Fast and Accurate Hypersonic CFD Simulations: Impact of Automatic Shock-Aligned Meshes

Block-adapted, shock-fitted structured grid for the Orion reentry capsule in hypersonic conditions, showing blocks precisely aligned with the shock surface and refined grid clustering near critical high-gradient regions for improved simulation accuracy.

Figure 1: Block Adapted Shock Fitted Structured Grid for Hypersonic Simulations for Orion Reentry Capsule Configuration.

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Computational fluid dynamics is critically essential and highly recommended for predicting the aerothermal environment of reentry vehicles experiencing hypersonic flow. In these regimes, shock waves are a dominant flow phenomenon. It is needless to say capturing these shock waves to the finest level possible is critically essential for accurately predicting the hypersonic flow field. Traditionally, two distinct approaches, known as shock fitting and shock capturing, have been widely used to handle such discontinuities.

Shock Capturing involves implicit handling of shocks through numerical schemes that can deal with discontinuities without explicitly locating them. They employ artificial viscosity or flux limiters to stabilize the solution and prevent non-physical oscillations. However, they may produce smeared shock profiles and require fine grids to achieve higher accuracy, potentially increasing computational costs.

Shock Fitting, on the other hand, explicitly tracks the position of shock waves within the CFD domain. It treats the shock as a moving boundary within the domain, solving additional equations to update its position and speed. This approach provides a sharp and accurate representation of shocks without the smearing effects seen in shock capturing. However, it is more complex to implement, requiring additional equations for shock dynamics and frequent grid adjustments to accommodate moving shocks.

To sum up, shock capturing is robust, versatile and easier to apply to a wide range of problems, albeit with potential accuracy trade-offs. while on the other hand, shock fitting offers superior accuracy for specific applications but at the cost of increased complexity and implementation effort.

Flowchart illustrating the shock-fitting loop, showing the iterative process of extracting the shock surface, smoothing it, adapting nearby blocks, regenerating the mesh, and updating the CFD solution until convergence is achieved.
Figure 2: Flow Chart for the Shock Fitting Loop.

To commence the simulation, an initial structured grid must be created. The baseline mesh adopts an analytical sphere as its outer domain, with no specialized adjustments made to accommodate shock features. This streamlined approach allows for swift setup of the initial grid, requiring minimal effort and time investment. Furthermore, maintaining symmetry along the X-Y plane aids in reducing grid points, thereby enhancing simulation efficiency.

Two-part illustration of the Orion capsule simulation setup:
(a) Hemispherical flow domain showing the outer computational boundary used for the hypersonic analysis.
(b) Structured multiblock mesh wrapped around the Orion capsule, highlighting block connectivity and mesh refinement near the capsule surface.
Figure 3: a. Hemispherial flow domain. b. Structured multiblock mesh around the Orion capsule.
Mach contour visualization on the baseline structured grid around the Orion reentry capsule, showing shock formation, flow acceleration, and key high-speed aerodynamic features in the hypersonic regime.
Figure 4: Mach contour on the baseline structured grid.

Following the structured grid generation, the flow simulation is conducted using MISTRAL, a Navier-Stokes solver tailored for reacting flows.

Initially, the solution is computed on an Euler grid, without implementing specialized boundary layer clustering for the capsule wall.

This simplification is deliberate, aimed at minimizing computational time, as the primary focus of the initial iteration is the extraction of the shock surface.

The process of detecting and extracting shocks commences with the post-processing of the MISTRAL solution to derive the Mach distribution in the flow domain. The location of the bow shock is determined by selecting a percentage of the freestream Mach number, typically ranging between 90% to 95%. Subsequently, a Mach iso-contour sheet is extracted from the flow solution utilizing the Paraview visualization package. Following the extraction, the Mach sheet is saved as an STL file and imported into GridPro for further processing.

Two-part visualization of Mach contour extraction and processing:
(a) Mach contour sheet generated from the baseline grid CFD solution, showing the raw shock surface and flow gradients.
(b) Smoothed Mach contour sheet produced in GridPro, highlighting a cleaner, more continuous shock surface suitable for shock-fitted mesh adaptation.
Figure 5: a. Extracted Mach contour sheet after postprocessing on the baseline grid CFD solution. b. Mach contour sheet after smoothing in GridPro.

Given the coarse resolution of the bow shock on the initial grid, the Mach iso-surface may display roughness. To address this, a smoothing process becomes imperative. Utilizing GridPro’s built-in subdivision scheme, the extracted Mach contour is smoothed and enhanced to make it more suitable for subsequent stages of the shock-capturing procedure.

Two-stage visualization of the shock alignment process:
(a) The baseline grid showing the original block arrangement before adaptation.
(b) Nearby blocks realigned to follow the shock contour, improving shock resolution and mesh conformity to high-gradient flow regions.
Figure 6: a. Baseline grid. b. Nearby blocks aligned to the shock contour.

With the shock contour sheet in hand, we’re ready to delve into the actual shock-capturing process. Firstly, the tool automatically pinpoints the block faces closest to the extracted shock contour sheet. Next, those faces proximate to the shock undergo splitting and a buffer layer of the block is created around the shock. Notably, this splitting operation maintains the integrity of the block structure, relieving the user from the burden of resolving any ensuing issues.

