OpenFOAM Solver Research Articles

Reduced-Order Model Approaches for Predicting Airfoil Performance

This study delves into the construction of reduced-order models (ROMs) of a flow field over a NACA 0012 airfoil at a moderate Reynolds number and an angle of attack of 8∘. Numerical simulations were computed through the finite-volume solver OpenFOAM. The analysis considers two different reduction techniques: the standard Galerkin projection method, which involves projecting the governing equations onto proper orthogonal decomposition modes (POD−ROMs), and the cluster-based network model (CNM), a fully data-driven nonlinear approach. An analysis of the topology of the dominant POD modes was conducted, uncovering a traveling wave pattern in the wake dynamics. We compared the performances of both ROM techniques regarding their prediction of flow field behavior and integral quantities. The ROM framework facilitates the practical actuation of control strategies with significantly reduced computational demands compared to the full-order approach.

Computation of Real-Fluid Thermophysical Properties Using a Neural Network Approach Implemented in OpenFOAM

Machine learning based on neural networks facilitates data-driven techniques for handling large amounts of data, either obtained through experiments or simulations at multiple spatio-temporal scales, thereby finding the hidden patterns underlying these data and promoting efficient research methods. The main purpose of this paper is to extend the capabilities of a new solver called realFluidReactingNNFoam, under development at the University of Perugia, in OpenFOAM with a neural network algorithm for replacing complex real-fluid thermophysical property evaluations, using the approach of coupling OpenFOAM and Python-trained neural network models. Currently, neural network models are trained against data generated using the Peng–Robinson equation of state assuming a mixture’s frozen temperature. The OpenFOAM solver, where needed, calls the neural network models in each grid cell with appropriate inputs, and the returned results are used and stored in suitable OpenFOAM data structures. Such inference for thermophysical properties is achieved via the “Neural Network Inference in C made Easy (NNICE)” library, which proved to be very efficient and robust. The overall model is validated considering a liquid-rocket benchmark comprised of liquid-oxygen (LOX) and gaseous-hydrogen (GH2) streams. The model accounts for real-fluid thermodynamics and transport properties, making use of the Peng–Robinson equation of state and the Chung transport model. First, the development of a real-fluid model with an artificial neural network is described in detail. Then, the numerical results of the transcritical mixing layer (LOX/GH2) benchmark are presented and analyzed in terms of accuracy and computational efficiency. The results of the overall implementation indicate that the combined OpenFOAM and machine learning approach provides a speed-up factor higher than seven, while preserving the original solver accuracy.

Dynamic Mesh Simulations in OpenFOAM: A Hybrid Eulerian–Lagrangian Approach

The past few decades have witnessed a growing popularity in Eulerian–Lagrangian solvers due to their significant potential for simulating aerodynamic flows, particularly in cases involving strong body–vortex interactions. In this hybrid approach, the two component solvers are mutually coupled in a two-way fashion. Initially, the Lagrangian solver can supply boundary conditions to the Eulerian solver, while the Eulerian solver functions as a corrector for the Lagrangian solution in regions where the latter cannot achieve high accuracy. To utilize such tools effectively, it is vital for them to be capable of handling dynamic mesh movements. This study builds upon the previous research conducted by our team and extends the capabilities of the hybrid solver to handle dynamic meshes. While OpenFOAM, the Eulerian component of this hybrid code, incorporates built-in dynamic mesh properties, certain modifications are necessary to ensure its compatibility with the Lagrangian solver. More specifically, the evolution algorithm of the pimpleFOAM solver needs to be divided into two discrete steps: first, updating the mesh, and later, evolving the solution. This division enables a proper coupling between pimpleFOAM and the Lagrangian solver as an intermediate step. Therefore, the primary objective of this specific paper is to adapt the OpenFOAM solver to meet the demands of the hybrid solver and subsequently validate that the hybrid solver can effectively address dynamic mesh challenges using this approach. This approach introduces a pioneering method for conducting dynamic mesh simulations within the OpenFOAM framework, showcasing its potential for broader applications. To validate the approach, various test cases involving dynamic mesh movements are employed. Specifically, all these cases employ the Lamb–Oseen diffusing vortex, but each case incorporates different types of mesh movements, including translational, rotational, oscillational, and combinations thereof. The results from these cases demonstrate the effectiveness of the proposed OpenFOAM algorithm, with the maximum relative errors —when compared to the analytical solution across all presented cases—capped at 2.0% for the worst-case scenario. This affirms the algorithm’s capability to successfully handle dynamic mesh simulations with the proposed solver.

