Collaborators

The present study examines the quantity of surface wetting in a two-phase oil and water pipe flow. The study is performed by employing an Eulerian-Eulerian computational fluid dynamics model using the S-gamma droplet size distribution model within STAR-CCM+. In the North Sea, production of oil and gas, water-phase surface processes such as scale and corrosion account for 40-50% of operating expenses. The objective of the study is to investigate best practices for the prediction of phase distribution aimed at evaluating the degree of the wall in contact with the water phase (water-wetting). The model is validated by performing detailed numerical simulations corresponding to the experimental studies by Kumara, Halvorsen, and Melaaen (Meas. Sci. Technol., vol. 20, p. 114004, 2009). The comparison yields good agreement with the observed measurements with slight deviations in the predicted dispersion rate but accurate prediction of the liquid holdup. Comparison of droplet sizes to those observed in experiments by Elseth (PhD, Telemark University College, 2001) indicates that tuning of the S-gamma model is necessary to provide accurate droplet size predictions. The surface wetting is then evaluated with its interdependence with liquid holdup and dispersion rate. Increase in the dispersion with a decrease in the Richardson number is observed in agreement with stability analysis of the Kelvin-Helmholtz instability.

In this contribution, we review recent developments and applications of a dynamic clustering algorithm SWINGER tailored for the multiscale molecular simulations of biomolecular systems. The algorithm on-the-fly redistributes solvent molecules among supramolecular clusters. In particular, we focus on its applications in combination with the adaptive resolution scheme, which concurrently couples atomistic and coarse-grained molecular representations. We showcase the versatility of our multiscale approach on a few applications to biomolecular systems coupling atomistic and supramolecular water models such as the well-established MARTINI and dissipative particle dynamics models and provide an outlook for future work.

The present study investigated a new microchannel profile design encompassing condensate drainage slits for improved moisture removal with use of triangular shaped plain fins. Heat transfer and pressure drop correlations were developed using computational fluid dynamics (CFD) and defined in terms of Colburn j-factor and Fanning f-factor. The microchannels were square 2.00 × 2.00 mm and placed with 4.50 mm longitudinal tube pitch. The transverse tube pitch and the triangular fin pitch were varied from 9.00 to 21.00 mm and 2.50 to 10.00 mm, respectively. Frontal velocity ranged from 1.47 to 4.40 m·s⁻¹. The chosen evaporator geometry corresponds to evaporators for industrial refrigeration systems with long frosting periods. Furthermore, the CFD simulations covered the complete thermal entrance and developed regions, and made it possible to extract virtually infinite longitudinal heat transfer and pressure drop characteristics. The developed Colburn j-factor and Fanning f-factor correlations are able to predict the numerical results with 3.41% and 3.95% deviation, respectively.

A homogeneous compression ignition (HCCI) engine is taken for numerical investigation on the application of renewable fuels contained blends of methanol and DME with the base diesel fuel, which will be replaced with diesel in different percentages. First, the combustion and engine performance of the engine for two and three-component fuels will be discussed and secondly, the simultaneous effect of EGR in 20% by mass and engine speed in two blends of having maximum and minimum diesel proportion are compared and examined. The results indicate that the replacement of diesel with 20% of DME and 30% by methanol (D50M30DME20) at 1400 rpm generates a greater pressure and accumulated heat (AHR_peak = 330.569 J), whereas D80M20/2000 rpm/EGR20 gives a defective combustive performance with poor engine efficiency (IMEP = 7.21 bar). The interesting point is that the proposed optimum blend of D50 can achieve the best performance with  35% mechanical efficiency of 35%. The case of D60M10DME30 though dominates in terms of RPR = 3.177 bar/deg and ignition delay (ID = 4.54 CA) that gives the highest exergy performance coefficient (EPC = 2.063) due to its high work and lowest irreversibility.

