The objective of thermonuclear fusion consists of producing electricity from the coalescence of light nuclei in high temperature plasmas. The most promising route to fusion envisages the confinement of such plasmas with magnetic fields, whose most studied configuration is the tokamak. Disruptions are catastrophic collapses affecting all tokamak devices and one of the main potential showstoppers on the route to a commercial reactor. In this work we report how, deploying innovative analysis methods on thousands of JET experiments covering the isotopic compositions from hydrogen to full tritium and including the major D-T campaign, the nature of the various forms of collapse is investigated in all phases of the discharges. An original approach to proximity detection has been developed, which allows determining both the probability of and the time interval remaining before an incoming disruption, with adaptive, from scratch, real time compatible techniques. The results indicate that physics based prediction and control tools can be developed, to deploy realistic strategies of disruption avoidance and prevention, meeting the requirements of the next generation of devices.

We propose a numerical method tailored to perform interface-resolved simulations of evaporating multicomponent two-phase flows. The novelty of the method lies in the use of Robin boundary conditions to couple the transport equations for the vaporized species in the gas phase and the transport equations of the same species in the liquid phase. The Robin boundary condition is implemented with the cost-effective procedure proposed by Chai et al. [1] and consists of two steps: (1) calculating the normal derivative of the mass fraction fields in cells adjacent to the interface through the reconstruction of a linear polynomial system, and (2) extrapolating the normal derivative and the ghost value in the normal direction using a linear partial differential equation. This methodology yields a second-order accurate solution for the Poisson equation with a Robin boundary condition and a first-order accurate solution for the Stefan problem. The overall methodology is implemented in an efficient two-fluid solver, which includes a Volume-of-Fluid (VoF) approach for the interface representation, a divergence-free extension of the liquid velocity field onto the entire domain to transport the VoF, and the temperature equation to include thermal effects. We demonstrate the convergence of the numerical method to the analytical solution for multicomponent isothermal evaporation and observe good overall computational performance for simulating non-isothermal evaporating two-fluid flows in two and three dimensions.

In this contribution, we present a robust and efficient computational framework capable of accurately capturing the dynamic motion and large deformation/deflection responses of highly-flexible rods interacting with an incompressible viscous flow. Within the partitioned approach, we adopt separate field solvers to compute the dynamics of the immersed structures and the evolution of the flow field over time, considering finite Reynolds numbers. We employ a geometrically exact, nonlinear Cosserat rod formulation in the context of the isogeometric analysis (IGA) technique to model the elastic responses of each rod in three dimensions (3D). The Navier–Stokes equations are resolved using a pressure projection method on a standard staggered Cartesian grid. The direct-forcing immersed boundary method is utilized for coupling the IGA-based structural solver with the finite-difference fluid solver. In order to fully exploit the accuracy of the IGA technique for FSI simulations, the proposed framework introduces a new procedure that decouples the resolution of the structural domain from the fluid grid. Uniformly distributed Lagrangian markers with density relative to the Eulerian grid are generated to communicate between Lagrangian and Eulerian grids consistently with IGA. We successfully validate the proposed computational framework against two- and three-dimensional FSI benchmarks involving flexible filaments undergoing large deflections/motions in an incompressible flow. We show that six times coarser structural mesh than the flow Eulerian grid delivers accurate results for classic benchmarks, leading to a major gain in computational efficiency. The simultaneous spatial and temporal convergence studies demonstrate the consistent performance of the proposed framework, showing that it conserves the order of the convergence, which is the same as that of the fluid solver.

This study presents direct numerical simulation results of two-layer Rayleigh-Benard convection, investigating the previously unexplored Rayleigh-Weber parameter space 10(6) <= Ra <= 10(8) and 10(2) <= We <= 10(3). Global properties, such as the Nusselt and Reynolds numbers, are compared against the extended Grossmann-Lohse theory for two fluid layers, confirming a weak Weber number dependence for all global quantities and considerably larger Reynolds numbers in the lighter fluid. Statistics of the flow reveal that the interface fluctuates more intensely for larger Weber and smaller Rayleigh numbers, something also reflected in the increased temperature root mean square values next to the interface. The dynamics of the deformed two-fluid interface is further investigated using spectral analysis. Temporal and spatial spectrum distributions reveal a capillary wave range at small Weber and large Rayleigh numbers, and a secondary energy peak at smaller Rayleigh numbers. Furthermore, the maxima of the space-time spectra lie in an intermediate dispersion regime, between the theoretical predictions for capillary and gravity-capillary waves, showing that the gravitational energy of the interfacial waves is strongly altered by temperature gradients.

