Browsing by Author "Mifsud, Michael"
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Item Open Access A case study on the aerodynamic heating of a hypersonic vehicle(Royal Aeronautical Society, 2012-09-30T00:00:00Z) Mifsud, Michael; Estruch-Samper, David; MacManus, David G.; Chaplin, Ross; Stollery, J. L.A Parabolised Navier-Stokes (PNS) flow solver is used to predict the aerodynamic heating on the surface of a hypersonic vehicle. This case study highlights some of the main heat flux sensitivies to various conditions for a full-scale vehicle and illustrates the use of different complimentary methods in assessing the heat load for a realistic application. Different flight phases of the vehicle are considered, with freestream conditions from Mach 4 to Mach 8 across a range of altitudes. Both laminar and turbulent flows are studied, together with the effect of the isothermal wall temperature, boundary-layer transition location and body incidence. The effect of the Spalart-Allmaras and Baldwin-Lomax turbulent models on the heat transfer distributions is assessed. A rigorous assessment of the computations is conducted through both iterative and grid convergence studies and a supporting experimental investigation is performed on a 1/20th scale model of the vehicle's forebody for the validation of the numerical results. Good agreement is found between the PNS predictions, measurements and empirical methods for the vehicle forebody. The present PNS approach is shown to provide useful predictions of the heat transfer over the axisymmetric vehicle body. A highly complex flow field is predicted in the fin-body-fin region at the rear of the vehicle characterised by strong interference effects which limit the predictions over this region to a predominately qualitative level.Item Open Access Reduced-order modelling for high-speed aerial weapon aerodynamics(Cranfield University, 2008-10) Mifsud, Michael; Shaw, Scott T.; MacManus, David G.In this work a high-fidelity low-cost surrogate of a computational fluid dynamics analysis tool was developed. This computational tool is composed of general and physics- based approximation methods by which three dimensional high-speed aerodynamic flow- field predictions are made with high efficiency and an accuracy which is comparable with that of CFD. The tool makes use of reduced-basis methods that are suitable for both linear and non-linear problems, whereby the basis vectors are computed via the proper orthogonal decomposition (POD) of a training dataset or a set of observations. The surrogate model was applied to two flow problems related to high-speed weapon aerodynamics. Comparisons of surrogate model predictions with high-fidelity CFD simulations suggest that POD-based reduced-order modelling together with response surface methods provide a reliable and robust approach for efficient and accurate predictions. In contrast to the many modelling efforts reported in the literature, this surrogate model provides access to information about the whole flow-field. In an attempt to reduce the up-front cost necessary to generate the training dataset from which the surrogate model is subsequently developed, a variable-fidelity POD- based reduced-order modelling method is proposed in this work for the first time. In this model, the scalar coefficients which are obtained by projecting the solution vectors onto the basis vectors, are mapped between spaces of low and high fidelities, to achieve high- fidelity predictions with complete flow-field information. In general, this technique offers an automatic way of fusing variable-fidelity data through interpolation and extrapolation schemes together with reduced-order modelling (ROM). Furthermore, a study was undertaken to investigate the possibility of modelling the transonic flow over an aerofoil using a kernel POD–based reduced-order modelling method. By using this type of ROM it was noticed that the weak non-linear features of the transonic flow are accurately modelled using a small number of basis vectors. The strong non-linear features are only modelled accurately by using a large number of basis vectors.Item Open Access A variable-fidelity aerodynamic model using proper orthogonal decomposition(Wiley, 2016-04-20) Mifsud, Michael; MacManus, David G.; Shaw, S. T.A variable-fidelity aerodynamic model based on proper orthogonal decomposition (POD) of an ensemble of computational fluid dynamics (CFD) solutions at different parameters is presented in this article. The ensemble of CFD solutions consists of two subsets of numerical solutions or snapshots computed at two different nominal orders of accuracy or discretization. These two subsets are referred to as the low-fidelity and high-fidelity solutions or data, whereby the low fidelity corresponds with computations made at the lower nominal order of accuracy or coarser discretization. In this model, the relatively inexpensive low-fidelity data and the more accurate but expensive high-fidelity data are considered altogether to devise an efficient prediction methodology involving as few high-fidelity analyses as possible, while obtaining the desired level of detail and accuracy. The POD of this set of variable-fidelity data produces an optimal linear set of orthogonal basis vectors that best describe the ensemble of numerical solutions altogether. These solutions are projected onto this set of basis vectors to provide a finite set of scalar coefficients that represent either the low-fidelity or high-fidelity solutions. Subsequently, a global response surface is constructed through this set of projection coefficients for each basis vector, which allows predictions to be made at parameter combinations not in the original set of observations. This approach is used to predict supersonic flow over a slender configuration using Navier–Stokes solutions that are computed at two different levels of nominal accuracy as the low-fidelity and high-fidelity solutions. The numerical examples show that the proposed model is efficient and sufficiently accurate.