Nearly frictionless water transport makes carbon nanotubes promising materials for use as conduits in nanofluidic applications. Here, we conduct molecular dynamics simulations of water flow within amorphous silica nanopores coated by a (39,39) single-walled carbon nanotube (SWCNT). Our atomistic models describe the interaction between water and pore walls based on two possible scenarios, translucency and opacity to wetting of a SWCNT. Simulation results indicate that the SWCNT coating enhances water flow through silica pores ca. 10 times compared to predictions from the classical Hagen–Poiseuille relation. By varying the strength of the water–pore interaction, we study the relationship between surface wettability and hydrodynamic slippage. We observe an increase in the slip length for higher values of water contact angle. Moreover, cases with SWCNT opacity and translucency to wetting display a substantial difference in the computed slippage, showing that the water contact angle is not the only factor that determines the slip boundary condition under nanoconfinement. We attribute this disparity to the corrugation of the potential energy landscape at the inner pore wall. The present study provides a theoretical framework for the use of carbon nanotube-based coatings in designing more efficient nanofluidic conduits.

Near-well flow analysis is an important tool for gaining detailed insight of the flow behaviour and for improving well design and production optimization of real reservoirs. One challenge of accurate numerical modelling of the flow field in the vicinity of the well is related to the scale disparity factor in space and time. The numerical scale gap between the reservoir and the wellbore justifies the representation of a well as a point or line sink/source term in traditional reservoir models. However, standard numerical techniques for reservoir simulation are incapable of resolving the near-singular character of the pressure field in the vicinity of the well. Under the assumption that all length scales have impact on flow patterns, we present a proof-of-concept study aimed at improving the quality of the numerical simulation by considering the geometry and fluid flow near the wellbore in a fully connected system, thus accounting for the fine scale phenomena by means of a hybrid Navier-Stokes/Darcy wellbore model coupled with a full scale reservoir model. A weak coupling method based on fixed-point iterations, that preserves the mass flux transport across the coupled interface, while adjusting productivity indices, is demonstrated via numerical experiments. Several different numerical experiments are performed to demonstrate the versatility and the improved well performance insight that the coupled method offers, including horizontal well inflow profile, influence of formation damage and optimal well configuration.

In this paper, we derive the non-singular Green’s functions for the unbounded Poisson equation in one, two and three dimensions using a spectral cut-off function approach to impose a minimum length scale in the homogeneous solution. The resulting non-singular Green’s functions are relevant to applications which are restricted to a minimum resolved length scale (e.g. a mesh size h) and thus cannot handle the singular Green’s function of the continuous Poisson equation. We furthermore derive the gradient vector of the non-singular Green’s function, as this is useful in applications where the Poisson equation represents potential functions of a vector field.

The mitigation of CO₂ emissions is an effective measure to solve the climate change issue. In the present study, we propose an alternative approach for CO₂ capture by employing supersonic flows. For this purpose, we first develop a computational fluid dynamics (CFD) model to predict the CO₂ condensing flow in a supersonic nozzle. Adding two transport equations to describe the liquid fraction and droplet number, the detailed numerical model can describe the heat and mass transfer characteristics during the CO₂ phase change process under the supersonic expansion conditions. A comparative study is performed to evaluate the effect of CO₂ condensation using the condensation model and dry gas assumption. The results show that the developed CFD model predicts accurately the distribution of the static temperature contrary to the dry gas assumption. Furthermore, the condensing flow model predicts a CO₂ liquid fraction up to 18.6% of the total mass, which leads to the release of the latent heat to the vapour phase. The investigation performed in this study suggests that the CO₂ condensation in supersonic flows provides an efficient and eco-friendly way to mitigate the CO₂ emissions to the environment.

This work reports on numerical investigation of effects of ambient pressure (P_am) on spray combustion under engine-like conditions. Three cases with different P_am of 42, 85 and 170 bar at a fixed ambient temperature of 1000 K are considered. Zero-dimensional calculations are first performed for autoignition of stagnant adiabatic homogenous mixtures to evaluate performance of the selected diesel surrogate fuel models and to identify the P_am effects on the most reactive mixture. An Eulerian-based transported probability density function model is then chosen for the three-dimensional computational fluid dynamics study. The results show the predicted ignition delay times and flame lift-off lengths are in reasonably good agreement with experiment, with the relative difference below 28%. The current work reveals that low-temperature reactions occur across a wide range of mixture fraction but a noticeable rise of temperature (>100 K above ambient temperature) is detected first on the fuel-lean side of the stoichiometric line in all three cases. The high-temperature ignition occurs first on the fuel-rich side in the 42 and 85 bar cases, where the igniting mixture appears to be more fuel-rich in the latter case. As P_am is further increased to 170 bar, the igniting mixture becomes more fuel-lean and the high-temperature ignition occurs on the fuel-lean side. The ignition behavior is found to depend on both physical and chemical processes. At 170 bar, the reaction rate increases and the associated transition from low- to high-temperature ignition is relatively fast, as compared to the transport of warmer products from the lean zone into the fuel-rich mixture. Also, within the fuel-rich region, the local temperature is low due to liquid fuel vaporization and the condition is not appropriate for ignition. These collectively cause the high-temperature ignition to occur on the fuel-lean side. Analyses on the quasi-steady spray flame structures reveal that, apart from poorer air entrainment due to reduced lift-off length, the higher rich-zone temperature and lower scalar dissipation rate also lead to a higher peak soot volume fraction at higher P_am.

