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

Tiltrotor CFD part II: aerodynamic optimisation of tiltrotor blades

This paper presents aerodynamic optimisation of tiltrotor blades with high-fidelity computational fluid dynamics. The employed optimisation framework is based on a quasi-Newton method, and the required high-fidelity flow gradients were computed using a discrete adjoint solver. Single-point optimisations were first performed, to highlight the contrasting requirements of the helicopter and aeroplane flight regimes. It is then shown how a trade-off blade design can be obtained using a multi-point optimisation strategy. The parametrisation of the blade shape allowed to modify the twist and chord distributions, and to introduce a swept tip. The work shows how these main blade shape parameters influence the optimal performance of the tiltrotor in helicopter and aeroplane modes, and how a compromise blade shape can increase the overall tiltrotor performance. Moreover, in all the presented cases, the accuracy of the adjoint gradients resulted in a small number of flow evaluations for finding the optimal solution, thus indicating gradient-based optimisation as a viable tool for modern tiltrotor design

Efficient Inverse Design of Transonic Airfoils using Variable-Resolution Models and Manifold Mapping

This paper presents an efficient approach for simulation-based inverse design of airfoil shapes using variable-fidelity computational fluid dynamics models and manifold mapping (MM). Inverse design involves determining an airfoil shape fulfilling a given target performance characteristic. In particular, the pressure coefficient distribution is typically used in aerodynamic inverse design. Such a task can be challenging when using computationally expensive simulations. In the context of local optimization, the MM technique searches for a new design in the vicinity of the current design by constructing a fast multi-fidelity model, which is setup by the available evaluations of each of the high- and low-fidelity models at the current design. The MM-based multi-fidelity model predicts the high-fidelity model response at the new design by evaluating the low-fidelity model at the new design and applying the MM mapping. The MM-based multi-fidelity model is embedded within the trust-region algorithm and terminates based on the convergence of the argument, objective, and trust-region radius to yield the optimal design. The MM-based multi-fidelity algorithm only needs one high-fidelity model evaluation per design iteration. The proposed approach is illustrated on the inverse design of airfoils in transonic inviscid flow with the NACA 2412 airfoil as baseline and the pressure distribution of the RAE 2822 airfoil at Mach 0.734 and lift coefficient 0.824 as the target. Using eight B-spline design variables, the results indicate the MM technique is able to reach the target distribution at a low computational cost when compared to derivative-free local search

Multi-level CFD-based Airfoil Shape Optimization With Automated Low-fidelity Model Selection

AbstractComputational fluid dynamic (CFD) models are ubiquitous in aerodynamic design. Variable-fidelity optimization algorithms have proven to be computationally efficient and therefore suitable to reduce high CPU-cost related to the design process solely based on accurate CFD models. A convenient way of constructing the variable-fidelity models is by using the high-fidelity solver, but with a varying degree of discretization and reduced number of flow solver iterations. So far, selection of the appropriate parameters has only been guided by the designer experience. In this paper, an automated low- fidelity model selection technique is presented. By defining the problem as a constrained nonlinear optimization problem, suitable grid and flow solver parameters are obtained. Our approach is compared to conventional methods of generating a family of variable-fidelity models. Comparison of the standard and the proposed approaches in the context of aerodynamic design of a transonic airfoil indicates that the automated model generation can yield significant computational savings

From 3D Models to 3D Prints: an Overview of the Processing Pipeline

Due to the wide diffusion of 3D printing technologies, geometric algorithms for Additive Manufacturing are being invented at an impressive speed. Each single step, in particular along the Process Planning pipeline, can now count on dozens of methods that prepare the 3D model for fabrication, while analysing and optimizing geometry and machine instructions for various objectives. This report provides a classification of this huge state of the art, and elicits the relation between each single algorithm and a list of desirable objectives during Process Planning. The objectives themselves are listed and discussed, along with possible needs for tradeoffs. Additive Manufacturing technologies are broadly categorized to explicitly relate classes of devices and supported features. Finally, this report offers an analysis of the state of the art while discussing open and challenging problems from both an academic and an industrial perspective.Comment: European Union (EU); Horizon 2020; H2020-FoF-2015; RIA - Research and Innovation action; Grant agreement N. 68044