Searcharxiv⌕ Search

arXiv subjects

Omar Matar

Publications and source records attributed to Omar Matar.

8 recordsLinked to original sources
arXiv2024

Richtmyer-Meshkov Instability at high Mach Number: Non-Newtonian Effects

The Richtmyer-Meshkov instability (RMI) occurs when a shock wave passes through an interface between fluids of different densities, a phenomenon prevalent in a variety of scenarios including supersonic combustion, supernovae, and inertial confinement fusion. In the most advanced current numerical modelling of RMI, a multitude of secondary physical phenomena are typically neglected that may crucially change in silico predictions. In this study, we investigate the effects of shear-thinning behaviour of a fluid on the RMI at negative Atwood numbers via numerical simulations. A parametric study is carried out over a wide range of Atwood and Mach numbers that probes the flow dynamics following the impact on the interface of the initial shock wave and subsequent, reflected shocks. We demonstrate agreement between our numerical results and analytical predictions, which are valid during the early stages of the flow, and examine the effect of the system parameters on the vorticity distribution near the interface. We also carry out an analysis of the rate of vorticity production and dissipation budget which pinpoints the physical mechanisms leading to instability due to the initial and reflected shocks. Our findings indicate that the shear-thinning effects have a significant impact on instability growth and the development of secondary instabilities, which manifest themselves through the formation of Kelvin-Helmholtz waves. Specifically, we demonstrate that these effects influence vorticity generation and damping, which, in turn, affect the RMI growth. These insights have important implications for a range of applications, including inertial confinement fusion and bubble collapse within non-Newtonian materials.

physics.flu-dyn↗
arXiv2022

Deep Gaussian Process-based Multi-fidelity Bayesian Optimization for Simulated Chemical Reactors

New manufacturing techniques such as 3D printing have recently enabled the creation of previously infeasible chemical reactor designs. Optimizing the geometry of the next generation of chemical reactors is important to understand the underlying physics and to ensure reactor feasibility in the real world. This optimization problem is computationally expensive, nonlinear, and derivative-free making it challenging to solve. In this work, we apply deep Gaussian processes (DGPs) to model multi-fidelity coiled-tube reactor simulations in a Bayesian optimization setting. By applying a multi-fidelity Bayesian optimization method, the search space of reactor geometries is explored through an amalgam of different fidelity simulations which are chosen based on prediction uncertainty and simulation cost, maximizing the use of computational budget. The use of DGPs provides an end-to-end model for five discrete mesh fidelities, enabling less computational effort to gain good solutions during optimization. The accuracy of simulations for these five fidelities is determined against experimental data obtained from a 3D printed reactor configuration, providing insights into appropriate hyper-parameters. We hope this work provides interesting insight into the practical use of DGP-based multi-fidelity Bayesian optimization for engineering discovery.

cs.CE↗
arXiv2021

Data-Centric Engineering: integrating simulation, machine learning and statistics. Challenges and Opportunities

Recent advances in machine learning, coupled with low-cost computation, availability of cheap streaming sensors, data storage and cloud technologies, has led to widespread multi-disciplinary research activity with significant interest and investment from commercial stakeholders. Mechanistic models, based on physical equations, and purely data-driven statistical approaches represent two ends of the modelling spectrum. New hybrid, data-centric engineering approaches, leveraging the best of both worlds and integrating both simulations and data, are emerging as a powerful tool with a transformative impact on the physical disciplines. We review the key research trends and application scenarios in the emerging field of integrating simulations, machine learning, and statistics. We highlight the opportunities that such an integrated vision can unlock and outline the key challenges holding back its realisation. We also discuss the bottlenecks in the translational aspects of the field and the long-term upskilling requirements of the existing workforce and future university graduates.

cs.CE↗
arXiv2021

Taylor bubble motion in stagnant and flowing liquids in vertical pipes. Part I: Steady-states