Development of functional nanofluidic devices requires understanding the fundamentals of capillary driven flow in nanochannels. In this context, we conduct molecular dynamics simulations of water capillary imbibition in silica nanoslits under externally applied electric (E) fields with strengths between 0 and 1 V nm⁻¹. For increasing E-fields, we observe a systematic lowering in the meniscus contact angle and a decrease in the corresponding water filling rates. These results contrast markedly the classical Washburn–Bosanquet's equation which predicts an increase in filling rates for lower water contact angles. Our study provides evidence that the observed decrease in water filling rates can be attributed to the interplay between two underlying mechanisms, a reduced fluidity of interfacial water and a systematic alignment of the water molecules in the bulk as a response to the particular strength of the applied E-field. Therefore, during water capillary filling a constant E-field applied in the direction parallel to the water imbibition leads to a lower than expected filling rate caused by a viscosity increase in the bulk and an altered solid–liquid friction on the channel walls. These coupled mechanisms governing capillarity under the action of applied E-fields could be manipulated for controlling imbibition of polar liquid solutions in nanofluidic devices.

Regularized Green's functions for mixed unbounded-periodic domains are derived. The regularization of the Green's function removes its singularity by introducing a regularization radius which is related to the discretization length and hence imposes a minimum resolved scale. In this way the regularized unbounded-periodic Green's functions can be implemented in an FFT-based Poisson solver to obtain a convergence rate corresponding to the regularization order of the Green's function. The high order is achieved without any additional computational cost from the conventional FFT-based Poisson solver and enables the calculation of the derivative of the solution to the same high order by direct spectral differentiation. We illustrate an application of the FFT-based Poisson solver by using it with a vortex particle mesh method for the approximation of incompressible flow for a problem with a single periodic and two unbounded directions.

The sand shot in the DISAMATIC process is simulated by the discrete element method (DEM) taking into account the influence and coupling of the airflow with computational fluid dynamics (CFD). The DEM model is calibrated by a ring shear test, a sand pile experiment and a slump test. Subsequently, the DEM model is used to model the propagation of the green sand inside the mold chamber and the results are compared to experimental video footage. The chamber contains two cavities designed to quantify the deposited mass of green sand. The deposition of green sand in these two cavities is investigated with three cases of different air vent settings which control the ventilation of the chamber. These settings resulted in different air- and particle-velocities as well as different accumulated masses in the cavities, which were successfully simulated by the model.

A hydrodynamic journal bearing has been investigated using both the traditional two-dimensional (2D) Reynolds equation, and the full solution being the three-dimensional (3D) Navier-Stokes equations.

The two approaches are compared by performing an investigation of two inlet groove designs: the axial and the circumferential groove, respectively, on a bearing with length-to-diameter ratio of 0.5 exposed to a sinusoidal load pattern. Pressure distributions, journal orbits and frictional losses are compared. The modelling of grooves by pressure boundary conditions versus geometric conditions is examined. It is investigated if the presence of a groove increases frictional losses and the increase relates to groove dimensions. Furthermore, the influence of the groove design on the flow field is studied using the 3D solution.

