct numerical simulation (DNS) is not deemed as a practical method in industry due to the high computational cost and time. This study is the first DNS carried out on a model of an emulsification device model. The goal of this study is to set a benchmark for future CFD investigations using industrially favorable tools (RANS, LES, etc.). A scale-up model HPH is designed and the results show a successful modeling of the flow field mimicking the flow behavior inside a typical HPH.

In nuclear fusion reactors, plasmas are heated to very high temperatures of more than 100 million kelvin and, in so-called tokamaks, they are confined by magnetic fields in the shape of a torus. Light nuclei, such as deuterium and tritium, undergo a fusion reaction that releases energy, making fusion a promising option for a sustainable and clean energy source. Tokamak plasmas, however, are prone to disruptions as a result of a sudden collapse of the system terminating the fusion reactions. As disruptions lead to an abrupt loss of confinement, they can cause irreversible damage to present-day fusion devices and are expected to have a more devastating effect in future devices. Disruptions expected in the next-generation tokamak, ITER, for example, could cause electromagnetic forces larger than the weight of an Airbus A380. Furthermore, the thermal loads in such an event could exceed the melting threshold of the most resistant state-of-the-art materials by more than an order of magnitude. To prevent disruptions or at least mitigate their detrimental effects, empirical models obtained with artificial intelligence methods, of which an overview is given here, are commonly employed to predict their occurrence—and ideally give enough time to introduce counteracting measures.

Sprays and atomization processes are extremely diffused both in nature and in industrial applications. In this paper we analyze the influence of the nozzle turbulence on primary atomization, focusing on the resulting turbulent field and atomization patterns in the Near Field (NF). In order to do so, a Synthetic Boundary Condition (SBC) and a Mapped Boundary Condition (MBC), producing respectively isotropic and anisotropic turbulent fields, have been generated as inflow conditions for the spray Direct Numerical Simulations (DNS). We present a specific methodology to ensure consistency on turbulence intensity and integral lengthscale between the two inflows. The analysis performed on the turbulent field (using one-point statistics and spectrum analysis) reveals a significantly stronger turbulent field generated by the inflow boundary conditions with anisotropic structures. While the increased turbulence field generated in the MBC case results in a higher number of droplets generated, the probability functions of both cases are extremely similar, leading to the non-obvious conclusion that the atomization patterns are only slightly affected by the inflow condition. These considerations are supported by the analysis of droplet size distributions, radial distribution functions, axial and radial distributions, highlighting extremely similar behaviors between the MBC and the SBC cases. Finally, these analyses and their computations are presented in detail, underlining how this type of point-process characterization shows interesting potential in future studies on sprays.

Alpha particles with energies on the order of megaelectronvolts will be the main source of plasma heating in future magnetic confinement fusion reactors. Instead of heating fuel ions, most of the energy of alpha particles is transferred to electrons in the plasma. Furthermore, alpha particles can also excite Alfvénic instabilities, which were previously considered to be detrimental to the performance of the fusion device. Here we report improved thermal ion confinement in the presence of megaelectronvolts ions and strong fast ion-driven Alfvénic instabilities in recent experiments on the Joint European Torus. Detailed transport analysis of these experiments reveals turbulence suppression through a complex multi-scale mechanism that generates large-scale zonal flows. This holds promise for more economical operation of fusion reactors with dominant alpha particle heating and ultimately cheaper fusion electricity.

We present a numerical study of emulsions in homogeneous and isotropic turbulence (HIT) at Re-lambda = 137. The problem is addressed via direct numerical simulations, where the volume of fluid is used to represent the complex features of the liquid-liquid interface. We consider a mixture of two iso-density fluids, where fluid properties are varied with the goal of understanding their role in turbulence modulation, in particular the volume fraction (0.03 < alpha < 0.5), viscosity ratio (0.01 < mu(d)/mu

The JET 2019-2020 scientific and technological programme exploited the results of years of concerted scientific and engineering work, including the ITER-like wall (ILW: Be wall and W divertor) installed in 2010, improved diagnostic capabilities now fully available, a major neutral beam injection upgrade providing record power in 2019-2020, and tested the technical and procedural preparation for safe operation with tritium. Research along three complementary axes yielded a wealth of new results. Firstly, the JET plasma programme delivered scenarios suitable for high fusion power and alpha particle (alpha) physics in the coming D-T campaign (DTE2), with record sustained neutron rates, as well as plasmas for clarifying the impact of isotope mass on plasma core, edge and plasma-wall interactions, and for ITER pre-fusion power operation. The efficacy of the newly installed shattered pellet injector for mitigating disruption forces and runaway electrons was demonstrated. Secondly, research on the consequences of long-term exposure to JET-ILW plasma was completed, with emphasis on wall damage and fuel retention, and with analyses of wall materials and dust particles that will help validate assumptions and codes for design and operation of ITER and DEMO. Thirdly, the nuclear technology programme aiming to deliver maximum technological return from operations in D, T and D-T benefited from the highest D-D neutron yield in years, securing results for validating radiation transport and activation codes, and nuclear data for ITER.