A Fast and Efficient Method for Multiobjective Aerodynamic Optimization of a Civil Aircraft Fuselage

Unmanned aerial vehicles (UAV) are used in the military field for missions such as observation, surveillance and seeking object. UAV observation can be used to monitor humans, weather, forests, agriculture, and fisheries and so on. UAV can be operated for very broad missions with low development costs compared to manned aerial vehicles with a low risk of death. The design of an aircraft affects the performances of the aircraft itself. Aircraft flying characteristics are influenced by the value of coefficient of drag (CD) and coefficient of lift (CL). The value of CD affects how much aircraft friction with the air, while the value of CL affects how much lifting force the aircraft is produced so it can fly. The design output needs the most optimal CD and CL values to get the optimal aircraft performance. In this study, we simulated the effect of 4 digit NACA changes on the characteristics of the plane’s CD and CL. This study uses variations modification of NACA digits with different variables. NACA airfoil 4 digit series (MPXX) designates camber lines, maximum camber position and thickness. Based on the results of this study, the optimal CD and CL values for the Airfoil NACA with the Aerosonde UAV model are designs that have a large ratio of lift and drag (CL / CD). The lower the CD value and the higher the CL value, the better the performance of the UAV. The design that has the largest CL / CD is the NACA 6412 Airfoil.

This paper presents a new multi-objective optimization method, which is inspired from the idea of non-dominated sorting genetic algorithm (NSGA) and genetic quantum algorithm (GQA). The GQA has been tested on well known test beds in single objective optimization and compared with the genetic algorithm (GA) in the lead author’s previous work [22]. This paper aims to apply the idea of GQA to multi-objective optimization (MOO). The developed method is called non-dominated sorting genetic quantum algorithm (NSGQA). The developed method is tested with benchmark problems collected from literature, which have characteristics representing various aspects of a MOO problem. Test results show that NSGQA has better performance on most benchmark problems than currently popular MOO methods such as the NSGA. The integration of GQA with MOO, and the systematic comparison with other MOO methods on benchmark problems, should be of general interest to researchers on MOO and to practitioners using MOO methods in design.

Kenyalang is a fuel cell powered Unmanned Aerial Vehicle (UAV) developed by Universiti Teknologi MARA (UiTM). This paper discusses the aircraft performances analysis of Kenyalang. Computational Fluid Dynamic (CFD) using Numeca software had been performed to obtain the aerodynamics characteristic of the Kenyalang UAV in the form of lift (CL) and drag (CD) coefficients. Unstructured mesh and standard one - equation turbulence model, and Spalart-Allmaras selected in the simulation. Lift coefficients (CL) and drag coefficients (CD) were studied at flight condition of Mach 0.08 (~26 m/s) at different angles of attack, α. The CFD data results were used to obtain Stall Speed, Take off Distance and Rate of Climb, and the results are shown in this paper.

Surrogate-based method can dramatically reduce the number of expensive function evaluations in real-world multi- objective optimization problems (MOP). When the number of objectives is small, using surrogate models combined with expected hypervolume improvement (EHVI) infill sampling criterion (ISC) has been proved to be efficient to provide a set of solutions with good diversity and good proximity to the Pareto front (PF) in aerodynamic shape optimization. However, traditional hypervolume-based infilling strategies use only one kind of ISC to generate one or multiple sample points, the advantages of various kinds of ISC cannot be comprehensively utilized and the parallelization is not easy to implement. This paper proposes a combined multi-point infilling strategy based on Kriging models and develops an efficient global multi-objective constrained optimization method (EGMOCO) to solve multi- objective aerodynamic shape optimization with complex constraints. Multiple sample points are generated by using four ISC considering hypervolume at each iteration and then evaluated in parallel. Firstly, the performance of EGMOCO is compared with that of single criterion EHVI strategy on six benchmarks within the same computational budget to prove its effectiveness, and then EGMOCO is implemented in an aerodynamic shape optimization problem with complex constraints. The result shows that EGMOCO has good performance in balancing local exploitation and global exploration with faster convergence rate and high robustness, the whole PF can be fully explored in limited evaluations and the constraint handling is effective especially for real-world problems with complex and nonlinear constraints, the comprehensive aerodynamic performance of the airfoil is greatly improved. It can be confirmed that Kriging-based multi-objective optimization method combined with multi-point infilling strategy performs better than single infilling criterion EHVI, since different sample infilling criteria can complement with each other, both local exploitation and global exploration can be considered and well balanced.