It is well known that translocation events of a polymer or rod through pores or narrower parts of micro- and nanochannels have a stochastic nature due to the Brownian motion. However, it is not clear whether the objects of interest need to have a larger size than the entrance to exhibit the deviation from the dynamics of the surrounding fluid. We show by numerical analysis that the particle injection into the narrower part of the channel is affected by thermal fluctuation, where the particles have spherical symmetry and are smaller than the height of the constriction. The Péclet number (Pe) is the order parameter that governs the phenomena, which clarifies the spatio-temporal significance of Brownian motion compared to hydrodynamics. Furthermore, we find that there exists an optimal condition of Pe to attain the highest flow rate of particles relative to the dispersant fluid flow. Our finding is important in science and technology from nanopore DNA sequencers and lab-on-a-chip devices to filtration by porous materials and chromatography.

Microbial filter feeders are an important group of grazers, significant to the microbial loop, aquatic food webs, and biogeochemical cycling. Our understanding of microbial filter feeding is poor, and, importantly, it is unknown what force microbial filter feeders must generate to process adequate amounts of water. Also, the trade-off in the filter spacing remains unexplored, despite its simple formulation: A filter too coarse will allow suitably sized prey to pass unintercepted, whereas a filter too fine will cause strong flow resistance. We quantify the feeding flow of the filter-feeding choanoflagellate Diaphanoeca grandis using particle tracking, and demonstrate that the current understanding of microbial filter feeding is inconsistent with computational fluid dynamics (CFD) and analytical estimates. Both approaches underestimate observed filtration rates by more than an order of magnitude; the beating flagellum is simply unable to draw enough water through the fine filter. We find similar discrepancies for other choanoflagellate species, highlighting an apparent paradox. Our observations motivate us to suggest a radically different filtration mechanism that requires a flagellar vane (sheet), something notoriously difficult to visualize but sporadically observed in the related choanocytes (sponges). A CFD model with a flagellar vane correctly predicts the filtration rate of D. grandis, and using a simple model we can account for the filtration rates of other microbial filter feeders. We finally predict how optimum filter mesh size increases with cell size in microbial filter feeders, a prediction that accords very well with observations. We expect our results to be of significance for small-scale biophysics and trait-based ecological modeling.

We propose a novel partitioning method for block-structured adaptive meshes utilizing the meshless Lagrangian particle concept. With the observation that an optimum partitioning has high analogy to the relaxation of a multi-phase fluid to steady state, physically motivated model equations are developed to characterize the background mesh topology and are solved by multi-phase smoothed-particle hydrodynamics. In contrast to well established partitioning approaches, all optimization objectives are implicitly incorporated and achieved during the particle relaxation to stationary state. Distinct partitioning sub-domains are represented by colored particles and separated by a sharp interface with a surface tension model. In order to obtain the particle relaxation, special viscous and skin friction models, coupled with a tailored time integration algorithm are proposed. Numerical experiments show that the present method has several important properties: generation of approximately equal-sized partitions without dependence on the mesh-element type, optimized interface communication between distinct partitioning sub-domains, continuous domain decomposition which is physically localized and implicitly incremental. Therefore it is particularly suitable for load-balancing of high-performance CFD simulations.

In this work, three-dimensional computational fluid dynamics (CFD) studies of sulphur oxides (SO_x) and sulphuric acid (H₂SO₄) formation processes in a large, low speed two-stroke marine diesel engine are carried out. The current numerical study aims to investigate the conversion of sulphuric dioxide (SO₂) to sulphuric trioxide (SO₃) and the possibility of H₂SO₄ condensation which are the prerequisites to better understand the corrosion-induced wear phenomenon. This is achieved with the aid of the implementation of a multicomponent surrogate model, which comprises a skeletal n-heptane mechanism and a reduced sulphur subset mechanism. In the present work, performance of the coupled CFD-chemical kinetic model is evaluated using both qualitative and quantitative methods. The modelling results show that the temporal and spatial evolutions of SO_x predicted by the skeletal model are similar to those by the base mechanism. Predictions of the variations of SO_x and the associated SO₂ to SO₃ conversion in response to the change of fuel sulphur content, swirl velocity, start of injection, scavenge pressure and humidity qualitatively agree with numerical and experimental results from the literature. The model is further evaluated using the measured SO₂ to SO₃ conversion levels in a low load, low scavenge pressure case and a low load, high scavenge pressure case. The absolute values of simulated and measured conversion levels are close, although the former appear to be higher. The current results show that the flame impinges at the cylinder liner near top dead centre. The gas is cooled rapidly by the wall temperature and H₂SO₄ is produced in the region where the local temperature is less than 600 K. Based on the flue gas correlation, the acid dew point temperature is higher than the wall temperature, suggesting that acid condensation may begin early at the top part of the cylinder liner. The predicted distribution corresponds well with the distribution of corroded parts observed in service engines. The model is expected to serve as an important tool to simulate the rates of SO₂ absorption into lubricating oil film and H₂SO₄ condensation in this combustion system.