A multi-region and a multiphase MHD OpenFOAM solver for fusion reactor analysis

Several systems in nuclear fusion reactors utilize liquid metals as working fluids and the design of these systems cannot overlook the magnetohydrodynamics effects arising from the interaction between the electrically conductive fluid and the magnetic fields used to confine the plasma, since these effects significantly influence the flow features. In this context, rigorous studies and research activities are imperative to provide high–quality numerical data and develop precise predictive numerical tools. This work introduces two OpenFOAM magnetohydrodynamics solvers and outlines their respective validation processes. The mMRF solver can simulate single–phase, incompressible MHD flow for multiple electro–coupled domains. Meanwhile, the mIF solver is capable of simulating two–phase MHD flow involving incompressible and immiscible fluids. The mMRF solver has demonstrated outstanding results in simulating classical 2D benchmarks up to high magnetic field intensities, while the mIF solver proved its ability by estimating, with a discrepancy of less than 10%, the velocity of a bubble rising within a liquid metal under an imposed magnetic field.

Validation of High Speed Reactive Flow Solver in OpenFOAM with Detailed Chemistry

An OpenFOAM® based hybrid-central solver called reactingPimpleCentralFoam is validated to compute hydrogen-based detonations. This solver is a pressure-based semi-implicit compressible flow solver based on central-upwind schemes of Kurganov and Tadmor. This solver possesses the features of standard OpenFOAM® solvers namely, rhoCentralFoam, reactingFoam and pimpleFoam. The solver utilizes Kurganov & Tadmor schemes for flux splitting to solve the high-speed compressible regimes with/without hydrodynamic discontinuity. In this work, we present the validation results that were obtained from one-dimensional (1D) and two-dimensional (2D) simulations with detailed chemistry. We consider three different mixtures that fall into the categories of weakly unstable mixture (2H2 +O2 +3.76Ar and 2H2 +O2 +10Ar), and moderately unstable mixture (2H2 +O2 +3.76N2), based on their approximate effective activation energy. We performed the numerical simulations in both laboratory frame of reference (LFR) and shock-attached frame of reference (SFR) for the 1D cases. The 1D simulation results obtained using this solver agree well with the steady-state calculations of Zel’dovich von Neumann Döring (ZND) simulations with an average error below 1% in all cases. For the 2D simulations, circular hot-spots were used to perturb the initially-planar detonations to develop into spatio-temporally unstable detonation front. The convergence is declared when the front does not deviate much from the CJ speed (Chapman-Jouguet) and the regularity of cellular pattern on the numerical smoke foils reaches a steady state. We have verified from our preliminary studies that the SFR-based simulations are computationally cheaper in comparison to the LFR simulations and that the required grid resolution is always lesser in the former than the latter to reach the same level of accuracy (in terms of speed of the detonation front and cell sizes from the numerical smoke foil). We have also verified that at least 24 points per induction zone length (for weakly unstable mixture) and 40 points per induction zone length (for moderately unstable mixture) are required to sufficiently resolve the detonation structures that are independent of grids, boundary and initial conditions. Further reduction in computational cost of approximately 50% is achieved by using non-uniform grids, which converge effectively to the same solutions in comparison to the results from twice the number of grids with uniform resolution.

Oscillatory dynamics of discrete reaction-zones for hydrogen–oxygen diffusion flames within a narrow channel

