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The purpose of this paper is to study the predictability of the recently proposed length scale-based two-equation k-kL model for external aerodynamic flows such as those also encountered in the high-lift devices.

The two-equation k-kL model solves the transport equations of turbulent kinetic energy (TKE) and the product of TKE and the integral length scale to obtain the effect of turbulence on the mean flow field. In theory, the use of governing equation for length scale (kL) along with the TKE promises applicability in a wide range of applications in both free-shear and wall-bounded flows with eddy-resolving capability.

The model is implemented in the in-house unstructured grid computational fluid dynamics solver to investigate its performance for airfoils in difficult-to-predict situations, including stalling and separation. The numerical findings show the good capability of the model in handling the complex flow physics in the external aerodynamic computations.

The model performance is studied for stationary turbulent external aerodynamic flows, using five different airfoils, including two multi-element airfoils in high-lift configurations which, in the knowledge of the authors, have not been simulated with k-kL model until now.

This paper aims to investigate numerically the turbulent flow characteristics over a backward facing step. Different turbulence models with hybrid computational grid have been used to study the detached flow structure in this case. Comparison between the numerical results and the available experiment data is carried out in the present study. The results of the different turbulence models were in a good agreement with the experimental results. The numerical results also concluded that the k-kl-ω turbulence model gave favorable results compared with the experiment.

It is very important to study the flow characteristics of detached flows. Therefore, the current study investigates numerically the flow characteristics in backward facing step by using two-, three- and seven-equation turbulence models in the finite volume code ANSYS Fluent. In addition, hybrid grid has been used to improve the capability of the unstructured mesh elements for predicting the flow separation in this case. Comparison between the different turbulence models and the available experimental data was done to find the most suitable turbulence model for simulating such cases of detached flows.

The present numerical simulations with the different turbulence models predicted efficiently the flow characteristics over the backward facing step. The transition k-kl-ω gave the best acceptable results compared with experimental data. This is a good concluded remark in the fields of fluid mechanics and hydrodynamics because the phenomenon of flow separation is not easy to be predicted numerically and can affect greatly on the predicted drag of moving bodies in many engineering applications.

The CFD results of using different turbulence models have been validated with the experimental work, and the results of k-kl-ω proven acceptable with flow characteristics. The results of the current study conclude that the use of k-kl-ω turbulence model will contribute towards a more efficient utilization in the fields of fluid mechanics and hydrodynamics.

The purpose of this study is to present and demonstrate a numerical method for solving chemically reacting flows. These are important for energy conversion devices, which rely on chemical reactions as their operational mechanism, with heat generated from the combustion of the fuel, often gases, being converted to work.

The numerical study of such flows requires the set of Navier-Stokes equations to be extended to include multiple species and the chemical reactions between them. The numerical method implemented in this study also accounts for changes in the material properties because of temperature variations and the process to handle steep spatial fronts and stiff source terms without incurring any numerical instabilities. An all-speed numerical framework is used through simple low-dissipation advection upwind splitting (SLAU) convective scheme, and it has been extended in a multi-component species framework on the in-house density-based flow solver. The capability of solving turbulent combustion is also implemented using the Eddy Dissipation Concept (EDC) framework and the recent k-kl turbulence model.

The numerical implementation has been demonstrated for several stiff problems in laminar and turbulent combustion. The laminar combustion results are compared from the corresponding results from the Cantera library, and the turbulent combustion computations are found to be consistent with the experimental results.

This paper has extended the single gas density-based framework to handle multi-component gaseous mixtures. This paper has demonstrated the capability of the numerical framework for solving non-reacting/reacting laminar and turbulent flow problems. The all-speed SLAU convective scheme has been extended in the multi-component species framework, and the turbulent model k-kl is used for turbulent combustion, which has not been done previously. While the former method provides the capability of solving for low-speed flows using the density-based method, the later is a length-scale-based method that includes scale-adaptive simulation characteristics in the turbulence modeling. The SLAU scheme has proven to work well for unsteady flows while the k-kL model works well in non-stationary turbulent flows. As both these flow features are commonly found in industrially important reacting flows, the convection scheme and the turbulence model together will enhance the numerical predictions of such flows.