Taylor bubbles are a feature of the slug flow regime in gas-liquid flows in vertical pipes. Their dynamics exhibits a number of transitions such as symmetry-breaking in the bubble shape and wake when rising in downward-flowing and stagnant liquids, respectively, as well as breakup in sufficiently turbulent environments. Motivated by the need to examine the stability of a Taylor bubble in liquids, a systematic numerical study of a steadily-moving Taylor bubble in stagnant and flowing liquids is carried out, characterised by a dimensionless inverse viscosity ($Nf$), and Eötvös ($Eo$), and Froude ($Fr$) numbers based on the centreline liquid velocity, using a Galerkin finite-element method. A boundary-fitted domain is used to examine the dependence of the steady bubble shape on a wide range of $Nf$ and $Eo$. Our analysis of the bubble nose and bottom curvatures shows that the intervals $Eo = \left[ 20,30 \right)$ and $Nf=\left[60,80 \right)$ are the limits below which surface tension and viscosity, respectively, have a strong influence on the bubble shape. In the interval $Eo = \left(60,100 \right]$, all bubble features studied are weakly-dependent on surface tension. This is Part I of a two-part publication in which its companion paper (Abubakar & Matar, 2021) reports the results of a linear stability analysis of the steady-states discussed herein.

physics.flu-dyn↗
arXiv2021

Taylor bubble motion in stagnant and flowing liquids in vertical pipes. Part II: Linear stability analysis

In this study, we examine the linear stability of an axisymmetric Taylor bubble moving steadily in a flowing liquid enclosed in a circular tube. Linearisation is performed about axisymmetric base states obtained in Part I of this study by Abubakar and Matar (2021). The stability is characterised by the dimensionless inverse viscosity $\left( Nf \right)$, Eötvös $\left( Eo \right)$, and Froude numbers $\left( U_m \right)$, the latter being based on the centreline liquid velocity. The analysis shows that there exist regions of $(Nf,Eo,U_m)$ space within which the bubble is unstable and assumes an asymmetric shape. To elucidate the mechanisms underlying the instability, an energy budget analysis is carried out which reveals that perturbation growth is driven by the bubble pressure for $Eo \geq 100$, and by the tangential interfacial stress for $Eo < 100$. Examples of the asymmetric bubble shapes and their associated flow fields are also provided near the onset of instability for a wide range of $Nf$, $Eo$, and $U_m$.

physics.flu-dyn↗
arXiv2021

On the missing link between pressure drop, viscous dissipation and the turbulent energy spectrum

We present convincing evidence of a direct connection between the pressure drop, viscous dissipation, and the turbulent energy spectrum. We use this finding to explain Nikuradse's experimental results of pressure drop for turbulent flows in rough pipes, in terms of a modified Kolmogorov length scale that varies with the surface roughness. Furthermore, we use Laufer's measurements of turbulent energy spectra in pipe flow to calculate -- to a good approximation -- the turbulent component of the pressure drop directly from an averaged turbulent energy spectrum. We also show that the incompressibility assumption, leads to the conclusion that viscous dissipation in fully-developed (laminar and turbulent) pipe flow, cannot increase the temperature of the fluid through viscous heating.

physics.flu-dyn↗
arXiv2010

Interfacial instability in turbulent flow over a liquid film in a channel

We revisit here the stability of a deformable interface that separates a fully-developed turbulent gas flow from a thin layer of laminar liquid. Unlike previous work, the turbulent base state velocity profile proposed here requires only a specification of a flowrate or pressure drop, and no a posteriori choice of parameters. Moreover, the base state contains sufficient detail such that it allows for instability due to a viscosity-contrast mechanism (which turns out to be dominant) as well as instability due to a critical-layer-type mechanism, and it is validated against the experimental and numerical data available in the literature. Furthermore, the effect of perturbations in the turbulent stress distributions is investigated, and demonstrated, for the first time, to be small for cases wherein the liquid layer is thin. The detailed modelling of the liquid layer elicits two unstable modes, and mode competition can occur, although in most cases the instability is due to the viscosity-contrast mechanism. In particular, there is the possibility that surface roughness can reduce the growth rate of the interfacial mode, and promote a liquid-layer instability to the status of most dangerous mode. Our base-state model facilitates a new definition of `slow' and `fast' waves. We use our linear stability analysis to determine the factors that affect the wave speed and demonstrate that the waves are `slow' according to the definition proposed here. Finally, we compare our results with experimental data, and good agreement is obtained.

physics.flu-dyn↗