Real Fluid Research Articles

Novel approach for modeling a full-sized air-cooled heat exchanger using porous media and iterative processes

Air-Cooled Heat Exchangers (ACHE) have gained importance through their extensive use in the oil and gas industry. Many researchers studied ACHE extensively and proposed analysis methods. Most of them investigate part of the ACHE in their modeling. Others consider only pressure drop in their calculations in simulating the porous media (fins and surrounding air). These assumptions lead to unprecise modeling results. In contrast to existing literature, by incorporating computational fluid dynamics (CFD) with real geometry design, this paper includes a study of a full-size ACHE with precise geometric measurements, commencing at the hot water's input and going all the way to the ACHE's exit through a U-path tube. By incorporating the complete geometry dimensions of the U-path tube length from the hot water inlet to the outlet, this methodology has the potential to produce more accurate predictions of temperature distribution, heat flow rate, logarithmic mean temperature difference (LMTD), and fin efficiency for each tube along the entire length of the ACHE. Further, unlike other works of literature, the porous media in this research includes calculations for pressure drops and heat transmission in place of real geometry design which gives more sensible and accurate modeling results. Moreover, a novel verification method is proposed by presenting an iterative process for verification of entire geometry design calculations by comparison with the Real Geometric Design. The incorporation of Real Geometry Design and Computational Fluid Dynamics (CFD) Code programs can lead to more precise and efficient methodologies for modeling air-cooled exchangers, offering valuable insights that can ultimately enhance their design and performance. In this work, the convergence with the actual geometrical design is less than 1%, demonstrating the superiority of the suggested strategy.

Real Fluid Modeling and Simulation of the Structures and Dynamics of Condensation in CO2 Flows Shocked Inside a de Laval Nozzle, Considering the Effects of Impurities

Because of the currently changing climate, Carbon Capture and Storage (CCS) is increasingly becoming an important contemporary topic. However, this technique still faces various challenges. For the compression of CO2 to its supercritical condition for efficient transport, one of the important challenges is mastering the two-phase flow in the pump. Indeed, phase changes that appear on the blade tips of an impeller or rotor in such pumps can lead to performance and stability issues. Moreover, these phase change phenomena (vaporization and condensation) can be significantly modified by the presence of impurities (N2, O2, H2S, etc.) whose nature depends on the source of the CO2 production. In this work, we focus on analyzing the high pressure flow behavior of CO2 mixed with varying levels of impurities in a de Laval nozzle, for which experimental results are available. Numerical simulations are performed using a real-fluid model (RFM) implemented in the CONVERGE CFD solver. In this model, a tabulation approach is used to provide the thermodynamic and transport properties of the mixture of CO2 with the impurities. The study is carried out with different inlet conditions, and the results are in good agreement with the available experimental data. In addition, the results provide insights on the interaction of the shock wave with the observed condensation phenomenon, as well as its impact on the amount of condensation and other thermodynamic variables. The research indicates that the presence of impurities mixed with CO2 significantly affects the observed condensation in gas streams, which is a crucial factor that cannot be overlooked when implementing CCS systems.

Deep learning–assisted phase equilibrium analysis for producing natural hydrogen

The development of natural hydrogen is an emerging topic in the current energy transition trend. The production process involves compositional multiphase flow via subsurface porous media. This makes studying the compositional phase equilibrium behavior essential for reliable reservoir simulation and prediction. Herein, we develop an iterative flash calculation scheme and a deep learning algorithm using a thermodynamics-informed neural network (TINN) to perform accurate, robust, and fast phase equilibrium calculations for realistic fluid mixtures of natural hydrogen. The application of TINN architecture can accelerate the calculations for nearly 20 times. The effect of capillarity on phase equilibrium states is demonstrated. Based on simulation results, suggestions for the natural hydrogen industry chain are provided to control the possible phase transitions under certain environmental conditions that may be observed in the natural hydrogen reservoirs, storage and transportation facilities. The extremely low critical temperature of hydrogen challenges the robustness of flash calculations but facilitates the separation of impurities by liquefying certain undesired species. Moreover, phase transitions under control can be an effective approach for carbon dioxide capture and sequestration with optimized operating conditions over the phase equilibrium analysis.