The condensation phenomenon of vapor plays an important role in various industries, such as the steam flow in turbines and refrigeration system. A mathematical model is developed to predict the spontaneous condensing phenomenon in the supersonic flows using the nucleation and droplet growth theories. The numerical approach is validated with the experimental data, which shows a good agreement between them. The condensation characteristics of water vapor in the Laval nozzle are described in detail. The results show that the condensation process is a rapid variation of the vapor-liquid phase change both in the space and in time. The spontaneous condensation of water vapor will not appear immediately when the steam reaches the saturation state. Instead, it occurs further downstream the nozzle throat, where the steam is in the state of supersaturation.

Graphene has attracted considerable attention due to its characteristics as a 2D material and its fascinating properties, providing a potential building block for nanofabrication. In nanochannels the solid–liquid interface plays a non-negligible role in determining the fluid dynamics. Therefore, for an optimal design of nanofluidic devices, a comprehensive understanding of the slippage in a water flow confined between graphene walls is important. In nanoconfinement, experimental and computational studies have found the slip length to increase nonlinearly when the shear rate is larger than a critical value. Here, by conducting molecular dynamics simulations, we study the influence of the graphene crystallographic orientation on the slip boundary conditions inside a nanoslit channel. The flow in channels with heights of 2.0, 2.4 and 2.8 nm is driven parallel to the zig-zag and arm-chair crystallographic directions. We extract flow rates, velocity profiles, slip velocities and slip lengths. The slip velocity displays a linear relationship to the shear stress up to a critical value, which is not size dependent. Moreover, the slip length is found to be shear stress dependent above a critical shear stress value of 0.4 MPa. Furthermore, our results indicate that after this critical shear stress is reached, the flow rates are significantly influenced (up to 10%) by the particular orientation of the graphene topology.

The variational multiscale method is reviewed as a framework for developing computational methods for large-eddy simulation of turbulent flow. In contrast to other articles reviewing this topic, which focused on large-eddy simulation of turbulent incompressible flow, this study covers further aspects of numerically simulating turbulent flow as well as applications beyond incompressible single-phase flow. The various concepts for subgrid-scale modeling within the variational multiscale method for large-eddy simulation proposed by researchers in this field to date are illustrated. These conceptions comprise (i) implicit large-eddy simulation, represented by residual-based and stabilized methods, (ii) functional subgrid-scale modeling via small-scale subgrid-viscosity models and (iii) structural subgrid-scale modeling via the introduction of multifractal subgrid scales. An overview on exemplary numerical test cases to which the reviewed methods have been applied in the past years is provided, including explicit computational results obtained from turbulent channel flow. Wall-layer modeling, passive and active scalar transport as well as developments for large-eddy simulation of turbulent two-phase flow and combustion are discussed to complete this exposition.

In the petroleum industry, water-and-gas breakthrough in hydrocarbon reservoirs is a common issue that eventually leads to uneconomic production. To extend the economic production lifetime, inflow-control devices (ICDs) are designed to delay the water-and-gas breakthrough. Because the lifetime of a hydrocarbon reservoir commonly exceeds 20 years and it is a harsh environment, the reliability of the ICDs is vital.

With computational fluid dynamics (CFD), an inclined nozzle-based ICD is characterized in terms of the Reynolds number, discharge coefficient, and geometric variations. The analysis shows that especially the nozzle edges affect the ICD flow characteristics. To apply the results, an equation for the discharge coefficient is proposed.