A diffusion flame in the fuel-oxidizer mixing layer within a narrow channel can be split into several stationary, discrete flame segments at some particular conditions. This unique flame structure has deeply been analyzed in previous literature. In this paper, by performing numerical simulations using a transient, low-Mach number, reacting flow solver in OpenFOAM, unsteady dynamics of separated reaction zones for low Lewis number, hydrogen–oxygen diffusion flames in a 30 × 5 × 0.75 mm3 microchannel are newly discovered. For a variety of inflow rates (H2/O2 flow rate of 300/150, 200/100, and 100/50 sccm) and wall temperatures (Tw = 900, 800, 700, 600, and 500 K) investigated, stable and continuous flame sheets can only be witnessed at large Reynolds numbers or high wall temperatures. Flames at other conditions are found in a discrete form, presenting an unstable and repetitive feature. Specifically, in the wake of the leading, anchored diffusion flame, edge flames with tribrachial structures are consecutively established and then propagate downstream, while eventually end by moving out of the channel, or being extinguished halfway, or behaving in a mixed mode (the two events occur alternately for two successively generated edge flames). Effects of Lewis numbers on flame behaviors are also studied via helium addition to both the fuel and oxidizer stream. Isolated reaction zones at a steady state can be witnessed for a relatively large Lewis number under a high level of addition.

High-Order Spectral Irregular Wave Generation Procedure in Experimental and Computational Fluid Dynamics Numerical Wave Tanks, with Application in a Physical Wave Tank and in Open-Source Field Operation and Manipulation

The accurate generation of a target sea state in numerical or experimental wave tanks is a fundamental line of research for the ocean engineering community. It guarantees the quality and relevance of wave–structure interaction tests. This study presents a reproducible irregular wave generation and qualification procedure, accounting for the nonlinear aspects of wave propagation. It can be used for both numerical simulation and experiments. The presented numerical and experimental results are obtained from the OpenFOAM solver and the Ecole Centrale Nantes wave tank facilities, respectively. The procedure comprises two steps: First, the wavemaker motion is calibrated numerically to generate the target wave spectrum at the position of interest. This is achieved with a wavemaker-equipped nonlinear potential flow solver. The open-source HOS-NWT solver, based on the high-order spectral method, was employed in this study. Then, the corrected wavemaker motion is used directly in the experimental wave tank. OpenFOAM simulations were performed to generate waves with the relaxation method, using wave elevation and velocity field data from HOS-NWT. The procedure was finally tested for mild and extreme breaking sea states. The waves generated by the HOS-NWT solver, the experiment, and the OpenFOAM simulation were compared from both stochastic and deterministic perspectives.

Implementation and Validation of Explicit Immersed Boundary Method and Lattice Boltzmann Flux Solver in OpenFOAM

In this work, the explicit boundary-condition-enforced immersed boundary method (EIBM) and the lattice Boltzmann flux solver (LBFS) are integrated into OpenFOAM to efficiently solve incompressible flows with complex geometries and moving boundaries. The EIBM applies the explicit technique to greatly improve the computational efficiency of the original boundary-condition-enforced immersed boundary method. In addition, the improved EIBM inherits the accurate interpretation of the no-slip boundary condition and the simple implementation from the original one. The LBFS uses the finite volume method to discretize the recovered macroscopic governing equations from the lattice Boltzmann equation. It enjoys the explicit relationship between the pressure and density, which avoids solving the pressure Poisson equation and thus saves much computational cost. Another attractive feature of the LBFS lies in its simultaneous evaluation of the inviscid and viscous fluxes. OpenFOAM, as an open-source CFD platform, has drawn increasing attention from the CFD community and has been proven to be a powerful tool for various problems. Thus, implementing the EIBM and LBFS into such a popular platform can advance the practical application of these two methods and may provide an effective alternative for complicated incompressible flow problems. The performance of the integrated solver in OpenFOAM is comprehensively assessed by comparing it with the widely used numerical solver in OpenFOAM, namely, the Pressure-Implicit with Splitting of Operators (PISO) algorithm with the IBM. A series of representative test cases with stationary and moving boundaries are simulated. Numerical results confirm that the present method does not have any streamline penetration and achieves the second-order accuracy in space. Therefore, the present method implemented in the open-source platform OpenFOAM may have good potential and can serve as a powerful tool for practical engineering problems.