Following this, blocks lying beyond the buffer layer are automatically deleted (as shown in Figure 7a). Next, a new outer domain surface, encapsulating the capsule is generated by scaling up the shock contour sheet by a small percentage.

Two-step visualization of the shock-fitted meshing process:
(a) Smoothed shock-fitted blocks showing improved block alignment along the shock surface.
(b) Final block-adapted shock-fitted structured grid with boundary layer clustering, highlighting refined near-wall resolution and precise shock-conforming topology.
Figure 7: a. Shock-fitted blocks after smoothing. b. The final block-adapted shock-fitted structured grid after boundary layer clustering.

Consequently, the outer faces of the buffer layer blocks serve as the boundary faces of this new outer envelope, establishing a zone characterized by shock-aligned grid lines. A detailed view of the mesh obtained after the initial shock-fitting iteration is presented in Figure 7b.

It’s important to note that the decision to split the topology hinges on the specifics of each case. In scenarios where there’s no need to reduce the computational domain’s size, this step may be bypassed. However, in instances like the one described here, where pinpointing the shock’s location and the primary flow physics region is challenging before simulation, employing this process can significantly slash the computational domain by over half. Such reduction translates into substantial savings in computational time and resources.

The Mach contour image in Figure 8 clearly demonstrates that the shock is significantly crisper and closer to the body. The cells are noticeably better aligned with both the general flow direction and the shock’s location. Remarkably, just one shock-fitting iteration was sufficient to achieve a good solution, highlighting the efficiency and effectiveness of the block-adapted shock alignment method.

Flowfield comparison for the Orion reentry capsule in a hypersonic regime, shown before and after implementing block-adapted shock fitting. The image highlights sharper shock resolution, improved shock alignment with the mesh, and clearer flow structures in the adapted simulation.
Figure 8: Hypersonic simulations flow field comparison. Before and after implementing block-adapted shock fitting.

The computed results are compared to data from Reference, which utilizes the US3D code. Figure 9 compares surface pressure variation along the symmetry line (in the z direction) of the capsule. The maximum pressure error is less than 1%, which is well within acceptable standards, validating the quality of the obtained solution.

Pressure distribution comparison for the Orion reentry capsule, showing block-adapted, shock-fitted simulation results alongside those from the US3D code. The image highlights differences and agreements in shock location, pressure gradients, and overall aerodynamic loading on the capsule surface.
Figure 9: Block adapted shock fitted pressure solution comparison with the results obtained from US3D code.

The next test case considered to validate the tool was the leading nose region of the Space Launch System. Two structured grids were generated- a baseline grid (0.7 million) and a shock-fitted grid (0.762 million) and CFD computations were done at Mach 5. Figure 10 shows the grids and the improvement in the flow field with the block-adapted shock alignment method.

Side-by-side hypersonic simulation results for the SLS configuration, showing the flowfield before and after block-adapted shock fitting. The comparison highlights clearer shock structures, improved shock alignment with the mesh, and enhanced resolution of high-gradient regions in the adapted case.
Figure 10: Hypersonic simulations results: Before and after block adapted shock fitting for SLS configuration.

The third test case involves hypersonic simulations for a blunt body configuration at Mach 20. Here also 2 grids – Baseline (5.92 million) and shock-fitted grids (5.61 million) were employed. Figure 11 below shows the crisp representation of the bow shock with block-adapted shock-fitted grids.

Side-by-side hypersonic simulation results for a blunt body, comparing the flowfield before and after block-adapted shock fitting. The image highlights improved shock resolution, sharper shock boundaries, and enhanced accuracy in the adapted mesh configuration.
Figure 11: Hypersonic simulations results: Before and after block-adapted shock fitting for a blunt body configuration. Image courtesy HiFUN.

The block-adapted shock alignment approach is straightforward to implement, requiring fewer re-meshing and CFD simulation iterations compared to other shock-fitting procedures or adaptive shock-capturing methods. Additionally, it only increases the cell count of the base grid by a smaller amount.

This method can be seamlessly integrated into the existing GridPro-CFD solver-post-processor loop without any modifications. The base-structured hexahedral meshes, with their inherently low dissipation properties, enhance shock capture accuracy. By using the shock surface to identify shock-interfering blocks and refining these blocks through wrapping, the resulting grid is sufficiently dense and aligned with the shock contour to capture it accurately. Typically, executing this loop for one or two iterations is sufficient.

A key advantage of this approach is the minimal increase in cell count and the presence of one-to-one connected cells. Due to the limited number of iterative loops and uni-directional cell refinement, the increase in cell count remains marginal. Importantly, any computational fluid dynamics solver compatible with hexahedral meshes can utilize the shock-fitted grids, as one-to-one cell connectivity with neighbouring cells is consistently maintained.

A workflow for shock-fitting grid generation has been developed and rigorously tested, proving effective in accurately capturing shocks. Demonstrated through the Orion re-entry capsule and SLS rocket test cases, this new mesh generation process can rapidly produce accurate CFD estimates for hypersonic geometries. It stands as a viable and promising alternative to traditional shock-fitting or shock-capturing mesh generation methods. The efficacy of these novel approaches is evident, showcasing significant improvements in the flow field due to the highly precise representation of the shock contour.

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