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The approximate factorisation‐conjugate gradient squared (AF‐CGS) method has been successfully demonstrated for unsteady turbulent aerofoil flows and transonic inviscid flows in two and three dimensions. The method consists of a conjugate gradient solution of the linear system at each step with the ADI approximate factorisation as a preconditioner. In the present paper the method is adapted to obtain rapid convergence for steady aerofoil flows when compared to the basic explicit method. Modifications to the original method are described, convergence criteria are examined and the method is demonstrated for transonic flow including AGARD test case 9 for the RAE2822 aerofoil.

The paper presents a numerical technique for the simulation of the effects of grey‐diffusive surface radiation on fluid flow using a finite volume procedure for two‐dimensional (plane and axi‐symmetric) geometries. The governing equations are solved sequentially, and the non‐linearities and coupling of variables are accounted for through outer iterations (coefficients updates). In order to reduce the number of outer iterations, a multigrid algorithm was implemented. The radiating surface model assumes a non‐participating medium, semi‐transparent walls and constant elementary surface temperature and radiation fluxes. The calculation of view factors is based on the analytical evaluation for the plane geometry and numerical integration for axi‐symmetric geometry. Ashadowing algorithm was implemented for the calculation of view factors in general geometries. The method for the calculation of view factors was first tested by comparison with available analytical solutions for a complex geometric configuration. The flow prediction code combined with radiation heat transfer was verified by comparisons with analytical one‐dimensional solutions. Further test calculations were done for the flow and heat transfer in a cavity with a radiating submerged body. As an example of the capabilities of the method, transport processes in metalorganic chemical vapour deposition (MOCVD) reactors were simulated.

An axisymmetric shock-tube model of the high-pressure shock-tube facility at the Texas A&M University has been developed. The shock tube is non-conventional with a non-uniform cross-section and features a driver section with a smaller diameter than the driven section. The paper aims to discuss these issues.

Computations were carried out based on the finite volume approach and the AUSM+ flux-differencing scheme. The adaptive mesh refinement algorithm was applied to the time-dependent flow fields to accurately capture and resolve the shock and contact discontinuities as well as the very fine scales associated with the viscous effects. The incorporation of a conjugate heat transfer model enhanced the credibility of the results.

The shock-tube model is validated with simulation of the bifurcation phenomenon and with experimental data. The model is shown to be capable of accurately simulating the shock and expansion wave propagations and reflections as well as the flow non-uniformities behind the reflected shock wave as a result of reflected shock/boundary layer interaction or bifurcation. The pressure profiles behind the reflected shock wave agree with the experimental results.

This paper presents one of the first studies to model the entire flow field history of a non-uniform diameter shock tube with a conjugate heat transfer model beginning from the bursting of the diaphragm while simultaneously resolving the fine features of the reflected shock-boundary layer interaction and the post-shock region near the end-wall, at conditions useful for chemical kinetics experiments. An important discovery from this study is the possible existence of hot spots in the end-wall region that could lead to early non-homogeneous ignition events. More experimental and numerical work is needed to quantify the hot spots.

The purpose of the paper is to analyze the active suppression of the aeroelastic vibrations of ailerons with strongly nonlinear characteristics by neural network/reinforcement learning (NN/RL) control method and comparing it with the classic robust methods of suppression.

The flexible wing and aileron with hysteresis nonlinearity is treated as a plant-controller system and NN/RL and robust controller are used to suppress the nonlinear aeroelastic vibrations of aileron. The simulation approach is used for analyzing the efficiency of both types of methods in suppressing of such vibrations.

The analysis shows that the NN/RL controller is able to suppress the nonlinear vibrations of aileron much better than linear robust method, although its efficiency depends essentially on the NN topology as well as on the RL strategy.

Only numerical analysis was carried out; thus, the proposed solution is of theoretical value, and its application to the real suppression of aeroelastic vibrations requires further research.

The work shows the NN/RL method has a great potential in improving suppression of highly nonlinear aeroelastic vibrations, opposed to the classical robust methods that probably reach their limits in this area.

The work raises the questions of controllability of the highly nonlinear aeroelastic systems by means of classical robust and NN/RL methods of control.

The paper aims to develop an efficient data-driven modeling approach for the hydroelastic analysis of a semi-circular pipe conveying fluid with elastic end supports. Besides the structural displacement-dependent unsteady fluid force, the steady one related to structural initial configuration and the variable structural parameters (i.e. the variable support stiffness) are considered in the modeling.

The steady fluid force is treated as a pipe preload, and the elastically supported pipe-fluid model is dealt with as a prestressed hydroelastic system with variable parameters. To avoid repeated numerical simulations caused by parameter variation, structural and hydrodynamic reduced-order models (ROMs) instead of conventional computational structural dynamics (CSD) and computational fluid dynamics (CFD) solvers are utilized to produce data for the update of the structural, hydrodynamic and hydroelastic state-space equations. Radial basis function neural network (RBFNN), autoregressive with exogenous input (ARX) model as well as proper orthogonal decomposition (POD) algorithm are applied to modeling these two ROMs, and a hybrid framework is proposed to incorporate them.

