Ning Qin

For accurately resolving flow features such as shocks and vortices, it is desirable for the mesh edges to be aligned or orthogonal to these features, which minimizes interpolation errors and allows the Rankine‐Hugoniot condition across discontinuities to be satisfied. For this, we develop a three‐dimensional structured mesh generation method that aligns hexahedral grids with flow features to improve resolution accuracy and efficiency. For this purpose, a novel sweeping strategy is introduced. We first generate two‐dimensional cross‐sectional meshes using the cross‐field method, and then extrude them into volumetric blocks. Flow features extracted from an initial solution are embedded as geometric constraints. A direction‐aware mechanism can handle two alternatives. If the feature's sweep direction aligns with the geometry, the feature curve is embedded directly into the cross‐sectional block. On the other hand, if they differ, a separate mesh domain is created for the feature and coupled via an overlapping grid strategy. Numerical tests on transonic flows show that the method captures λ‐shocks, tip vortices and wakes with far fewer cells than uniform refinement, while achieving comparable or better resolution. The resulting anisotropic grids suppress numerical dissipation along critical flow structures, offering a practical balance between computational cost and solution fidelity.

This paper presents the design of shock control bumps on a double-fuselage aircraft with a natural laminar flow (NLF) wing section. Both two-dimensional (2D) and three-dimensional (3D) bumps were investigated to identify the high-impact factors on both shock control and natural laminar flow for the aircraft, and to understand the associated flow physics. Firstly, two key geometric parameters, namely the bump crest location and the bump height, were optimized to trade off shock control and laminar flow. The optimized 2D bump results in 8.19% total drag reduction in the wing section, specifically, 8.61% pressure drag reduction and 6.23% viscous drag reduction. The total drag coefficient of the aircraft reduces by 8.12 counts while the lift slightly increases. Then, the robustness of the bump at off-design conditions was verified as well. Finally, the 2D bump was converted to 3D bumps according to the transonic area rule to explore more alternative designs, and it was found that the two have similar performances, confirming the effectiveness of the transonic area rule applied in the shock-control-bump design.

Mesh adaptation techniques can significantly impact Computational Fluid Dynamics by improving solution accuracy and reducing computational costs. In this review, we begin by defining the concept of mesh adaptation, its core components and the terminology commonly used in the community. We then categorise and evaluate the main adaptation strategies, focusing both on error estimation and mesh modification techniques. In particular, we analyse the two most prominent families of error estimation: feature-based techniques, which target regions of high physical gradients and goal-oriented adjoint methods, which aim to reduce the error in a specific integral quantity of interest. Feature-based methods are advantageous due to their reduced computational cost: they do not require adjoint solvers, and they have a natural ability to introduce anisotropy. A substantial portion of the literature relies on second-order derivatives of scalar flow quantities to construct sensors that can be equidistributed to minimise discretisation error. However, when used carelessly, these methods can lead to over-refinement, and they are generally outperformed by adjoint-based techniques when improving specific target quantities. Goal-oriented methods typically achieve higher accuracy in fewer adaptation steps with coarser meshes. It will be seen that various approaches have been developed to incorporate anisotropy into adjoint-based adaptation, including hybrid error sensors that combine feature-based and goal-oriented indicators, sequential strategies and adjoint weighting of fluxes. After years of limited progress, recent work has demonstrated promising results, including certifiable solutions and applications to increasingly complex cases such as transonic compressor blades and film-cooled turbines. Despite these advances, several critical challenges remain: efficient parallelisation, robust geometry integration, application to unsteady flows and deployment in high-order discretisation frameworks. Finally, examples of the potential role of artificial intelligence in guiding or accelerating mesh adaptation are also discussed.

In this paper, a high Reynolds number compressible flow simulation method based on the immersed boundary method (IBM) is developed on the adaptive Cartesian grids to address two problems: one is the ability of large-scale Cartesian grid generation, and the other is the resolution of thin shear layers. For the former, an efficient automatic parallel generation method of adaptive Cartesian grids is proposed based on the k-d tree theory. The method has good parallel scalability and computational efficiency, e.g., the generation of 1.41 × 109 cells by 2048 cores takes only 0.40 min. For the latter, an IBM-wall function coupling method is designed to simulate geometrical configurations with high Reynolds numbers in the parallel framework. Numerical experiments show that the presented method can yield results consistent with the use of body-fitted grids. In conclusion, the presented method can realize a fully automatic simulation of high Reynolds number compressible flows, significantly reducing the labor cost in the computational fluid dynamics process, and can improve the accuracy and efficiency of engineering applications.

