Parameterization and geometric optimization of balloon launched sensorcraft for atmospheric research missions

We present a method for the payload centric automated design and manufacturing of balloon launched, high altitude gliders. The purpose of these gliders is to conduct directed measurements of atmospheric phenomena with a variety of payloads. A bespoke airframe design is generated that can protect the payload, ensure recoverability and extend sampling times. A manufacturing technique, that relies heavily on rapid prototyping, allows for rapid realization of the aircraft design. This allows atmospheric scientists and researchers unprecedented access to a broad range of altitudes

Improving machine dynamics via geometry optimization

The central thesis of this paper is that the dynamic performance of machinery can be improved dramatically in certain cases through a systematic and meticulous evolutionary algorithm search through the space of all structural geometries permitted by manufacturing, cost and functional constraints. This is a cheap and elegant approach in scenarios where employing active control elements is impractical for reasons of cost and complexity. From an optimization perspective the challenge lies in the efficient, yet thorough global exploration of the multi-dimensional and multi-modal design spaces often yielded by such problems. Morevoer, the designs are often defined by a mixture of continuous and discrete variables - a task that evolutionary algorithms appear to be ideally suited for. In this article we discuss the specific case of the optimization of crop spraying machinery for improved uniformity of spray deposition, subject to structural weight and manufacturing constraints. Using a mixed variable evolutionary algorithm allowed us to optimize both shape and topology. Through this process we have managed to reduce the maximum roll angle of the sprayer by an order of magnitude , whilst allowing only relatively inexpensive changes to the baseline design. Further (though less dramatic) improvements were shown to be possible when we relaxed the cost constraint. We applied the same approach to the inverse problem of reducing the mass while maintaining an acceptable roll angle - a 2% improvement proved possible in this cas

Modelling the dispersion of aircraft trajectories using Gaussian processes

This work investigates the application of Gaussian processes to capturing the probability distribution of a set of aircraft trajectories from historical measurement data. To achieve this, all data are assumed to be generated from a probabilistic model that takes the shape of a Gaussian process.The approach to Gaussian process modelling used here is based on a linear expansion of trajectory data into set of basis functions that may be parametrized by a multivariate Gaussian distribution. The parameters are learned through maximum likelihood estimation.The resulting probabilistic model can be used for both modelling the dispersion of trajectories along the common flightpath and for generating new samples that are similar to the historical data.The performance of this approach is evaluated using three trajectory datasets; toy trajectories generated from a Gaussian distribution, sounding rocket trajectories that are generated by a stochastic rocket flight simulator and aircraft trajectories on a given departure path from DFW airport, as measured by ground-based radar. The results indicate that the maximum deviation between the probabilistic model and test data obtained for the three data sets are respectively 4.9%, 7.6% and 13.1%

Robust gas turbine and airframe system design in light of uncertain fuel and CO2 prices

This paper presents a study that numerically investigated which cruise speed the next generation of short-haul aircraft with 150 seats should fly at and whether a conventional two- or three-shaft turbofan, a geared turbofan, a turboprop, or an open rotor should be employed in order to make the aircraft's direct operating cost robust to uncertain fuel and carbon (CO2) prices in the Year 2030, taking the aircraft productivity, the passenger value of time, and the modal shift into account. To answer this question, an optimization loop was set up in MATLAB consisting of nine modules covering gas turbine and airframe design and performance, flight and aircraft fleet simulation, operating cost, and optimization. If the passenger value of time is included, the most robust aircraft design is powered by geared turbofan engines and cruises at Mach 0.80. If the value of time is ignored, however, then a turboprop aircraft flying at Mach 0.70 is the optimum solution. This demonstrates that the most fuel-efficient option, the open rotor, is not automatically the most cost-efficient solution because of the relatively high engine and airframe costs

Parametric geometry models for hypersonic aircraft: integrated external inlet compression