The proposed approach is validated by comparing its predictions with theoretical solutions. When the steady fluid force is absent, the predictions agree well with the “inextensible theory”. The pipe always loses its stability via out-of-plane divergence first, regardless of the support stiffness. However, when steady fluid force is considered, the pipe remains stable throughout as flow speed increases, consistent with the “extensible theory”. These results not only verify the accuracy of the present modeling method but also indicate that the steady fluid force, rather than the extensibility of the pipe, is the leading factor for the differences between the in- and extensible theories.

The steady fluid force and the variable structural parameters are considered in the data-driven modeling of a hydroelastic system. Since there are no special restrictions on structural configuration, steady flow pattern and variable structural parameters, the proposed approach has strong portability and great potential application for other hydroelastic problems.

This paper aims to present a numerical method based on computational fluid dynamics that allows investigating the buffet envelope of reference equivalent wings at the equivalent cost of several two-dimensional, unsteady, turbulent flow analyses. The method bridges the gap between semi-empirical relations, generally dominant in the early phases of aircraft design, and three-dimensional turbulent flow analyses, characterised by high costs in analysis setups and prohibitive computing times.

Accuracy in the predictions and efficiency in the solution are two key aspects. Accuracy is maintained by solving a specialised form of the Reynolds-averaged Navier–Stokes equations valid for infinite-swept wing flows. Efficiency of the solution is reached by a novel implementation of the flow solver, as well as by combining solutions of different fidelity spatially.

Discovering the buffet envelope of a set of reference equivalent wings is accompanied with an estimate of the uncertainties in the numerical predictions. Just over 2,000 processor hours are needed if it is admissible to deal with an uncertainty of ±1.0° in the angle of attack at which buffet onset/offset occurs. Halving the uncertainty requires significantly more computing resources, close to a factor 200 compared with the larger uncertainty case.

To permit the use of the proposed method as a practical design tool in the conceptual/preliminary aircraft design phases, the method offers the designer with the ability to gauge the sensitivity of buffet on primary design variables, such as wing sweep angle and chord to thickness ratio.

The infinite-swept wing, unsteady Reynolds-averaged Navier–Stokes equations have been successfully applied, for the first time, to identify buffeting conditions. This demonstrates the adequateness of the proposed method in the conceptual/preliminary aircraft design phases.

Transonic flutter and active flap control, in two dimensions, are simulated by coupling independent structural dynamic and inviscid aerodynamic models, in the time domain. A flight control system, to actively control the trailing edge flap motion, has also been incorporated and, since this requires perfect synchronisation of fluid, structure and control signal, the “strong” coupling approach is adopted. The computational method developed is used to perform transonic aeroelastic and aeroservoelastic calculations in the time domain, and used to compute stability (flutter) boundaries of 2D wing sections. Open and closed loop simulations show that active control can successfully suppress flutter and results in a significant increase in the allowable speed index in the transonic regime. It is also shown that active control is still effective when there is free‐play in the control surface hinge. Flowfield analysis is used to investigate the nature of flutter and active control, and the fundamental importance of shock wave motion in the vicinity of the flap is demonstrated.

The purpose of this paper is to discuss a data interpolation method of curved surfaces from the point of dimension reduction and manifold learning.

Instead of transmitting data of curved surfaces in 3D space directly, the method transmits data by unfolding 3D curved surfaces into 2D planes by manifold learning algorithms. The similarity between surface unfolding and manifold learning is discussed. Projection ability of several manifold learning algorithms is investigated to unfold curved surface. The algorithms’ efficiency and their influences on the accuracy of data transmission are investigated by three examples.

It is found that the data interpolations using manifold learning algorithms LLE, HLLE and LTSA are efficient and accurate.

The method can improve the accuracies of coupling data interpolation and fluid-structure interaction simulation involving curved surfaces.

The purpose of this paper is to document an efficient and accurate approach to generate aerodynamic tables using computational fluid dynamics. This is demonstrated in the context of a concept transport aircraft model.

Two designs of experiment algorithms in combination with surrogate modelling are investigated. An adaptive algorithm is compared to an industry-standard algorithm used as a benchmark. Numerical experiments are obtained solving the Reynolds-averaged Navier–Stokes equations on a large computational grid.

This study demonstrates that a surrogate model built upon an adaptive design of experiments strategy achieves a higher prediction capability than that built upon a traditional strategy. This is quantified in terms of the sum of the squared error between the surrogate model predictions and the computational fluid dynamics results. The error metric is reduced by about one order of magnitude compared to the traditional approach.

This work lays the ground to obtain more realistic aerodynamic predictions earlier in the aircraft design process at manageable costs, improving the design solution and reducing risks. This may be equally applied in the analysis of other complex and non-linear engineering phenomena.

This work explores the potential benefits of an adaptive design of experiment algorithm within a prototype working environment, whereby the maximum number of experiments is limited and a large parameter space is investigated.

A finite element solution procedure is presented for the simulation of transient incompressible fluid flows using triangular meshes. The algorithm is based on the artificial compressibility technique in connection with a dual time‐stepping approach. A second‐order discretization is employed to achieve the required accuracy in real‐time while an explicit multistage Runge‐Kutta scheme is used to march in the pseudo‐time domain. A standard Galerkin finite element method, stabilized by using an artificial dissipation technique, is used for the spatial discretization. The performance of the proposed algorithm is demonstrated by solving a set of internal and external problems including flows with purely transient and periodic behavior.