An on-the-fly unsteady adjoint-based aerodynamic and aeroacoustic optimization methodology is presented, aiming to achieve practical engineering applications to explore high-efficiency and low-noise design for aerodynamic shapes. Firstly, a novel on-the-fly hybrid CFD-CAA approach is developed with a close integration of unsteady Reynolds-averaged Navier–Stokes equations and a fully viscous time-domain FW-H formulation. Subsequently, an adjoint-based sensitivity analysis method is proposed for unsteady aerodynamic and aeroacoustic problems with either stationary or moving boundaries, wherein a unified architecture for discrete-adjoint sensitivity analysis of both aerodynamics and aeroacoustics is achieved by integrating the on-the-fly hybrid CFD-CAA approach. The on-the-fly approach facilitates direct evaluation of partial derivatives required for solving adjoint equations, eliminating the need for explicitly preprocessing flow and adjoint variables at all time levels in a standalone adjoint CAA solver and consequently substantially reducing memory consumption. The proposed optimization methodology is implemented within an open-source suite SU2. Results show that the proposed on-the-fly adjoint methodology is capable of achieving highly accurate sensitivity derivatives while significantly reducing memory requirements by an order of magnitude, and further demonstrations of single-objective and coupled aerodynamic and aeroacoustic optimizations highlight the potential of the proposed method in exploring high-efficiency and low-noise design for aerodynamic shapes.

We present an approach to sensor placement for turbulent mean flow data assimilation in the context of Reynolds-averaged Navier–Stokes (RANS) simulations. It entails generating a spatial uncertainty map through the eigenspace perturbations (ESPs) of the baseline turbulence model (e.g., the k−ω shear stress transport model) to quantify the epistemic structural errors in the model. A novel greedy search algorithm is proposed to place sensors targeting regions of highest uncertainty in the spatial uncertainty map generated from ESP. The algorithm is computationally efficient (e.g., computational cost negligible compared to a RANS solution) and is both easy to implement and tune. It involves two hyper-parameters (a constraint to avoid sensor clustering and the number of sensors) which we investigate in-depth. A variational (adjoint-based) data assimilation approach is used for flow reconstruction. The proposed strategy was tested on three two-dimensional wall-bounded flows (Reynolds number ranging 5.6×103–9.36×105) involving flow separation and reattachment. For the wall-mounted hump case, we found that data assimilation using 33 sensors with our proposed sensor placement algorithm reduced the average velocity prediction error by 60% vs 38% with a simple uniform placement of sensors. Furthermore, we found that we could achieve 61% error reduction using our algorithm with only three sensors. Notably, in all tested cases, the error reduction using our method for sensor placement was close in accuracy to the instances where the entire flow field data were used for flow reconstruction, which involved two to three orders of magnitude more data points than the placed sensors.

A method to generate feature-aligned anisotropic structured meshes automatically is presented for high resolution of two-dimensional complicated flow features such as normal and oblique shock waves, shock reflection, shock/shock interaction, and shock/boundary-layer interaction. The method starts from extraction of dominant flow features to be treated alongside geometric entities. This is followed by automatic generation of multiblock structured meshes of the flow domain using a cross-field based method so that the flow feature entities are embedded along with the geometries. The cross-field method allows for the automatic blocking so that anisotropic quadrilateral meshes generation and adaptation to resolve flow features can be carried out. The resulting mesh possesses high element quality for orthogonality and high resolution of the flow features, suitable for the shock capturing methods and higher-order reconstruction schemes. The method is demonstrated through a number of aerodynamic flow test cases with discussion on its efficiency, accuracy, and robustness.

The reduction of noise for commercial aircraft has become an important challenge for engineers, with engine noise being one of the major contributors to the overall sound levels near airport. For modern turbofan engines, characterized by high bypass ratios, one of the main noise sources is the interaction between the turbulent rotor wake and the leading edge of the downstream outlet guide vanes. A passive noise control method that has been gaining interest in the research community is the use of serrated leading edges for the vanes. Studies done on flat plates and airfoils with serrated leading edges showed a reduction in airfoil turbulent flow interaction noise, with an increased benefit when increasing the serrations amplitude and the existence of an optimal wavelength. From an aerodynamic standpoint, some studies show that serrations delay stall, but with a cost in aerodynamic performance at design point. Very little data exists for assessing the acoustic benefits of serrations on the leading edge of outlet guide vanes, where the noise predictions require addressing both the broadband and tonal noise. Preliminary results indicate some noise reduction, but without quantifying the benefits against the serrations parameters. It is also unclear how the total pressure losses in the outlet guide vanes row are affected by the presence of serrations. In this paper, we report a parametric study based on leading edge serrations to investigate the effect of the amplitude and wavelength on noise levels, as well as on aerodynamic performance. The NASA source diagnostic test (SDT) fan with swept outlet guide vanes was used as the test case, being representative of a modern turbofan. The unsteady flow and radiated noise were computed using a hybrid Lattice-Boltzmann/very-Large-Eddy-Simulation model implemented in the PowerFlow computational fluid dynamics solver. The flow characteristics and the noise levels were validated for the datum geometry against existing experimental data. Correlations for the far-field overall sound pressure level and the total pressure loss coefficient were built in relation to the serration parameters and a discussion on the best combination of serrations amplitude and wavelength has been given. These correlations can be further used in a multidisciplinary optimisation process.