Challenges and attempts to make intelligent microswimmers

The study of microswimmers’ behavior, including their self-propulsion, interactions with the environment, and collective phenomena, has received significant attention over the past few decades due to its importance for various biological and medical applications. Microswimmers can easily access micro-fluidic channels and manipulate microscopic entities, enabling them to perform sophisticated tasks as untethered mobile microrobots inside the human body or microsize devices. Thanks to the advancements in micro/nano-technologies, a variety of synthetic and biohybrid microrobots have been designed and fabricated. Nevertheless, a key challenge arises: how to guide the microrobots to navigate through complex fluid environments and perform specific tasks. The model-free reinforcement learning (RL) technique appears to be a promising approach to address this problem. In this review article, we will first illustrate the complexities that microswimmers may face in realistic biological fluid environments. Subsequently, we will present recent experimental advancements in fabricating intelligent microswimmers using physical intelligence and biohybrid techniques. We then introduce several popular RL algorithms and summarize the recent progress for RL-powered microswimmers. Finally, the limitations and perspectives of the current studies in this field will be discussed.

Identifying dominant flow features from very-sparse Lagrangian data: a multiscale recurrence network-based approach

Realistic fluid flow problems often require that Lagrangian tracers are deployed in a sparse or very-sparse manner, such as for oceanic and atmospheric flows where large-scale motion needs characterisation. Data sparsity represents a significant issue in Lagrangian analysis, especially for data-driven methods that rely heavily on large datasets. We propose a multiscale spatial recurrence network (MSRN) methodology for characterising very-sparse Lagrangian data, which exploits individual tracks and a spatial recurrence criterion to identify the spatio-temporal complexity of tracer trajectories. The MSRN is an unsupervised modelling framework that does not require a priori parameter setting, and—through the quantification of persistent link activation at specific trajectory intervals—can reveal the presence of dominant looping scales in a variety of salient fluid flows. This new paradigm is shown to be successful for the study of Lagrangian tracers seeded in complex (realistic) flows, including unsteady and advection-dominated problems. This makes MSRNs an effective and versatile tool to characterise sensor trajectories in key problems such as environmental processes critical to understanding and mitigating climate change.Graphic abstract

Thermal characteristics for the flow of Williamson hybrid nanofluid with distinct shape factors

AbstractThe main purpose of the present article is to investigate the flow of 2‐D, incompressible, steady, hydro magnetic Williamson hybrid nanofluid with three distinct shape factors namely spherical, cylindrical, and platelet shapes under the influence of thermal radiation and viscous dissipation effects on the flow. The aim of the current work is to investigate the thermal conduction capacity of three different shaped nanoparticles by comparison. We have modelled copper and molybdenum disulfide nanoparticles suspension in Williamson fluid blood as a conventional real fluid passing through a horizontal stretching cylinder in this case. A set of non‐linear PDEs are used to conceivably formulate the problem's physical model. The transformation from these modelled PDEs to ODEs is accomplished through the use of appropriate similarity variables. To address the problem, the RK method of order four is used in conjunction with shooting system in order to get first order ordinary equations from non‐linear higher order ordinary differential equations. To run the code for numerical results, computational Matlab bvp4c solver is used and graphs are depicted to explain the impact of various embedded physical quantities on the momentum and energy profiles accompanying the rates of shear stress and heat transfer for the considered Williamson hybrid nanofluid. The use of spherical shaped nanoparticles is thought to improve the thermal conductivity rate of the flowing fluid more than cylinder and platelet shaped nanoparticles. The skin friction coefficient is enhancing for larger values of magnetic parameter and curvature parameter but Weissenberg number has a negative trend. The rate of cooling is high for greater values of magnetic parameter, Williamson fluid parameter, heat generation parameter, thermal conduction parameter, viscous dissipation parameter and thermal radiation parameter.

Physics-Based Differentiable Rendering for Efficient and Plausible Fluid Modeling from Monocular Video.

Realistic fluid models play an important role in computer graphics applications. However, efficiently reconstructing volumetric fluid flows from monocular videos remains challenging. In this work, we present a novel approach for reconstructing 3D flows from monocular inputs through a physics-based differentiable renderer coupled with joint density and velocity estimation. Our primary contributions include the proposed efficient differentiable rendering framework and improved coupled density and velocity estimation strategy. Rather than relying on automatic differentiation, we derive the differential form of the radiance transfer equation under single scattering. This allows the direct computation of the radiance gradient with respect to density, yielding higher efficiency compared to prior works. To improve temporal coherence in the reconstructed flows, subsequent fluid densities are estimated via a coupled strategy that enables smooth and realistic fluid motions suitable for applications that require high efficiency. Experiments on synthetic and real-world data demonstrated our method's capacity to reconstruct plausible volumetric flows with smooth dynamics efficiently. Comparisons to prior work on fluid motion reconstruction from monocular video revealed over 50-170x speedups across multiple resolutions.