This study explores heat and turbulent modulation in three-dimensional multiphase Rayleigh–Bénard convection using direct numerical simulations. Two immiscible fluids with identical reference density undergo systematic variations in dispersed-phase volume fractions, 0.0≤𝛷≤0.5, and ratios of dynamic viscosity, 𝜆𝜇, and thermal diffusivity, 𝜆𝛼, within the range [0.1–10]. The Rayleigh, Prandtl, Weber and Froude numbers are held constant at 108, 4, 6000 and 1, respectively. Initially, when both fluids share the same properties, a 10 % Nusselt number increase is observed at the highest volume fractions. In this case, despite a reduction in turbulent kinetic energy, droplets enhance energy transfer to smaller scales, smaller than those of single-phase flow, promoting local mixing. By varying viscosity ratios, while maintaining a constant Rayleigh number based on the average mixture properties, the global heat transfer rises by approximately 25 % at 𝛷=0.2 and 𝜆𝜇=10. This is attributed to increased small-scale mixing and turbulence in the less viscous carrier phase. In addition, a dispersed phase with higher thermal diffusivity results in a 50 % reduction in the Nusselt number compared with the single-phase counterpart, owing to faster heat conduction and reduced droplet presence near walls. The study also addresses droplet-size distributions, confirming two distinct ranges dominated by coalescence and breakup with different scaling laws.

We propose an analytical model to estimate the interface temperature Theta(Gamma) and the Nusselt number Nu for an evaporating two-layer Rayleigh-Benard configuration in statistically stationary conditions. The model is based on three assumptions: (i) the Oberbeck-Boussinesq approximation can be applied to the liquid phase, while the gas thermophysical properties are generic functions of thermodynamic pressure, local temperature and vapour composition, (ii) the Grossmann-Lohse theory for thermal convection can be applied to the liquid and gas layers separately and (iii) the vapour content in the gas can be taken as the mean value at the gas-liquid interface. We validate this setting using direct numerical simulations in a parameter space composed of the Rayleigh number (10(6) <= Ra <= 10(8)) and the temperature differential (0.05 <= epsilon <= 0.20), which modulates the variation of state variables in the gas layer. To better disentangle the variable property effects on Theta(Gamma) and Nu, simulations are performed in two conditions. First, we consider the case of uniform gas properties except for the gas density and gas-liquid diffusion coefficient. Second, we include the variation of specific heat capacity, dynamic viscosity and thermal conductivity using realistic equations of state. Irrespective of the employed setting, the proposed model agrees very well with the numerical simulations over the entire range of Ra-epsilon investigated.

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.

This study presents a novel pressure-based methodology for the efficient numerical solution of a four-equation two-phase diffuse interface model. The proposed methodology has the potential to simulate low-Mach flows with mass transfer. In contrast to the classical conservative four-equation model formulation, the adopted set of equations features volume fraction, temperature, velocity and pressure as the primary variables. The model includes the effects of viscosity, surface tension, thermal conductivity and gravity, and has the ability to incorporate complex equations of state. Additionally, a Gibbs free energy relaxation procedure is used to model mass transfer. A key characteristic of the proposed methodology is the use of high performance and scalable solvers for the solution of the Helmholtz equation for the pressure, which drastically reduces the computational cost compared to analogous density-based approaches. We demonstrate the capabilities of the methodology to simulate flows with large density and viscosity ratios through extended verification against a range of different test cases. Finally, the potential of the methodology to tackle challenging phase change flows is demonstrated with the simulation of three-dimensional nucleate boiling. <comment>Superscript/Subscript Available</comment

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.

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.