This paper aims to conduct, a detailed investigation of various Reynolds averaged Navier–Stokes (RANS) models to study their performance in attached and separated flows. The turbulent flow over two airfoils, namely, National Advisory Committee for Aeronautics (NACA)-0012 and National Aeronautics and Space Administration (NASA) MS(1)-0317 with a static stall setup at a Reynolds number of 6 million, is chosen to investigate these models. The pre-stall and post-stall regions, which are in the range of angles of attack 0°–20°, are simulated.

RANS turbulence models with the Boussinesq approximation are the most commonly used cost-effective models for engineering flows. Four RANS models are considered to predict the static stall of two airfoils: Spalart–Allmaras (SA), Menter’s k – ω shear stress transport (SST), k – kL and SA-Bas Cakmakcioglu modified (BCM) transition model. All the simulations are performed on an in-house unstructured-grid compressible flow solver.

All the turbulence models considered predicted the lift and drag coefficients in good agreement with experimental data for both airfoils in the attached pre-stall region. For the NACA-0012 airfoil, all models except the SA-BCM over-predicted the stall angle by 2°, whereas SA-BCM failed to predict stall. For the NASA MS(1)-0317 airfoil, all models predicted the lift and drag coefficients accurately for attached flow. But the first three models showed even further delayed stall, whereas SA-BCM again did not predict stall.

The numerical results at high Re obtained from this work, especially that of the NASA MS(1)-0317, are new to the literature in the knowledge of the authors. This paper highlights the inability of RANS models to predict the stall phenomenon and suggests a need for improvement in modeling flow physics in near- and post-stall flows.

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.

In recent years, the airfoil sections with blunt trailing edge (called flatback airfoils) have been proposed for the inboard regions of large wind‐turbine blades because they provide several structural and aerodynamic performance advantages. The purpose of this paper is to optimize the shape of these airfoils for optimal performance using a multi‐objective genetic algorithm.

A multi‐objective genetic algorithm is employed for shape optimization of flatback airfoils to achieve two objectives, namely the generation of maximum lift as well as the maximum lift to drag ratio. The commercially available software FLUENT is employed for calculation of the flow field using the Reynolds‐Averaged Navier‐Stokes (RANS) equations in conjunction with a two‐equation Shear Stress Transport (SST) turbulence model and a three‐equation k‐kl‐ω turbulence model.

It is shown that the multi‐objective genetic algorithm based optimization can generate superior flatback airfoils compared to those obtained by using a single objective genetic algorithm.

The method of employing genetic algorithms for shape optimization of flatback airfoils could be considered as an excellent example for the optimization of other types of wind turbine blades such as DU FX and S series airfoils.

This paper is the first to employ the multi‐objective genetic algorithm for shape optimization of flatback airfoils for wind‐turbine blades to achieve superior performance.

The Reynolds-averaged Navier–Stokes (RANS) equations represent the computational workhorse for engineering design, despite their numerous flaws. Improving and quantifying the uncertainties associated with RANS models is particularly critical in view of the analysis and optimization of complex turbomachinery flows.

First, an efficient strategy is introduced for calibrating turbulence model coefficients from high-fidelity data. The results are highly sensitive to the flow configuration (called a calibration scenario) used to inform the coefficients. Second, the bias introduced by the choice of a specific turbulence model is reduced by constructing a mixture model by means of Bayesian model-scenario averaging (BMSA). The BMSA model makes predictions of flows not included in the calibration scenarios as a probability-weighted average of a set of competing turbulence models, each supplemented with multiple sets of closure coefficients inferred from alternative calibration scenarios.

Different choices for the scenario probabilities are assessed for the prediction of the NACA65 V103 cascade at off-design conditions. In all cases, BMSA improves the solution accuracy with respect to the baseline turbulence models, and the estimated uncertainty intervals encompass reasonably well the reference data. The BMSA results were found to be little sensitive to the user-defined scenario-weighting criterion, both in terms of average prediction and of estimated confidence intervals.

