State-of-the-art in aerodynamic shape optimisation methods

Aerodynamic optimisation has become an indispensable component for any aerodynamic design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind turbines, internal pipe flows, and cavities, among others, and is thus relevant in many facets of technology. With advancements in computational power, automated design optimisation procedures have become more competent, however, there is an ambiguity and bias throughout the literature with regards to relative performance of optimisation architectures and employed algorithms. This paper provides a well-balanced critical review of the dominant optimisation approaches that have been integrated with aerodynamic theory for the purpose of shape optimisation. A total of 229 papers, published in more than 120 journals and conference proceedings, have been classified into 6 different optimisation algorithm approaches. The material cited includes some of the most well-established authors and publications in the field of aerodynamic optimisation. This paper aims to eliminate bias toward certain algorithms by analysing the limitations, drawbacks, and the benefits of the most utilised optimisation approaches. This review provides comprehensive but straightforward insight for non-specialists and reference detailing the current state for specialist practitioners

State of the Art in the Optimisation of Wind Turbine Performance Using CFD

Wind energy has received increasing attention in recent years due to its sustainability and geographically wide availability. The efficiency of wind energy utilisation highly depends on the performance of wind turbines, which convert the kinetic energy in wind into electrical energy. In order to optimise wind turbine performance and reduce the cost of next-generation wind turbines, it is crucial to have a view of the state of the art in the key aspects on the performance optimisation of wind turbines using Computational Fluid Dynamics (CFD), which has attracted enormous interest in the development of next-generation wind turbines in recent years. This paper presents a comprehensive review of the state-of-the-art progress on optimisation of wind turbine performance using CFD, reviewing the objective functions to judge the performance of wind turbine, CFD approaches applied in the simulation of wind turbines and optimisation algorithms for wind turbine performance. This paper has been written for both researchers new to this research area by summarising underlying theory whilst presenting a comprehensive review on the up-to-date studies, and experts in the field of study by collecting a comprehensive list of related references where the details of computational methods that have been employed lately can be obtained

High-lift devices topology optimisation using structured-chromosome genetic algorithm

This paper addresses the problem of including the choice of the High-Lift Devices (HLDs) configuration as a decision variable of an automatic optimisation tool. This task requires the coupling of an estimation routine and an optimisation algorithm. For the former, SU2 flow solver has been used. The Structured-Chromosome Genetic Algorithm (SCGA) optimiser has been employed to search for the optimal HLD. SCGA can overcome the limitations dictated by standard fixed-size continuous optimisation algorithms. Indeed, using hierarchical formulations, it can manage configurational decisions that are conventionally the responsibility of expert designers. The search algorithm bases its strategy on revised genetic operators conceived for handling hierarchical search spaces. The presented research not only shows the practicability of delegating to a specialised optimisation algorithm the complete HLD design but is intended to be a proof of concept for the whole field of multidisciplinary design optimisation. Indeed, the aerospace sector as a whole would benefit by reducing human intervention from the decision process

Airfoil Optimization Through Differential Evolution

This thesis presents the development of a numerical optimization algorithm for airfoils, and how it can be used in design of wind turbine blades. It was found that the developed algorithm successfully improves the goal parameters under given conditions and constraints. This research was conducted on behalf of Winfoor AB who has developed a conceptually new blade design, in which every single blade is made up of three individual blades, kept together by rods in a truss like manner. Their wish was to develop a new airfoil for their turbine, with higher performance and a more docile stall, and yet remaining a high airfoil thickness in order to not alter structural stability. The task was conducted by describing the airfoils with B-splines and writing an optimization algorithm in MATLAB in which the flow characteristics of the airfoils were determined by the external software XFOIL. This thesis shows how to characterize numerical optimization problems, what differential evolution is and how it can be implemented in a MATLAB-code, how airfoils can be described with B-splines, the usage of XFOIL and how penalty functions can be imposed for constrained optimization problems, to mention some of the wisdoms this work has brought. This research is important as numerical optimization of airfoils is not yet the standard method for airfoil design, and thus it can possibly contribute with valuable insights and results to further development of airfoil optimization

Unsteady low-Reynolds number flow control in different regimes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106476/1/AIAA2013-353.pd

Aspects of Unstructured Grids and Finite-Volume Solvers for the Euler and Navier-Stokes Equations

One of the major achievements in engineering science has been the development of computer algorithms for solving nonlinear differential equations such as the Navier-Stokes equations. In the past, limited computer resources have motivated the development of efficient numerical schemes in computational fluid dynamics (CFD) utilizing structured meshes. The use of structured meshes greatly simplifies the implementation of CFD algorithms on conventional computers. Unstructured grids on the other hand offer an alternative to modeling complex geometries. Unstructured meshes have irregular connectivity and usually contain combinations of triangles, quadrilaterals, tetrahedra, and hexahedra. The generation and use of unstructured grids poses new challenges in CFD. The purpose of this note is to present recent developments in the unstructured grid generation and flow solution technology

Optimal Energy-Driven Aircraft Design Under Uncertainty

Aerodynamic shape design robust optimization is gaining popularity in the aeronautical industry as it provides optimal solutions that do not deteriorate excessively in the presence of uncertainties. Several approaches exist to quantify uncertainty and, the dissertation deals with the use of risk measures, particularly the Value at Risk (VaR) and the Conditional Value at Risk (CVaR). The calculation of these measures relies on the Empirical Cumulative Distribution Function (ECDF) construction. Estimating the ECDF with a Monte Carlo sampling can require many samples, especially if good accuracy is needed on the probability distribution tails. Furthermore, suppose the quantity of interest (QoI) requires a significant computational effort, as in this dissertation, where has to resort to Computational Fluid Dynamics (CFD) methods. In that case, it becomes imperative to introduce techniques that reduce the number of samples needed or speed up the QoI evaluations while maintaining the same accuracy. Therefore, this dissertation focuses on investigating methods for reducing the computational cost required to perform optimization under uncertainty. Here, two cooperating approaches are introduced: speeding up the CFD evaluations and approximating the statistical measures. Specifically, the CFD evaluation is sped up by employing a far-field approach, capable of providing better estimations of aerodynamic forces on coarse grids with respect to a classical near-field approach. The advantages and critical points of the implementation of this method are explored in viscous and inviscid test cases. On the other hand, the approximation of the statistical measure is performed by using the gradient-based method or a surrogate-based approach. Notably, the gradient-based method uses adjoint field solutions to reduce the time required to evaluate them through CFD drastically. Both methods are used to solve the shape optimization of the central section of a Blended Wing Body under uncertainty. Moreover, a multi-fidelity surrogate-based optimization is used for the robust design of a propeller blade. Finally, additional research work documented in this dissertation focuses on utilizing an optimization algorithm that mixes integer and continuous variables for the robust optimization of High Lift Devices

An Airfoil Shape Optimization Technique coupling PARSEC Parameterization and Evolutionary Algorithm

In this work an innovative optimization process for airfoil geometry design is introduced. This procedure is based on the coupling of a PARSEC parameterization for airfoil shape and a genetic algorithms (GA) optimization method to find Nash equilibria (NE). While the PARSEC airfoil parameterization method has the capability to faithfully describe an airfoil geometry using typical engineering parameters, on the other hand the Nash game theoretical approach allows each player to decide, with a more physical correspondence between geometric parameters and objective function, in which direction the airfoil shape should be modified. As a matter of fact the optimization under NE solutions would be more attractive to use when a well posed distinction between players variables exists