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The purpose of this paper is the examination of fluid flow around NACA0012 airfoil, with the aim of the numerical validation between the experimental results in the wind tunnel and the Lattice Boltzmann method (LBM) analysis, for the medium Reynolds number (Re = 191,000). The LBM–large Eddy simulation (LES) method described in this paper opens up opportunities for faster computational fluid dynamics (CFD) analysis, because of the LBM scalability on high performance computing architectures, more specifically general purpose graphics processing units (GPGPUs), pertaining at the same time the high resolution LES approach.

Process starts with data collection in open-circuit wind tunnel experiment. Furthermore, the pressure coefficient, as a comparative variable, has been used with varying angle of attack (2°, 4°, 6° and 8°) for both experiment and LBM analysis. To numerically reproduce the experimental results, the LBM coupled with the LES turbulence model, the generalized wall function (GWF) and the cumulant collision operator with D3Q27 velocity set has been used. Also, a mesh independence study has been provided to ensure result congruence.

The proposed LBM methodology is capable of highly accurate predictions when compared with experimental data. Besides, the special significance of this work is the possibility of experimental and CFD comparison for the same domain dimensions.

Considering the quality of results, root-mean-square error (RMSE) shows good correlations both for airfoil’s upper and lower surface. More precisely, maximal RMSE for the upper surface is 0.105, whereas 0.089 for the lower surface, regarding all angles of attack.

This study aims at investigating two-dimensional laminar flow of power-law fluids around three unconfined side-by-side cylinders.

The numerical study is performed by solving the governing (continuity and momentum) equations using a finite volume-based code ANSYS Fluent. The numerical results have been presented for different combinations of the governing dimensionless parameters (dimensionless spacing, 1.2 = L = 4; Reynolds number, 0.1 = Re = 100; power-law index, 0.2 = n = 1.8). The dependence of the kinematic and macroscopic characteristics of the flow such as streamline patterns, distribution of the surface pressure coefficient, total drag coefficient with its components (pressure and friction) and total lift coefficient on these dimensionless parameters has been discussed in detail.

It is found that the separation of the flow and the apparition of the wake region accelerate as the dimensionless spacing decreases, the number of the cylinder increases and/or the fluid behavior moves from shear-thinning to Newtonian then to shear-thickening behavior. In addition, the distribution of the pressure coefficient on the surface of the cylinders presents a complex dependence on the fluid behavior index and Reynolds number when the dimensionless spacing between two adjacent cylinders is varied. At low Reynolds numbers, the drag coefficient of shear-thinning fluids is stronger than that of Newtonian fluids; this tendency decreases progressively with increasing of Re until a critical value; beyond the critical Re, the opposite trend is observed. The lift coefficient of the middle cylinder is null, whereas, the exterior cylinders experience opposite lift coefficients, which show a complex dependence on the dimensionless spacing, the Reynolds number and the power-law index.

The flow over bluff bodies is a practical engineering problem. In the literature, it can be seen that the previous studies on non-Newtonian fluids are limited to the flow over one or two cylinders (effect of an odd number of cylinders on each other). Besides that, the available results concerning the flow of Newtonian fluids over three cylinders are limited to the high Reynolds numbers region only. However, this work treats the flow of non-Newtonian power-law fluids past three circular cylinders in side-by-side arrangements under a wide range of Re. The outcome of the present study demonstrates that the augmentation of the geometry complexity to three cylinders (effect of pair surrounding cylinders on the surrounded ones in what concerns Von Karman Street phenomenon) causes a drastic change in the flow patterns and in the macroscopic characteristics. The present results may be used to predict the flow behavior around multiple side-by-side cylinders.

The paper aims to expand the scope of application of the lattice Boltzmann method (LBM), especially in the field of aircraft engineering. The traditional LBM is usually applied to incompressible flows at a low Reynolds number, which is not sufficient to satisfy the needs of aircraft engineering. Devoted to tackling the defect, the paper proposes a developed LBM combining the subgrid model and the multiple relaxation time (MRT) approach. A multilayer adaptive Cartesian grid method to improve the computing efficiency of the traditional LBM is also employed.

The subgrid model and the multilayer adaptive Cartesian grid are introduced into MRT-LBM for simulations of incompressible flows at a high Reynolds number. Validated by several typical flow simulations, the numerical methods in this paper can efficiently study the flows under high Reynolds numbers.