In this paper we are investigating a method for the design and integration of 3D externalcompression inlet geometries on parametric geometries of air-breathing hypersonic aircraft.We view the geometries as the first stage of a mixed compression inlet. The investigations arebased on waverider geometries generated with the osculating cones waverider forebodydesign method. The osculating cones method is further utilized to create a secondcompression surface before the inlet cowl, essentially creating a second waverider geometryon the underside of the forebody. This way, we achieve greater compression for the part ofthe flow to be captured by the inlet cowl using a geometry that does not require sidewalls(like 2D ramps do), and has a potentially larger capture area than axisymmetric inletgeometries such as half-cones. The integration method is explained in detail, validated andfurther examined with CFD simulations. Those include measurements of the sensitivity ofthe flowfield to angle of attack, sideslip and Mach number changes. A number of options fordesigning the downstream internal compression part of the inlet are also discussed

Efficient parameterization of waverider geometries

This paper summarizes the results of investigations into the development of parametric waverider geometry models, with emphasis on their efficiency, in terms of their ability to cover a large feasible design space with a sufficiently small number of design variables to avoid the “curse of dimensionality.” The work presented here is focused on the parameterization of idealized waverider forebody geometries that provide the baseline shapes upon which more sophisticated and realistic hypersonic aircraft geometries can be built. Three different aspects of rationalizing the decisions behind the parametric geometry models developed using the osculating cones method are considered. Initially, three different approaches to the design method itself are discussed. Each approach provides direct control over different aspects of the geometry for which very specific shapes would be more complex to obtain indirectly, thus enabling the geometry to more efficiently meet any related design constraints. Then, a number of requirements and limitations are investigated that affect the available options for the parametric design-driving curves of the inverse design method. Finally, the performance advantages that open up with increasing flexibility of the design-driving curves in the context of a design optimization study are estimated. This allows one to reduce the risk of overparameterizing the geometry model, while still enabling a variety of meaningful shapes. Although the osculating cones method has mainly been used here, most of the findings also apply to other similar inverse design algorithms

Engineering design applications of surrogate-assisted optimization techniques

The construction of models aimed at learning the behaviour of a system whose responses to inputs are expensive to measure is a branch of statistical science that has been around for a very long time. Geostatistics has pioneered a drive over the last half century towards a better understanding of the accuracy of such ‘surrogate’ models of the expensive function. Of particular interest to us here are some of the even more recent advances related to exploiting such formulations in an optimization context. While the classic goal of the modelling process has been to achieve a uniform prediction accuracy across the domain, an economical optimization process may aim to bias the distribution of the learning budget towards promising basins of attraction. This can only happen, of course, at the expense of the global exploration of the space and thus finding the best balance may be viewed as an optimization problem in itself. We examine here a selection of the state of-the-art solutions to this type of balancing exercise through the prism of several simple, illustrative problems, followed by two ‘real world’ applications: the design of a regional airliner wing and the multi-objective search for a low environmental impact hous

Parametric geometry models for hypersonic aircraft components: blunt leading edges

In this paper we report the results of investigations into the efficient parameterization of blunt leading edge shapes for hypersonic aircraft geometries. The investigations mostly revolve around waverider geometries generated with inverse design techniques, such as the osculating cones waverider forebody design method. The shapes presented however, can be utilized to introduce bluntness to any wedge-like geometry with sharp leading edges. Initially, we present detailed descriptions of three different variations of the rational Bézier curve based parameterization that was developed, and the variety of shapes that can be obtained is demonstrated. Afterwards their performance is evaluated utilizing 2D CFD analysis. In our simulations, the rational Bézier curve leading edges outperform circular ones when it comes to minimizing both drag and peak heating rates or peak temperatures. Additionally, with higher order rational Bézier leading edge shapes, higher levels of geometric continuity can be achieved at the interface between the blunt part and the original wedge-like geometry, resulting in a smoother transition. Preliminary results indicate that this can potentially affect the receptivity and hence transition mechanisms. Finally, the 2D geometry formulations are extended to full 3D waverider forebody geometries

Notes on the connections between shape definition and the objective function landscape

The key to effective shape optimization is the selection of the appropriate mathematical formulation for the parametric description of the geometry of the artifact being optimized. It is widely understood that a good parameterization scheme is concise, mathematically well-posed, robust and flexible. What is less clear, however, is the way in which the choice of parameterization approach influences the features of the resulting objective function landscape. In this article we examine the issue through a simple, four-variable design problem. Key words: optimal design, shape optimization, geometry design, brachistochrone, modality