The flow over two different shaped bluff bodies in tandem arrangement was numerically investigated by using the finite volume method with Computational Fluid Dynamics (CFD) techniques. The shape of the downstream main bluff body is a right circular cylinder, with shape unchanged, while the shape of the upstream bluff body varies between: circle, triangle, square, ellipse and cylindrical half-shell. The hydraulic diameters of both front and rear bluff bodies are equal. The analysis is carried out for Reynolds numbers of 100, 300 and 500, and center-to-center distance ratios, L/D, of 1.5, 2, 3, 4.5 and 6. Flow characteristics in terms of the lift and drag coefficients and Strouhal number are analyzed and the vortex shedding patterns around the bluff bodies are described. The influence of the shape of the fore cylinder on the flow characteristics is the innovation point of this paper. It is concluded that the center-to-center distance ratio, L/D, and the shape of the upstream bluff body have important effects on the drag and lift coefficients, vortex shedding frequencies from the two bluff bodies, and flowfield characteristics.

In this paper, an improved aerodynamic performance optimization method for 3-D low Reynolds number (Re) rotor blade is proposed. A conventional optimization procedure of blade is usually divided into three parts, such as the parameterization method, the fitness value evaluation and the optimization algorithm. This work is mainly focused on the first two parts. The parametrization method, Camber-FFD, is presented based on the camber parametrization method and the free-form deformation algorithm (FFD). The shape of 3-D blade is parameterized by the incidence angles and the coordinates of the maximum camber points. The fitness value evaluation has been realized with the help of an adaptive topological back propagation multi-layer forward artificial neural network (BP-MLFANN). During the training of BP-MLFANN, the hybrid particle swarm optimization method combined with the modified very fast simulate annealing algorithm (HPSO-MVFSA) is adopted to determine the neural network topology adaptively. To verify the effectiveness of this aerodynamic optimization method, the aerodynamic performance of a 3-D low-Re blade, such as Blade D900, is optimized, and the results are compared and analyzed based on the experiments and simulations. It is proved that this aerodynamic optimization method is feasible.

A staged diversity enhancement method for constrained multiobjective evolutionary optimization

Effective optimization on Bump inlet using meta-model multi-objective particle swarm assisted by expected hyper-volume improvement

Complex network clustering has been extensively studied in recent years, mostly through optimization approaches. In such approaches, the multi-objective optimization methods have been shown to be capable of overcoming the limitations (e.g., instability) of the single-objective methods. Nevertheless, such methods suffer from the shortcoming of incapability of maintaining a good tradeoff between exploration and exploitation, that is, to find better solutions based on the good ones obtained so far. In this paper, we present a new nature-inspired heuristic optimization method, called multi-objective discrete moth-flame optimization (DMFO) method, which achieves such a tradeoff. We describe the detailed algorithm of DMFO that utilizes the Tchebycheff decomposition approach with an \(l_2\)-norm constraint on the direction vector (2-Tch). Furthermore, we show the experimental results on synthetic and several real-world networks that verify that the proposed DMFO and the algorithm are both effective and promising for tackling the task of complex network clustering.

There are various configurations and parameters that contribute to the Design of Unmanned Aerial Vehicles for specific applications. This paper deals with an innovative design of an unmanned aerial vehicle for a specified class of UAVs that require demands such as long endurance, minimized landing space with vertical take-off and landing (VTOL) capabilities. The focal point of this design is superimposing the high endurance blended wing design into tri-copter to address these parameters. The preliminary calculations are initially performed for the blended wing VTOL vehicle based on the required payload capacity and endurance. Superimposing the tri-copter will decrease the aerodynamic efficiency of the vehicle. Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical methods and algorithms to solve complex problems involving fluid flow which will effectively employed to reduce the cost and time during the conceptual and preliminary design stages. CFD analysis was carried out to estimate the major parameters like lift, drag, lift coefficient (CL) and drag coefficient (CD) for various Angle of Attack (AoA) for configurations of blended wing vehicle with and without tri-copter system in the cruise condition. Thus, the vehicle design and propulsion system is effectively optimized using this drag estimation.

Design optimization has been increasingly investigated for an airfoil, aiming to reduce the vorticity in the wake and increase the aerodynamic performance. In the current work, a two-dimensional (2D) S833 airfoil equipped with a flapping fringe at the trailing edge has been studied using computational fluid dynamics (CFD) simulations. The objective is to investigate the influence of the length (Lf) and flapping frequency (f) of the fringe on shedding vortices from the airfoil and the drag and lift coefficients. The validation of the current numerical approach for both static and dynamic motions of the airfoil was conducted. First, four different computational meshes were created for the static bare airfoil S833 model, and the simulated drag and lift coefficients were compared against experimental results. It is observed that the second finest mesh contributes to the best agreement with the measurement data. In addition, the numerical accuracy of the dynamic simulation was assessed by reproducing the pressure distribution around the airfoil NACA0014 with a periodic plunging motion at different time phases within one plunging cycle. Good agreements between the simulated and previous computational results are obtained. Moreover, the investigation of S833 airfoil equipped with a flapping fringe reveals that the model with Lf =0.01 m (10% of the chord length) associated with a flapping frequency below the shedding frequency of the bare airfoil can significantly alter the coherent structure of the shedding vortices, breaking the routine large-scale vortex into small-scale weak vortices. It also results in reducing the intensity of vortices and shortening the distance between each pair of vortices to accelerate the dissipation of vorticity. In addition, the equipped flapping trailing edge fringe can achieve extra benefit in aerodynamic performance in terms of the reduction of the drag coefficients and the enhancement of lift coefficients.

