Browsing by Author "Sánchez Moreno, Francisco"
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Item Open Access Deep-learning methods for non-linear transonic flow-field prediction(AIAA, 2023-05-08) Sureshbabu, Sanjeeth; Tejero, Fernando; Sánchez Moreno, Francisco; MacManus, David; Sheaf, Christopher T.It is envisaged that the next generation of ultra-high bypass ratio engines will use compact aero-engine nacelles. The design and optimisation process of these new configurations have been typically driven by numerical simulations, which can have a large computational cost. Few studies have considered the nacelle design process with low order models. Typically these low order methods are based on regression functions to predict the nacelle drag characteristics. However, it is also useful to develop methods for flow-field prediction that can be used at the preliminary design stages. This paper investigates an approach for the rapid assessment of transonic flow-fields based on convolutional neural networks (CNN) for 2D axisymmetric aeroengine nacelles. The process is coupled with a Sobel filter for edge detection to enhance the accuracy in the prediction of the shock wave location. Relative to a baseline CNN built with guidelines from the open literature, the proposed method has a 75% reduction in the mean square error for Mach number prediction. Overall, the presented method enables the fast prediction of the flow characteristics around civil aero-engine nacelles.Item Open Access Robustness of optimisation algorithms for transonic aerodynamic design(Unknown, 2022-07-01) Sánchez Moreno, Francisco; MacManus, David G.; Tejero, Fernando; Matesanz García, Jesús; Sheaf, Christopher T.In design optimisation problems, it is essential to ensure the convergence to the optimal design space with the lowest variability possible. In this respect, the optimisation algorithm plays a key role as it drives the exploration of the design space. This paper presents a statistical assessment of two genetic algorithms (NSGA-II and IBEA) and a particle swarm optimiser (OMOPSO) for the transonic aerodynamic design of compact nacelles for future aero-engines. OMOPSO is the most suitable optimisation algorithm due to the lowest variability to find an optimised design with a reasonable convergence rate of the optimisation.Item Open Access Transonic nacelle design for future medium range aero-engines(ICAS, 2022-09-09) Schreiner, B. Deneys J.; MacManus, David; Tejero, Fernando; Sánchez Moreno, Francisco; Sheaf, Christopher T.It is expected that future civil aero-engines will operate at low specific thrust and high-bypass ratios to improve propulsive efficiency. This may result in an increment in fan diameter and associated weight and nacelle drag penalties. For this reason, these new architectures may use compact nacelles to meet the benefits of the new engine cycles. The aim of the current work is to evaluate the aerodynamic design and performance of compact nacelles for medium range, single-aisle aircraft with a cruise Mach number of M = 0.80. This work encompasses the 3D multi-point, multi-objective optimisation of nacelles by considering cruise conditions as well as a range of off-design requirements such as an increased cruise Mach number, a windmilling engineout diversion scenario and a windmilling end-of-runway case at high-incidence. This paper also explores the robustness and sensitivity of selected designs to flight Mach number (M), massflow capture ratio (MFCR) and angle of attack (AoA). The limits of the feasible design space for this new design challenge are identified. It is concluded that relative to a conventional aero-engine nacelle, the nacelle length (Lnac/rhi) can be reduced by approximately 13% with a mid-cruise drag reduction of 5.8%, whilst maintaining an acceptable aerodynamic performance at off-design conditions.