1,721,003 research outputs found
Aircraft aerodynamic design: geometry and optimization
No full textOptimal aircraft design is impossible without a parametric representation of the geometry of the airframe. We need a mathematical model equipped with a set of controls, or design variables, which generates different candidate airframe shapes in response to changes in the values of these variables. This model's objectives are to be flexible and concise, and capable of yielding a wide range of shapes with a minimum number of design variables. Moreover, the process of converting these variables into aircraft geometries must be robust. Alas, flexibility, conciseness and robustness can seldom be achieved simultaneously.Aircraft Aerodynamic Design: Geometry and Optimization addresses this problem by navigating the subtle trade-offs between the competing objectives of geometry parameterization. It begins with the fundamentals of geometry-centred aircraft design, followed by a review of the building blocks of computational geometries, the curve and surface formulations at the heart of aircraft geometry. The authors then cover a range of legacy formulations in the build-up towards a discussion of the most flexible shape models used in aerodynamic design (with a focus on lift generating surfaces). The book takes a practical approach and includes MATLAB®, Python and Rhinoceros® code, as well as ‘real-life’ example case studies
Black-box calibration for complex systems simulation
No full textPredicting or measuring the output of complex systems is an important and challenging part of many areas of science. If multiple observations are required for parameter studies and optimization, accurate, computationally intensive predictions or expensive experiments are intractable. This paper looks at the use of Gaussian process based correlations to correct simple computer models with sparse data from physical experiments or more complex computer models. In essence, physics based computer codes and experiments are replaced by fast problem specific statistics based codes. Two aerodynamic design examples are presented. First a cheap two dimensional potential flow solver is calibrated to represent the flow over the wing of an unmanned air vehicle. The rear wing of a racing car is then optimized using rear wing simulations calibrated to include the effects of the flow over the whole car
Novel passive vibration isolators
No full textWe present the design of a novel anti-vibration mounting. The mounting takes the form of a triangular
truss which is ‘folded’ such that each section extends in the opposite direction to the previous section. The
geometry of this complex, compact structure is optimised to exploit the reflections that occur in vibrational
waves travelling through the structure to provide significant levels of vibration isolation. In this study we
have achieved a 15dB reduction in vibration energy compared to a baseline regular structure
Design space reduction in optimization using generative topographic mapping
No full textDimension reduction in design optimization is an extensively researched area. The need arises in design problems dealing with very high dimensions, which increase the computational burden of the design process because the sample space required for the design search varies exponentially with the dimensions. This work describes the application of a latent variable method called Generative Topographic Mapping (GTM) in dimension reduction of a data set by transformation into a low-dimensional latent space. The attraction it presents is that the variables are not removed, but only transformed and hence there is no risk of missing out on information relating to all the variables. The method has been tested on the Branin test function initially and then on an aircraft wing weight problem. Ongoing work involves finding a suitable update strategy for adding infill points to the trained GTM in order to converge to the global optimum effectively. Three update methods tested on GTM so far are discussed
Global optimization of deceptive functions with sparse sampling
No full textThis paper introduces a new method of calculating the expected improvement infill criterion, which does not rely on accurate model parameter estimation. The parameter estimation is embedded within the search of the infill criterion, wherein parameter changes are assessed using likelihood ratio tests. Unlike the traditional expected improvement, a new formulation we present cannot be 'fooled' by unlucky sampling or deceptive functions. The new method is introduced both mathematically and illustratively using a one-variable test function. It is then shown to outperform traditional expected improvement when optimizing the geometry of a passive vibration isolating truss
Dataset for paper "Quantifying Soft Tissue Artefacts and Imaging Variability in Motion Capture of the Fingers"
No full textThis is a dataset supports: Metcalf, C., et al (2020). Quantifying Soft Tissue Artefacts and Imaging Variability in Motion Capture of the Fingers. Annals of Biomedical Engineering. DOI: 10.1007/s10439-020-02476-2
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The influence of strut-connectors in stented vessels: a comparison of pulsatile flow through five coronary stents
No full textThe design of coronary stents has evolved significantlyover the past two decades. However, they still face theproblem of in-stent restenosis, formation of neointima within12 months of the implant. The biological response after stentimplantation depends on various factors including the stentgeometry which alters the hemodynamics. This study takesfive different coronary stent designs, used in clinical practice,and explores the hemodynamic differences arising due to thedifference in their design. Of particular interest is the designof the segments (connectors) that connect two struts.Pulsatile blood flow analysis is performed for each stent,using 3-D computational fluid dynamics (CFD), and variousflow features viz. recirculation zones, velocity profiles, wallshear stress (WSS) patterns, and oscillatory shear indices areextracted for comparison. Vessel wall regions with abnormalflow features, particularly low, reverse, and oscillating WSS,are usually more susceptible to restenosis. Unlike previousstudies, which have tried to study the effect of designparameters such as strut thickness and strut spacing onhemodynamics, this work investigates the differences in theflow arising purely due to differences in stent-shape, otherparameters being similar. Two factors, the length of theconnectors in the cross-flow direction and their alignmentwith the main flow, are found to affect the hemodynamicperformance. This study also formulates a design index(varying from 18.81% to 24.91% for stents used in thisstudy) that quantifies the flow features that could affectrestenosis rates and which, in future, could be used foroptimization studies
Assessment of an Empirical Bob-skeleton Steering Model
No full textAbstractThe sport of Skeleton involves the headfirst decent on a Bobsleigh ice track, whereby an athlete lies face forward on a sled with two runners. The athlete steers by applying reactive control movements with his or her shoulders and knees. There is a limited understanding of how these control movements effect the sled direction (yaw), which currently restricts advances in sled design. These limitations exist due to a lack of understanding at the ice-runner interaction contact point. Without knowing exactly how the runners create friction and why, runner design and athlete control is misunderstood. This paper discusses the measurement and analysis of on-track recorded data of various sled motion, forces and steering input parameters. These parameters have been used to develop an empirical ‘steering’ model, with the integration of athlete steering forces to determine sled reaction and response from steering input. Validation of the model shows a good relationship between real and approximated sled yaw throughout the descent. Such a model gives an insight into which forces are the primary cause of sled direction change and therefore how best to manipulate and change such forces to maximise control for the athlete. Future work includes validation of various runner friction coefficients so that control of different runners can be explored
Multi-objective optimisation using expected quantile improvement for decision making in disease outbreaks
No full textOptimization under uncertainty is important in many applications, particularly to inform policy and decision making in areas such as public health. A key source of uncertainty arises from the incorporation of environmental variables as inputs into computational models or simulators. Such variables represent uncontrollable features of the optimization problem, and reliable decision making must account for the uncertainty they propagate to the simulator outputs. Often, multiple, competing objectives are defined from these outputs such that the final optimal decision is a compromise between different goals. Here, we present emulation-based optimization methodology for such problems that extends expected quantile improvement (EQI) to address multiobjective optimization. Focusing on the practically important case of two objectives, we use a sequential design strategy to identify the Pareto front of optimal solutions. Uncertainty from the environmental variables is integrated out using Monte Carlo samples from the simulator. Interrogation of the expected output from the simulator is facilitated by use of (Gaussian process) emulators. The methodology is demonstrated on an optimization problem from public health involving the dispersion of anthrax spores across a spatial terrain. Environmental variables include meteorological features that impact the dispersion, and the methodology identifies the Pareto front even when there is considerable input uncertainty
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