This paper describes the formulation and application of a design framework that supports the complex task of multidisciplinary design optimisation of Unmanned Aerial Vehicles (UAVs). The framework includes a Graphical User Interface (GUI), a robust Evolutionary Algorithm optimiser, several design modules, mesh generators and post-processing capabilities in an integrated platform. Traditional deterministic optimisation techniques for MDO are effective when applied to specific problems and within a specified range. A new class of optimisation techniques named Hierarchical Asynchronous Parallel Evolutionary Algorithms (HAPEAs) have shown to be robust as they require no derivatives or gradients of the objective function, have the capability of finding globally optimum solutions amongst many local optima, can be executed asynchronously in parallel and adapted easily to arbitrary solver codes without major modifications. The application of the methodology is illustrated on multi-criteria and multidisciplinary design problems. Results indicate the practicality and robustness of the method in finding optimal solutions and Pareto trade-offs between the disciplinary analyses and producing a set of non dominated individuals.= thickness-to-chord ratio Cm = pitching moment coefficient W SC = wing structural weight AR = wing aspect ratio λ br = taper ratio root to break λ bt = taper ratio break to tip Λ = wing 1/4 chord sweep b l = break location
Papilledema is a swelling of the optic disc secondary to elevated intracranial pressure (ICP). We analyzed 79 peer-review journal articles and provided a concise summary of the etiology, epidemiology, pathophysiology, clinical presentation, evaluation, natural history, differential diagnosis, treatment, and prognosis of papilledema. Only studies written in English with the full text available were included. Although many etiologies of papilledema exist, idiopathic intracranial hypertension is the most common and, thus, a large focus of this review.
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