A Computational Fluid Dynamics Enhanced Oil Recovery Formulation Based on the Volume Average Procedure on the Full Momentum Equation: Effects of Polymer Solution Injection in Real Reservoirs with Anisotropic Permeability

Summary In this work, we propose a new methodology to simulate the process of enhanced oil recovery (EOR) in a 3D domain, considering a non-Newtonian fluid phase. The mass balance for the two phases and the balance of momentum are based on the volume averaging theory, which upscales the information on the microscale to make viable the solution in a real case. The full balance of momentum is used in place of the usually adopted Darcy’s law, and the equations are written for each phase in terms of porosity and fluid saturation. The equations are introduced in a new numerical solver developed for the OpenFOAM toolbox, which is an open-source C++ library created to simulate problems of computational fluid dynamics (CFD). First, the methodology is verified by comparing the results obtained from the volume averaging theory equations with Darcy’s law. Then, Newtonian and non-Newtonian cases for Buckley-Leverett, 2D, and 3D meshes are presented. We also present cases with a 3D mesh in a domain extracted from a real reservoir and properties of real injector fluids. The present approach is able to accommodate anisotropic permeability, heterogeneity, and non-Newtonian effects. We compare fluid saturation over time for the different cases as well as the accumulated volume of oil over time and the flow output of the domain. The simulations performed were able to demonstrate the effectiveness of polymeric solutions, comparing polyacrylamide (PAA) and polymeric surfactant (PS) cases with different concentrations, for better use in the production of available resources in reservoirs. In the five-spot cases with polymeric solutions, lower flow rates are achieved when the concentration is increased and the oil production until breakthrough is up to 45% higher when compared with water injection.

Random organization and non-equilibrium hyperuniform fluids on a sphere.

Randomly organizing hyperuniform fluid induced by reciprocal activation is a non-equilibrium fluid with vanishing density fluctuations at large length scales such as crystals. Here, we extend this new state of matter to a closed manifold, namely a spherical surface. We find that the random organization on a spherical surface behaves similar to that in two dimensional Euclidean space, and the absorbing transition on a sphere also belongs to the conserved directed percolation universality class. Moreover, the reciprocal activation can also induce a non-equilibrium hyperuniform fluid on a sphere. The spherical structure factor at the absorbing transition and the non-equilibrium hyperuniform fluid phases are scaled as S(l → 0) ∼ (l/R)0.45 and S(l → 0) ∼ l(l + 1)/R2, respectively, which are both hyperuniform according to the definition of hyperuniformity on a sphere with l, the wave number, and R, the radius of the spherical surface. We also consider the impact of inertia in realistic hyperuniform fluids, and it is found only by adding an extra length-scale, above which hyperuniform scaling appears. Our finding suggests a new method for creating non-equilibrium hyperuniform fluids on closed manifolds to avoid boundary effects.

Numerical approximations for fluid flow and heat transfer in the boundary layer with radiation through multiple Lie similarity transformations

The dependent or independent variables of differential equations may be reduced by applying its associated Lie point symmetries. Seven-dimensional Lie point symmetry algebra exists for differential equations representing heat transfer in a boundary layer flow in the presence of radiation. The linear combinations of these seven Lie symmetries are used first to deduce the invariants and then derive the Lie similarity transformations for the original set of partial differential equations (PDEs). This procedure is repeated for the set of transformed equations to further reduce the system of PDEs into the system of ordinary differential equations (ODEs). Multiple exact similarity transformations are obtained using this procedure. All these transformations map the system of three PDEs with three independent variables of flow and heat transfer under the specified set of conditions into two-dimensional systems of equations with only one independent variable, the system of ODEs. Approximate solutions for these reduced systems are established using the finite difference method to illustrate the effects of unsteadiness, Prandtl number, and radiation on the boundary layer thickness, flow, and heat transfer. This type of study was conducted under the effect of these parameters previously with a different set of similarity transformations. However, the Lie similarity transformations deduced in this work, which have not been employed, lead to different types of reduced systems of ODEs, thereby providing different velocities and temperature profiles and providing valid solutions for previously unexplored regions for unsteadiness in the fluid flow and heat transfer. Some of these transformations and their resulting systems provide results that contradict the flow and heat transfer in real fluids.