Multi-objective topology optimization of heat transfer surface using level-set method and adaptive mesh refinement in OpenFOAM

The present study proposes a new efficient and robust algorithm for multi-objectives topology optimization of heat transfer surfaces to achieve heat transfer enhancement with a less pressure drop penalty based on a continuous adjoint approach. It is achieved with a customized OpenFOAM solver, which is based on a volume penalization method for solving a steady and laminar flow around iso-thermal solid objects with arbitrary geometries. The fluid-solid interface is captured by a level-set function combined with a newly proposed robust reinitialization scheme ensuring that the interface diffusion is always kept within a single local grid spacing. Adaptive mesh refinement is applied in near-wall regions automatically detected by the level-set function to keep high resolution locally, thereby reduces the overall computational cost for the forward and adjoint analyses. The developed solver is first validated in a drag reduction problem of a flow around a two-dimensional cylinder at the Reynolds numbers of 10 and 40 by comparing reference data. Then, the proposed scheme is extended to heat transfer problems in a two-dimensional flow at the Prandtl number of 0.7 and 6.9. Finally, three-dimensional topology optimization for multi-objective problems is considered for cost functionals with different weights for the total drag and heat transfer. Among various solutions obtained on the Pareto front, 4.0% of heat transfer enhancement with 12.6% drag reduction is achieved at the Reynolds number of 10 and the Prandtl number of 6.9. Moreover, the optimization of a staggered pin-fin array demonstrates that the optimal shapes and arrangement of the fins strongly depend on the number of rows from the inlet. Specifically, the pin-fins in the first and third rows extended in the upstream direction further enhance heat transfer, while the fins in the second row vanish to reduce pressure loss.

Effects of Premixed and Diffusion Conditions on the Iso-Octane/ammonia and Iso-Octane/ethanol Flames

ABSTRACT The combustion engines fueled by liquid hydrocarbon fuel significantly release emissions such as CO, CO2, and soot. Renewable fuels such as zero-carbon fuel and biofuel mitigate these emissions of IC engines when used with liquid hydrocarbon fuel. Previously, ammonia and ethanol were used in IC engines and also studied fundamentally, but these fuels were tested separately. In the current study, a comparative effect of these renewable fuels on the emission characteristics of hydrocarbon fuel was made on premixed and diffusion flame conditions. A kinetic mechanism was prepared by adding the sub-mechanisms of ammonia combustion, soot precursors formation and nitrogen oxide emissions to the detailed mechanism of iso-octane flame. The combustion conditions of premixed flow flame, counterflow flame and coflow flame were adopted. The Arrhenius model with soot surface reaction pathways was used in the premixed flow flame and counterflow flame analysis. The Moss-Brooke model with soot surface reaction pathways was added in OpenFOAM Solver to study the soot formation in normal and inverse coflow flames. The results tell that a higher reduction in peak combustion temperature was observed in premixed flame instead of diffusion flame thanks to alternative fuels. Ethanol greatly reduced the peak temperature of the premixed flame rather than ammonia. The impact of carbon-free fuel on total reduction in CO and CO2 emissions was higher than that of biofuel at premixed and diffusion flame conditions. Ethanol impact on total reduction in benzene formation was stronger than ammonia at premixed and normal coflow flames. Pyrene was reduced highly by ammonia rather than ethanol at diffusion flame conditions. The study suggests that biofuel can be used from 0% to 90% in iso-octane fuel, and better results may be achieved when its fraction is ≥ 70%. In contrast, the use of ammonia with iso-octane may be better if its fraction is < 70% because a higher reduction in burning velocity will occur with higher NO2 emissions at NH3 ≥70%.

Unsteady conjugate heat transfer simulation of wall heat loads for rotating detonation combustor

Rotating detonation engines (RDEs) are the most promising pressure-gain combustion devices, but their long-duration operations are hindered by the harsh thermal environment inside the chamber. This study analyzes the instantaneous and average heat loads on chamber walls of RDEs based on the newly developed unsteady conjugate heat transfer (CHT) OpenFOAM solver named multiRegionBYRFoam. To enhance accuracy in predicting heat transfer characteristics compared to decoupled simulations focusing solely on fluid or solid behavior, three-dimensional CHT simulations are conducted for a premixed H2/air annular RDE coupling the detonation simulation with heat conduction in both inner and outer chamber walls. The transient time evolutions of wall heat flux in RDEs are numerically captured for the first time and agree well with experiments. The calculated peak wall heat flux is 1.98 MW/m2 at the inner wall and 2.63 MW/m2 at the outer wall when a single detonation wave propagates with a mass flow rate of 0.227 kg/s. By investigating the influence of inlet flow conditions and detonation modes, valuable guidelines on designing efficient thermal management systems for RDEs are obtained: larger mass flow rates and multi-wave modes result in higher average wall heat flux; the heat flux at the outer wall exceeds that at the inner wall while both walls require effective cooling for gas turbine engines with a rotating detonation combustor. Furthermore, a novel heat transfer model for RDEs is proposed based on a thermal operation map depicting total heat transfer rates to describe the nonlinear impact of mass flow rate and number of detonation waves, which can be employed to predict total wall heat loads under specific operation conditions of RDE.

