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A collaborative design environment is needed for multidisciplinary design optimization (MDO) process, based on all the modules those for different design/analysis disciplines, and a systematic coupling should be made to carry out aerodynamic shape optimization (ASO), which is an important part of MDO.

Computerized environment for aircraft synthesis and integrated optimization methods (CEASIOM)-ASO is developed based on loosely coupling all the existing modules of CEASIOM by MATLAB scripts. The optimization problem is broken down into small sub-problems, which is called “sequential design approach”, allowing the engineer in the loop.

CEASIOM-ASO shows excellent design abilities on the test case of designing a blended wing body flying in transonic speed, with around 45 per cent drag reduction and all the constraints fulfilled.

Authors built a complete and systematic technique for aerodynamic wing shape optimization based on the existing computational design framework CEASIOM, from geometry parametrization, meshing to optimization.

CEASIOM-ASO provides an optimization technique with loosely coupled modules in CEASIOM design framework, allowing engineer in the loop to follow the “sequential approach” of the design, which is less “myopic” than sticking to gradient-based optimization for the whole process. Meanwhile, it is easily to be parallelized.

The critical Mach number, lift-to-drag ratio and drag force play important role in the performance of the wings. This paper aims to investigate the effect of taper stacking, which has been used to generalize wing sweeping, on those parameters.

The results obtained are based on steady-state turbulent flowfields computations. The baseline wing is ONERA M6. Various wing planforms are generated by linearly or parabolically varying the spanwise stacking location. The critical Mach number is determined by changing the freestream Mach number for a fixed angle of attack. On the other hand, the analysis of the drag force is carried out by changing the angle of attack to keep the lift force constant.

By changing the stacking location, the critical Mach number and the corresponding lift-to-drag ratio have increased by around 7 and 3%, respectively. A reduction of 12.8% in total drag force has been observed in one of the analyzed cases. Moreover, there exist some cases in which the values of drag reduce significantly while the lift is the same.

The results of this new stacking approach have implied that the drag force can be decreased without decreasing the lift. This outcome is valuable for increasing the range and endurance of an aircraft.

This work generalizes wing sweeping by modifying the taper stacking along the span. In literature, wing sweep is enhanced using segmented stacking of taper distribution. The present study is further enhancing this concept by introducing continuous stacking (infinite number of stacking segments) for the first time.

Winglets play a major role in saving fuel costs because they reduce the lift-induced drag formed at the wingtips. The purpose of this paper is to obtain the best orientation of the winglet for the Office National d’Etudes et de Recherches Aérospatiales (ONERA) M6 wing at Mach number 0.84 in terms of lift to drag ratio.

A computational fluid dynamics analysis of the wing-winglet configuration based on the ONERA M6 airfoil on drag reduction for different attack angles at Mach 0.84 was performed using analysis of systems Fluent. First, the best values of cant and sweep angles in terms of aerodynamic performance were selected by performing simulations. The analysis included cant angle values of 30°, 40°, 45°, 55°, 60°, 70° and 75°, while for the sweep angles 35°, 45°, 55°, 65° and 75° angles were used. The aerodynamic performance was measured in terms of the obtained lift to drag ratios.

The results showed that slight alternations in the winglet configuration can improve aerodynamic performance for various attack angles. The best lift to drag ratio for the winglet was achieved at a cant angle of 30° and a sweep angle of 65°, which caused a 5.33% increase in the lift to drag ratio. The toe-out angle winglets as compared to the toe-in angles caused the lift to drag ratio to increase because of more attached flow at its surface. The maximum value of the lift to drag ratio was obtained with a toe-out angle (−5°) at an angle of attack 3° which was 2.53% greater than the zero-toed angle winglet.

This work is relatively unique because the cant, sweep and toe angles were analyzed altogether and led to a significant reduction in drag as compared to wing without winglet. The wing model was compared with the results provided by National Aeronautics and Space Administration so this validated the simulation for different wing-winglet configurations.

Environmental and operational restrictions increasingly drive modern aircraft design due to the growing impact of global warming on the ecology. Regulations and industrial measures are being introduced to make air traffic greener, including restrictions and environmental targets for aircraft design that increase aerodynamic efficiency. This study aims to maximize aerodynamic efficiency by identifying optimal values for sweep angle, taper ratio, twist angle and wing incidence angle parameters in wing design while keeping wing area and span constant.

