Research

Transitional Flow in Pipes

Transition from laminar to turbulent regime is accompanied by a large change in flow related processes such as mixing, heat transfer and drag friction that increase dramatically. This work addresses the fundamental question of the transitioninstability in diverging/sudden expansion pipe flows of an ultimate active control strategy focusing on the fundamental understanding of the flow physics. This subject represents one of the most important and challenging problems in contemporary physics and fluid engineering.

From a theoretical point of view, the classical linear stability theory predicts large critical speeds for transition, whereas experiments indicate the occurrence of transition at lower flow rates. This project intends to clarify this scientific ambiguity and to shade more lights into the transition mechanisms and their consequences on critical flows. Since laboratory and numerical experiments are complementary and inevitable tools to fully understand such complex flow physics, the project will also aims at providing high fidelity numerical simulations that compare with controlled and well-monitored laboratory experiments. Therefore, one of the direct outputs of this work will be the quantitative simulation and validation from experiments including a large range of flow and geometrical parameters.

The knowledge that will be acquired through INTRA is of interest for many industries, such as those occurring in internal or external aerodynamics (nozzles, compressors and high-pressure turbine blades) and hydrodynamics (heat exchangers, oil transporting pipelines, flow assurance, ultraviolet disinfection of bacteria in flow treatment systems applications.

Fig.: Direct Numerical Simulation (DNS) results of localized turbulence in diverging pipe flow with the expansion ratio of 1:2 and deriving half angle of 14° at Re= 700 and with perturbation amplitude of A=1. The picture shows the lambda-2 structure and colored by vorticity field.

Renewable Energies

In the current research, computer aided numerical simulation and computational fluid dynamics (CFD) are used to design, investigate and optimize Savonius-style wind turbines as a class of vertical axis wind turbines (VAWT) as well as horizontal axis tidal turbines (HATT) as a first step of R&D for implementation. While the former class of turbines appear to be promising for energy conversion because of their better self-starting capability, flexible design promises and low wind operations; the latter class is preferred because of good startup capability, more stable receiving torque, and being more efficient and profitable compared to vertical ones.

In this project, Direct Numerical Simulations (DNS) will be carried out in order to capture the flow instabilities and transition to turbulence occurring on the blade of a Savonius wind turbine. Simulations will be conducted with a high-order spectral element method, solving the incompressible Navier-Stokes equations. The simulations will be performed for a wide range of Reynolds numbers to understand the main flow characteristic for different operating conditions. In this context, a receptivity analysis of the blade to the flow instabilities needs to be taken into account on the inflow condition. The results will then be utilized for the boundary-layer control on the blade surface, and also to modify the Savonius wind turbine blade’s profile to achieve higher performances.

The prediction of the three-bladed rotor for a HATT performance is done using realizable κ-ε turbulence model (a Reynolds Average Navier-Stokes model, RANS) with standard wall function is selected to capture flow characteristics influenced by rotor and near the wall region (see fig. 1). Therefore, one of the objectives of this project is to carry the Large Eddy Simulations (LES), i.e. numerical simulation with higher resolution and more accurate turbulent models, to capture the flow instabilities and transition to turbulence occurring on the blade of a horizontal axis tidal turbine. The harsh and highly turbulent environments in which tidal stream turbines operate in, poses a design challenge mainly with regards to survivability of the turbine owing to the fact that tidal turbines are exposed to significant intermittent hydrodynamic loads.For this purpose, LES method provides more accurate prediction of flow properties at large scales than RANS method, in the cost of more computational resource demand.

Fig. 34mm pitch streamlines and -300 [Pa] pressure isosurface colored by velocity at two different angularvelocity, top 70 rpm and bottom 140 rpm (left) and pitch pressure distribution at 140 rpm from different point of views (bottom).

Laminar to Turbulent Transition and Turbulent High-Speed Flows

This work focuses on the use of DNS to study the transition mechanism occurring in compressible wall-bounded flows subjected to strong heat transfer at the wall. The study will focus on the following key points: We will conduct highly-resolved direct numerical simulations (DNS) of high-speed zero-pressure-gradient flows over a flat plate subjected to wall heat transfer where laminar boundary layer is imposed upstream to follow the Blasius profile. Free-stream “vortical disturbances” with “blowing and suction” boundary conditions at the wall will be implemented in order to produce both Klebanoff modes and TS waves.

The main goal of the current work is to systematically investigate different LTT scenarios in the presence of wall heat transfer. Toward this end, selective DNS for strongly heated and cooled isothermal walls as well as for the adiabatic wall temperature will be performed. These are the STBLs either with adiabatic or isothermal wall. Each of these cases consists of two simulations with only Klebanoff modes and TS waves active and three different simulations comprising both effects. The results are then compared to each other to identify the effect of wall heat transfer. Afterward, a comprehensive study will be performed to provide detailed information on LTT, and similarities and differences between different cases will be further clarified. The overall 15 DNS simulations will expectantly cover some available gaps in the literature.