A delicate step in the BMSA is the selection of suitable scenario-weighting criteria, i.e. suitable prior probability mass functions (PMFs) for the calibration scenarios. The role of such PMFs is to assign higher probability to calibration scenarios more likely to provide an accurate estimate of model coefficients for the new flow. In this paper, three mixture models are constructed, based on alternative choices of the scenario probabilities. The authors then compare the capabilities of three different criteria.

A theoretical study is performed to investigate transport phenomena in channel flows under uniform heating from either both side walls or a single side. The anisotropic t^2¯− ε_t heat‐transfer model is employed to determine thermal eddy diffusivity. The governing boundary‐layer equations are discretized by means of a control volume finite‐difference technique and numerically solved using a marching procedure. It is found that under strong heating from both walls, laminarization occurs as in the circular tube flow case; during the laminarization process, both the velocity and temperature gradients in the vicinity of the heated walls decrease along the flow, resulting in a substantial attenuation in both the turbulent kinetic energy and the temperature variance over the entire channel cross section; both decrease causes a deterioration in heat transfer performance; and in contrast, laminarization is suppressed in the presence of one‐side‐heating, because turbulent kinetic energy is produced in the vicinity of the other insulated wall.

This paper aims to discuss about the two-dimensional numerical simulations of fluid flow and heat transfer through high thermal conductivity metal foams filled in a vertical channel using the commercial software ANSYS FLUENT.

The Darcy Extended Forchheirmer model is considered for the metal foam region to evaluate the flow characteristics and the local thermal non-equilibrium heat transfer model is considered for the heat transfer analysis; thus the resulting problem becomes conjugate heat transfer.

Results obtained based on the present simulations are validated with the experimental results available in literature and the agreement was found to be good. Parametric studies reveal that the Nusselt number increases in the presence of porous medium with increasing thickness but the effect because of the change in thermal conductivity was found to be insignificant. The results of heat transfer for the metal foams filled in the vertical channel are compared with the clear channel in terms of Colburn j factor and performance factor.

This paper serves as the current relevance in electronic cooling so as to open up more parametric and optimization studies to develop new class of materials for the enhancement of heat transfer.

The novelty of the present study is to quantify the effect of metal foam thermal conductivity and thickness on the performance of heat transfer and hydrodynamics of the vertical channel for an inlet velocity range of 0.03-3 m/s.

Wind turbines are one of the best candidates to solve the problem of increasing energy demand in the world. The aim of this paper is to apply a multi-objective structural optimization study to a Phase II wind turbine blade produced by the National Renewable Energy Laboratory to obtain a more efficient small-scale wind turbine.

To solve this structural optimization problem, a new Non-Dominated Sorting Genetic Algorithm (NSGA-II) was performed. In the optimization study, the objective function was on minimization of mass and cost of the blade, and design parameters were composite material type and spar cap layer number. Design constraints were deformation, strain, stress, natural frequency and failure criteria. ANSYS Composite PrepPost (ACP) module was used to model the composite materials of the blade. Moreover, fluid–structure interaction (FSI) model in ANSYS was used to carry out flow and structural analysis on the blade.

As a result, a new original blade was designed using the multi-objective structural optimization study which has been adapted for aerodynamic optimization, the NSGA-II algorithm and FSI. The mass of three selected optimized blades using carbon composite decreased as much as 6.6%, 11.9% and 14.3%, respectively, while their costs increased by 23.1%, 29.9% and 38.3%. This multi-objective structural optimization-based study indicates that the composite configuration of the blade could be altered to reach the desired weight and cost for production.

ACP module is a novel and advanced composite modeling technique. This study is a novel study to present the NSGA-II algorithm, which has been adapted for aerodynamic optimization, together with the FSI. Unlike other studies, complex composite layup, fiber directions and layer orientations were defined by using the ACP module, and the composite blade analyzed both aerodynamic pressure and structural design using ACP and FSI modules together.