Due to the high energy consumption of buildings, there is a demand for both economically and environmentally effective designs for building energy system retrofits. While multi-objective optimization can be used to solve complicated problems, its use is not yet widespread in the industry. This study first aims to develop an efficient and applicable multi-objective building energy system optimization method, used to dimension energy production and storage retrofit components in a case campus building in Lahti, Finland. Energy consumption data of the building are obtained with a dynamic energy model. The optimization model includes economic and environmental objectives, and the approach is found to function satisfactorily. Second, this study aims to assess the feasibility and issues of multi-objective single-building energy system optimization via the analysis of the case optimization results. The results suggest that economically beneficial local energy production and storage retrofits could not always lead to life cycle CO2-eq emission reductions. The recognized causes are high life cycle emissions from the retrofit components and low Nordic grid energy emissions. The performed sensitivity and feasibility analyses show that correctness and methodological comparability of the used emission factors and future assumptions are crucial for reliable optimization results.

For multi-objective optimization under condition of complicated objective function, the data processing in the evaluation is sometime tediously long, special algorithm is needed to be adopted. Since the remarkable features of uniform distribution of test points within the test domain and the small number of tests, fully representative of each point, and easy to perform regression analysis, the uniform test design method is hybrid with the “intersection” method for multi-objective optimization to simplify the complicated data process in evaluation first. Furthermore, the "intersection" multi-objective optimization methodology is combined with sequential uniform design so as to get a more precise approximation for solving multi-objective optimization problem, the procedure for searching optimum of the “intersection“ multi-objective optimization methodology with sequential uniform design algorithm is put forward. A multi-objective optimization of linear programming problem with three variables is taken as our example, which involves a maximum for one objective and a minimum for another objective. The result for applying the novel approach to the example indicates the effectiveness of current hybrids.

An aerodynamic technique to calculating lift and drag coefficients is one of the required instruments in the wing design process. During the last decades, several tools and software have been developed according to aero-dynamics and numerical methods. Nowadays, aeronautical architecture requires many calculations. Today’s techno-logists use a variety of simulation techniques to avoid a expensive model testing. This paper explains how wing profiles can be modelled using ANSYS Fluent and tested by low-speed tests considering experimental literature re-sults. With the selected wing profile, the geometry is shaped in two dimensions and designed in three dimensions. Computational fluid dynamics (CFD) was adopted as the method for studying wing profiles. Wing profiles created at 0 to 20-degree attack angles are calculated in the simulation area equal to the actual wind tunnel scale, and equations are solved using the RNG k-Epsilon turbulence model. The process of developing the grids was realized with Ansys Mesher software. The solution stage and the result show operations were carried out with the CFD Post software. The study of the low velocity and high transport wing profiles, the drag coefficient, the lift coefficient, and the effect on the lift-drag ratio were studied using a numerical procedure. After determining the high efficiency of wing profi-les, production of a selected profile began with a static examination.

This work presents a numerical Simulation of an underwater glider to investigate the effect of angle of attack on the hydrodynamic coefficients such as lift, drag, and torque. Due to the vital role of these coefficients in designing the controllers of a glider, and to obtain an accurate result, this simulation has been carried on at a range of operating velocities. The total length of the underwater glider with two wings is 900 mm with a 4-digits NACA0009 profile. The fluid flow regime is discretized and solved by computational fluid dynamics and finite volume method. Since the Reynolds number range for this study is in a turbulent flow state (up to 3.7e06), the κ-ω SST formulation was used to solve Navier-Stokes equations and continuity and the angles of attack ranging are from - 8 to 8 degrees. The main purpose of this research is to study the effect of each of the dynamics parameters of glider motion such as velocity and angle of attacks on the hydrodynamic coefficients. Based on the results, the drag and lift coefficients are enhanced with increasing the angle of attack. In addition, the drag coefficient enhanced with increasing the velocity however, when the glider velocity is increased, the lift coefficient does not change significantly except at the highest angle of attack that decreases. The highest drag coefficient is 0.0246, which corresponds to the angle of attack of -8 and the Reynolds number of 3738184. In addition to simple geometry, the glider studied in this paper shows relatively little resistance to flow.