Fig.: From top to bottom: side view, top view at y+=10 and 30 and top zoom view of transitional boundary layer with an adiabatic wall. The inlet flow is initialized with the Blasius profile having, respectively, the free-stream and momentum thickness Reynolds numbers of and at free-stream Mach number and temperature . The laminar boundary layer is perturbed by blowing and suction method. Here, the mesh resolution in streamwise, wall-normal and spanwise directions are Nx=3584, Ny=128, and Nz= 256.

Electrohydrodynamics (EHD)

The efficient removal of a dispersed/suspended phase from another continuous bulk phase is highly desirable in many industrial applications. Such applications can be found, for instance, in purification of water or oil, in oil-in-water (OiW) or water-in-oil (WiO) dispersions, respectively. One practical way to enhance this phase removal is to utilize a strong external electric field, i.e. voltage alternating current (AC) and/or direct current (DC). However, the conventional electro-separators are bulky and need too long time to separate the column of coalesced water from crude oil. Additionally, once designed, the operating parameters for electro-separators are not flexible, therefore, in many circumstances the electric part of the electro-separators is turned off1 due to not being efficient or even worst because of induced problems such as chain formation, tip vortex and droplet breakup (instead of coalescence) among others (see figure 1). Therefore, understanding the underlying physics in demulsification devices and its extension to predict such systems’ behaviors is crucial for such industries.

The aim of this project id to develop a meshless Lagrangian incompressible smoothed particle hydrodynamics (ISPH) solver, with mathematical development and numerical implementation to accommodate EHD and 3D capabilities. This will permit a thorough investigation of the EHD phenomena at stake to address the given difficulties and also to take profit of the advantages of this method. This method has key advantages of naturally following interface for highly nonlinear free surface and multiphase hydrodynamic problems, where the convective term is absent in the Navier-Stokes equations due to its Lagrangian formulation.

Fig. (left) Chain formation in 20% water-in-Buchan crude oil emulsion at 50 Hz and 1.6 kV. Photomicrographs showing emulsion at 22 ms (Chen et al. 1994). (middle) Breakup process of a distilled water droplet in oil subjected to DC electric field. The Ca is 0.214 (Luo et al. 2017). (c) SPH simulation of bubble breakup caused by tip vortex. Time is increasing from left to right and top to bottom (Zainali et al. 2013).

Heat Transfer and Phase Change

Boiling is an efficient heat transfer mechanism that occurs in many industrial and natural processes such as metal hardening in liquid medium, cooling system of chemical fuel, chilling of biological species and cryogenic fuel tank. Film boiling occurs when vapor bubbles amalgamate and form a continuous layer of vapor over a hot surface, thus the liquid phase is separated from it. On the other hand, pool boiling happens when the heating surface is submerged in a large body of stagnant liquid. The heat flow passes through a low thermal conductivity vapor layer. This mechanism changes with a change in the heat flux magnitude. Although great numbers of experimental and analytical researches have been performed to understand the nature of boiling phenomena in the past decade, the theory of boiling is complex and not yet fully developed. With advancement in numerical simulations and the development of new physical models in the past few years, discovering the transient and dynamic aspects of multiphase flows with phase change has become more promising.

Fig.: Numerical simulation of film boiling using lattice boltzmann method (LBM). Top to bottom and left to rigth shows the time snapshots of the computational domain.

Machine Learning for Multiphase Flows

Gas-liquid two-phase flows through long pipelines are one of the most common cases found in chemical, oil, and gas industries. In contrast to the gas/Newtonian liquid systems, the pressure drop has rarely been investigated for two-phase gas/non-Newtonian liquid systems in pipe flows. In this regard, an Artificial Neural Networks (ANN) model is presented by employing a large number of experimental data to predict the pressure drop for a wide range of operating conditions, pipe diameters, and fluid characteristics. Utilizing a Multiple-Layer Perceptron Neural Network (MLPNN) model, the predicted pressure drop is in a good agreement with the experimental results. In most cases, the deviation of the predicted pressure drop from the experimental data does not exceed 5%. It is observed that the MLPNN provides more accurate results for horizontal pipelines in comparison with other empirical correlations that are commonly used in industrial applications.

Fig.: Schematics of slug flow in liquid–gas (top), and the structure of the artificial neural network for predicting pressure drop (bottom).

The project "Analysis of soot filter regeneration by combined numerical and experimental investiga-tions", khown as ASORNE is finaced jointly by the French National Research Agency (ANR) and German Research Fundation (DFG) under ANR-20-CE92-0007-01 agreement number. ASORNE is a collaboration between CORIA Lab. CNRS-UMR6614, National Institute of Applied Sciences of Rouen Normandie in France and Institute of Chemical Process Engineering, University of Stuttgart in Germany with a budget of 690k€. For more details about the project, please click here.