Numerical investigation of combustion instability in a liquid rocket engine: Interaction effect between hydrodynamics and acoustic mode

In this paper, we present the numerical evidence of multiple bifurcations in thermoacoustic instability as we decrease the equivalence ratio (ϕ) from fuel-rich (ϕ = 1.5) to fuel-lean (ϕ =0.59) within a single-element coaxial liquid rocket engine burning hydrogen peroxide and methane. An axisymmetric compressible Large Eddy Simulation solver in an open-source platform OpenFOAM combined with a global methane chemical kinetical mechanism was used to model the turbulent mixing and combustion process. After the validation of grid independence and simulation results, the synchronization phenomenon between hydrodynamic instability, acoustics and combustion is the main focus of this paper. The results here first revealed that in a direction of decreasing equivalence ratios, the first transition to limit cycle state from combustion noise state was observed via intermittency. A second bifurcation was also observed, leading to quasi-period thermoacoustic instability from the limit cycle state. Intrinsic vorticity modes and natural acoustic modes could be regarded as oscillators. The competition and cooperation between the two modes led to a phenomenon beyond limit cycle states. The vortex dynamics of thermoacoustic systems are dominated by the interaction of intrinsic vorticity modes and natural acoustic modes and exhibit an adjustment of vortex shedding frequencies, resulting in different stability regions. Herein, the flame index was performed in more detail to distinguish between the premixed flame and diffusion flame. Results indicated that the burning mode was an important driver in promoting instability whilst it also served as a medium for competition and cooperation between the natural acoustic modes and intrinsic vorticity modes.

Hydrodynamics of a cold circulating fluidized bed for methanol-to-olefins (MTO) process: experimental and computational investigation

The present study aims to investigate the hydrodynamic behavior of gas–solid flow in a pseudo-two-dimensional cold circulation fluidized bed specifically designed to mimic a plane cut of an industrial methanol-to-olefins (MTO) bed. The solid velocity pattern was experimentally examined using the Particle Image Velocimetry with Digital Image Analysis (PIV-DIA) technique. The hydrodynamics of this pseudo-2D bed were studied using the twoPhaseEulerFoam solver in OpenFOAM, and the adjusted solver was validated through solid particle velocity and solid volume fraction comparisons, showing good agreement with experimental data. Additionally, the study explores different geometries, including symmetric and asymmetric baffles, to understand their impact on the mixing characteristics of the circulating fluidized bed for MTO. The findings highlight the significant role of asymmetric baffles in enhancing mixing behavior. Furthermore, the DIA technique was employed to study the effects of bubbles on gas–solid mixing, revealing that the low mixing region of the bed limited the diameter of bubbles.

Investigating aerodynamics of a 3D blade in rainy conditions: Application of hybrid superhydrophobic-hydrophilic surfaces

In the realm of wind turbine blade design, it is essential to consider the impacts of real-world environmental conditions. Among these, rain stands out as an unpredictable natural phenomenon, with its intensity varying based on environmental factors. This study delves into the aerodynamic effects of different rain intensities on a three-dimensional wind turbine blade—a crucial investigation since rain can influence both the efficiency of energy capture and operational safety. A custom OpenFoam solver was employed for numerical analysis, and its accuracy was first verified by contrasting simulation outcomes with experimental results. Our findings reveal that while the critical angle of attack is 14° in dry conditions, it increases to 17° under the influence of rain. When maintaining a constant angle of attack, rainy conditions result in a lowered lift coefficient and a heightened drag coefficient. Significantly, the thickness of the boundary layer and the presence of a separation bubble are deeply affected by rain intensity. During heavy rainfall, the boundary layer's thickness can diminish by up to six times compared to dry scenarios. Towards the study's conclusion, blades were integrated with hybrid superhydrophobic-hydrophilic surfaces to enhance aerodynamics during rainfall. Data suggests that these surface alterations effectively regulate the boundary layer's thickness and manage the flow separation zone, ultimately boosting the blade's aerodynamic efficiency in wet conditions. These findings set the stage for subsequent research focused on developing blade designs responsive to the ever-fluctuating environmental dynamics.