An insight into wax/asphaltene deposition behavior in the wellbore regions of gas condensate reservoirs

Wax/asphaltene deposition has been an important problem in the gas condensate reservoirs development. The cold plate device is designed to reveal the effect of operating conditions on the wax/asphaltene deposition behavior. The characteristic of wax/asphaltene deposition with well conditions is determined. The results show that when the temperature difference was considered, the growth rate of wax deposition thickness in the operation period was that stabilizing first, rising again, and then slowing down. However, the temperature and hydrogen bonding interaction significantly affects the asphaltene deposition process. The asphaltene deposition rate was stable at the beginning period of operation, then increased significantly, and decreased gradually after reaching the peak value of 21.61 g/cm2·h. An identification diagram of the wellbore deposition location is established. Increased deposition surface area of the cold plate structural design ensures qualitative and quantitative characterization of wax/asphaltene deposition traits. The real well fluids components were employed in the experiments to obtain critical conditions for wax/asphaltene deposition which approximated actual production conditions. This diagram facilitates the reliable identification of wax/asphaltene removal areas in the wellbore during production. This study provides a comprehensive understanding of the wax/asphaltene deposition behavior, which helps the gas condensate well operation safety and efficiency.

The simulation of non-stationary gas pressure in a pipeline with pumping and injection

In this work, based on the fundamental research of I. A. Charny on the unsteady movement of a real fluid in pipes, an equation that describes the pressure dynamics in a complex section of a gas pipeline was compiled. The use of the Dirac impulse function made it possible to describe the dynamics of unsteady pressure in a single equation in the case of point pumping and injection at given points. Linearization of the model by averaging the velocity of the gas made it possible to bring the equation to a hyperbolic form. If we neglect the forces of inertia compared to the forces of resistance, then the mathematical model will represent a partial differential equation of the second order parabolic type. The dynamics of pressure at specific points of pumping and injection under boundary conditions of the second kind (rates are given) was obtained using the finite cosine Fourier transform. The working formula that allows you to determine the pressure at any point at a given point in time is a trigonometric series. The series are rapidly convergent, so there is no difficulty in working with them. Particular cases are considered (without pumping and injection). The fulfillment of the boundary conditions is checked. It is easy to rebuild the working formula for pumping and / or injection at several points in a given area. Calculations of the mass flow and average velocity are made. In practice, the pressure is usually set at the start and end points of the area under study. In this case, it becomes possible to go to the costs (to derivatives) at the ends of the section under consideration.

Temperature- and curvature-dependent surface tensions and Tolman lengths for real fluids: A mesoscopic investigation

The curvature and temperature dependency of the liquid-vapor surface tension has a significant influence on the accurate prediction of the nanobubble/nanodrop nucleation process. In this work, a mesoscopic approach combining the pseudo-potential multiphase lattice Boltzmann method (LBM), the principle of dynamic similarity, and the van der Waals theory of corresponding states is adopted to quantitatively investigate the curvature and temperature dependency of the surface tension and Tolman length for real fluids (water and R134a). By Tolman length, we mean the distance from the surface of tension to the equimolar surface, which measures the extent by which the surface tension of a nanodrop/nanobubble deviates from the corresponding flat interface limit. We show that the Tolman lengths for flat liquid-vapor interfaces (δF) increase with the increase of temperature and are proportional to (1−Tr)−1.044. Equations for predicting surface tensions of water and R134a with effects of temperature and curvature radius taken into consideration are proposed. We demonstrate that the surface tensions increase while the Tolman lengths (δB) decrease with the increase of curvature for nanobubbles. For nanodroplets, however, the surface tensions decrease while the Tolman lengths (δD) increase with the increase of curvature. Effects of the equation of state for real fluids, which determines the interparticle interaction force in the pseudo-potential LBM, are also discussed. This mesoscopic approach can quantify the curvature dependency of liquid-vapor surface tensions for various real fluids in a wide temperature range with low computation costs, providing a new avenue for the accurate prediction of nucleation processes in micro-/nanoscale phase change heat transfer with applications to boiling, evaporation, and condensation.

