A geometry optimization framework for photonic crystal design

AbstractThe performance of photonic crystal devices can depend strongly on their geometry. Alas, their fundamental physics offers relatively little by way of pointers in terms of optimum shapes, so numerical design search techniques must be used in an attempt to determine high performance layouts. We discuss strategies for solving this type of optimization problem, the main challenge of which is the conflict between the enormous size of the space of potentially useful designs and the relatively high computational cost of evaluating the performance of putative shapes. The optimization technique proposed here operates over increasing levels of fidelity, both in terms of the resolution of its non-parametric shape definition and in terms of the resolution of the numerical analysis of the performance of putative designs. This is a generic method, potentially applicable to any type of electromagnetic device shape design problem. We also consider a methodology for assessing the robustness of the optima generated through this process, investigating the impact of manufacturing errors on their performance. As an illustration, we apply this technology to the design of a two-dimensional photonic crystal structure; the result features a large complete band gap structure and a topology that is different from previously published designs

Tradeoffs in jet inlet design: a historical perspective

The design of the inlet(s) is one of the most demanding tasks of the development process of any gas turbine-powered aircraft. This is mainly due to the multi-objective and multidisciplinary nature of the exercise. The solution is generally a compromise between a number of conflicting goals and these conflicts are the subject of the present paper. We look into how these design tradeoffs have been reflected in the actual inlet designs over the years and how the emphasis has shifted from one driver to another. We also review some of the relevant developments of the jet age in aerodynamics and design and manufacturing technology and we examine how they have influenced and informed inlet design decision

A parallel updating scheme for approximating and optimizing high fidelity computer simulations

Approximation methods are often used to construct surrogate models, which can replace expensive computer simulations for the purposes of optimization. One of the most important aspects of such optimization techniques is the choice of model updating strategy. In this paper we employ parallel updates by searching an expected improvement surface generated from a radial basis function model. We look at optimization based on standard and gradient-enhanced models. Given Np processors, the best Np local maxima of the expected improvement surface are highlighted and further runs are performed on these designs. To test these ideas, simple analytic functions and a finite element model of a simple structure are analysed and various approaches compared

Self-designing parametric geometries

The thesis of this paper is that script-based geometry modelling offers the possibility of building `self-designing' intelligence into parametric airframe geometries. We show how sophisticated heuristics (such as optimizers and complex decision structures) can be readily integrated into the parametric geometry model itself using a script-driven modelling architecture. The result is an opportunity for optimization with the scope of conceptual design and the fidelity of preliminary design. Additionally, the proposed `self-design' philosophy of using an integrated design heuristic to construct much of the geometry is a good mechanism for de-constraining the design space, as we can take the design variables as a starting point from which we generate a feasible design, wherever possible. We illustrate these ideas through the parametric geometry model of a twin-engined light aircraft

Classifier systems can reduce conceptual design cycle time

Though very widely used in preliminary and detail design, commercial parametric CAD engines have not reached their full potential yet at the conceptual stage of industrial design processes. One possible reason is their lack of robustness when it comes to generating a wide variety of geometries, as demanded by the global nature of conceptual design. Such large, multi-dimensional design spaces often have regions of infeasibility, where the corresponding CAD models would lead to failure as early as the geometry generation process itself or as late as the final stages of some expensive multidisciplinary analysis process integrated into the concept design tool. In this paper we discuss the use of Radial Basis Function classifier systems as a means of mapping out infeasible regions of the design space. The ultimate aim is to equip the concept design tool with the ability to avoid such areas, thus saving time by reducing the number of failed simulations on unphysical or otherwise unsuitable candidate designs

Topology optimisation: increasing the speed and reliability of design

In this paper, topology optimisation is applied to the design of the rear fuselage of an unmanned aerial vehicle (UAV). A comparison is drawn between the performance of a design created through evolutionary structural optimisation (ESO) and a baseline design modelled on a manually designed and successfully flow fuselage geometry, for different wing shapes. The loading for each wing shape is determined by full-potential (FP) aerodynamic analysis. A Kriging model is then employed in a multidisciplinary optimisation procedure driving a trade study between aerodynamic efficiency and aircraft structural weight. Using this procedure, a Pareto front is populated to give a set of optimal designs which satisfy maximum aerodynamic efficiency and minimum weight objectives. A wide search of the design space is achieved with little manual intervention, which makes use of the high fidelity weight estimate extracted from topology optimization results