A novel diffusion flux modeling for laminar premixed flame simulation with OpenFOAM

In this study, we developed a mass diffusion coefficient model for premixed combustion to reduce the computational time, in mixture-averaged diffusivities to serve as a microcomputer resource. In the development, a preliminary theory was derived to construct the associated variables and corrected using a benchmark model as the mixture-averaged model based on Chapman–Enskog binary diffusion. In the validation, the calculation results obtained using the proposed model with a benchmark case, regardless of thermal diffusion and for several fuels at various pressures, temperatures, and initial mixture compositions, showed good agreement. Validation was also performed with the two-dimensional premixed and partially premixed combustion models by implementing the novel diffusion coefficient model in OpenFOAM software. The OpenFOAM solver results were in good agreement with the experimental results. This solver showed good simulation performance at both micro and macro scales. In addition, the processing time was reduced by approximately 70% in all the simulated premixed flame models. Based on these findings, we conclude that the developed model allows researchers to work with more complex premixed combustion modeling with less computational time.

Bayesian Optimization of Wall-Normal Blowing and Suction-Based Flow Control of a NACA 4412 Wing Profile

Active flow-control techniques have shown promise for achieving high levels of drag reduction. However, these techniques are often complex and involve multiple tunable parameters, making it challenging to optimize their efficiency. Here, we present a Bayesian optimization (BO) approach based on Gaussian process regression to optimize a wall-normal blowing and suction control scheme for a NACA 4412 wing profile at two angles of attack: 5 and 11 ∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ$$\\end{document}, corresponding to cruise and high-lift scenarios, respectively. An automated framework is developed by linking the BO code to the CFD solver OpenFOAM. RANS simulations (validated against high-fidelity LES and experimental data) are used in order to evaluate the different flow cases. BO is shown to provide rapid convergence towards a global maximum, even when the complexity of the response function is increased by introducing a model for the cost of the flow control actuation. The importance of considering the actuation cost is highlighted: while some cases yield a net drag reduction (NDR), they may result in an overall power increase. Furthermore, optimizing for NDR or net power reduction (NPR) can lead to significantly different actuation strategies. Finally, by considering losses and efficiencies representative of real-world applications, still a significant NPR is achieved in the 11∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ$$\\end{document} case, while net power reduction is only marginally positive in the 5∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ$$\\end{document} case.

Comparison of Actuator Line Modelling of Tidal Power Kites with ADCP Measurements

The potential for tidal energy to be a part of future renewable energy systems is expanding. Tidal turbines deployed in open waters or channels are effective methods to harness energy from tidal currents. Sharing similar functionality with wind turbines, horizontally mounted tidal turbines require a minimum tidal current velocity to operate effectively. The Deep Green (DG) power plant which is based on a tethered kite model aims, however, to operate efficiently in tidal current velocities as low as 1.2 m/s. The kite wing is steered in a lemniscate trajectory ( ) almost perpendicular to the tidal current. In the trajectory, the relative flow velocity through the turbine attached to the wing reaches several times the tidal current velocity, enabling efficient operation of the turbine in relatively low-velocity tidal currents. This could reduce geographical limitations in installing large-scale tidal power arrays.&#x0D; In a previous project, numerical modelling of the DG was carried out in a tidal flow using Large Eddy Simulations (LES) and Actuator Line Modelling (ALM) implemented in OpenFOAM solver. ALM using momentum sources has been used in modelling wind turbines and has been validated against experimental data and observations. The ALM has been further developed in order to be able to model wings (here the kite) that move in arbitrary paths compared to horizontally mounted turbines with rotational paths. This numerical model for the DG kite in a tidal flow has, however, up to now not been validated against observations, which is beneficial before further analyses are made, e.g., optimization studies.&#x0D; In this study, Acoustic Doppler Current Profiler (ADCP) observations taken in the wake of a DG are compared to the results from the numerical model under similar conditions. Comparing the numerical results directly with the observations leads to discrepancies, hence the model data is resampled in a similar way that the ADCP would measure and process data using a virtual ADCP for the model. Flow properties such as the instantaneous and time-averaged stream velocities are in turn compared for both the tidal flow without the DG and with a DG. The effect of the DG on the tidal flow is analysed using the model and the observations. After resampling the model data, the model and observations show good agreement. This suggests 1) that the DG model using ALM can be used for further analysis and 2) that whilst comparing model data with ADCP observations for studying the small-scale effects of tidal turbine wakes, care should be taken to sample the model data consistently with observations.