Structure, Dynamics, and Rheology of Realistic Gaussian-Core Fluids: Unexpected Anomalies and Their Macromolecular Origin

We experimentally investigate the structure, dynamics, and linear rheology of dendrimer solutions as a model system of Gaussian-core fluids and ultrasoft colloids, and compare the results with those obtained by the coarse-grained approach. In the overpacked regime, particles pack in a way similar to Bernal’s celebrated plasticine model. Meanwhile, the interparticle interaction displays a counterintuitive softening under densification. Such behaviors result in transport properties remarkably different from the predictions of the simple Gaussian-core model. Particularly, we find a strong coupling between the rearrangement of interparticle configuration and intraparticle dynamics. These unexpected observations demonstrate the decisive role of intraparticle complexity in the structure and dynamics of ultrasoft colloids.

Interactive Simulation of Realistic Fluid Movement Based on SPH Method

With the continuous progress of computer simulation technology, fluid simulation has been developed rapidly, and it has beeen widely used in many fields, especially in engineering compution, game and special effects in movie. Nevertheless, with the increasing requirements of fidelity of the motion and interaction of subjects, fluid simulation requires more realistic simulation results. However, the motion of real fluid and objects is often difficult to be expressed by simple process, which can only be realized by the physical laws in the real world. Physical-based fluid simulation is one of the most challenging research issues due to its complexity in theory and computations. Among numerous fluid simulation models, Smoothed Particle Hydrodynamics (SPH) based fluid simution is the most widely used meshless method to simulate the realistic fluid motion. As a simple and flexible method, SPH partical characteristics make it naturally suitable for fluid simulation modeling and feasible to deal with many fluid simulation computation problems in a robust and stable way. The SPH basic principle, kernel function, discretization scheme and boundary treatments are introduced. The fluid movement is solved by SPH method in accordance with Navier-Stokes equations. The accuracy and stability of the fluid solution equation was improved by correcting the pressure and velocity fields. Secondly, the water surface was modeled and the rendering speed of the fluid surface was optimized by simplifying the fluid particles calculation. The SPH model is developed to simulate impulsive wave generated by dam-break and high speed landslide. It shows the model can simulate the movement process of the fluid fragment and coalescence, and available to simulate the blood, volcanic explosion and tsunami propagation.

Revised Enskog theory for Mie fluids: Prediction of diffusion coefficients, thermal diffusion coefficients, viscosities, and thermal conductivities.

Since the 1920s, the Enskog solutions to the Boltzmann equation have provided a route to predicting the transport properties of dilute gas mixtures. At higher densities, predictions have been limited to gases of hard spheres. In this work, we present a revised Enskog theory for multicomponent mixtures of Mie fluids, where the Barker-Henderson perturbation theory is used to calculate the radial distribution function at contact. With parameters of the Mie-potentials regressed to equilibrium properties, the theory is fully predictive for transport properties. The presented framework offers a link between the Mie potential and transport properties at elevated densities, giving accurate predictions for real fluids. For mixtures of noble gases, diffusion coefficients from experiments are reproduced within ±4%. For hydrogen, the predicted self-diffusion coefficient is within 10% of experimental data up to 200 MPa and at temperatures above 171K. Binary diffusion coefficients of the CO2/CH4 mixture from simulations are reproduced within 20% at pressures up to 14.7 MPa. Except for xenon in the vicinity of the critical point, the thermal conductivity of noble gases and their mixtures is reproduced within 10% of the experimental data. For other molecules than noble gases, the temperature dependence of the thermal conductivity is under-predicted, while the density dependence appears to be correctly predicted. Predictions of the viscosity are within ±10% of the experimental data for methane, nitrogen, and argon up to 300bar, for temperatures ranging from 233 to 523K. At pressures up to 500bar and temperatures from 200 to 800K, the predictions are within ±15% of the most accurate correlation for the viscosity of air. Comparing the theory to an extensive set of measurements of thermal diffusion ratios, we find that 49% of the model predictions are within ±20% of the reported measurements. The predicted thermal diffusion factor differs by less than 15% from the simulation results of Lennard-Jones mixtures, even at densities well exceeding the critical density.

Equilibrium thermodynamic properties of Lennard–Jones fluid mixtures from a single-component effective fluid model

ABSTRACT The equilibrium thermodynamic properties of binary Lennard–Jones mixtures are determined by means of a Monte Carlo-based perturbation theory for an effective single-component fluid. The results for the equation of state and the excess energy are compared with simulation data obtained for two equimolar binary Lennard–Jones fluid mixtures at different temperatures along a wide range of densities. The satisfactory accuracy achieved seems to suggest that this approach might be a useful tool to deal with mixtures with a wide variety of intermolecular interactions including mixtures of real fluids.