Some numerical simulations for the lid-driven flow of cavity, flow around iced GLC305, LB606b and ONERA-M6 are completed. The paper presents the investigation results, indicating that the methods are accurate and effective for the separated flow after icing.

LBM is developed with the addition of the subgrid model and the MRT method. A numerical strategy is proposed using a multilayer adaptive Cartesian grid method and its treatment of boundary conditions. The paper refers to innovative algorithm developments and applications to the aircraft engineering, especially for iced wing simulations with flow separations.

In general, the existing compressor design methods require abundant knowledge and inspiration. The purpose of this study is to identify an intellectual design optimization method that enables a machine to learn how to design it.

The airfoil design process was solved using the reinforcement learning (RL) method. An intellectual method based on a modified deep deterministic policy gradient (DDPG) algorithm was implemented. The new method was applied to agents to learn the design policy under dynamic constraints. The agents explored the design space with the help of a surrogate model and airfoil parameterization.

The agents successfully learned to design the airfoils. The loss coefficients of a controlled diffusion airfoil improved by 1.25% and 3.23% in the two- and four-dimensional design spaces, respectively. The agents successfully learned to design under various constraints. Additionally, the modified DDPG method was compared with a genetic algorithm optimizer, verifying that the former was one to two orders of magnitude faster in policy searching. The NACA65 airfoil was redesigned to verify the generalization.

It is feasible to consider the compressor design as an RL problem. Trained agents can determine and record the design policy and adapt it to different initiations and dynamic constraints. More intelligence is demonstrated than when traditional optimization methods are used. This methodology represents a new, small step toward the intelligent design of compressors.

Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural network (PINN), which was proposed to encode physical laws into neural networks, is a less data-demanding approach for flow field reconstruction. However, when the fluid physics is complex, it is tricky to obtain accurate solutions under the PINN framework. This study aims to propose a physics-based data-driven approach for time-averaged flow field reconstruction which can overcome the hurdles of the above methods.

A multifidelity strategy leveraging PINN and a nonlinear information fusion (NIF) algorithm is proposed. Plentiful low-fidelity data are generated from the predictions of a PINN which is constructed purely using Reynold-averaged Navier–Stokes equations, while sparse high-fidelity data are obtained by field or experimental measurements. The NIF algorithm is performed to elicit a multifidelity model, which blends the nonlinear cross-correlation information between low- and high-fidelity data.

Two experimental cases are used to verify the capability and efficacy of the proposed strategy through comparison with other widely used strategies. It is revealed that the missing flow information within the whole computational domain can be favorably recovered by the proposed multifidelity strategy with use of sparse measurement/experimental data. The elicited multifidelity model inherits the underlying physics inherent in low-fidelity PINN predictions and rectifies the low-fidelity predictions over the whole computational domain. The proposed strategy is much superior to other contrastive strategies in terms of the accuracy of reconstruction.

In this study, a physics-informed data-driven strategy for time-averaged flow field reconstruction is proposed which extends the applicability of the PINN framework. In addition, embedding physical laws when training the multifidelity model leads to less data demand for model development compared to purely data-driven methods for flow field reconstruction.

This study aims to develop an experimentally validated three-dimensional numerical model for predicting different flow patterns produced with a gas dynamic virtual nozzle (GDVN).

The physical model is posed in the mixture formulation and copes with the unsteady, incompressible, isothermal, Newtonian, low turbulent two-phase flow. The computational fluid dynamics numerical solution is based on the half-space finite volume discretisation. The geo-reconstruct volume-of-fluid scheme tracks the interphase boundary between the gas and the liquid. To ensure numerical stability in the transition regime and adequately account for turbulent behaviour, the k-ω shear stress transport turbulence model is used. The model is validated by comparison with the experimental measurements on a vertical, downward-positioned GDVN configuration. Three different combinations of air and water volumetric flow rates have been solved numerically in the range of Reynolds numbers for airflow 1,009–2,596 and water 61–133, respectively, at Weber numbers 1.2–6.2.

The half-space symmetry allows the numerical reconstruction of the dripping, jetting and indication of the whipping mode. The kinetic energy transfer from the gas to the liquid is analysed, and locations with locally increased gas kinetic energy are observed. The calculated jet shapes reasonably well match the experimentally obtained high-speed camera videos.