Immersed-boundary/soft-sphere method for particle–particle-fluid interaction in a viscous flow: An OpenFOAM solver

We developed a stable OpenFOAM solver for Immersed Boundary Method based on direct forcing and regularized delta function. The soft-sphere model and a lubrication model were implemented to consider particle–particle collision in a viscous flow. We proposed a fluid–structure interaction (FSI) coupling method to accurately calculate the fluid forcing term and particle velocity. Our solver was validated for fixed and moving bodies, including rotation. The accuracy of various FSI schemes was evaluated in predicting the solid and fluid flow behavior in a viscous flow. It was demonstrated that neglecting or simplifying the fluid momentum change affects the accuracy of the solid velocity and fluid flow dynamic; for higher solid-to-fluid density ratios, a larger deviation was predicted. Furthermore, the FSI schemes highly influenced the behavior of the formed vortices.The solver was validated to predict the effective restitution coefficient of particles in a viscous flow as a function of the Stokes number. We also thoroughly analyzed the dynamic flow behavior of colliding particles through the pressure and velocity field and fluid force. This analysis helped us accurately determine the rebound velocity of particles in case of high Stokes numbers when the effect of viscous force is significant.

Cooling a cavity equipped with a hot electrical element using nano-encapsulated phase change material /water: Study of mixed convection and natural convection

According to phase change materials (PCMs) operate at their phase change temperature, they can store a lot of latent heat energy without changing the temperature, so these materials are widely used in thermal storage tanks. The direct use of PCMs is not possible in all systems, therefore encapsulation of PCMs has been suggested by researchers. In the present work, the thermal performance of the natural and mixed convection flow inside a nested cylinder with a hot electrical element is investigated. Nano-encapsulated phase change material (PCMs) are mixed with the water-based fluid. Also, the effects of forced convection due to inner cylinder rotation along with natural convection are studied. Fluid flow, temperature distribution, melting zone of PCM nanocapsules, Nusselt numbers, and thermal performance are simulated using computational fluid dynamics by developing OpenFOAM solvers using C++ code. The governing PDE equations are solved in the FVM method and solved using the SIMPLE algorithm. The simulations are modeled for different Ra numbers (102−104), Reynolds numbers (0–20), and θf values. θf values correspond to the dimensionless melting temperature of the core of nanocapsules. This number depends on the temperature of the cold and hot sources and the phase change temperature of the core of NEPCMs. Based on the results, it is showed that there is an optimal number for θf, which is in the range of 0.3–0.5 in the lower Ra numbers (102), and θf=0.5 at upper Ra numbers (104). In the case of dominant conduction heat transfer mechanism, the presence of nanocapsules did not affect heat transfer. However, at a high Ra number, it was able to enhance Nusselt number by up to 13%. Also, at high Ra numbers (104), the rotation of the inner cylinder does not help to improve heat transfer.

Influence of Van Gent Parameters on the Overtopping Discharge of a Rubble Mound Breakwater

The choice of the values of the friction parameters may strongly influence the numerical modeling of the interaction between waves and porous media. Here, an assessment of such an influence is carried out using the OpenFOAM solver IhFoamV1 to simulate the response of the Catania harbor breakwater under extreme wave attack. The numerical model was validated by comparison with an experimental dataset, and a sensitivity analysis of the overtopping discharge estimate to van Gent parameter β was carried out testing values suggested by previous studies. A discussion on the importance of a careful estimate of such a parameter when dealing with the numerical modeling of porous coastal structures is presented. Indeed, variations in the non-dimensional overtopping discharge higher than 150% were observed as a consequence of a small variation (10–20%) in the absolute value of β.