The Lagrangian particle approach is used to further investigate the ICD. This allows for erosion modeling by injecting sand particles into the system. By altering the geometry and modeling several scenarios while analyzing the erosion in the nozzles and at the nozzle edges, an optimized design for incompressible media is found. With a filleted design and an erosion-resistant material, the mean erosion rate in the nozzles may be reduced by a factor of more than 2,500.

We present a combined numerical (particle vortex method) and experimental (soap film tunnel) study of a symmetric foil undergoing prescribed oscillations in a two-dimensional free stream. We explore pure pitching and pure heaving, and contrast these two generic types of kinematics. We compare measurements and simulations when the foil is forced with pitching oscillations, and we find a close correspondence between flow visualisations using thickness variations in the soap film and the numerically determined vortex structures. Numerically, we determine wake maps spanned by oscillation frequency and amplitude, and we find qualitatively similar maps for pitching and heaving. We determine the drag–thrust transition for both pitching and heaving numerically, and we discuss it in relation to changes in wake structure. For heaving with low oscillation frequency and high amplitude, we find that the drag–thrust transition occurs in a parameter region with wakes in which two vortex pairs are formed per oscillation period, in contrast to the common transition scenario in regions with inverted von Kármán wakes.

We investigate with experiments and computer simulations the nonequilibrium dynamics of DNA polymers crossing arrays of entropic barriers in nanofluidic devices in a pressure-driven flow. With increasing driving pressure, the effective diffusivity of DNA rises and then peaks at a value that is many times higher than the equilibrium diffusivity. This is an entropic manifestation of “giant acceleration of diffusion.” The phenomenon is sensitive to the effective energy landscape; thus, it offers a unique probe of entropic barriers in a system driven away from equilibrium.

We present a novel high order multiresolution Poisson solver based on regularized Green's function solutions to obtain exact free-space boundary conditions while using fast Fourier transforms for computational efficiency. Multiresolution is a achieved through local refinement patches and regularized Green's functions corresponding to the difference in the spatial resolution between the patches. The full solution is obtained utilizing the linearity of the Poisson equation enabling super-position of solutions. We show that the multiresolution Poisson solver produces convergence rates that correspond to the regularization order of the derived Green's functions.

Nanoscale capillarity has been extensively investigated; nevertheless, many fundamental questions remain open. In spontaneous imbibition, the classical Lucas–Washburn equation predicts a singularity as the fluid enters the channel consisting of an anomalous infinite velocity of the capillary meniscus. Bosanquet's equation overcomes this problem by taking into account fluid inertia predicting an initial imbibition regime with constant velocity. Nevertheless, the initial constant velocity as predicted by Bosanquet's equation is much greater than those observed experimentally. In the present study, large scale atomistic simulations are conducted to investigate capillary imbibition of water in slit silica nanochannels with heights between 4 and 18 nm. We find that the meniscus contact angle remains constant during the inertial regime and its value depends on the height of the channel. We also find that the meniscus velocity computed at the channel entrance is related to the particular value of the meniscus contact angle. Moreover, during the subsequent visco-inertial regime, as the influence of viscosity increases, the meniscus contact angle is found to be time dependent for all the channels under study. Furthermore, we propose an expression for the time evolution of the dynamic contact angle in nanochannels which, when incorporated into Bosanquet's equation, satisfactorily explains the initial capillary rise.

We consider the very challenging problem of efficient uncertainty quantification for acoustic wave propagation in a highly heterogeneous, possibly layered, random medium, characterized by possibly anisotropic, piecewise log-exponentially distributed Gaussian random fields. A multi-level Monte Carlo finite volume method is proposed, along with a novel, bias-free upscaling technique that allows to represent the input random fields, generated using spectral FFT methods, efficiently. Combined together with a recently developed dynamic load balancing algorithm that scales to massively parallel computing architectures, the proposed method is able to robustly compute uncertainty for highly realistic random subsurface formations that can contain a very high number (millions) of sources of uncertainty. Numerical experiments, in both two and three space dimensions, illustrating the efficiency of the method are presented.

We report a quantitative framework to guide the braiding pattern design of multilayer helical assemblies. We optimize the structural pattern so as to maximize the construction’s resistance to axial loads and concurrently minimize its torsional propensity. To that extent, we consider helical assemblies comprised of up to five layers, for which we identify favorable structural patterns, providing a database that covers most practical applications.