The model is used for the virtual studies of new GDVN nozzle designs and optimisation of their operation.

To the best of the authors’ knowledge, the developed model numerically reconstructs all three GDVN flow regimes for the first time.

The rapid growth in cruise shipping coupled with increasing public awareness of climate change has led to increasing concerns about the impact cruise shipping poses on the environment, especially regarding air emissions. This study analyses the cruise shipping network of ports in and around the emission control areas (ECAs) to understand the structural properties of the network and ports.

A complex network approach was used to analyse the network data of 239 voyages serviced by 14 international cruise lines, visiting 127 ports across 44 countries in the Caribbean Sea.

It is found that the network has a small-world property with a short average path length and a high clustering coefficient. The regulations affect connections among ports, in which most ports in ECAs have lower connections than ports outside ECAs. A few ports in ECAs play important key roles, but many ports outside ECAs play a more important role in the network because the regulations are barriers for cruise ships entering the ports.

The findings of this study have drawn useful guidelines for cruise lines and port authorities to improve their operations. Constrictive recommendations are suggested to policymakers for designing reasonable regulations to attract more cruise shipping to travel in ECAs.

A few earlier studies presented infeasible heatline trajectories for natural convection within annular domains involving an inner circular cylinder and outer square/circular enclosure. The purpose of this paper is to revisit and illustrate the correct heatline trajectories for various test cases.

Galerkin finite element based methodology and space adaptive grid have been used to simulate natural convective flows within the annular domains. The prediction of heatlines involves derivatives at the nodes, which are evaluated based on finite element basis functions and contributions from neighboring elements.

The heatlines in the earlier work indicate infeasible heat flow paths such as heat flow from one portion to the other of isothermal hot walls and heat flow across the adiabatic walls. Current results illustrate physically consistent heat flow paths involving perpendicularly emerging heatlines from hot to cold walls for conductive transport, long heat flow paths around the closed-loop heatline cells for convective transport and parallel layout of heatlines to the adiabatic walls. Results also demonstrate complex heatlines involving multiple flow vortices and complex flow structures.

Current work translates heatfunctions from energy flux vectors, which are determined by using basis sets. This work demonstrates the expected heatline trajectories for various scenarios involving conductive and convective heat transport within enclosures with an inner hot object as a first attempt, and the results are precursors for the understanding of energy flow estimates.

The purpose of this study is to address the issue that the traditional V-shaped ball valve profile shape is limiting the flow control characteristics in a series structure and to optimize the design profile by proposing an open-hole profile.

This paper proposes a Gaussian process regression surrogate model based on the genetic algorithm optimization of swarm intelligence, combined with the Expected Improvement point addition criterion, to optimize and correct the design profile. The flow regulation performance of the optimized V-shaped regulating ball valve is verified through a combination of numerical simulation and experiment.

The results demonstrate that the optimized V-shaped regulating ball valve has higher flow regulation accuracy and a more stable flow regulation process. After optimization, the flow characteristic curve of the spool is closer to the ideal equal percentage characteristic. The simulation results of the flow field are consistent with the experimental results.

The proposed method significantly reduces the optimization time, has higher efficiency and solves the problem that traditional optimization methods struggle with, which is ensuring optimal flow regulation performance. Compared to the traditional trial-and-error optimization method, the proposed method is more effective. The feasibility of the method is supported by experimental results.

The research focused on analysing a unique type of heat exchanger that uses swirling air flow over heated tubes. This heat exchanger includes a round baffle plate with holes and opposite-oriented trapezoidal air deflectors attached at different angles. The deflectors are spaced at various distances, and the tubes are arranged in a circular pattern while maintaining a constant heat flux.

This setup is housed inside a circular duct with airflow in the longitudinal direction. The study examined the impact of different inclination angles and pitch ratios on the performance of the heat exchanger within a specific range of Reynolds numbers.

The findings revealed that the angle of inclination significantly affected the flow velocity, with higher angles resulting in increased velocity. The heat transfer performance was best at lower inclination angles and pitch ratios. Flow resistance decreased with increasing angle of inclination and pitch ratio.

The average thermal enhancement factor decreased with higher inclination angles, with the maximum value observed as 0.94 at a pitch ratio of 1 at an angle of 30°.