Roles of Fast Neutrino-Flavor Conversion on the Neutrino-Heating Mechanism of Core-Collapse Supernova.

One of the greatest uncertainties in any modeling of the inner engine of core-collapse supernova (CCSN) is neutrino-flavor conversions driven by neutrino self-interactions. We carry out large-scale numerical simulations of a multienergy, multiangle, three-flavor framework and general relativistic quantum kinetic neutrino transport in spherical symmetry with an essential set of neutrino-matter interactions under a realistic fluid profile of CCSN. Our result suggests that the neutrino heating in the gain region is reduced by ∼40% due to fast neutrino-flavor conversion (FFC). We also find that the total luminosity of neutrinos is enhanced by ∼30%, for which the substantial increase of heavy-leptonic neutrinos by FFCs are mainly responsible. This study provides evidence that FFC has a significant impact on the delayed neutrino-heating mechanism.

Numerical Investigations of Pseudo-Boiling and Multi-Component Mixing Under Trans-/supercritical Conditions for Engine Applications

ABSTRACT The fuel injection and mixing process are often carried out under trans-/supercritical conditions for engine applications; however, the process is still unclear. In this study, based on OpenFOAM, a multi-component trans-/supercritical spray model based on the KT/KNP scheme is developed, which covers the special real fluid equation of state, various mixing rules and modified thermodynamic properties. In addition, the PIMPLE algorithm is extended to deal with the high nonlinearity. First, a one-dimensional advection case is applied to evaluate the performance of the model. Then, the effect of various mixing rules and pseudo-boiling phenomenon on n-heptane/nitrogen jet are thoroughly analyzed under trans-/supercritical conditions. The results show that the jet is extremely sensitive to the changes of the initial jet temperature and chamber pressure, and the “heat shield” effect of pseudo-boiling delays the breakup and mixing in the transcritical jet. With the mixing of different components, unlike the single-component condition, the pseudo-boiling intensity will increase. The increase of pressure and occurrence of mixing will lead to the decrease of pseudo-boiling temperature, and the pseudo-boiling will end earlier, which is obviously different from the single-component fluid case. For the n-heptane/nitrogen mixture, when the mole fraction of n-heptane in the mixture changes from 1.0 to 0.7, and the pseudo-boiling temperature decreases from 571 K to 465 K. With increasing injection temperature or chamber pressure, the pseudo-boiling intensity gradually decreases, and the potential core shortens, the difference among various mixing rules decreases. When the injection temperature is higher than 571 K, the pseudo-boiling phenomenon no longer exists. When the chamber pressure reaches 9 MPa, the pseudo-boiling strength is very low. Therefore, the spray mixing under supercritical conditions will be more sufficient. With the occurrence of mixing, the critical parameter gradually transitions from the critical value of n-heptane to the critical value of nitrogen, which strongly depends on the mixing rule.

Onset of Viscous Dissipation Instability in Plane Couette Flow with Temperature-Dependent Viscosity

The conditions for the onset of dissipation thermal instability with temperature-dependent viscosity in the plane Couette flow of a Newtonian fluid are analyzed. The studied system consists of a horizontal fluid layer confined between an adiabatic (fixed) lower wall and an isothermal (moving) upper wall. Both the exponential and the linear fluidity models are considered in order to account for the thermodependency of the fluid’s viscosity. The linear stability analysis of the base solution with respect to arbitrarily oriented normal modes is carried out numerically by employing a shooting method. The most unstable disturbances are proven to be stationary longitudinal rolls, and their stability is governed by three dimensionless parameters: the viscous dissipation Rayleigh number, Prandtl number and a parameter that represents the variability of the viscosity with temperature. It is shown that the effect of the variation of the viscosity is to promote the stability of the base flow. As expected, the two viscosity models’ results diverge as the variability of the viscosity increases, and the exponential model is found to be more stable than the linear fluidity one. By considering the thermophysical properties of real fluids, it is shown that viscous dissipation thermal instability precedes hydrodynamic instability. An energy budget analysis is proposed to better understand both the stabilization effect of the thermal variability of the viscosity and differences with viscous dissipation hydrodynamic instability.