Finding optimal wing values by using gradient-based and evolutionary algorithm methods is very time-consuming. Therefore, an artificial neural network-based surrogate model was developed. Computational fluid dynamics (CFD) analyses were carried out by using Reynolds-averaged Navier–Stokes equations to create a properly trained data set using a feedforward neural network.

The results showed how a wing could be optimized by using a CFD-based surrogate model. The two optimum results obtained resulted in increases of 10.7397% and 10.65% in the aerodynamic efficiency of the baseline design ONERA M6 wing.

The originality of this study lies in the combination of sweep angle, taper ratio, twist angle and wing incidence angle within the scope of wing optimization calculations.

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.

The discontinuous Galerkin finite element method (DGFEM) is very suited for realizing high order resolution approximations on unstructured grids for calculating the hyperbolic conservation law. However, it requires a significant amount of computing resources. Therefore, this paper aims to investigate how to solve the Euler equations in parallel systems and improve the parallel performance.

Discontinuous Galerkin discretization is used for the compressible inviscid Euler equations. The multi-level domain decomposition strategy was used to deal with the computational grids and ensure the calculation load balancing. The total variation diminishing (TVD) Runge–Kutta (RK) scheme coupled with the multigrid strategy was employed to further improve parallel efficiency. Moreover, the Newton Block Gauss–Seidel (GS) method was adopted to accelerate convergence and improve the iteration efficiency.

Numerical experiments were implemented for the compressible inviscid flow problems around NACA0012 airfoil, over M6 wing and DLR-F6 configuration. The parallel acceleration is near to a linear convergence. The results indicate that the present parallel algorithm can reduce computational time significantly and allocate memory reasonably, which has high parallel efficiency and speedup, and it is well-suited to large-scale scientific computational problems on multiple instruction stream multiple data stream model.

The parallel DGFEM coupled with TVD RK and the Newton Block GS methods was presented for hyperbolic conservation law on unstructured meshes.

In this study, dynamic mesh method is implemented on a real coded genetic algorithm to demonstrate gain in computational time as well as in higher performance for optimized parameters. Since the differences developed at each step in geometries of new members are not significant, therefore, it is possible to use dynamic mesh methods for new members. In this work, because the population members are obtained by modifying the pervious ones, each member is considered as one step of geometry‐change of a deforming body, for examples, a wing inflating, deflating or cambering.

To outline a transonic wing design problem by applying real coded genetic algorithm (GA) and dynamic mesh technique to reduce the optimization time and cost.

Dynamic mesh technique was used in the design of a transonic wing by matching it with heuristic algorithms.

It is observed that the drag coefficient can be reduced by 25 percent. While this has been done, the lift coefficient is tried to be close to the design value determined at the beginning as a design constraint.

It is the first time that the dynamic mesh technique is used for regenerating the mesh structures of the new population members in the GA.

This paper seeks to outline a forward swept wing (FSW) design problem to reduce the optimization time and cost and to compare it with previous backward swept wing (BSW) results to see the differences.

Dynamic mesh technique was used in the design of a transonic FSW by coupling it with heuristic algorithms. To obtain the initial FSW mesh from BSW domain, a modified dynamic mesh method was developed. It was also compared with experimental results.

It is observed that the drag coefficient can be reduced by 15 percent in 500 calculations while the lift coefficient is tried to be close to the design value determined at the beginning as a design constraint. Especially, the taper ratio change direction differs from previous BSW optimization.

It is the first time that the dynamic mesh technique is used for obtaining the mesh structures of the new FSW members through genetic optimization. A modified dynamic mesh was used to convert BSW domain to FSW, which means a huge movement for the cells. A physical model of initial FSW is also produced for wind tunnel and tested.

The compressible Navier‐Stokes equations are solved numerically for turbulent transonic aerospace applications on parallel computers. An Explicit Algebraic Reynolds Stress Model (EARSM) models the turbulence. Expressing the EARSM as an extension of an eddy‐viscosity model makes the implementation straightforward in a flow solver with existing two‐equation eddy‐viscosity models. The k−ω transport equations are used as a platform for the model. The EARSM approach significantly improves the shock position for transonic flow over wings without substantial increase in computational cost. Industrial use of advanced flow modelling requires a short turn‐around time of computations. This is enabled through the use of parallel computers. To achieve good parallel performance the computational load has to be evenly distributed between the processors of the parallel computer. A heuristic algorithm is described for distributing and splitting the blocks of a structured multiblock grid for a good static load balance. Speed‐up results are presented for turbulent flow around a wing on a number of parallel platforms.